Microwave-assisted Production of Solid Lipid Nanoparticles
Rohan Shah
A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy
February 2016
Department of Chemistry and Biotechnology
Faculty of Science, Engineering and Technology
Swinburne University of Technology
Melbourne, Australia
Abstract Abstract
The oral route is the first choice for drug administration, except in very specific situations such as when an immediate, systemic or local effect is intended. The oral route is also the most convenient and safest route of drug administration due to its easy and non- invasive nature, which also provides higher patient compliance and fewer complications. Despite these positive attributes, therapeutic efficacy of drug delivery systems can be problematic and can often be obscured due to physicochemical properties of the drugs and/or physiological constraints. Poor water solubility and/or poor permeability, the risk of degradation in the stomach and liver and poor hepatic first-pass metabolism are the major causes that not only affect oral bioavailability but also encumber the development of delivery systems. Industry estimates suggest that approximately 70 - 75% of new drug candidates and 40% of currently marketed drugs fail due to solubility and/or stability issues, prompting significant need for research in advanced lipophilic drug delivery systems.
Solid lipid nanoparticles (SLNs) present a promising technology for lipophilic drug delivery. Their unique combination of small particle size, large specific surface area, solid nature, particle shape and surface chemistry has generated enormous enthusiasm and anticipation regarding pharmaceutical applications. SLNs can combine the advantages of other traditional colloidal carriers such as liposomes, emulsions, polymeric nanoparticles and micelles, and at the same time reduce their associated shortcomings. Some of the potential attractive features of SLNs include protection of incorporated drug molecules from the external biological environment, physicochemical stability, controlled drug release and target specificity. Their development, however, is still in its early stages and more research is required around their manufacture, characterisation and drug loading capacity.
The SLNs generated in this thesis were prepared using a novel microwave-assisted microemulsion technology, and were compared with SLNs prepared by more conventional thermal heating. Stearic acid was used as the lipid with Tween® 20 as the surfactant. Various drugs were tested for their uptake and stability using these SLNs. Tetracycline-loaded SLNs were smaller, with lower polydispersity, physically more stable and had higher encapsulation efficiencies than conventionally produced drug- laden SLNs.
iii Abstract
An aim of the thesis was to provide potential drug delivery systems for lipophilic drugs belonging to the Biopharmaceutical Classification System (BCS) Class II and Class IV. For this purpose, drugs from different categories (and different chemistries) were selected, including antifungal drugs (clotrimazole, miconazole nitrate and econazole nitrate) and non-steroidal anti-inflammatory drugs (NSAIDs) (indomethacin, ketoprofen and nimesulide). These studies were aimed at evaluating the physicochemical and biological properties of the drug-loaded SLNs.
The drug-loaded SLNs had a small size (200-300 nm), low polydispersity (0.1-0.3) and a moderate negative zeta potential (with the exception of miconazole nitrate and econazole nitrate). The crystallinity of the stearic acid was reduced, as evidenced by differential scanning calorimetry (DSC) and X-ray diffraction (XRD), when fabricated into SLNs - suggesting increased drug payload. The encapsulation efficiency of the drug- loaded SLNs was between 70% and 92% depending on the physicochemical properties of the drugs. The stability and encapsulation efficiency of drug-loaded SLNs were found to be influenced by the pH and electrolytes in the dispersion medium. Electron microscopy suggested that the SLNs were spherical to ellipsoidal in shape. The SLNs loaded with drugs exhibited biphasic drug release behaviours. The release mechanisms were, however, different for both drug categories. The SLNs loaded with NSAIDs exhibited a high initial “burst” followed by a sustained-release of drugs. The release mechanism was governed by Fickian diffusion. In contrast, the SLNs loaded with antifungal drugs (different drug chemistry) exhibited a slow, controlled and incomplete release of drugs, and was governed by non-Fickian release mechanisms.
The viability of A549 epithelial cells when exposed to SLNs was found to be concentration-dependent. The small size (<300 nm) of SLNs produced by microwave- assisted microemulsion technique was suitable for internalisation by epithelial cells. The SLN uptake by human epithelial cells (A549 and HeLa cells) was found to be energy- dependent. Confocal laser scanning microscopy (CLSM), fluorescence microscopy and flow-assisted cell sorting (FACS) techniques were used to ascertain that the SLN uptake by human epithelial cells was mediated by clathrin-dependent endocytosis.
All these findings suggest that the SLNs produced by the novel microwave-assisted microemulsion technique can be used as potential drug delivery systems, and therefore, facilitate further development of the SLNs.
iv Dedication
Dedicated to my parents, Mr. Mahendra Shah and Mrs. Sangita Shah…!
v
Acknowledgements Acknowledgements
Although I declare that this thesis is my own work, this thesis would not have the spirit that it has without the invaluable contributions provided by many people, and I am pleased to acknowledge their support, assistance and encouragement here.
To my primary supervisor, advisor and guide Professor Ian Harding, this journey of PhD has been an incredible journey led by you. I sincerely thank you for believing in me and accepting me to pursue my PhD under you. I appreciate your generosity with reception of my postulations. Thanks most of all for the granting me complete freedom in conducting this research. Your enduring support and guidance have always motivated to give a little more.
To my supervisor and mentor “Godfather” Professor Enzo Palombo, your guidance, support and constant encouragement have been, and continue to motivate me to think bigger and perform better. I will always be indebted to you for inventing opportunities for me that have served as a strong foundation for my career and establish myself as a researcher. You, like my father, have always inspired me to “earn” people. I will always be grateful for taking care of me during these five years.
To my associate supervisor Dr. Daniel Eldridge, your enduring patience, backing and guidance have helped me navigate through the PhD journey. I appreciate all your time in correcting my writing despite your hectic teaching schedules. You have always enthused me with your extraordinary abilities of “striking-the right-cord” to inspire students to enjoy what they learn.
This study was made possible through the financial support from the Department of State Development, Business and Innovation (State Government of Victoria). I am grateful to them, and to Australia India Institute, for providing the Victoria India Doctoral Scholarship. I would like to take this opportunity to thank Professor Amitabh Mattoo and the staff at the Institute for their constant support, assistance, encouragement and arranging the “cultural yatra” during these years.
I am particularly grateful to a number of academic scholars for their educational insights and useful critiques: A/Professor Bob Laslett, Dr. Peter Mahon, Dr. Francois Malherbe, Dr. Tony Barton, Dr. Jitendra Mata, Professor Peter Kingshott, Professor Sarah Russell,
vii
Acknowledgements
Dr. Mandy Ludford-Menting, Dr. Igor Sbarski, Dr. James Wang, Dr. De Ming Zhu, Dr. Pablo Juliano and A/Professor Shannon Notley.
I truly appreciate the support of the Faculty of Science, Engineering and Technology at Swinburne University of Technology through the funding and resources provided to me. I am thankful to Chris Key, Soula Mougos, Ngan Nguyen, Dr. Huimei Wu, Andrea Chisholm, Angela McKellar, Katharine Adcroft, Dr. Rebecca Alfred, Chris Anthony, Antonina Gatt and Dr. Adrian Disdale for their support and assistance during my research work. I owe particular thanks to Savithri Galappathie for taking care of me all these years.
To Neil Clifford, Glenda Runciman, Karin Grolimund, Stephen Morris, Adam Winterhalter, Gavin Robertson and Daniel Teis for providing the samples, technical advice and for their well wishes.
The quality of work was enriched through the presence of awesome colleagues in laboratory and office; Matthew Quinn, Dr. Dhivya Rajasekaran, Gurvinder Kalra, Dr. Vi Truong Khanh, Yen, Vy Pham, Dr. Hayden Webb, Dr. Mohammad Al-Kobaisi, Tasnuva Tamanna, Dr. Elizabeth Ouwar, Eng Hooi Tay (Nelson), Dr. Kaylass Poorun and Dr. Abirami Ramalingam. I owe a particular thanks to my fellow “VIDS” colleagues for sharing this PhD journey with me.
To my friends, Dr. Vandana Gulati, Dr. Pankaj Gulati, Dr. Avinash Karpe, Amol Ghodke, Mrudula Borse and Dr. Atul Kamboj and my niece Ryka, my housemates and friends in Australia, for their constant presence and unforgettable memories in Melbourne.
I would also like extend my heartfelt thanks to Dr. Makarand Jawadekar, Mr. Vidyadhar Jawadekar and Mr. Amitabh Mehta for their appreciation of my progress and their constant encouragement to excel. I would like to thank Professor Rainer Müller, the pioneer of the SLN technology for his encouraging words and useful insights on my research at the AAPS and the CRS conferences.
I am very grateful to Springer-Verlag, Heidelberg, Germany for encouraging and agreeing to publish “Lipid Nanoparticles – Production, Characterisation and Stability” as a SpringerBriefs in Pharmaceutical Sciences and Drug Development, specifically; Dr. Isabel Ullmann, Assistant Editor (Life Sciences/Biomedicine Europe II, Editorial); Dr. Jutta Lindenborn and Ms. Amudha Vijayarajan (Project Coordinators); Mrs. Gomathi
viii
Acknowledgements
Karthikeyan (Production Editor) and Mr. Ramasubramaniyan V. (Production Coordinator).
To my extended family; “Pradhim”, “Spectrum”, the Jadhavs, Venugopals, Mehtas, Kulkarnis, Shettys, Jains, Raskars, Mayurs, Sangares, Holays, Vaidyas, Wanis and Vaghelas. I am deeply humbled by the unwavering support received from you over the years. Thanks for the patience and taking care of family in my absence.
To my best friend Dr. Snehal Jadhav, no words can express, no act of gratitude can convey, what your support has meant to me. Thanks for listening to me, encouraging me over the years and finally pushing me over the finish line. Your presence made things easy for me in Melbourne. I owe this achievement to you!
I am extremely thankful to my family, the Shah-Mehta family. I have been extremely fortunate in my life to have you all who have shown me unconditional love and support. Thanks for always being there!
To my dearest sister Mayuri Shah, your love and support has always motivated me to work harder and do better. The relationship and bond that we share holds an enormous amount of meaning to me. I would like to extend heartfelt thanks for always lifting my spirits and leading me all the way.
Finally I would like to acknowledge the unending love, support and blessings of the two most important people in my life, my mom and my dad. I am sure that no one would be as proud of me as you two. If I have been able to walk thus far, and if I ever see further, it would always be by standing on your shoulders. You are my world! I will always be indebted to you both for all the sacrifices that you have made for Mayuri and me. Thanks for being our parents!
Rohan Shah
September 2015
ix
Declaration Declaration
I, Rohan Shah, hereby declare that the thesis titled “Microwave-assisted production of solid lipid nanoparticles” is no more than 100,000 words in length, exclusive of figures, tables, appendices and references. None of this material has been submitted previously, in whole or in part, for the award of any other degree or diploma at any university. This thesis contains no material previously published or written by another person, except where due reference is made in the text of the thesis. I warrant that I have obtained, where necessary, permission from the copyright owners to use any third party copyright material reproduced in the thesis or to use any of my own published work in which the copyright is held by another party.
Rohan Shah
February 2016
xi
Publications arising of this work Publications arising of this work
Books
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2015). Lipid Nanoparticles – Production, Characterisation and Stability, SpringerBriefs in Pharmaceutical Sciences and Drug Development, Springer, ISBN 978-3-319-10711-0.
Peer-reviewed journal articles
Shah, R., Rajasekaran, D., Ludford-Menting, M., Eldridge, D., Palombo, E. and Harding, I., (2016). Transport of stearic acid-based solid lipid nanoparticles (SLNs) into human epithelial cells, Colloids and Surfaces B: Biointerfaces, 140: 204-212.
Shah, R., Malherbe, F., Eldridge, D., Palombo, E. and Harding, I., (2014). Physicochemical characterisation of solid lipid nanoparticles (SLNs) prepared by a novel microemulsion technique, Journal of Colloid and Interface Science, 428: 286-294.
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2014). Optimisation and Stability Assessment of Solid Lipid Nanopa rticles using Particle Size and Zeta Potential, Journal ofh P ysical Science, 25: 59-75.
Conferences: Oral presentations
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2014). Formulation and characterisation of non-steroidal anti-inflammatory drug (NSAID)-loaded solid lipid nanoparticles (SLNs) by a novel microwave-based technique, 29th Australian Colloid and Surface Science Student Conference, Ballarat, Australia (Feb 2-7)
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2013). Optimisation and stability assessment of solid lipid nanoparticles using particle size and zeta potential, 4th International Conference for Young Chemists, Penang, Malaysia (Jan 31- Feb 3)
Conferences: Poster presentations
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2015). Non-steroidal anti- inflammatory drugs encapsulated into solid lipid nanoparticles: Characterisation,
xiii
Publications arising of this work cytotoxic and anti-inflammatory studies, 42nd Annual Meeting & Exposition of the Controlled Release Society, Edinburgh, Scotland (Jul 26-29)
Shah, R., Rajasekaran, D., Ludford-Menting, M., Eldridge, D., Palombo, E. and Harding, I., (2015). Solid lipid nanoparticles as intracellular drug transporters: An investigation of the uptake mechanism and pathway in epithelial cells, 42nd Annual Meeting & Exposition of the Controlled Release Society, Edinburgh, Scotland (Jul 26- 29)
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2015). Encapsulation of antifungal agents into solid lipid nanoparticles: Physicochemical characterisation and biocompatibility studies, 42nd Annual Meeting & Exposition of the Controlled Release Society, Edinburgh, Scotland (Jul 26-29)
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2015). Encapsulation, cytotoxic and anti-inflammatory effects of non-steroidal anti-inflammatory drugs into stearic acid lipid nanoparticles, 7th Biennial Australian Colloid and Interface Symposium, Hobart, Australia (Feb 1-5)
Shah, R., Eldridge, D., Palombo, E. and Harding, I., (2014). Physicochemical analysis of solid lipid nanoparticles engineered by a novel microemulsion technology, 5th Pharmaceutical Sciences World Congress, Melbourne, Australia (Apr 13-16)
Shah, R., Malherbe, F., Eldridge, D., Palombo, E. and Harding, I., (2013). Novel microemulsion- based technique for improved production of solid lipid nanoparticles (SLNs), AAPS Annual Meeting and Exposition, San Antonio, United States of America (Nov 10-14)
Shah, R., Malherbe, F., Eldridge, D., Palombo, E. and Harding, I., (2013). Characterisation and production of solid lipid nanoparticles by microemulsion technique: Conventional conductive heating vs. Novel microwave heating, Drug Delivery Australia, Sydney, Australia (Oct 24-25)
Shah, R., Malherbe, F., Eldridge, D., Palombo, E. and Harding, I., (2012). Particle size and zeta potential of solid lipid nanoparticles, Drug Delivery Australia, Melbourne, Australia (Nov 26-27)
xiv
Table of contents Table of Contents
Contents Page
Abstract of the thesis Iii
Dedication V
Acknowledgements vii
Declaration xi
Publications arising out of this thesis xiii
Table of contents xv
List of Tables xxvii
List of Figures xxxi
Abbreviations xxxvii
Chapter 1: Literature Review 1
1.1 Rationale behind the Introduction of Colloidal Drug Carriers 2
1.2 Introduction to Colloidal Drug Carriers 3
1.2.1 Nanocapsules and polymeric nanoparticles 4
1.2.2 Liposomes 4
1.2.3 Nanoemulsions and microemulsions 5
1.3 Lipid nanoparticles – History and Scope 6
1.4 Lipid nanoparticles – Types 10
1.4.1 Solid lipid nanoparticles (SLNs) 10
1.4.2 Nanostructured lipid carriers (NLCs) 12
1.4.3 Lipid-drug conjugates (LDCs) 12
1.4.4 Polymer-lipid hybrid nanoparticles (PLNs) 13
1.5 Production of Solid Lipid Nanoparticles 14
1.6 Introduction to the Microemulsion Technique of SLN Production 20
1.7 Conventional thermal heating Vs. Microwave heating 21
xv Table of contents
Contents Page
1.8 Microwave Technology 22
1.8.1 Introduction to microwaves 23
1.8.2 Microwave theory 24 1.8.2.1 Frictional heating 25 1.8.2.2 Ohmic heating 26
1.8.3 Dielectric properties of materials 27
1.8.4 Microwave-assisted microemulsion technique of SLN 29 production
1.9 Physicochemical Characterisation of SLNs 29
1.9.1 Particle size 30
1.9.2 Particle morphology and ultrastructure 32
1.9.3 Crystallinity and polymorphism 33
1.9.4 Surface charge 35
1.10 Structure of SLNs 38
1.10.1 Drug-enriched shell model 38
1.10.2 Drug-enriched core model 39
1.10.3 Solid Solution model 39
1.11 Stability of SLNs 40
1.11.1 Electrostatic stabilisation 41
1.11.2 Steric stabilisation 44
1.12 Drug Release Mechanisms 44
Chapter 2: Research Objectives and Organisation of Thesis 49
2.1 Research Objectives 50
2.2 Organisation of the thesis 52
Chapter 3: Experimental Section 55
3.1 Materials 56
xvi Table of contents
Contents Page
A. Production, physicochemical characterisation and in vitro release 56 studies
3.1.1 Solid lipids 56
3.1.2 Surfactants and stabilisers 57
3.1.3 Drug substances 57
3.1.4 Other chemicals 57
B. In vitro cell culture studies 57
3.1.5 Cells 57
3.1.6 Cell culture media and other chemicals 58
3.2 Instrumentation 59
3.2.1 Discover LabMate Microwave system 59
3.2.2 BIC-90Plus Particle analyser 59
3.2.3 Partica LA-950V2 63
3.2.4 Shimadzu UFLC system 64
3.2.5 2920 Modulated DSC 65
3.2.6 D8 Advance Diffractometer 66
3.3 Methods 68
A. Production, physicochemical characterisation and in vitro drug 68 release studies
3.3.1 Production of solid lipid nanoparticles (SLNs) 68
3.3.2 Particle characterisation 69 3.3.2.1 Dynamic light scattering (DLS) 69 3.3.2.2 Laser diffraction (LD) 70 3.3.2.3 Zeta potential 73 3.3.2.4 Scanning laser microscopy (SEM) 73 3.3.2.5 Measurements of pH 74
3.3.3 Encapsulation efficiency (EE) and loading capacity (LC) 74 measurements
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Contents Page
3.3.4 Separation effectiveness of centrifugal ultrafiltration 76
3.3.5 In vitro drug release studies 76
3.3.6 Determination of drugs by high performance liquid 78 chromatography (HPLC)
3.3.7 Differential scanning calorimetry (DSC) analysis 78
3.3.8 X-ray diffraction (XRD) analysis 79
B In vitro cell culture studies 79
3.3.9 Thawing of cells 79
3.3.10 Subculturing of cells 80
3.3.11 Cryopreservation of cells 80
3.3.12 Cell viability assay 81
3.2.13 Statistical analysis 81
3.4 Preparation of buffers and media 82
A. Phosphate buffer saline (PBS) pH 7.4 82
B. Cell culture 82
3.4.1 Complete DMEM 82
3.4.2 Cell freezing media 83
3.4.3 Potassium-free medium 83
C. Antimicrobial assays 84
D. Simulated gastrointestinal (GI) fluids 84
Chapter 4: Introduction and Optimisation of A Novel Microwave-assisted 85 Microemulsion Technique for Production of SLNs
Abstract 86
4.1 Introduction 87
4.2 Chapter Aims 89
4.3 Methods 90
xviii Table of contents
Contents Page
4.3.1 Preparation of solid lipid nanoparticles (SLNs) and solid lipid 90 microparticles (SLMs)
4.3.2 Particle characterisation 90
4.3.3 Selection of Formulation 90 4.3.3.1 Design of Experiment (DoE) 90 4.3.3.2 Formulation annotation 91
4.3.4 Influence of solvents for preparation of SLNs 92
4.3.5 Evaluation of formulation parameters 92 4.3.5.1 Influence of excipients 92 4.3.5.2 Short-term storage stability 94
4.4 Results and Discussion 95
4.4.1 Preparation of SLNs 95
4.4.2 Selection of the formulation 95 4.4.2.1 Assessment of particle size and PI 95 4.4.2.2 Assessment of zeta potential 103
4.4.3 Influence of solvents 105
4.4.4 Evaluation of formulation parameters 108 4.4.4.1 Influence of the amount of stearic acid and Tween® 20 108 4.4.4.2 Influence of acid, base and salt 109 4.4.4.3 Influence of co-emulsifiers 110 4.4.4.4 Influence of stabilisers 112 4.4.4.5 Short-term stability 112
4.5 Conclusions 115
Chapter 5: Physicochemical Characteristics of SLNs: Microwave-assisted 117 microemulsion technique Vs. Conventional microemulsion technique
Abstract 118
5.1 Introduction 119
5.2 Chapter Aims 122
5.3 Methods 123
xix Table of contents
Contents Page
5.3.1 Screening of lipids 123
5.3.2 Preparation of SLNs 123 5.3.2.1 Conventional microemulsion technique 123 5.3.2.2 Novel microwave-assisted microemulsion technique 124
5.3.3 Particle characterisation 125 5.3.3.1 Determination of hydrodynamic diameter and PI 125 5.3.3.2 Zeta potential measurements 125
5.3.4 Determination of tetracycline by HPLC 125
5.3.5 Encapsulation efficiency and loading capacity measurements 126
5.3.6 Crystallinity of SLNs 126
5.3.7 Short-term stability of SLN dispersions 127
5.3.8 In vitro drug release studies 127
5.3.9 Investigation of antimicrobial susceptibility of the tetracycline- 127 loaded SLNs
5.3.10 Evaluation of cell viability of SLN dispersions 128
5.4 Results and Discussions 129
5.4.1 Screening of lipids 129
5.4.2 Preparation of SLNs 130
5.4.3 Particle characterisation 131
5.4.4 Encapsulation efficiency and loading capacity measurements 134
5.4.5 Crystallinity of SLNs 135
5.4.6 Short-term stability studies 141
5.4.7 In vitro drug release studies 143
5.4.8 Antimicrobial susceptibility studies 144
5.4.9 Cell viability after exposure to SLNs 145
5.5 Conclusions 146
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Contents Page
Chapter 6: Incorporation of Non-Steroidal Anti-Inflammatory Drugs 147 (NSAIDs) into SLNs
Abstract 148
6.1 Introduction 149
6.2 Chapter Aims 153
6.3 Methods 154
6.3.1 Preparation of SLNs 154
6.3.2 Particle characterisation 154 Determination of hydrodynamic diameter and PI using DLS 154 Determination of particle diameter using LD 154 Zeta potential measurements 154 Scanning electron microscopy (SEM) 154
6.3.3 Determination of NSAIDs by HPLC 155
6.3.4 Encapsulation efficiency and loading capacity measurements 155
6.3.5 Crystallinity of SLNs 156
6.3.6 Evaluation of cell viability of SLN dispersions 156
6.3.7 Evaluation of anti-inflammatory activity of drug-loaded SLNs 157 on lipopolysaccharide (LPS)-induced A549 cells
6.4 Results and Discussion 158
6.4.1 Preparation of SLNs 158
6.4.2 Particle characterisation 158
6.4.3 Separation of SLNs and encapsulation studies 162
6.4.4 Crystallinity of SLNs 164
6.4.5 In vitro cell culture studies 167 6.4.5.1 Cell viability assay 167 6.4.5.2 Anti-inflammatory activity by inhibition of IL-6 and 167 IL-8 in LPS-induced A549 cells
6.5 Conclusions 172
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Chapter 7: Incorporation of Anti-fungal agents into SLNs 173
Abstract 174
7.1 Introduction 175
7.2 Chapter Aims 179
7.3 Methods 180
7.3.1 Preparation of SLNs 180
7.3.2 Particle characterisation 180 Determination of hydrodynamic diameter and PI using DLS 180 Determination of particle diameter using LD 180 Zeta potential measurements 180 Scanning electron microscopy (SEM) 180
7.3.3 Determination of anti-fungal drugs by HPLC 181
7.3.4 Encapsulation efficiency and loading capacity measurements 181
7.3.5 Crystallinity of SLNs 182
7.3.6 Evaluation of cell viability of SLN dispersions 182
7.3.7 Evaluation of anti-fungal activity of drug-loaded SLNs on 183 Candida albicans
7.4 Results and Discussion 184
7.4.1 Preparation of SLNs 184
7.4.2 Particle characterisation 184
7.4.3 Separation of SLNs and encapsulation studies 187
7.4.4 Crystallinity of SLNs 189
7.4.5 Cell viability assay 192
7.4.6 Anti-fungal activity on C. albicans 193
7.5 Conclusions 195
xxii Table of contents
Contents Page
Chapter 8: In vitro Drug Release Properties of SLNs 197
Abstract 198
8.1 Introduction 199
8.2 Chapter Aims 206
8.3 Methods 207
8.3.1 Determination of drugs by HPLC analysis 207
8.3.2 In vitro drug release studies 207
8.3.3 Drug Release data modelling 208
8.3.4 Evaluation of release profile comparison 208
8.3.5 Data fitting and statistical analysis 209
8.4 Results and Discussion 210
8.4.1 Drug release studies of SLNs loaded with NSAIDs 210 8.4.1.1 Indomethacin-loaded SLNs 210 8.4.1.2 Ketoprofen-loaded SLNs 214 8.4.1.3 Nimesulide-loaded SLNs 217
8.4.2 Summary of release of NSAIDs from SLNs 219
8.4.3 Drug release studies of SLNs loaded with anti-fungal drugs 220 8.4.3.1 Miconazole nitrate-loaded SLNs 220 8.4.3.2 Econazole nitrate-loaded SLNs 224 8.4.3.3 Clotrimazole-loaded SLNs 226
8.4.4 Summary of release of anti-fungal drugs from SLNs 228
8.4.5 Drug release comparison 230
8.5 Conclusions 234
Chapter 9: An Investigation of the Uptake Mechanism and Pathway of SLNs 235 used as intracellular drug transporters
Abstract 236
9.1 Introduction 237
xxiii Table of contents
Contents Page
9.2 Chapter Aims 241
9.3 Methods 242
9.3.1 Preparation of SLNs 242
9.3.2 Particle Characterisation 242 Determination of hydrodynamic size and PI using DLS 242 Determination of particle diameter using LD 242 Zeta potential measurements 242
9.3.3 Crystallinity of SLNs 243
9.3.4 Evaluation of cell viability of SLN dispersions 243
9.3.5 Fluorescence Microscopy 244
9.3.6 Fluorescence-assisted cell sorting (FACS) or flow cell 245 cytometry
9.3.7 Confocal Laser Scanning Microscopy (CLSM) 245
9.3.8 Investigation of SLN uptake by human epithelial cells 246 9.3.8.1 Inhibition of endocytosis 246 9.3.8.2 Inhibition of clathrin-mediated endocytosis 246 9.3.8.3 Inhibition of caveolae-mediated endocytosis 247 9.3.8.4 Inhibition of micropinocytosis 247
9.4 Results and Discussion 248
9.4.1 Preparation and Characterisation of SLNs 248
9.4.2 Crystallinity of SLNs 250
9.4.3 Cell viability of SLN dispersions 252
9.4.4 Investigation of cellular uptake pathway 253
9.5 Conclusions 269
Chapter 10: A pH-dependent study on the stability of SLNs 271
Abstract 272
10.1 Introduction 273
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Contents Page
10.1.1 Electrostatic stabilisation 274
10.1.2 Steric stabilisation 275
10.2 Chapter Aims 277
10.3 Methods 278
10.3.1 Preparation of SLNs 278
10.3.2 Particle characterisation 278 Determination of particle size and PI using DLS 278 Determination of zeta potential 278
10.3.3 Stability studies 278 Effect of pH on particle size and zeta potential 278 Effect of simulated gastrointestinal (GI) fluids 279
10.3.4 Encapsulation efficiency and loading capacity measurements 279
10.4 Results and Discussions 281
10.4.1 Influence of pH on the physical stability of drug-free SLNs 281
10.4.2 Influence of drug incorporation on pH-dependent stability of 285 SLNs
10.4.3 Effect of simulated GI fluids 290
10.5 Conclusions 293
Chapter 11: Summary of Conclusions and Future Perspectives 295
11.1 Conclusions 296
11.1.1 Introduction and Optimisation of A Novel Microwave- 296 assisted Microemulsion Technique for Production of SLNs
11.1.2 Physicochemical Characteristics of SLNs: Microwave- 297 assisted microemulsion technique Vs. Conventional microemulsion technique
11.1.3 Incorporation of NSAIDs into SLNs 299
11.1.4 Incorporation of Anti-fungal agents into SLNs 300
11.1.5 In vitro Drug Release Properties of SLNs 301
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11.1.6 An Investigation of the Uptake Mechanism and Pathway of 303 SLNs used as intracellular drug transporters
11.1.7 An Investigation of the pH-dependence and electrolyte- 304 dependence on the physical stability of the SLNs
11.1.8 Summary of Conclusions 306
11.2 Future Perspectives 307
11.2.1 Preparation of the SLNs 307
11.2.2 Structure of the SLNs 307
11.2.3 Stability of the SLNs 308
11.2.4 Drug release studies 309
11.2.5 In vivo studies 309
References 311
Appendices 359
xxvi List of tables List of Tables
Table Title Page
1.1 Examples of drug substances encapsulated into lipid nanoparticles 7
1.2 Currently marketed cosmetic products containing lipid nanoparticles 9
1.3 Comparison of colloidal drug carriers 11
Mechanisms, advantages and disadvantages of methods used in the 1.4 15 production of lipid nanoparticles
The ISM frequencies allowed according to the international 1.5 24 agreements
1.6 Dielectric properties of different solvents 28
3.1 The specifications of UFLC system 65
3.2 Composition of phosphate buffered saline (pH 7.4) 82
3.3 Composition of complete DMEM used in cell culture 83
Composition of cell freezing medium used in cryopreservation of 3.4 83 cells
3.5 Composition of potassium-free medium 83
3.6 Microbiological media used in this study 84
3.7 Composition of simulated GI fluids 84
4.1 DoE: Factors and levels for 22 factorial designs 91
4.2 DoE: Factors and levels for full factorial designs 92
4.3 Composition of stearic acid-based SLNs 93
4.4 Particle characteristics of SLNs stabilised with Tween® 20 96
4.5 Particle characteristics of SLNs stabilised with Tween® 80 97
4.6 Particle characteristics of SLNs stabilised with Cremophor® EL 97
Particle size characteristics of lipid particle dispersions prepared 4.7 98 using other lipid-surfactant combinations
Zeta potential of stearic acid-based and Imwitor® 900K-based SLNs 4.8 104 stabilised with surfactants
xxvii List of tables
Table Title Page
4.9 Dielectric properties of solvents relevant to this study 106
5.1 Composition of drug-free and tetracycline-loaded SLNs 123
5.2 HPLC method for analysis of tetracycline 125
5.3 Screening of lipids based on solubility of tetracycline 129
Encapsulation efficiency and loading capacity of tetracycline-loaded 5.4 134 SLNs
5.5 DSC data of tetracycline-loaded SLNs 136
5.6 Anti-microbial activity of SLNs 144
Physicochemical properties of non-steroidal anti-inflammatory drugs 6.1 151 employed as model drugs in this study
6.2 HPLC method for analysis of NSAIDs 155
6.3 Particle characterisation of SLNs loaded with NSAIDs 158
Encapsulation efficiency and loading capacity of SLNs loaded with 6.4 163 NSAIDs
6.5 DSC data of SLNs loaded with NSAIDs 164
Physicochemical properties of anti-fungal drugs employed as model 7.1 178 drugs in this study
7.2 HPLC method for analysis of anti-fungal agents 181
7.3 Particle characterisation of SLNs loaded with anti-fungal drugs 184
Encapsulation efficiency and loading capacity of SLNs loaded with 7.4 189 anti-fungal drugs
7.5 DSC data of SLNs loaded with anti-fungal drugs 190
Anti-Candida albicans activity of SLNs loaded with anti-fungal 7.6 193 drugs
Release exponents and release mechanisms from polymeric dosage 8.1 203 forms
8.2 HPLC method for analysis of drugs encapsulated in SLNs 207
8.3 Model fitting of indomethacin release profiles 213
xxviii List of tables
Table Title Page
8.4 Model fitting of ketoprofen release profiles 216
8.5 Model fitting of nimesulide release profiles 218
Comparative summary of parameters for release of NSAIDs from 8.6 220 SLNs
8.7 Model fitting of miconazole nitrate release profiles 222
8.8 Model fitting of econazole nitrate release profile 225
8.9 Model fitting of clotrimazole release profile 227
Comparative summary of parameters for release of anti-fungal drugs 8.10 230 from SLNs
Comparison of release profiles of nimesulide (reference) and 8.11 232 miconazole nitrate (test) by model-independent approaches
9.1 Pharmacologic inhibitors of specific endocytosis pathway 247
9.2 Physical characteristics of SLNs used in cellular uptake studies 248
9.3 DSC analysis of SLNs used in cellular uptake studies 250
10.1 Zeta potential of SLNs from previous chapters 273
xxix
List of figures List of Figures
Figure Title Page
1.1 The Biopharmaceutical Classification System 2
1.2 Types of lipid nanoparticles 10
A schematic depiction of the steps involved in the microemulsion 1.3 21 technique of SLN production
1.4 The electromagnetic spectrum 24
1.5 Typical microwave radiation 25
1.6 Frictional heating due to dipolar polarisation 26
1.7 Ohmic heating to charge polarisation 26
1.8 Schematic representation of an electrical double layer 36
1.9 Drug incorporation models of solid lipid nanoparticles 38
1.10 Schematic form of potential energy vs. distance curve 42
3.1 A typical microwave reactor 59
3.2 A typical setup of a DLS instrument 60
3.3 A schematic representation of a HPLC setup 65
3.4 A cutaway view of a standard DSC cell 66
3.5 A schematic representation of an X-ray diffractometer 67
3.6 Influence of real refractive index on the diameters of drug-free SLNs 71
Contour plots from particle size analysis of SLNs stabilised with 4.1 101 Tween® 20
Contour plots from particle size analysis of SLNs stabilised with 4.2 101 Tween® 80
Contour plots from particle size analysis of SLNs stabilised with 4.3 102 Cremophor® EL
4.4 Effect of solvents on particle characteristics of SLNs 107
Particle characteristics of stearic acid-based SLNs stabilised with 4.5 108 Tween® 20
xxxi
List of figures
Figure Title Page
4.6 Particle characteristics of SLNs on addition of acid, base and salt 109
4.7 Effect of co-emulsifiers on particle characteristics of SLNs 111
4.8 Effect of stabiliser on particle characteristics of SLNs 112
4.9 Short-term stability of SLNs stored at 4°C 113
5.1 Chemical structure of tetracycline 121
5.2 Particle size of drug-free and tetracycline-loaded SLNs 131
5.3 Polydispersity index of drug-free and tetracycline-loaded SLNs 132
5.4 Zeta potential of SLNs drug-free and tetracycline-loaded SLNs 133
5.5 DSC analysis of drug-free and tetracycline-loaded SLNs 137
5.6 XRD analysis drug-free and tetracycline-loaded SLNs 140
5.7 Short-term stability studies of SLNs dispersions at 4°C 142
Drug release profiles of tetracycline-loaded SLNs in phosphate 5.8 143 buffered saline (PBS, pH 7.4) at 37°C
Viability of A549 cells measured by MTT assay for tetracycline- 5.9 145 loaded SLNs
6.1 Biosynthesis of prostaglandins and thromboxane 150
6.2 SEM image of drug-free SLNs viewed at 60,000× magnification 159
SEM image of indomethacin-loaded SLNs viewed at 60,000× 6.3 159 magnification
SEM image of ketoprofen-loaded SLNs viewed at 60,000× 6.4 159 magnification
SEM image of nimesulide-loaded SLNs viewed at 40,000× 6.5 159 magnification
6.6 Light scattering of nimesulide-loaded SLNs in water 163
6.7 DSC analysis of SLNs loaded with NSAIDs 165
6.8 XRD analysis of SLNs loaded with NSAIDs 167
Viability of A549 cells measured by MTT assay for SLNs loaded with 6.9 168 NSAIDs
xxxii
List of figures
Figure Title Page
Viability of 3T3-L1 cells measured by MTT assay for SLNs loaded 6.10 168 with NSAIDs
Inhibition of IL-6 expression in LPS-induced A549 cells by SLNs 6.11 170 loaded with NSAIDs
Inhibition of IL-8 expression in LPS-induced A549 cells by SLNs 6.12 171 loaded with NSAIDs
SEM image of clotrimazole-loaded SLNs viewed at 60,000× 7.1 185 magnification
SEM image of miconazole nitrate-loaded SLNs viewed at 60,000× 7.2 185 magnification
SEM image of econazole nitrate-loaded SLNs viewed at 60,000× 7.3 185 magnification
7.4 Light scattering of clotrimazole-loaded SLNs in water 188
7.5 DSC analysis of SLNs loaded with anti-fungal drugs 189
7.6 XRD analysis SLNs loaded with anti-fungal drugs 191
Viability of A549 cells measured by MTT assay for SLNs loaded with 7.7 192 anti-fungal drugs
Viability of 3T3-L1 cells measured by MTT assay for SLNs loaded 7.8 193 with anti-fungal drugs
8.1 In vitro drug release of indomethacin from SLNs 210
8.2 Schematic diagram showing biphasic release of drugs from SLNs 211
8.3 In vitro drug release of ketoprofen from SLNs 215
8.4 In vitro drug release of nimesulide from SLNs 217
8.5 Overlay of drug release profiles of NSAIDs from SLNs 219
8.6 In vitro drug release of miconazole nitrate from SLNs 221
8.7 In vitro drug release of econazole nitrate from SLNs 224
8.8 In vitro drug release of clotrimazole from SLNs 226
8.9 Overlay of drug release profiles of anti-fungal drugs from SLNs 229
xxxiii
List of figures
Figure Title Page
Comparison of release of indomethacin (acidic) and miconazole 8.10 231 nitrate (basic) from SLNs
9.1 Major endocytic pathways of uptake in cells 240
9.2 Chemical structure of Rhodamine 123 240
Crystallinity of SLNs as conducted by (a) differential scanning 9.3 251 calorimetry (DSC) and (b) X-ray diffraction (XRD) analysis
Viability of A549 cells incubated with SLNs used in cellular uptake 9.4 253 studies
Viability of HeLa cells incubated with SLNs used in cellular uptake 9.5 253 studies
Uptake of SLNs by A549 cells as investigated by fluorescence 254- 9.6 imaging 255
Uptake of SLNs by HeLa cells as investigated by fluorescence 256- 9.7 imaging 257
FACS data showing cellular uptake of non-fluorescent SLNs at 37C 9.8 259 and fluorescent SLNs at 4C and 37C by A549 cells
FACS data showing cellular uptake of non-fluorescent SLNs at 37C 9.9 260 and fluorescent SLNs at 4C and 37C by HeLa cells
261- 9.10 Uptake of SLNs by A549 cells as investigated by CLSM imaging 262
263- 9.11 Uptake of SLNs by HeLa cells as investigated by CLSM imaging 264
FACS data showing inhibition of clathrin-mediated endocytosis in 9.12 266 A549 cells at 37C
FACS data showing inhibition of clathrin-mediated endocytosis in 9.13 267 HeLa cells at 37C
A schematic diagram of the fraction of stearic acid and stearate ions 10.1 275 in solution as a function of pH
10.2 A schematic diagram of the surface of the stearic acid-based SLNs 280
10.3 Particle sizes of drug-free SLNs as a function of pH 282
10.4 Zeta potentials of drug-free SLNs as a function of pH 282
xxxiv
List of figures
Figure Title Page
A schematic representation of the surface of a stearic acid-based SLN 10.5 suspended in an aqueous solution (i.e. SLNs dispersion) as a function 284 of pH.
10.6 Particle sizes of indomethacin-loaded SLNs as a function of pH 286
10.7 Particle sizes of miconazole nitrate-loaded SLNs as a function of pH 286
10.8 Zeta potential of indomethacin-loaded SLNs as a function of pH 287
10.9 Zeta potential of miconazole nitrate-loaded SLNs as a function of pH 287
10.10 The effect of pH on the encapsulation efficiency of SLNs 289
10.11 The effect of pH on the loading capacity of SLNs 290
The effect of gastrointestinal fluids on the particle sizes of drug-free 10.12 290 SLNs
The effect of gastrointestinal fluids on the particle sizes of 10.13 291 indomethacin-loaded SLNs
The effect of gastrointestinal fluids on the particle sizes of miconazole 10.14 291 nitrate-loaded SLNs
xxxv
Abbreviations Abbreviations
AFM Atomic force microscopy
AIC Akaike information criterion
ANOVA Analysis of variance
BCS Biopharmaceutics Classification System
BHIB Brain heart infusion broth
C888 Compritol® 888 ATO
CEL Cremophor® EL
CLSM Confocal laser scanning microscopy
CMC Critical micelle concentration
COX Cyclooxygenase
CP Cetyl palmitate
D114 Dynasan® 114
DAPI 4’, 6-diamidino-2-phenylindole, dihydrochloride
DF Drug-free
DL Drug-loaded
DLS Dynamic light scattering
DLVO Deraguin Landau Verwey Overbeek
DMEM Dulbecco’s Modified Eagle’s Medium
DMSO Dimethyl sulfoxide
DoE Design of Experiment
DSC Differential scanning calorimetry
EDL Electrical double layer
EDTA Ethylene diamine tetra acetic acid
xxxvii Abbreviations
EE Encapsulation efficiency
ELISA enzyme-linked immunosorbent assay
ELS electrophoretic light scattering
FACS Flow-assisted cell sorting
FBS Fetal bovine serum
GI Gastrointestinal
GIT Gastrointestinal tract
GRAS Generally-recognised-as-safe
HLB Hydrophilic lipophilic balance
HPLC High performance liquid chromatography
I900 Imwitor® 900K
IL Interleukin
ISM Industrial, Scientific and Medical
ISO International Standards Organisation
LC Loading capacity
LD Laser diffraction
LDC Lipid-drug conjugate
LED Light emitting diode
LPS Lipopolysaccharide
MIC Minimum inhibitory concentration
MSC model selection criterion
MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide
NB Nutrient agar
NLC Nanostructured lipid carrier
xxxviii Abbreviations
NSAID Non-steroidal anti-inflammatory drug
o/w Oil-in-water
PALS Phase analysis light scattering
PBS Phosphate buffered solution
PCS Photon correlation spectroscopy
PGTS prostaglandin-endoperoxide synthases
PI Polydispersity index
QELS Quasi elastic light scattering
R123 Rhodamine 123
RES Reticuloendothelial system
RI Recrystallisation index
SA Stearic acid
SD Standard deviation
SDB Sabouraud dextrose broth
SEM Scanning electron microscopy
SLM Solid lipid microparticles
SLN Solid lipid nanoparticle
T20 Tween® 20
T80 Tween® 80
TEM Transmission electron microscopy
WE85 Witepsol® E85
XRD X-ray diffraction
xxxix
Chapter 1 Literature review 1
Literature Review
1 Chapter 1 Literature review
1.1 Rationale behind the Introduction of Colloidal Drug Carriers
Ever-emerging technologies, such as lead optimisation, computational and combinatorial chemistry, have been, and will continue to remain, major contributors of advances in drug discovery. Despite great success in these drug discovery programmes, only a few molecules find their way into clinical use as drugs. High lipophilicity and, intrinsically low water solubility are common characteristics of the hits, leads and development candidates from such drug discoveries (Porter et al., 2007). While many of these drug candidates have exceptional in vitro potency, compromises have to be made due to their low water solubility; this presents a significant challenge in the drug discovery and development process. Additionally, the risk of reduced and variable absorption after oral administration is a major concern. Drug absorption is primarily dependent on water solubility, although a number of variables such as drug permeability, dose and the surrounding biological environment are important factors (Williams et al., 2013).
The Biopharmaceutics Classification System (BCS) was first developed by Amidon et al. (1995) to further illustrate the relationship between solubility-permeability on oral absorption of various drugs. Figure 1.1 depicts the four classes of drug substances categorised using the principles of BCS. A detailed description of the principles of BCS is documented elsewhere (Chen et al., 2011; Dahan et al., 2009; Yu et al., 2002).
Class II Class I
Low solubility High solubility → High permeability High permeability
Class IV Class III
Permeability Permeability Low solubility High solubility Low permeability Low permeability
Solubility →
Figure 1.1 The Biopharmaceutical Classification System (adapted from Amidon et al., 1995).
The Class II category is most relevant for drug substances that have high potency but often face challenges due to limited water solubility. Lack of water solubility is a significant risk factor because it often results in poor and highly variable bioavailability,
2 Chapter 1 Literature review patient non-compliance and drug precipitation after dosing (Merisko-Liversidge and Liversidge, 2008). Poor water solubility of drugs limits development of formulations deliverable by oral and parenteral routes. The focus, therefore, is often on the development of drug delivery systems for effective transport of Class II drugs. Class IV drugs are also relevant, but have an additional problem associated with low permeability.
Several formulation strategies have been reported to address solubility issues including size reduction, complexation and solubilisation in surfactant solutions, pro-drug designing, derivatisation, modulation of crystallinity and encapsulation (Bikiaris, 2011). Despite these efforts, however, roughly 70 - 75% of development candidates and approximately 40% of currently marketed drugs are practically insoluble (Di et al., 2009, 2011; Kawabata et al., 2011; Williams et al., 2013).
1.2 Introduction to Colloidal Drug Carriers
A more recent and successful strategy to improve solubility is encapsulation of the drug into a colloidal carrier system. Colloidal carriers protect the drug from biological degradation, modulate release kinetics of the drug and modify its biodistribution (Bunjes and Siekmann, 2005). The rationale for introducing colloidal drug carriers is to achieve the most optimised therapeutic outcomes for the encapsulated drug substances. The use of colloidal drug carriers in drug delivery not only improves the therapeutic index but also reduces the associated side effects (Jaafar-Maalej et al., 2012). There is increasing optimism that these carriers will elicit significant and innovative benefits in early diagnosis, prevention and control of disease. Thus, there is an increasing emphasis on the development of such drug carriers. Nanocapsules and polymeric nanoparticles are polymer-based colloidal systems used in drug delivery applications. Lipid-based colloidal carriers have been introduced to overcome the toxicological issues exhibited by polymeric systems. Prominent research has been carried out on lipid systems such as liposomes, nanoemulsions, micelles, cubosomes and lipid nanoparticles (Arias, 2013; Garg and Goyal, 2014; Gong et al., 2012; Mulet et al., 2013; Müller et al., 2011; Pan et al., 2013; Rizwan and Boyd, 2015; Rösler et al., 2012; Weber et al., 2014; Yoon et al., 2013).
3 Chapter 1 Literature review
1.2.1 Nanocapsules and polymeric nanoparticles
Nanocapsules are polymeric carriers which form a barrier between the oil (core) and the surrounding aqueous dispersion. Solvent displacement and interfacial polymerisation are the two most commonly employed nanocapsule production methods (Alvarez-Román et al., 2001; Andrieu et al., 1989; Couvreur et al., 2002; Mora-Heurtas et al., 2012; Xi et al., 2012). Polymeric nanoparticles are composed of biodegradable macromolecular polymers (Barratt et al., 2000). Several procedures, including interfacial polymerisation (Kreuter, 1994), micro fluidisation (Bodmeier et al., 1990), solvent evaporation (Venier- Julienne and Benoit, 1996), solvent diffusion and high sheer homogenisation (Gurny et al., 1981), have been employed to prepare polymeric nanoparticles. However, preparation of polymer-based colloidal carriers can involve the use of toxicologically harmful reactive cross-linkers and carcinogenic monomers. Complete removal of these constituents is a difficult task (Reis et al., 2006). Moreover, slow degradation of the polymer results in its accumulation, and the possible production of toxic metabolites (Bunjes and Siekmann, 2005). Despite these limitations, nanocapsules have proven commercially successful, and polymeric injectable depot formulations, such as Lupron® (leuprolide), Nutropin® (recombinant human growth hormone), Sandostatin® (octreotide), Decapeptyl® (triptorelin) and Parlodel® (bromocriptine) are being marketed.
1.2.2 Liposomes
Liposomes, considered to be the original drug carriers, were first described in 1965 as a cell membrane model (Bangham et al., 1965). However, it was not until around 1986 that they were introduced to the cosmetic market as drug carriers by Dior. The first dermal liposomal product was launched in the late 1980s as Pevaryl®-Lipogel, produced and marketed by Cilag A. G. (Naeff, 1996). Successful development of intravenous liposomal formulations, such as Doxyl®, Caelyx® (both doxorubicin), DaunoXome® (daunorubicin) and AmBisome® (amphotericin B), and dermal formulations, such as “Capture”, have demonstrated the usefulness of liposomes as lipid drug carriers. Liposomes can be prepared by several techniques including mechanical dispersion, solvent dispersion and detergent dialysis (Akbarzadeh et al., 2013). Liposomes have been accepted for intravenous and topical application due to their composition (Torchilin, 2005). There are, however, some drawbacks associated with the storage stability of
4 Chapter 1 Literature review liposomes. Incorporation of drugs into the phospholipid bilayer may decrease their stability. The hydrolysis of the ester linkages and oxidation of unsaturated fatty acids often result in chemical instability. Liposomes often suffer rapid degradation due to the acidic pH in the gastrointestinal tract (GIT), specifically the stomach, or due to intestinal enzymes and bile salts when taken orally. Additional limitations, such as large scale manufacturing and sterilisation after production, make commercialisation of liposomes more difficult (de Mendoza et al., 2010).
1.2.3 Nanoemulsions and microemulsions
Parenteral emulsions have been used as calorie source for decades (Waitzberg et al., 2006). Parenteral emulsions are lipid emulsions which are essentially heterogeneous systems composed of two immiscible liquids (Tamilvanan, 2004). Whilst nanoemulsions are generally thermodynamically unstable, microemulsions can be thermodynamically stable; optically isotropic, transparent or translucent, mixtures of water, oil, surfactant and co-surfactant (McClements, 2012). These systems are produced in large quantities and also exhibit long-term stability. Due to these advantages, lipid emulsions have been employed as drug carriers. Several drug-loaded colloidal emulsions, including Daizemuls®/Diazepam-Lipuro® (diazepam), Liple® (alprostadil), Diprivan® (propofol), Limethason® (dexamethasone palmitate, Lipo-NSAID®/Ropion® (flurbiprofen axetil) and Etomidat-li puro® (etomidate), are commercially available. However, there are some drawbacks associated with lipid emulsions. Drug molecules with high mobility in the liquid oil droplet may diffuse out of the droplet disturbing the stabilizing surfactant film. These effects may cause mechanical (film rupture or reduction in film elasticity) or electrochemical (modification of zeta potential) instabilities. Such instabilities can induce coalescence or particle growth (Washington, 1996). The high mobility of drug molecules from the emulsion droplets allows rapid equilibration in the aqueous phase, a phenomenon called “drug leakage”, and causes fast release of drugs. This limits the use of lipid emulsions as sustained-release formulations (Magenheim et al., 1993, Washington, 1996).
5 Chapter 1 Literature review
1.3 Lipid nanoparticles – History and Scope
Speiser (1986) were the first to use solid lipids in the preparation of nanopellets. They used high sheer homogenisers followed by ultrasonication to produce nanopellets for peroral administration. Lipospheres, which are carrier systems similar to nanopellets, were later produced by Domb (1993). The use of solid lipid-based particles as drug carriers has been greatly exploited ever since.
The use of solid lipid was introduced to lower drug mobility observed with liquid lipids. Reduction in mobility prevents drug leakage and also counteracts drug migration into the emulsifier film. The solid core of the colloidal carrier provides better physicochemical stability. A few of the advantages that the solid lipid imparts to the carrier system are outlined here:
Solid core o Enhanced physicochemical stability of colloidal carrier o Enhanced chemical stability of encapsulated drug molecules Reduced mobility of drug molecules o Enhanced mechanical stability o Reduction in electrochemical stability changes induced due to diffusing drug molecules o Prevention of drug leakage o Sustained-release of drugs Static emulsifier-particle interface o Facilitates surface modification o Facilitates drug targeting
Solid lipid nanoparticles (SLNs) are the first generation lipid nanoparticles. Gasco (1993) and Müller and Lucks (1996) prepared SLNs by different production techniques. The number of research groups actively involved in similar research increased rapidly in subsequent years. SLNs have roused increasing attention in the scientific community as promising drug carriers due to their simplicity and versatility. Second generation lipid nanoparticles, i.e. nanostructured lipid carriers (NLCs) and lipid-drug conjugates (LDCs), were developed in the early 2000s.
Lipid nanoparticles have been widely studied for delivery of drugs through dermal and transdermal (Gomes et al., 2014; Schäfer-Korting et al., 2007; Souto et al., 2007), peroral
6 Chapter 1 Literature review
(Jenning and Gohla, 2001), parenteral (Yang et al., 1999), ocular (Attama et al., 2008; Cavalli et al., 2002; Gasco et al., 2003), pulmonary (Chattopadhyay et al., 2007; Liu et al., 2008; Videira et al., 2002) and rectal (Sznitowska et al., 2000, 2001) routes. Illustrative examples of drugs relevant to different routes of administration that have been encapsulated into lipid nanoparticles are listed in Table 1.1.
Table 1.1 Examples of drug substances encapsulated into lipid nanoparticles
Drug Type of lipid Route of Reference nanoparticles administration
Apomorphine SLNs Oral Tsai et al., 2011
Acyclovir SLNs/NLCs Ocular Seyfoddin and Al-Kassas, 2013
Beclomethasone SLNs/NLCs Pulmonary Jaafar-Maalej et al., 2011
Bixin SLNs Oral Rao et al., 2014
Celecoxib NLCs Pulmonary and Joshi and Patravale, 2008; Topical Patlolla et al. 2010
Curcumin SLNs Oral Kakkar and Kaur, 2011; Kakkar et al., 2011
Digoxin SLNs Oral Hu et al., 2010
Docetaxel NLCs Parenteral Liu et al., 2011
Econazole SLNs Topical Passerini et al., 2009; Sanna et nitrate al., 2007
Emodin SLNs - Wang et al., 2012
Finasteride NLCs Topical Gomes et al., 2014
Flurbiprofen NLCs Topical Gonzalez-Mira et al., 2010
Itraconazole NLCs Pulmonary Pardeike et al., 2011
Indomethacin SLNs Topical Castelli et al., 2005
Ketoconazole SLNs/NLCs Topical Das et al., 2014a
Ketoprofen SLNs Topical Puglia et al., 2008
Loratadine SLNs/NLCs Topical Üner et al., 2014
Lopinavir SLNs Oral Alex et al., 2011
7 Chapter 1 Literature review
Drug Type of lipid Route of Reference nanoparticles administration
Minoxidil NLCs Topical Gomes et al., 2014
Meloxicam SLNs/NLCs Topical Khalil et al., 2013
Nevirapine SLNs/NLCs Oral Kuo and Chung, 2011b
Naproxen NLCs Topical Puglia et al., 2008
Oryzalin SLNs - Lopes et al., 2012
Paromomycin SLNs - Ghadiri et al., 2012
Praziquantel SLNs Oral Yang et al., 2009
Quercetin SLNs/NLCs Oral and Chen-yu et al., 2012; Li et al., Topical 2009
Q10 NLCs Dermal Keck et al, 2014a
Resveratrol SLNs/NLCs Oral Neves et al., 2013
Retinoic acid SLNs Topical Castro et al., 2009
Simvastatin SLNs/NLCs Oral Tiwari and Pathak, 2011
Stavudine SLNs Oral Kuo and Chung, 2011a
Tretinoin SLNs Topical Ridolfi et al., 2012
Thymopentin SLNs Pulmonary Li et al., 2010
Vinpocetine NLCs Oral Zhuang et al., 2010
Valdecoxib NLCs Topical Joshi and Patravale, 2006
Zanamivir SLNs Oral Shi et al., 2015
Zidovudine SLNs - Singh et al., 2010
The first marketed product containing lipid nanoparticles was a cosmetic product introduced in 2005 and many products have been introduced since then. Table 1.2 provides an overview of cosmetic products containing lipid nanoparticles currently available on the market.
8 Chapter 1 Literature review
Table 1.2 Currently marketed cosmetic products containing lipid nanoparticles (adapted from Pardeike et al., 2009)
Product name Producers
Cutanova Cream Nanorepair Q10 Dr. Rimpler GmbH Cutanova Cream Nanovital Q10 (Wedemark, Germany) Intensive Serum Nanorepair Q10
Surmer Crème Légère Nano-Protection Isabelle Lancray (Paris, Surmer Crème Riche Nano-Restructurante France) Surmer Elixir de Beauté Nano-Vitalisant (sérum) Surmer Masque Crème Nano-Hydratant Surmer Crème Contour des Yeux Nano- Remodelante Surmer Crème Cou Nano-Raffermissante
NanoLipid Restore CLR™ CLR Chemisches NanoLipid Q10 CLR™ Laboratorium Dr. Kurt Richter GmbH (Berlin, NanoLipid Basic CLR™ Germany) NanoLipid Repair CLR™
IOPE SuperVital Amore Pacific Corp. (South Korea) Cream Serum Eye cream Extra moist softener Extra moist emulsion
Swiss Cellular White Illuminating Eye Essence Laboratories La Prairie Swiss Cellular White Intensive Ampoules (Zurich, Switzerland)
Regenerations Crème Intensiv Scholl (Mannheim, Germany)
NLC Deep Effect Eye Serum Beate Johnen (Aschleim, NLC Deep Effect Repair Cream Germany) NLC Deep Effect Reconstruction Cream NLC Deep Effect Reconstruction Serum
Olivenöl Anti Falten Pflegekonzentrat Dr. Theiss Naturwaren Olivenöl Augenpflegebalsam GmbH (Homburg, Germany)
9 Chapter 1 Literature review
Despite their wide study, no commercially available pharmaceutical product contains these lipid nanoparticles. The regulations to develop a pharmaceutical product are more stringent compared to cosmetic products; the latter often benefitting from shorter times of product development and market introduction. However, some of the features discussed earlier and later in this chapter (Section 1.4), as well as novel technologies being introduced (such as the one described in this thesis), have made the use of lipid nanoparticles as pharmaceutical drug carriers look promising in the near future.
1.4 Lipid nanoparticles – Types
1.4.1 Solid lipid nanoparticles (SLNs)
SLNs are colloidal particles derived from oil-in-water emulsions where the liquid lipid is replaced with a lipid matrix that is solid at body temperature, and stabilised by the use of surfactants. A schematic diagram depicting an SLN is shown in Figure 1.2 (a). SLNs potentially emphasise the benefits of colloidal carriers discussed earlier whilst reducing the associated shortcomings (Table 1.3) (Harde et al., 2011; Jain et al., 2010a).
Figure 1.2 Types of lipid nanoparticles. (a) Solid lipid nanoparticle (b) Nanostructured lipid carrier (c) lipid-drug conjugate (d) polymer-lipid hybrid nanoparticle
As discussed in Section 1.3, a few potential advantages associated with SLNs are listed as follows (Das and Chaudhury, 2011; Fang et al., 2008; Noack et al., 2012; Saupe et al., 2006):
Biocompatible and biodegradable colloidal carrier Prevention of degradation of drug in body fluids due to encapsulation Increased drug payload Longer half-life of drug
10 Chapter 1 Literature review
Possibility of sustained-release and controlled-release of drugs Longer shelf life Increased drug dissolution and absorption, improved bioavailability Drug targeting Large scale manufacture Feasibility of sterilisation
Table 1.3 Comparison of colloidal drug carriers (adapted from Harde et al., 2011)
Properties Lipid Liposomes Polymeric Emulsions nanoparticles nanoparticles
Biocompatibility Good Good Moderate Good (Systemic toxicity and/or cytotoxicity)
Residue from organic No Minimal Yes No solvent and/or polymer
Ability to deliver drugs Hydrophobic Hydrophobic Hydrophobic Hydrophobic and and and and hydrophilic hydrophilic hydrophilic hydrophilic
Ability to delivery Good Good Moderate Poor genes, gene products or other biotechnological products
Physical stability Good Poor Good Moderate
Stability in biological Good Poor Good Moderate environment
Encapsulation and drug High Moderate Moderate High loading
Sustained and Good Moderate Good Poor controlled release of drugs
Ability to avoid Yes Yes No Yes reticuloendothelial system
Sterilisation by Yes Yes No No autoclaving
Large scale production Yes Yes No Yes
11 Chapter 1 Literature review
Properties Lipid Liposomes Polymeric Emulsions nanoparticles nanoparticles
Drug targeting Moderate Moderate Moderate Poor
1.4.2 Nanostructured lipid carriers (NLCs)
Evolved from SLNs, NLCs were created with a controlled nanostructure of the lipid. NLCs are composed of a binary mixture of a solid lipid and a spatially distinct liquid lipid. As a result, the nanoparticle does not form a perfect crystal. The imperfections present in the solid matrix accommodate the drugs either as molecules or as amorphous crystals (Saupe et al., 2005). A schematic depiction of an NLC is shown in Figure 1.2 (b). NLCs have been applied in dermal applications (Müller et al., 2002b, 2007).
Many drugs are more soluble in a liquid lipid than in a solid lipid. This is a major drawback of SLNs prepared by hot homogenisation. The drug is solubilised in the lipid melt in the initial step of production method. The solubility of the drug reduces when crystallised into SLNs, and results in drug expulsion. The use of a liquid lipid in the preparation of NLCs helps reduce drug expulsion during storage (Severino et al., 2012).
1.4.3 Lipid-drug conjugates (LDCs)
Owing to their lipophilic nature, SLNs and NLCs can only effectively encapsulate lipophilic drugs. Hydrophilic drugs can only be incorporated at very low concentrations by solubilisation in the lipid melt. Thus, hydrophilic drugs can only be used if they are highly potent and therefore effective at very low concentrations (such as proteins and peptides). The lipophilicity of such highly potent drugs is inadequate for permeation through the GIT, resulting in poor bioavailability (Muchow et al., 2008). Transferring the drugs into LDCs can effectively overcome this situation. Formation of LDCs distinctly reduces the drug degradation in the GIT, with increased oral absorption and permeation through the GIT (Severino et al., 2012). Figure 1.2 (c) illustrates a schematic depiction of an LDC.
LDCs are synthetically prepared either by salt formation (with fatty acids) or by covalent linkage (esterification or amidation). Conjugation by salt formation usually involves solubilising the drug (free base form) and fatty acid in a suitable solvent; solvent removal
12 Chapter 1 Literature review by evaporation is achieved under reduced pressure. In the case of covalent linkage, reaction between the drug and a fatty acid alcohol in the presence of a suitable catalyst gives LDCs bulk, which is further purified by recrystallisation. The recrystallised LDC is homogenised in the presence of a surfactant solution by high pressure homogenisation to yield a nanoparticle formulation, considered to be that of a prodrug (Müller and Keck, 2004). Depending on the partition coefficient of the drug, LDCs can offer improved potential for in vivo drug targeting and drug distribution. Compared to micronised conjugate powder administered orally, LDCs provide enhanced bioavailability (Müller and Keck, 2004).
1.4.4 Polymer-lipid hybrid nanoparticles (PLNs)
Polymer- lipid hybrid nanoparticles (PLNs) are a new variation of SLN developed by Wong et al. (2004). Figure 1.2 (d) shows a structural depiction of a PLN system. The PLN is a suitable drug carrier for hydrophilic drugs that are usually used clinically in their salt forms. The cationic charges on most of these salts may lead to low drug incorporation into the lipid nanoparticles. The use of counter-ionic polymers, such as dextran sulphate, to form a drug-polymer complex has been looked upon as an interesting strategy. The drug-polymer complex was found to have good partitioning into the lipid matrix because of its high hydrophobicity; thereby improving the drug incorporation. The PLN system not only allows retarded release but also shows more complete release of drug (Wong et al., 2004). These nanoparticles are also attractive because of their capability to encapsulate and deliver multiple drugs (Wong et al., 2006a).
Some researchers have reported increased in vitro anti-tumor activity of doxorubicin- loaded PLN as against free doxorubicin solution. The cell lines used in these studies showed increased drug uptake and retention (Wong et al., 2006b, 2006c). It was further proved that the results obtained in vitro could be successfully achieved in vivo in established animal models (Wong et al., 2007).
While the current literature is relevant to all lipid nanoparticles, the focus of the current thesis is the development of SLNs, and therefore, lipid nanoparticles and SLNs are used interchangeably in this literature review.
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1.5 Production of Solid Lipid Nanoparticles
As the science of SLN technology has progressed, several approaches for the preparation of SLN dispersions have been reported since these carriers were first described in the early 1990s (Gasco, 1993; Müller and Lucks, 1994; Schwarz et al., 1994; Siekmann and Westesen, 1992). The preparation technique has a significant role in the performance of the colloidal formulation. The choice of preparation technique for SLN dispersions may be influenced by:
Physicochemical properties of the drug to be incorporated. Stability of the drug to be incorporated. Desired particle characteristics of the SLNs. Stability of the SLNs. Availability of the production equipment.
The production techniques can be categorised into two groups; techniques which require high energy for dispersion of the lipid phase (such as high pressure homogenisation, high sheer homogenisation and ultrasonication) and techniques which require precipitation of nanoparticles from homogenous systems (such as microemulsions, solvent-based techniques, membrane contactors and coacervation techniques). Table 1.4 gives a brief outline of the mechanisms involved in lipid nanoparticle formation by various techniques, and the major advantages and disadvantages associated with those techniques. Among the techniques employed in the production of the SLNs, high pressure homogenisation and microemulsion are the most well established and well documented.
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Table 1.4 Mechanisms, advantages and disadvantages of methods used in the production of lipid nanoparticles
Production technique Mechanism of particle formation Advantages Disadvantages
High pressure . High mechanical shear due to Hot homogenisation Hot homogenisation homogenisation strong turbulent eddies . Well established technology . Extremely high energy inputs (heat . Lowering of pressure across the and shear forces) . Effective dispersion of particles valves of homogenisers . High polydispersity . Reproducible . Strong cavitation forces . Temperature-induced degradation of . High lipid content drugs . Simple to scale-up . Complex crystallisation; leads to several lipid modifications and occurrence of supercooled melts
15 Cold homogenisation
. Effective dispersion of particles . Inappropriate for hydrophilic drugs; readily distribute in the aqueous . Suitable for thermo-sensitive drugs phase . No complex lipid modifications . Reduction in homogenisation . Increased drug-loading due to rapid efficiency at elevated temperatures cooling . Suitable for hydrophilic drugs; Cold homogenisation reduced lipid melting reduces drug loss . Extremely high energy inputs . Simple to scale-up . Large particles with high polydispersity
. Drug expulsion on storage
Production technique Mechanism of particle formation Advantages Disadvantages
Microemulsion . Lipid crystallisation due to . Sophisticated equipment not . Low lipid content technique rapid solidification of required microemulsion . Low energy inputs . Higher temperature gradients; faster lipid crystallisation, avoids particle aggregation . Simple to scale-up
Solvent evaporation . Lipid crystallisation due to . Sophisticated equipment not . Toxicological issues due to use of solvent evaporation in an anti- required organic solvents solvent 16 . Highly suitable for thermo-sensitive . Particle aggregation in absence of
drugs rapid solvent evaporation . Small particle diameters . Low lipid content . Simple to scale-up
Solvent diffusion . Lipid crystallisation due to . Sophisticated equipment not . Although rare, risk of toxicological diffusion of solvent from required risks due to incomplete evaporation internal organic phase to of organic solvents . Pharmaceutically accepted organic external aqueous phase solvents used; solvent recycling . Low lipid content feasible . Small particle diameters and low polydispersity . Simple to scale-up
Production technique Mechanism of particle formation Advantages Disadvantages
Double emulsion . Lipid crystallisation due to . Sophisticated equipment not . Low lipid content solidification of emulsion required . Low energy inputs
Solvent injection (or . Lipid crystallisation due to . Sophisticated equipment not . Solvent removal difficult; use of displacement) rapid diffusion of solvent from required freeze-drying or evaporation-under- internal organic phase to reduced-pressure . Pharmaceutically accepted organic external aqueous phase solvents used; solvent recycling . Low lipid content feasible . Highly efficient and versatile technique 17
. Simple to scale up
High shear . Shear between adjacent . Use of organic solvents can be . Unsuitable for higher lipid contents homogenisation particles avoided . High polydispersity and/or ultrasonication . Formation, growth and . Use of large amounts of surfactants . Physical instability due to high implosive collapse of bubbles can be avoided shearing due to cavitation forces . Simple technique with lower . Metal contamination due to production cost ultrasonication . Higher energy inputs . Poor encapsulation efficiency
Production technique Mechanism of particle formation Advantages Disadvantages
Supercritical fluid . Parallel processes of . Rapid and efficient solvent removal . Use of organic solvents extraction of supercritical fluid extraction . Monodispersed . Sophisticated equipment required emulsions (diffusion) of organic solvent from emulsions and lipid . Removal of low molecular weight dissolution impurities is easy with supercritical fluids . Expansion of organic phase; leads to lipid crystallisation . Supercritical fluid carbon dioxide causes plasticisation of lipid structures; thermodynamically stable lipid nanoparticle dispersions . Supercritical fluid lower melting
18 point of lipids; suitable for thermo-
sensitive drugs
Coacervation . Decrease in pH of micellar . Suitable for lipophilic drugs (by . Suitable for lipids that an form technique solution of an alkaline salts of solubilising in the micellar solution alkaline salts fatty acids by acidification after coacervation) . Not suitable for pH-sensitive drugs (coacervating solution) in . Suitable for hydrophobic ion pairs of presence of a polymeric hydrophilic drugs stabiliser causes proton exchange an lipid precipitation . Solvent-free technique (coacervation) . Use of sophisticated technique not required . Monodispersed . Simple to scale-up
Production technique Mechanism of particle formation Advantages Disadvantages
Membrane contactor . Lipid/oil phase infuses through . Controlled particle size with . Clogging of membrane pores; method membrane pores into the selection of membrane with correct frequent replacement or cleaning tangentially flowing aqueous pore size procedures phase to form droplets . Simple to scale-up . Oil droplets crystallise to form lipid nanoparticles
Phase inversion . Spontaneous inversion of o/w . Solvent-free technique . Particle aggregation temperature technique emulsion to w/o emulsion due . Use of large amounts of surfactants . Excipients influence the phase to thermal treatment can be avoided inversion behaviour (subsequent heating-cooling cycles) . Combines structural advantages of . Emulsion instability 19 polymeric nanocapsules and . Lipid crystallisation as a result liposomes; imparts stability to the of emulsion breakage due to system irreversible shock induced by rapid cooling . Suitable for thermo-sensitive drugs . Shorter heating periods avoids drug degradation
Chapter 1 Literature Review
Most of the techniques reported thus far, including high pressure homogenisation and the microemulsion technique, comprise two important steps:
(1) Creation of an oil-in-water (o/w) emulsion (2) Subsequent solidification of emulsion droplets to generate SLNs
The formation of an o/w emulsion, in itself, is a two-step process. The two phases, oil and aqueous, are separately but simultaneously heated to a specific temperature followed by high speed mixing of these two phases to form an o/w emulsion. The emulsions are subjected to homogenisation, ultrasonication or high shear processing depending on the approach used in the SLN production. In the case of solvent-based techniques, an oil-in- solvent type of emulsion is prepared. These techniques do not require heating of composition ingredients. Most of the solvents used in these techniques have the ability to solubilise the oil/lipids employed as solid lipid matrices in lipid nanoparticles.
The generation of SLNs from an o/w emulsion often requires precipitation of hot emulsion droplets. Often achieved by dispersion in cold water, this forms the basis of microemulsion-based techniques (see Section 1.6). In other methods, continuous high speed shearing at different temperatures has been employed to achieve solidification of emulsion droplets to form SLNs.
1.6 Introduction to the Microemulsion Technique of SLN Production
The preparation of SLN dispersions by precipitation from a hot microemulsion was described by Gasco (1993). A microemulsion is a thermodynamically stable system comprising of water and oil, stabilised by surfactant (and a co-surfactant, if required) and optically isotropic. Extensive research has been conducted on microemulsions, although the formation mechanism of microemulsions is unclear (Moulik and Rakshit, 2006).
Figure 1.3 depicts the preparation of SLN dispersion by precipitation from a hot microemulsion. The lipid phase and aqueous surfactant/co-surfactant system are separately heated to a temperature above the melting point of the solid lipid. The drug and the lipid are heated together to solubilise the drug in the molten lipid. The lipid melt is later emulsified in the hot surfactant/co-surfactant system under continuous stirring to yield a hot o/w microemulsion, which is then dispersed in cold water (typically 2 - 4ᵒC),
20 Chapter 1 Literature Review under mechanical stirring, to yield SLNs. Typically, microemulsion: aqueous phase ratios are 1:25 or 1:50.
L ip id p h a se So lid lip id H o t micr o e mu lsio n ( L ip id + D r u g ) n a n o p a r ticle s
Aq. phase
Step 2: Dispersing lipid Step 3: Dispersion in melt in aq. phase cold water
Step 1: Heating lipid and aqueous phase
Figure 1.3 A schematic depiction of the steps involved in the microemulsion technique of SLN production.
The major advantage of using microemulsion techniques in the production of SLNs is the high temperature gradient which aids in rapid crystallisation of lipid and thereby prevents particle aggregation. The microemulsion technique is simple with no specific requirement for sophisticated equipment. The technique is also industrially relevant because of its scale-up capability (Harde et al., 2011).
The microemulsion technique conventionally employs thermal energy in the production of SLNs and, therefore, this method has been referred to as the conventional microemulsion technique in this thesis. The focus of this thesis is to replace the conventional thermal heating with microwave heating in the production of SLNs. To the best of our knowledge, this is the first use of microwave heating for synthesis of a microemulsion which can be subsequently solidified to generate SLNs.
1.7 Conventional thermal heating Vs. Microwave heating
Traditionally, organic synthesis is carried out by conventional thermal heating or conductive heating. This is normally achieved by heating the reaction ingredients with
21 Chapter 1 Literature Review an external heat source such as a water bath or an oil bath mainly through conduction. The conductive heating depends on the thermal conductivity of various materials. The temperature of the reaction mixture is uneven with the reaction vessel being hotter than the interior of the reaction mixture. It is a slow and inefficient method of transferring energy. In pharmaceutical formulations prepared by melting or diffusion, conductive heating may result in a non-uniform product.
By contrast, microwave heating, also called dielectric heating, depends on the dielectric properties of the materials (see Section 1.8.2). The microwaves directly couple with the molecules in the reaction vessel and result in a rapid increase in temperature. Because the microwave heating is not dependent on thermal conductivity of the reaction vessel, instantaneous localised superheating will be achieved due to dipole polarisation and/or ionic conductance.
1.8 Microwave Technology
Extensive research on the use of microwave radiation as an energy source for several chemical reactions and other processes has been conducted during recent years. Microwave technology has been previously reported to be applied in various types of chemical syntheses such as:
Clean and sustainable synthesis of organic compounds via solvent-free reactions (Baig and Varma, 2012; Singh and Chowdhury, 2012; Tanaka and Toda, 2000; Vaddula et al., 2013; Watson et al., 2011). Synthesis of inorganic materials (Baghbanzadeh et al., 2011; Katsuki et al., 2012; Schubert and Hüsing, 2012; Vijayakumar et al., 2013; Wang et al., 2011; Zhu and Chen, 2014). Polymer chemistry and synthesis of polymeric nanoparticles (An et al., 2006; Bogdal and Pisarek, 2012; Hayden et al., 2014; Mallakpour and Rafiee, 2011; Pal et al., 2012; Rao et al., 2011; Zhang et al., 2015). Synthesis of compound libraries for generation and optimisation of new drug candidates (Kappe and Dallinger, 2006). Promotion of co-ordination chemistry and organometallic synthesis (Powell, 2010; 2011).
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Synthesis of peptides (Hojo et al., 2013; Lewandowski et al., 2013; Masuda et al., 2015; Pedersen et al., 2012).
In addition to chemical synthesis, microwave technology has been reported to be useful for other purposes:
Attempts have been made to investigate use of microwave irradiation for the extraction of natural products (Eskilsson and Bjorklund, 2000; Hao et al., 2002; Kaufmann and Christen, 2002; Pan et al., 2003). Microwave technology has also been used in the drying of pharmaceutical products (Loh et al., 2008; McLoughlin et al., 2000, 2003), with particular emphasis on the long-term stability of solid dispersions of drugs (Moneghini et al., 2009). Microwave technology has been used to design pharmaceutical formulations that can control the release of drugs (Nurjaya and Wong, 2005; Teng and Groves, 1990; Vandelli et al., 2004; Wong et al., 2002, 2005; Wong and Nurjaya, 2008) or improve dissolution properties (Bergese et al., 2003).
Whilst microwave chemistry is a well-established technique in syntheses, its use in pharmaceutical formulation has not yet reached its full potential, with only a few reported successes (An et al., 2006; Bergese et al., 2003; Kushare and Gattani, 2013; Moneghini and De Zordi, 2014; Moneghini et al., 2008, 2009; Waters et al., 2011).
1.8.1 Introduction to microwaves
Microwaves are a type of photon found at the lower end of the electromagnetic radiation spectrum (Figure 1.4) i.e. between frequencies 0.3 GHz and 300 GHz (corresponding to wavelengths ranging from 1 mm to 1 m). Applications such as wireless devices (2.4 – 5 GHz), satellite radio (2.3 GHz) and air traffic control systems operate in this range (Schmink and Leadbeater, 2010).
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Figure 1.4 The electromagnetic spectrum.
International agreements restrict the use of microwaves for other applications due to their wide use in the communication technology. The frequencies allowed for other applications such as industrial, scientific and medical (ISM) use are summarised in Table 1.5 (Nüchter et al., 2004). Amongst the ISM frequencies, 2.45 GHz is mostly preferred because it is also the frequency at which the majority of household ovens operate, it has the appropriate penetration depth required for interaction with most laboratory chemicals and the power sources that can generate this frequency are readily available (Hayes, 2004).
Table 1.5 The ISM frequencies allowed according to the international agreements
Frequency (GHz) Wavelength (cm)
0.43392 69.14
0.915 32.75
2.45# 12.24
5.80 5.17
24.125 1.36
# Commonly used ISM frequency
1.8.2 Microwave theory
As with all electromagnetic radiation, microwaves travel at the speed of light (3 × 108 m/s). Figure 1.5 is a schematic diagram of a typical microwave. A microwave consists of oscillating electric and magnetic fields that travel at right angles to each other in the form of photons (Neas and Collins, 1988).
24 Chapter 1 Literature Review
Figure 1.5 Typical microwave radiation (reprinted with permission from Hayes, 2002).
It is only the electric field component that is responsible for heating of substances, magnetic field interactions generally do not take place during chemical synthesis. Microwave-enhanced chemistry is based on efficient “microwave dielectric heating” effects. The dielectric heating of a material is dependent on its ability to absorb and convert microwave energy into heat energy. The extent to which different materials are heated in a microwave is different and dependent on their dielectric properties. The electric field component of the microwaves causes dielectric heating of materials by two mechanisms:
Frictional heating (i.e. dipolar polarisation) Ohmic heating (i.e. ionic conductance)
1.8.2.1 Frictional heating
The major mechanism responsible for frictional heating is based on the principle of dipolar polarisation. In this context, the mobility of dipoles and their ability to orient themselves in an alternating electric field are important properties that determine the ability to heat materials. This mechanism mostly applies to polar liquids such as water, methanol, etc. that possess a dipole moment. Such polar liquid molecules, also called dipoles, are sensitive to external electric fields. In frictional heating, these dipoles will continually attempt to “track” the alternating electric fields and realign themselves with the electric field by complete or partial rotation (Figure 1.6). At the commonly used ISM
25 Chapter 1 Literature Review frequency of 2.45 GHz, many chemical molecules find it difficult to track the alternating 9 electric fields (because the field changes 2.45 × 10 times every second). Dielectric heating occurs due to the torsional effect of the “jostling” of molecules as they rotate back and forth to align, and realign, with the alternating electric fields.
Figure 1.6 Frictional heating due to dipolar polarisation
1.8.2.2 Ohmic heating
In ohmic heating, the alternating electric field component of the microwave radiation causes movement of charged species such as ions within solutions, or electrons within solids. As the field oscillates, the ions or electrons align themselves with the alternating electric field (Figure 1.7). This results in an increased molecular collision rate, and therefore, an increased kinetic energy which is consequently converted to heat.
Figure 1.7 Ohmic heating due to charge polarisation
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1.8.3 Dielectric properties of materials
The dielectric heating characteristics of a material depends on its dielectric properties. This behaviour is measured in terms of dielectric coefficient, ε′. Also known as the relative permittivity, it is a measure of the ability of the material to store electric charges. Mathematically, it is represented by Equation 1.1,
C ε' = C0 … Equation 1.1 where C is the electrical capacity of the capacitor filled with the material and C0 is the electrical capacity of the evacuated capacitor
The other important dielectric property of a material to be considered is the dielectric loss factor, ε″ or the dynamic dielectric coefficient, which is the amount of irradiated microwave that is lost to the sample by being dissipated as heat. This is often obtained by comparing the amount of irradiated microwave energy to the amount of microwave energy that has coupled with the material and depends on its dielectric conductivity, σ and microwave frequency, f as represented by Equation 1.2, σ ε'' = 2πf
… Equation 1.2
The ability of a material to convert microwave energy into heat is dependent on both dielectric parameters – the dielectric coefficient and dielectric loss factor. The dielectric parameter that defines this property of the material is called the dissipation factor, tan represented by Equation 1.3,
ε″ tan δ = ε' … Equation 1.3
The dissipation factor can also be regarded as a measure of penetration depth, x. The penetration depth of microwave irradiation is inversely proportional to the dissipation factor, as represented in Equation 1.4.
1 tan δ ∝ x … Equation 1.4
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SLN formulations are composed of a lipid material, surfactant and water, with or without drugs. The formulation of o/w emulsions from these ingredients prior to SLN formation is done by microemulsion-based or homogenisation-based techniques (Table 1.4). In other SLN production techniques, such as solvent-based techniques, organic solvents including ethanol, acetone, isopropanol, benzyl alcohol, chloroform, cyclohexane, ethyl acetate and tetrahydrofuran are used (Battaglia et al., 2007; Cortesi et al., 2002; Dubes et al., 2003, Hu et al., 2002, 2004; Schubert and Müller-Goymann, 2003; Shahgaldian et al., 2003a, 2003b, 2003c; Siekmann and Westesen, 1996; Sjöström and Bergenståhl, 1992). The dielectric parameters for some solvents commonly used in SLN production are summarised in Table 1.6 (Hayes et al., 2002). In general, solvents are categorised as high, medium or low microwave absorbers on the basis of their dissipation factor (Kappe and Dallinger, 2006). These values vary with temperature and frequency of microwave energy. The dielectric properties of solvents summarised in Table 1.6 were measured at room temperature (25ºC) and 2.45 GHz.
Table 1.6 Dielectric properties of different solvents (from Hayes, 2002)
Solvent Boiling point Dielectric Dielectric loss Dissipation (ºC) coefficient (ε′) (ε″) factor (tan δ)
Ethylene glycol 197 37 49.95 1.350
Ethanol 78 24.3 22.866 0.941
Methanol 65 32.6 21.483 0.659
1-propanol 97 20.1 15.216 0.757
2-propanol 82 18.3 14.622 0.799
Water 100 80.4 9.889 0.123
1-butanol 118 17.1 9.764 0.571
2-butanol 100 15.8 7.063 0.447
Acetone 56 20.7 1.118 0.054
Chloroform 61 4.8 0.437 0.091
Ethyl acetate 77 6.0 0.354 0.059
Acetonitrile 82 37.5 2.325 0.062
Acetic acid 113 6.2 1.079 0.174
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Solvent Boiling point Dielectric Dielectric loss Dissipation (ºC) coefficient (ε′) (ε″) factor (tan δ)
Toluene 111 2.4 0.096 0.040
Hexane 69 1.9 0.038 0.020
The dielectric parameters, particularly the dielectric loss factor, may increase with an increase in temperature. Physical or chemical changes within the material during dielectric heating, may significantly alter the dielectric loss factor. Such changes often result in “thermal run away”, the phenomenon wherein the temperature of the reaction mixture increases rapidly despite unchanged microwave power.
Although microwaves have high heating capabilities, the energy of microwave photons (~ 1 J/mole) is much lower than that required to break chemical bonds such as C-C, C- O, C-H, O-H and H-H (4 - 800 kJ/mole). Microwaves, thus, have minimal adverse effects on the chemical structures of materials. Instead, they facilitate the chemical process making it a more uniform and rapid process (Nüchter et al., 2004).
1.8.4 Microwave-assisted microemulsion technique of SLN production
The microwave-assisted method proposed in this study is based on the principle of the microemulsion technique discussed in Section 1.6. The SLNs are precipitated from microemulsion templates which are typically formed by heating the lipid and aqueous phases separately with subsequent mixing of the two phases. The hypothesis of this thesis is that “single-pot” microwave heating of the formulation ingredients should generate emulsions with improved characteristics. While each of the formulation ingredients used in the synthesis of SLNs has its own dielectric properties, the contribution of water to dielectric heating is considered to be of profound importance because it forms the bulk of the formulation (~ 80 - 85%).
1.9 Physicochemical Characterisation of SLNs
SLNs are known to present three features - a solid nature, lipid matrix and colloidal particle size. These features are theorised to impart controlled drug release, biocompatibility and improved drug dissolution to the colloidal carriers. Appropriate
29 Chapter 1 Literature Review characterisation of SLNs is required to allow for the development of dispersions with the desired properties for the intended application.
The structural complexity and the colloidal size of SLN dispersions make characterisation a difficult task. The colloidal size of the particles alters physical features (e.g. increasing solubility and the tendency to form supercooled melts). The properties of bulk materials such as polymorphism and crystallinity can drastically change when these materials are dispersed into nanoparticles. Further complicating characterisation is the potential co-existence of other colloidal structures such as micelles, vesicles and emulsions in the dispersions. Thus, a comprehensive characterisation scheme is required to investigate the structure and behaviour of these complex colloidal carriers.
1.9.1 Particle size
Colloidal particles are defined on the basis of their size and structure and are defined as having any dimension smaller than 1 µm. Colloidal particles are often spherical, or at least regular in shape, and particle size measurements can confirm their colloidal size range. Nanoparticles are also traditionally defined on the basis of their size and structure and are defined as having any dimension smaller than 100 nm (as per the ISO Standards (2015)). All lipid particles produced and studied throughout this work are termed SLNs even if their sizes exceed this size limit of 100 nm. The justification for this is somewhat convoluted but is mostly justified by common usage, i.e. the majority of research papers reporting SLNs involve particles more in the colloidal range than in the nanometre range (Alex et al., 2011; Das et al., 2014a, 2014b; Shegokar et al., 2011; Silva et al., 2011). They involve structures which may or may not be genuinely nanosized and also may contain sub-structures which are nanosized. Moreover, SLNs are proposed to be used as drug carriers in clinical applications, where there is no magic or arbitrary cut-off point for particle size. “SLN”s which have sizes larger than 100 nm may well prove just as efficacious in drug delivery as those with sizes smaller than 100 nm and may even prove more acceptable due to the “fear factor” of genuine nanoparticles in the human body (Doktorovova et al., 2014). It would be confusing to invent a new terminology for drug carriers based on SLN structures simply because the particle size is outside the strict definition when they are just as potentially efficacious, based on the same chemistry and
30 Chapter 1 Literature Review same synthetic route, and are already in common usage throughout the chemical literature.
Particle size can substantially influence the material properties of SLNs. It is a key parameter that decides the fate of nanoparticles in the biological environment. For example, particles greater than 5 µm are detrimental to parenteral administration, since they may cause capillary blockages or embolisms (Wu et al., 2011).
Formulation parameters (e.g. lipid, surfactant, co-surfactant, dispersing medium and other excipients) and process parameters (e.g. production technique, homogenisation time, sonication time, homogenisation temperature, homogenisation pressure, production equipment, lyophilisation and sterilisation) are often referred to as principal quality parameters. Each of these factors influences the size and crystallisation of particles. The effect of each of these parameters on the particle characteristics, often investigated in terms of particle size, has been reported.
An increase in particle size long before visible macroscopic changes is often observed in unstable systems, making particle size a useful tool to predict formulation stability (Heurtault et al., 2003).
Particle size determination of lipid nanoparticles is often performed by light scattering methods such as photon correlation spectroscopy (PCS) and laser diffraction (LD). The speed and ease-of-use of commercially available equipment have made these techniques popular in SLN research.
PCS is based on measurement of hydrodynamic diameter from the Stokes’-Einstein equation (see Chapter 3, Section 3.2.2) and LD is based on measurement of particle diameter due to Fraunhofer, Mie and Rayleigh scattering (see Chapter 3, Section 3.2.2 3.2.3). PCS has been used by a number of researchers to measure particle size of lipid nanoparticles with various sizes reported, likely due to different formulation compositions. Tsai et al. (2012) reported sizes below 100 nm, while sizes of between 100 and 200 nm have been reported by many others (Gupta and Vyas, 2012; Noack et al., 2012; Priano et al., 2011; Varshosaz et al., 2012). Other researchers have reported SLNs with sizes varying from 200 to above 500 nm (de Souza et al., 2012; Jia et al., 2012; Xie et al., 2011; Yang et al., 2013). LD has been used by a number of researchers with mean sizes between 100 and 500 nm commonly reported, and the presence of a smaller microparticle sub-population often detected (Das et al., 2011; Doktorovova et al., 2011;
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Kovačević et al., 2011; Mitri et al., 2011; Noack et al., 2012). It is important that the particle sizing method is capable of detecting fractions of larger particles (i.e. microparticles in the lipid dispersions). The LD measurements are more applicable for larger particles, and hence particle sizing analysis solely on the basis of DLS may be insufficient. Therefore, simultaneous use of PCS and LD for size measurement is recommended.
1.9.2 Particle morphology and ultrastructure
Along with particle size, polydispersity and composition, the morphology and ultrastructure are important properties of nanoparticles and can strongly influence properties such as encapsulation efficiency. Morphology generally relates to the exterior of the particle and may be characterised by shape and surface structure whilst ultrastructure generally relates to the interior of the particle and can relate to internal partitioning through, for example, a core-shell structure (see Section 1.10) and SLN crystallinity (see Section 1.9.3). Ultrastructure can also relate to the formulation itself, as opposed to the nanoparticles by themselves. Formulation infrastructure can include nanoparticles themselves, but also structures such as micelles which can be simultaneously present.
Spherical particles have the smallest possible specific surface area for any given shape and are therefore stabilised with the smallest concentration of surfactant. Furthermore, because spherical particles have the longest diffusion pathway, they offer the potential for controlled (i.e. slow) release of incorporated drugs (Jores et al., 2004). A spherical shape also provides minimum contact with the surrounding aqueous medium, thus, providing protection to the incorporated drugs. By contrast, anisometric particles require a greater amount of surfactant for stabilisation. This could be desirable when the drug is to be incorporated into the surfactant layer or adsorbed onto the particle surface. Particle shape, thus, may need to be tailored, so as to influence the loading capacity and release properties of the drugs from the lipid nanoparticles (Bunjes, 2011; Bunjes and Siekmann, 2005). The results obtained from PCS and LD can also be influenced by the anisometric shape of the particles. Particle size results from PCS and LD should therefore be corroborated with electron microscopic techniques to characterise the shape of the lipid nanoparticles (Müller et al., 2000).
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Different components within the lipid nanoparticle dispersions can organise themselves into a number of different structures, both within and without the nanoparticle itself (Müller et al., 2000). The ultrastructure of systems should be given due consideration in predicting the organisation of encapsulated drug components within the dispersions. For example, surfactants that stabilise the lipid nanoparticles within the dispersion may self- assemble to form additional colloidal structures such as micelles. Such structures have a lipophilic domain which may pocket some of the drug molecules. The presence of these additional colloidal structures can influence drug incorporation and release (Müller et al., 2002).
1.9.3 Crystallinity and polymorphism
The release properties of SLNs rely on the solid state of the particles. Most SLN production techniques require heating of the lipid matrix above the melting point followed by solidification of the hot microemulsion after dispersion in the aqueous phase. Since the release properties of lipid nanoparticles are significantly influenced by their crystalline nature, it is important to study the crystallinity of SLNs prepared with any novel compositions or techniques which may alter that crystallinity. The critical crystallisation temperature is lipid-specific and may be influenced by other components present in dispersion. Bunjes et al. (2002) suggested induced crystallisation of triglycerides at higher temperatures due to interactions with the stabiliser. The presence of partial glycerides and/or residues of long fatty acids in glycerides may reduce the supercooling tendency (Ali et al., 2010; Bunjes et al., 1996; Westesen et al., 1997).
Notwithstanding this, many lipid materials such as such as tricaprin, trilaurin and trimyristin may remain partially crystallised in a colloidally dispersed state. Dispersions of such lipid materials may remain in the emulsion state, and are regarded as “emulsions of supercooled melts”. These may not crystallise and form the desired solid state until temperatures much lower than their melting points are reached. In such cases, recrystallisation of nanoparticles requires careful evaluation. SLN dispersions of triglycerides mentioned above and other glycerides such as those commercially available ® ® as Witepsol and Softisan , for example, usually exhibit retarded crystallisation (Choi et al., 2008; Kuntsche and Mäder, 2010; Lim and Kim, 2002). Special thermal treatment
33 Chapter 1 Literature Review such as lyophilisation or cooling in liquid nitrogen may be required to ensure that particles are formed in the solid state (Schwarz and Mehnert, 1997; Lim and Kim, 2002).
Crystallisation of lipids within SLNs can be further suppressed by the incorporation of drugs. Incorporation of ubidecarenone into tripalmitin-based nanoparticles, for example, reduced the crystallisation temperature by 10 ⁰C (Bunjes et al., 2001). The drug molecules are tightly bound to the carrier matrix at low concentrations, but when present in excess, they adhere to the carrier surface as a liquid phase, thus lowering the crystallinity (Bunjes et al., 2001). Addition of liquid lipid leads to suppression of the crystallisation temperature in NLCs (Ali et al., 2010; Awad et al., 2009; Jenning et al., 2000b). Incorporation of a drug and/or inclusion of liquid lipids also lead to a decreased melting point, however, the reduced melting temperature is usually lower than the crystallisation temperature (Müller et al., 2008).
Further changes can occur after the initial solidification of SLNs. The solid lipids employed in these production procedures usually display polymorphism which is also displayed in the colloidally dispersed state. Polymorphic transitions can occur for several weeks after the solidification of nanoparticles (Bunjes and Koch, 2005). For example, triglycerides occur in three polymorphic forms, the least stable α-form, the metastable β’-form and the most stable β-form. Triglyceride-based SLNs usually crystallise in the
α-form when solidified from a lipid melt. An intermediate βi-form of triglyceride nanoparticles has been reported when nanoparticles are produced by hot homogenisation. Both will eventually morph into the β-form over time. Variation of matrix components, incorporation of drug molecules and the presence of surfactant molecules can each influence these polymorphic transitions (Bunjes et al., 1996; Bunjes et al., 2001; Jenning et al., 2000a; Jores et al., 2003; Schubert et al., 2005; Westesen et al., 1997). Nanoparticles often transform into more stable forms on storage and on heating, and this may or may not be desirable. Polymorphic transitions are usually accompanied by changes in shape and size of the nanoparticles. Changes to particle characteristics can compromise pharmaceutically relevant properties such as drug incorporation and stability, for example by expelling the drug (on storage) as the SLNs becomes more crystalline, thus lowering the shelf life of the product (Freitas and Müller, 1999; Jenning et al., 2000c; Müller et al., 2002; Wissing et al., 2004). For all these reasons, investigation of crystallinity and polymorphic behaviour of SLNs nanoparticles should be included in the characterisation processes.
34 Chapter 1 Literature Review
Differential scanning calorimetry (DSC) and X-ray diffraction (XRD) are the two most widely employed techniques for characterisation of crystallinity and polymorphism of SLNs. DSC is a sensitive technique used in the characterisation of crystalline materials. The polymorphic form can be detected only indirectly by careful investigation of transition temperatures and melting enthalpies. For such cases, XRD is a more reliable technique which provides more detailed structural data. DSC data can be used to assign polymorphic form when supported by XRD data (Bunjes and Siekmann, 2005).
1.9.4 Surface charge
The surface characteristics of colloidal particles have a significant impact on their in vivo behaviour and stability. Electrostatic and steric repulsion play an important role in the stabilisation of colloidal systems.
The surface charge on SLNs is usually due to the presence of ionic surfactants and/or surfactant-dispersion medium interactions, but can also be an intrinsic charge, particularly if the lipid used is an acid. The surface charge on SLNs may also influence the adsorption, encapsulation and eventual release of drugs from the SLNs. It can also influence the stability of SLNs once drugs have been incorporated into them (Freitas and Müller, 1998).
Traditional inorganic colloidal particles usually acquire their surface charge due to the presence of ionized groups or ion adsorption from the medium. Organic colloidal particles such as stearic acid-based SLNs (as in this thesis) may acquire their surface charge from the ionisation of stearic acid. Surface charge can be directly measured by acid/base titration in the case of ionized surface groups or can be estimated in the case of adsorbed charge. In either case, however, it is not the surface charge, per se, which is of direct relevance to colloidal behaviour. It is the surface potential which results from the surface charge and more importantly, the potential that particles “feel” on close approach. Direct measurement of surface charge is problematic, direct measurement of surface potential is close to impossible, however measurement of the potential that particles “feel” is arguably simple to measure as the zeta potential. The zeta potential can be measured by measuring the potential at the plane of shear, or slipping plane, and serves as the characteristic parameter of choice for nanoparticle charge (Hunter, 2002).
35 Chapter 1 Literature Review
The spatial distribution of ions, traditionally referred to as the electrical double layer (EDL), around a charged surface determines its electrical state. A schematic depiction of an EDL is shown in Figure 1.8.
Figure 1.8 Schematic representation of an electrical double layer.
The EDL is a physical model consisting of two layers: a fixed layer and a diffuse layer (Figure 1.8). The fixed layer is a firmly bound layer while the diffuse layer is distributed within the solution in contact with the charged surface. The diffuse layer has an increased concentration of counter-ions. The fixed, bound layer has two surfaces of interest – the genuine particle surface and the surface representing the centre of bound, hydrated counter-ions, often referred to as the “Stern layer”. The ions beyond this layer form the diffuse layer, also called the “Gouy” or “Gouy-Chapman layer” (Delgado et al., 2007). The difference in the electrical charge within the EDL results in a potential difference from the surface to the Stern layer to the diffuse layer.
36 Chapter 1 Literature Review
The shear plane is then defined as the plane at which water molecules change from being bound to the surface to being free to move, and is dependent on the energy of mixing (shear). In the simplest case, this is considered a fixed position, as defined in the model presented in Figure 1.8. The potential at this plane (the “Stern potential”) is either equal to or slightly higher (in magnitude) than the measured potential at the shear plane which, in turn, is referred to as the zeta potential (ζ). The zeta potential is measured by determining the electrophoretic mobility by electro-acoustics, microelectrophoresis or phase analysis light scattering (PALS) (Eldridge, 2011). Of these various techniques available, electrophoretic mobility (and therefore, zeta potential) was measured by PALS in this thesis (see Chapter 3, Section 3.2.2).
The zeta potential of dispersions is usually influenced by the pH, ionic strength and the types of ions in the dispersion medium (Radomska-Soukharev, 2007). Lipid nanoparticles usually carry a negative charge developed by the surfactant system used in their stabilisation. However, cationic lipid nanoparticles have also been prepared which find application in DNA and gene delivery (Choi et al., 2008; Doktorovova et al., 2011; Olbrich et al., 2001; Tabatt et al., 2004). Zeta potential measurements have been undertaken to study the effect of electrolyte and pH on the stability of SLNs (Choi et al., 2014). The zeta potential of SLNs can be increased by the addition of surfactants such as egg phosphatidylcholine to the surfactant mixture (Lim and Kim. 2002). The presence of a co-solvent in the formulation can increase the zeta potential of the system (Trotta et al., 2003). Sterilisation and freeze drying of SLNs have negligible or minimal significant influence on their zeta potential (Cavalli et al., 1997; Schwarz and Mehnert, 1997; Lim and Kim, 2002). The presence of a cryoprotectant can also influence the zeta potential of SLNs (Cavalli et al., 1997; Schwarz and Mehnert, 1997; Soares et al., 2013; Varshosaz et al., 2012). Formulation parameters such as surfactants and the lipid matrix also affect zeta potential determinations (Kovačević et al., 2011, 2014). Addition of steric stabilisers to the systems may decrease the zeta potential due to the shift in the shear plane. Therefore, zeta potential is to be used as a primary indicator of electrostatic stability and may also provide an indication of stability of systems due to steric stabilisers.
37 Chapter 1 Literature Review
1.10 Structure of SLNs
SLNs have three different morphologies, based on the location of the encapsulated drug molecules,
Drug-enriched shell Drug-enriched core Homogenous matrix
These structures have been described based on the observations of Müller and co-workers (Müller et al., 2002a).
Figure 1.9 Drug incorporation models of solid lipid nanoparticles (a) drug-enriched shell model (b) drug-enriched core model (c) solid solution (homogenous matrix) model.
1.10.1 Drug-enriched shell model
A drug-enriched shell is a lipid core enclosed by a drug-enriched outer shell (Figure 1.9 (a)). Such a structure is obtained when hot liquid droplets cool rapidly to form lipid nanoparticles as a result of phase separation. The drug-enriched shell morphology can be explained by a lipid precipitation mechanism that occurs during production and by repartitioning of the drug that occurs during the cooling stage. After hot homogenisation, each droplet is a mixture of melted lipid and drug. Rapid cooling accelerates lipid precipitation at the core with a concomitant increase in drug concentration in the outer liquid lipid. Complete cooling leads to precipitation of a drug-enriched shell. This structural model is suitable for incorporation of drugs that are released as a burst. Such a rapid release is highly desirable, for example, in dermatological SLN formulations that require increased drug penetration, in addition to the occlusive effect of the SLN (Muchow et al., 2008). The controlled release of clotrimazole from a topical SLN formulation was due to its drug-enriched shell structure (Souto et al., 2004).
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The solubility of the drug in the surfactant-water mixture at elevated temperatures is another factor that can influence precipitation of drug in the shell. During the hot homogenisation process, the drug partially moves out of the lipid core due to its increased solubility in the surfactant solution. However, solubility of the drug in the surfactant solution decreases as the dispersion is cooled. This leads to drug enrichment in the shell, in cases where lipid core solidification has already started (Muchow et al., 2008).
1.10.2 Drug-enriched core model
A drug-enriched core is obtained when the recrystallisation mechanism is the opposite of that described for the drug-enriched shell model (Figure 1.9 (b)). This morphology is obtained when the drug has a tendency to crystallise prior to the lipid. The drug is solubilised in the lipid melt close to its saturation solubility. Subsequent cooling of the lipid emulsion causes super-saturation of the drug in the lipid melt; this leads to the drug recrystallizing prior to lipid recrystallisation. Additional cooling leads to lipid recrystallisation that forms a membrane around the already crystallised drug-enriched core. This structural model is suitable for drugs that require prolonged release over a period of time, governed by Fick’s law of diffusion (Müller )et al., 2002a .
1.10.3 Solid Solution model
A solid solution, also referred to as a homogenous matrix, is obtained when the drug is homogenously dispersed within the lipid matrix as discrete molecules or small amorphous clusters (Figure 1.9 (c)). This model is usually described for lipid nanoparticles prepared by a cold homogenisation technique, or when highly lipophilic drugs are incorporated such that a hot homogenisation technique can be employed without the use of surfactants or drug-solubilizing molecules. When a cold homogenisation technique is employed, the solubilised drug is dispersed in the bulk lipid. When subjected to high pressure homogenisation, mechanical agitation leads to the formation of lipid nanoparticles with a homogenous matrix. A similar result is obtained when the lipid droplets produced by a hot homogenisation technique are rapidly cooled; droplets tend to crystallise and there is no phase separation between the drug and the lipid. Such models are suitable for incorporation of drugs that exhibit prolonged release from particles (Muchow et al., 2008). An example of such a model is a prednisolone-
39 Chapter 1 Literature Review loaded solid lipid nanoparticle system that exhibits slow release of prednisolone, usually from 1 day to 6 weeks (Jenning and Gohla, 2000).
1.11 Stability of SLNs
The stabilisation of the hot emulsion from which SLNs form and continued stabilisation of the SLNs once formed are likely to involve quite different mechanisms. The hot emulsions contain liquid particles which can deform and for which parameters such as zeta potential are dynamic rather than static, especially during particle interaction. Stability of the hot emulsion is likely to arise from the well-known Gibbs-Marangoni effect and is largely driven by the choice of surfactant (Walstra, 1993). On cooling, however, the liquid emulsion solidifies to form a dispersion, and stability is now likely to relate to the well-known DLVO theory (and recent variants thereof) (Gambinossi et al., 2014; Ohki and Ohshima, 1999).
The SLNs distributed in the dispersion medium are in a constant state of random “Brownian” motion, and therefore frequently collide. If they “stick” on collision, then the overall surface area of the system will decrease, a process which lowers free energy, and is therefore thermodynamically favourable. Consequently, the system is thermodynamically unstable. Only if the particle size is extremely small, as is the case with microemulsions and micellar solutions, will the entropy caused by the sheer number of particles allow the system to be thermodynamically stable, Although nanosized particles may reach such an extreme small size that there are sufficient numbers of particles to result in thermodynamic stability, the particle size usually remains large enough that the system is inherently thermodynamically unstable. The stability of the SLNs dispersions thus depends on ensuring that particles do not “stick” on collision, a kinetic rather than thermodynamic effect. The forces that are operative during such collisions include:
Van der Waals forces. Electrostatic forces. Solvation forces. Electrical double layer compression. Polymeric inter-particle bridging.
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A colloidal suspension can be stabilised in both aqueous and non-aqueous media through two common mechanisms, specifically electrostatic stabilisation and steric stabilisation. Electrostatic repulsion can be achieved, for example, by the addition of ionic stabilisers to the medium; steric stabilisation can be accomplished, for example, by the addition of (large molecular) non-ionic stabilisers (Scheler, 2012).
1.11.1 Electrostatic stabilisation
The electrostatic stabilisation of colloidal particles can be explained by the classic Deraguin Landau Verwey Overbeek (DLVO) theory (Deraguin and Landau, 1941; Verwey, 1947). DLVO theory assumes that colloidal stability is due to the additive effect of forces between particles. In particular, DLVO theory accounts for attractive van der Waals forces and repulsive electrostatic forces. The van der Waals forces of attraction between particles arise from electromagnetic attraction. The energy of attraction (Va) for two spherical particles, each with a particle diameter r and separated by a distance D, is given by Equation 1.5,
Ar V = − a 12D … Equation 1.5 where A is the Hamaker constant. The energy of attraction is proportional to the Hamaker constant and the particle size, and inversely proportional to the distance of separation.
The electrostatic repulsive forces originate from overlapping diffuse layers in the electrical double layer surrounding the two approaching particles in the medium. The electrical double layer (see Section 1.9.3) consists of two layers: (1) a Stern layer with counter ions attracted to the particle surface and (2) a Gouy layer which is a diffuse layer of ions, predominantly again counter-ions. The energy of repulsion (Vr) between two spherical particles, each with a particle diameter r, is given by Equation 1.6,
32πrεk2T2γ2 V = e-κD r z2e2 … Equation 1.6 where ε is the permittivity of the dispersed phase, k is the Boltzmann constant, T is the absolute temperature, γ is the reduced surface potential, z is the ionic charge, e is the charge on an electron, κ is the inverse Debye-Hückel length (reciprocal of the thickness of the electrical double layer) and D is the distance between two spherical particles. The
41 Chapter 1 Literature Review energy of repulsion depends on the particle size, zeta potential, distance between the particles and dielectric constant of the dispersion medium. Ion concentration in the medium also has a significant influence on the energy of repulsion. The thickness of the electrical double layer decreases with increasing ionic strength of the medium, and consequently lowers the repulsive energy which can lead to aggregation (Nutan and Reddy, 2009).
The total potential energy of particle-particle interaction (Vt) is the sum of the energies of attraction (Va) and repulsion (Vr) generated from van der Waals attractive and electrostatic repulsive forces (Equation 1.7).
Vt = Va + Vr … Equation 1.7
Figure 1.10 Schematic form of potential energy vs. distance curve. The potential energy curve shows primary minimum (responsible for irreversible coagulation), primary maximum (responsible for kinetic stability of dispersions) and secondary minimum (responsible for reversible flocculation).
Figure 1.10 illustrates a potential energy vs. distance curve. The van der Waals attractive forces, as predicted from Equation 1.5, are inversely proportional to the distance between two particles. By contrast, repulsive forces, as predicted from equation 1.6, decay exponentially with increasing inter-particular distance. It can thus be concluded that van der Waals attractive forces predominate at two specific distances (dependent on the system) and these result in primary and secondary minima. Between these is a primary maximum which is dominated by electrostatic repulsive forces and is largely responsible
42 Chapter 1 Literature Review for the observed stability in colloidal dispersions, i.e. such stability is brought about by a distance-dependent barrier to close approach, somewhat akin to the activation energy which traditionally gives rise to kinetic (as opposed to thermodynamic) stability. The two particles are inseparable at a primary minimum where attractive forces are dominant. Such changes often cause irreversible changes, such as particle aggregation, in the system. The primary maximum is low and flat if the forces of repulsion are less than the van der Waals attractive forces. However, the particles remain in a dispersed state if their thermal energy is much higher than the primary maximum. The secondary minimum occurs at relatively large distances, and can cause loose particle flocculation, which can easily be reversed into dispersion by mechanical shaking. The particles repel each other and prevent coagulation if the thermal energy of the particles is larger than the secondary minimum. Not all features are apparent in all systems. The secondary minimum, for example, does not appear for small particles; it is operative only for larger particles (typically > 1 m and/or in high ionic strength).
A number of significant advances to the original DLVO model have been made since its inception, for example the extended-DLVO (x-DLVO) model (Van Oss et al., 1986). These include the introduction of solvation effects on the surface, as will be discussed in the next section on steric stabilisation. Whilst they are important to the quantitative determination of colloidal stability, they are complex and sometimes contradictory. The important aspects of the DLVO theory remain relevant and allow an understanding of the parameters required to both predict and change colloidal stability. Specifically;
Increasing the Hamaker constant (only possible by changing the lipid or substrate) will increase van der Waals forces thus decreasing stability. Increasing the surface potential (by, for example, adding a charged surfactant, altering the pH or decreasing the electrolyte concentration) will increase stability. Increasing the electrolyte concentration will decrease the zeta potential, thus decreasing stability. However, it can, in some cases, also increase the surface potential resulting in the opposite effect.
Note that in all of the above discussion, colloidal stability refers to the situation where the colloid remains dispersed and is therefore “stable” in the sense that it does not change. It does not refer to thermodynamic stability which would result in coagulation or flocculation and thus a change in the system.
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1.11.2 Steric stabilisation
Steric stabilisation is usually accomplished by the addition of polymeric material or large molecular sized non-ionic emulsifiers. The stabilising mechanism can be attributed to the effect of solvation forces. Addition of water-soluble non-ionic emulsifiers to the nanoparticle dispersions can stabilise the nanoparticles due to their adsorption on the nanoparticle surface. They can also be adsorbed onto the nanoparticles through strong interaction of an anchor segment. The tail or stabilizing segment extends into the bulk medium and is strongly solvated (Eastoe and Tabor, 2014). Thermodynamically, steric stabilisation can be indicated by estimation of Gibbs’ Free Energy (ΔG) using the Equation 1.8,
∆G = ∆H – T∆S … Equation 1.8 where ΔH is the enthalpy, T is the absolute temperature and ΔS is the entropy. Positive ΔG is indicative of a stable dispersion, while negative ΔG predicts particle aggregation.
Strong enthalpic interaction is responsible for good solvation between the solvent and the stabilizing segment of the emulsifier. The stabilizing segment cannot inter-penetrate as the two particles approach each other due to its presence in a good solvent, and consequently force the bulk medium out of the inter-particle space. This keeps particles apart and results in steric stabilisation.
Steric stabilisation can also be induced by polymeric materials, but large molecular non- ionic surfactants are more commonly used in SLNs. Small molecular weight non-ionic surfactants can also help induce a stable system. In this case, the size of the stabiliser is not sufficient for full steric stabilisation, but may give partial steric stabilisation to aid electrostatic stabilisation. More likely, the non-ionic surfactant can provide a solvation barrier to close contact, which modifies the DLVO model and has been well documented (Leal-Calderon et al., 1999, 2000). The solvation barrier is best thought of as an additional force in the DLVO model such that modern DLVO variants include calculations of van der Waals forces, electrostatic forces and solvation forces.
1.12 Drug Release Mechanisms
While SLNs are expected to provide a great potential for controlled release systems due to their solid core, the actual release profile from the SLNs is structure- and solubility-
44 Chapter 1 Literature Review dependent. Based on the location of the incorporated drugs within the SLNs matrix (see Section 1.10), different release patterns are observed such as burst release in drug- enriched shell structures and prolonged release in drug-enriched core models. The other important property that facilitates release of drugs is their “solubility” (Siepmann and Siepmann, 2013). The concentration of drug in the saturated solution depend on various factors such as temperature, pressure, solid state of the drug (such as polymorphic form of drug) and the particle size (Florence and Attwood, 2011). These factors determine the solubility, and hence ease of drug release from SLNs.
Depending on the chemistry of drug(s), types and amounts of excipient(s), production technique, geometry and dimension of the drug carriers and the environmental conditions during release of drug from the carriers, one or more mechanisms can be involved in release of drug from the carriers. An extensive account of release mechanisms has been reported elsewhere (Siepmann and Siepmann, 2008). One of the major contributors of drug release, i.e. diffusion of drugs from the drug carriers, has been discussed in this thesis.
The mass transport of drug by diffusion was described by Noyes and Whitney (1897). The fundamental basis for evaluation of drug release kinetics was mathematically represented by the well-known Noyes-Whitney equation (Equation 1.8),
dc = K(C – C ) dt s t … Equation 1.8 where dc/dt is the dissolution rate, K is the constant and Cs is the solubility of drug at the experimental temperature and Ct is the concentration of dissolved drug at time t.
The basic hypothesis of the Noyes-Whitney equation is that the diffusional mass transport through the liquid, unstirred boundary layer (the layer of liquid immediately surrounding the solid particles) is the rate-limiting step. The quantification of this step was done by application of Fick’s first law of diffusion (Fick, 1855a, 1855b) into their mathematical model. The Fick’s first law of diffusion can be represented by Equation 1.9,
dM dc = – SD dt dx … Equation 1.9
45 Chapter 1 Literature Review where dM/dt is the rate of mass transport, S is the surface area of particles available for mass transport, D is the diffusion coefficient and dc/dx is the concentration gradient over the distance x. The Noyes-Whitney theory, however, did not explain the physical meaning of the constant K.
Nernst (1904) and Brunner (1903) conducted further experimentation to confirm the Noyes-Whitney theory and explain the physical meaning of the constant K. Based on Fick's law of diffusion, the duo gave the Nernst-Brunner equation (Equation 1.10),
dM SD = – (C – C ) dt δ s t
... Equation 1.10 where dM/dt is the rate of mass transport, S is the surface area of particles available for mass transport, D is the diffusion coefficient, and Cs is the solubility of drug at the experimental temperature, Ct is the concentration of dissolved drug at time t. and δ is the thickness of liquid, unstirred boundary layer.
The Noyes-Whitney and Nernst-Brunner equations combined together the relationship for determination of physical constant K was established (Equation 1.11),
SD K = δγ … Equation 1.11 where δ is the thickness of liquid, unstirred boundary layer and γ is the solution volume. Nernst and Brunner assumed that the mass transport process at the surface proceeds much faster than that at the bulk (Siepmann and Siepmann, 2013). However, the real situation is not fully abrupt. Moreover, the ideal situation can never be achieved as the actual particle surface changes permanently with the progress of the dissolution process.
Based on these two theories and considering the Fick’s law of diffusion, several mechanistic and empirical theories were proposed by many researchers such as the Hixson-Crowell, Korsmeyer-Peppas, Hopfenberg, Baker-Lonsdale, Makoid-Banakar, Quadratic, Weibull and other such theories. A short description of some of the theories used in mathematical modelling of drug release profiles in this thesis is given in Chapter 8, Section 8.1.
In summary, a large proportion of highly potent, both newly discovered and currently available drugs are discarded due to their poor water solubility and poor membrane
46 Chapter 1 Literature Review permeability. SLNs may have the capability to deliver these cargoes to specific target sites in the body. Their biocompatible nature, small particle size (nanometre range), surface charge, solid form, good particle stability and drug release properties make SLNs interesting potential drug carriers. A number of strategies reported for their production, but the current study reports a novel microwave-assisted strategy to produce SLNs encapsulated with selected lipophilic drugs. The technique is cheaper, quicker and produces an improved product. The SLNs produced using the microwave-assisted technique have then been characterised using an array of analytical techniques.
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Chapter 2 Research objectives and thesis organisation 2
Research Objectives and Organisation of Thesis
49 Chapter 2 Research objectives and thesis organisation
2.1 Research Objectives
During the past few decades, the design of novel dosage forms or methods to further develop existing ones has gained increasing interest. With the advent of nanotechnology, new pharmaceutical dosage forms comprised of colloidal carriers have been discovered and are currently under development. The use of colloidal drug carriers not only improves the therapeutic index of drugs but also reduces the associated side effects, thereby achieving the most optimised therapeutic outcomes. The present thesis focusses on one such colloidal carrier - Solid Lipid Nanoparticles (SLNs).
Dispersions of SLNs stabilised with surfactants have been investigated thoroughly since their inception in the 1990s. Several techniques of SLN production including homogenisation-based techniques, solvent-based techniques, microemulsion-based techniques have been reported. The central hypothesis of this thesis is that microwave technology is an excellent technique that can be employed to produce SLNs with better physicochemical characteristics, improved encapsulation capabilities, good release properties and improved physical properties. The particles so produced are predicted to have the desired properties to be readily internalised by human cells. Therefore, the overall objective of this research effort was to develop a “novel” microwave-assisted procedure for the production of SLNs which are looked upon as potential candidates for efficacious drug delivery.
The research project was divided into several phases to achieve the following aims in order to realise the overall objective of the thesis:
To introduce and develop a novel method based on the use of microwave energy in the production of SLNs.
To compare the novel microwave-assisted technique to an already established technique based on similar principles i.e. the microemulsion method using conventional heating.
To characterise the SLNs using an array of techniques including dynamic light scattering (DLS, for measurements of particle size and particle size distribution), phase analysis light scattering (PALS, for zeta potential measurement), high performance liquid chromatography (HPLC, for encapsulation and drug release studies), differential scanning calorimetry (DSC, for thermal studies) and X-ray diffraction (XRD, for diffraction studies).
50 Chapter 2 Research objectives and thesis organisation
To investigate the suitability of the microwave-assisted microemulsion technique for encapsulation of drugs from different drug categories including antibiotics, non-steroidal anti-inflammatory drugs (NSAIDs) and antifungal drugs.
To characterise drug-loaded SLNs using various techniques.
To investigate the biocompatibility of the drug-loaded SLNs against human cells, and check for retention of their activity against inflammation-induced human cells (in the case of SLNs loaded with NSAIDs) and against C. albicans (in the case of SLNs loaded with antifungal drugs).
To investigate the drug release from SLNs employing the widely-used dialysis bag method and perform mathematical modelling to fit the drug release data into various kinetic models.
To investigate the effect of pH and simulated gastrointestinal fluids on stability of SLNs.
To investigate whether the SLNs are internalised by human epithelial cells for them to be deemed suitable to be used as drug carriers, and also decipher the mechanisms involved therein.
51 Chapter 2 Research objectives and thesis organisation
2.2 Organisation of the Thesis
This thesis is organised into eleven chapters.
Chapter 1 provides a comprehensive and critical review of solid lipid nanoparticles including a brief introduction to colloidal carriers, types of lipid nanoparticles, currently used techniques in SLN production, different SLN structures, characterisation techniques and their stability aspects. This chapter also provides a brief introduction to drug release mechanisms and a brief introduction to contextualise the use of microwave technology in the pharmaceutical area. In summary, this chapter provides a background of microwave technology especially relevant to their use in SLN production designed for drug delivery.
Chapter 2 gives a brief synopsis of the research statement including the overall objective and specific aims of the thesis. This chapter also summarises the organisation of the thesis with a brief description of the subsequent chapters.
Chapter 3 describes some of the general materials and methods adopted in this research, while chapter-specific methodologies will be discussed in subsequent chapters. This chapter also gives a general introduction (with brief theory) of some equipment used in this thesis.
Chapter 4 introduces the novel microwave-assisted microemulsion method used in the preparation of SLNs in this thesis. This chapter provides preliminary results obtained by experimental design to obtain an optimised formulation that can then be used to develop and validate the use of the novel technique in SLN production.
Chapter 5 demonstrates the potential advantages of using microwave heating over conventional thermal heating by comparing the physicochemical characteristics of tetracycline-loaded SLNs (tetracycline was used as a model drug in this chapter). A suite of analytical techniques such as DLS, PALS, DSC and XRD were used to characterise the SLNs. Drug encapsulation, stability, drug release, anti-microbial and cytotoxicity testing were also conducted on the SLNs.
Chapter 6 illustrates the use of SLNs as potential carriers of non-steroidal anti- inflammatory drugs (NSAIDs). Similar to earlier chapters, this chapter describes an extensive characterisation of drug-loaded SLNs with an assessment of biocompatibility.
52 Chapter 2 Research objectives and thesis organisation
This chapter also illustrates the anti-inflammatory effect of the drug-loaded SLNs on human cell lines.
Chapter 7 further investigates the suitability of using the novel production technique in encapsulation of drugs into the SLNs, this time extending to antifungal drugs. In addition to the physicochemical characterisations and cytotoxicity testing, this chapter also discusses the anti-Candida effect of drug-loaded SLNs which indicates their suitability to be used as potential drug carriers.
Chapter 8 studies the release of drugs (encapsulated into the SLNs and characterised in the earlier chapters) from the SLNs using the most commonly employed “dialysis bag” technique. This chapter also deals with mathematical expressions that can be used to fit the release data into various kinetic models. The possible release behaviours of drugs (different drug categories) and possible mechanisms involved are discussed in this chapter. The final part of this chapter provides a drug release profile comparison based on a few well-studied statistical methods.
Chapter 9 deals with an investigation carried out to decipher the mechanism of uptake of SLNs by human epithelial cells. This chapter also reports the systematic investigation carried out to evaluate the possible pathway involved in the cellular uptake of SLNs.
Chapter 10 deals with the investigation of the influence of pH and simulated gastrointestinal fluids on the physical stability of SLNs. This chapter also investigates the influence of these parameters on drug-loaded SLNs.
Chapter 11 summarises the conclusions of the studies undertaken in this research and discusses the future perspectives of this research.
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Chapter 3 Experimental Section 3
Experimental Section
55 Chapter 3 Experimental Section
3.1 Materials
3.1 A Production, physicochemical characterisation and in vitro release studies
3.1.1 Solid lipids
The solid lipids used in this research have a relatively high melting point (above 40C). Most of these solid lipids, with the notable exception of cetyl palmitate, are physiologically well-tolerated, of generally-recognised-as-safe (GRAS) status and accepted for human use. The solid lipids were selected from different lipid categories: fatty acids (stearic acid), synthetic glycerides (glyceryl monostearate, glyceryl distearate, glyceryl dibehenate and glyceryl trimyristate) and waxes (cetyl palmitate). Additionally, hydrogenated coco-glycerides were also employed as solid lipids.
Stearic acid (octadecanoic acid) is a saturated fatty acid extracted from animal and/or vegetable oil. Two different batches of stearic acid were used in this research. The initial study on optimisation and encapsulation of tetracycline was performed with stearic acid purchased from Sigma-Aldrich (Australia). The later research was performed with stearic acid purchased from ICN Biomedicals Inc. (USA).
Imwitor® 900K (glyceryl monostearate), Dynasan® 114 (glyceryl trimyristate), Softisan® 154 (hydrogenated palm oil) and Witepsol® E85 are marketed products obtained from Cremer Oleo GmBH & Co. KG (Hamburg, Germany). Imwitor® 900K is a pharmaceutical excipient widely used as a co-emulsifier, lubricant, plasticiser or a binding agent (Product Info Sheet Oleo). Dynasan® 114 acts as a lubricant in tablets. In ointments, creams and lotions, it is used as body imparting and structure forming component (Product Info Sheet Oleo). Witepsol bases have been used in the manufacture of suppository bases.
Compritol® 888 ATO (glyceryl dibehenate) and Precirol® ATO 5 (glyceryl distearate) were kindly provided by Gattefossé (France). Compritol® 888 ATO is a pharmaceutical ingredient used as thickening agent in dermal products and as a modified release agent, lubricant and compressing agent in tablets and capsules (Product Info Sheet Gattefossé). Precirol® ATO 5 is used as taste masking and a modified release agent in oral formulations (Product Info Sheet Gattefossé). Cetyl palmitate was a kind gift from Merck (Germany).
56 Chapter 3 Experimental Section
3.1.2 Surfactants and stabilisers
Non-ionic surfactants from Cremophor® EL, Tween® and Span® series. Tween® 20 (polyoxyethylene (20) sorbitan monolaurate), Tween® 80 (polyoxyethylene (20) sorbitan monooleate), Span®20 (sorbitan monolaurate) and Span®80 (sorbitan monooleate) were purchased from Merck (Germany). Cremophor® EL was obtained from Sasol (Germany). Lutrol® F68, used as a stabiliser, was obtained from Sigma-Aldrich (Australia).
3.1.3 Drug substances
Three categories of drug substances were chosen for encapsulation in this thesis: antibacterial agents, non-steroidal anti-inflammatory drugs (NSAIDs) and anti-fungal drugs. Unless otherwise specified, all drug substances used in this study were ≥ 98% pure and purchased from Sigma-Aldrich (Australia). These include tetracycline (CAS # 60- 54-8), indomethacin (CAS # 53-86-1), ketoprofen (CAS # 22071-15-4), nimesulide (CAS # 51803-78-2), clotrimazole (CAS # 23593-75-1), miconazole nitrate (CAS # 22832-87-7) and econazole nitrate (CAS # 24169-02-6). Tetracycline is an antibacterial agent. Indomethacin, ketoprofen and nimesulide are NSAIDs. Clotrimazole, miconazole nitrate and econazole nitrate are anti-fungal drugs.
3.1.4 Other chemicals
Methanol used in the high performance liquid chromatography (HPLC) analysis was of liquid chromatography grade. Ultra-purified water was obtained from a MilliQ® Plus purification system (Millipore, Germany) and all other chemicals and reagents used in the preparation of buffers were commercially sourced and of analytical grade.
3.1 B In vitro cell culture studies
3.1.5 Cells
The human lung A549, human cervical HeLa and mouse 3T3-L1 cell lines were kindly provided by Dr. Vandana Gulati, a colleague at Swinburne University of Technology. The cells were maintained and subcultured as described in Section 3.3.10.
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3.1.6 Cell culture media and other chemicals
Dulbecco’s Modified Eagle’s Medium (DMEM, Gibco), fetal bovine serum (FBS), 0.25% trypsin/ethylene diamine (EDTA) solution, penicillin G sodium (10,000 units/mL) and streptomycin (10,000 µg/mL) solution were obtained from Invitrogen Technologies (Australia). Dimethyl sulfoxide (DMSO) was obtained from Merck (Germany). Dulbecco’s phosphate buffered solution, 3-(4,5-dimethylthiazol-2- yl)-2,5- diphenyltetrazolium bromide (MTT), propidium iodide, Triton X-100, rhodamine 123, lipopolysaccharide (LPS) from Escherichia coli O111:B4, D(+)-sucrose, filipin III from Streptomyces filipinensis (Filipin) and cytochalasin B were purchased from Sigma- Aldrich (Australia). 4’, 6-diamidino-2- phenylindole, dihydrochloride (DAPI) and CellMask™ Deep Red Plasma membrane stain were obtained from Molecular Probes (USA). The human interleukin (IL)-6 and IL-8 enzyme-linked immuno-sorbant assay (ELISA) kits were obtained from ElisaKit.com (Scoresby, Australia).
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3.2 Instrumentation
3.2.1 Discover LabMate Microwave system
The microwave system used in this research is a 2.45 GHz Discover LabMate (CEM Corporation, Matthews, USA). It consists of a self-adjusting single-mode microwave cavity that houses the microwave reactor tube. A circular microwave applicator acts as the continuous microwave power delivery system. A rotating magnetic plate located below the floor of the microwave cavity facilitates continuous stirring of the ingredients in a reactor tube. The temperature control system uses an infrared sensor that is located below the microwave cavity floor. The infrared temperature sensor measures the temperature at the bottom of the reactor tube. The reaction temperature is programmable from 25 to 250 °C. Temperature is controlled by an external supply of cooling gas (either nitrogen or clean air). Pressure is programmable from 0 - 21 bar. The microwave reaction conditions are easily controlled and monitored using Synergy™ Application Software (CEM Corporation, Matthews, USA). A schematic depiction (cutaway view) of a typical microwave reactor is illustrated in Figure 3.1.
Figure 3.1 A typical microwave reactor.
3.2.2 BIC-90Plus Particle analyser
The particle size, polydispersity index (PI) and zeta potential analysis was primarily conducted on a BIC-90Plus particle analyser (Brookhaven Instruments, New York,
59 Chapter 3 Experimental Section
USA).The instrument uses a 35 mW red diode laser ( = 659 nm) with a photodetector at 90° and a thermostatted sample chamber set at 25°C.
3.2.2.1 Particle size analysis
The BIC-90Plus particle analyser makes use of the light scattering properties of particles to determine their particle size. The technique is well known as photon correlation spectroscopy (PCS), or quasi elastic light scattering (QELS), or dynamic light scattering (DLS). DLS is principally used to determine the size of sub-micron particles suspended in a liquid. DLS analyses the random thermal or Brownian motion of the particles suspended in the dispersion medium (Finsy, 1994). Figure 3.2 shows a representative diagram of a DLS setup used in sizing of SLNs.
Figure 3.2 A typical setup of a DLS instrument.
The particles are irradiated with a laser beam of a particular wavelength. The DLS measures the statistical intensity fluctuations in scattered light from multiple collisions of particles as a function of time; collisions arising from random Brownian motion of
60 Chapter 3 Experimental Section particles. Small particles, due to their high diffusion coefficient, cause high intensity fluctuations. Large particles, with relatively slower motion, cause lower fluctuations. An autocorrelation function is used to analyse the scattering intensity-time curve to derive parameters that relate to particle size and particle size distribution. The “method of cumulants” can be used to derive the particle size, determined as z-average diameter (also referred to as effective diameter) and PI, indicative of the width of the particle size distribution, from the autocorrelation function (Koppel, 1972).
Although DLS is the most widely accepted method, it is (like most particle sizing techniques) an indirect method of determination of particle size. DLS is used to characterise particle size depending on its translational diffusion coefficient D. A mathematical model based on the Stokes-Einstein equation (Equation 3.1) is used to convert the translational diffusion coefficient into hydrodynamic diameter to determine the particle size,
kT D = 3πηd
… Equation 3.1 where D is the translational diffusion coefficient, k is the Boltzmann constant (1.38 × 10- 23 J/K), T is the absolute temperature, η is the viscosity of the dispersion medium and d is the hydrodynamic diameter of the particle. Particle size determination requires knowledge of the temperature and viscosity of the dispersion medium during measurement. It is also important to be familiar with the fact that this technique measures the hydrodynamic diameter of the particle and this may be affected by the particle’s surface properties and concentration and types of ions in the dispersion medium.
The DLS requires a very small amount of sample without extensive sample preparation other than dilution. It is a rapid, non-invasive and non-destructive technique of sizing colloids. The technique is able to detect particles over the size range of ~ 3 to 3,000 nm. This operating range is relevant to SLN dispersions. However, this measurement range can be too narrow to detect interference from larger microparticles (> 3 µm) (Kaszuba and Connah, 2006). The presence of large particles or aggregates may have a significant impact on particle size measurements. The SLN dispersions are usually diluted to reduce multiple scattering effects. Dilution of formulations may alter their size distribution, thus resulting in the classic problem of changing the measure by the act of measuring it.
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Another disadvantage of this technique is the assumption that all particles are spherical. This assumption is less of a concern for SLNs than for other colloidal structures, however it can still be an issue, for example if SLNs crystallise into a platelet-like arrangement (Esposito et al., 2008, 2012). Such anisometric particles exhibit larger hydrodynamic diameter in DLS as compared to corresponding emulsions. Although crystallisation leads to volume reduction of particles, anisometric particles have larger particle diffusion coefficients (Westesen et al., 2001). Larger particle diffusion coefficients may influence the determination of particle sizes.
3.2.2.2 Zeta potential analysis
The BIC-90Plus particle analyser makes use of phase analysis light scattering (PALS) to measure electrophoretic mobility. The PALS is an extension of laser Doppler electrophoresis (or electrophoretic light scattering, ELS). The ELS measures the velocities of moving particles in terms of a Doppler shift in laser light that is scattered from them (Smith and Ware, 1978). The PALS is more sensitive (at least 1,000 times) than the conventional ELS. It does not require the application of large fields which may result in thermal problems nor does it cause denaturation. The measurement analyses the phase shift, and not the frequency shift. A slight movement of particles (equivalent to a fraction of their own diameter) yields good results. In addition, the auto-tracking feature available with the software compensates for thermal drift. The auto-tracking feature reduces the convection effects arising within the samples due to their heating. In short, measurements with higher resolution, better detection limits and improved precision can be obtained.
The zeta potential, ζ is commonly derived from electrophoretic mobility, µ using the Helmholtz-Smoluchowski equation (Equation 3.2),
εζ µ = 1000 × × f η
… Equation 3.2 where ε is the dielectric constant and η is the viscosity of the bulk phase (in this case, water) and f is an adjustable parameter on the size and integrity of particle surface. The Helmholtz-Smoluchowski equation is strictly only applicable under conditions of large particle size and/or high ionic strength and these conditions are rarely encountered in
62 Chapter 3 Experimental Section nanoparticle research, a common error, therefore, in zeta potential experiments. The Smoluchowski equation strictly applies only for spherical particles where the dimensions are much greater than the thickness of the electrical double layer (Goldberg et al., 2011), and these conditions were not met here. More sophisticated models include the Henry equation and the Wiersema approach and these are more applicable, but less often used, to nanoparticles including SLNs used in this study. For this reason, zeta potential measurements of SLN formulations should be treated qualitatively rather than quantitatively.
The zeta potential, in this thesis, was calculated using freely available software called “Zeta for Windows” compiled by Kosmulski (2002). It calculates the zeta potential based on input parameters such as the ionic strength, ionic conductivity, particle size, the dielectric constant of the solvent, the viscosity of the solvent, the temperature and the electrophoretic mobility. The calculations performed by the program are based on the equations published by Ohshima et al. (1982). The program requires a values greater than 10, where and a are the inverse Debye length the particle radius respectively. It works particularly well for particles that have a thin double layer compared to the particle radius.
3.2.3 Partica LA-950V2
Laser diffraction (LD), also called laser scattering, was also used in combination with DLS in this research. The instrument based on LD used to measure the particle size was a Partica LA-950V2 (Horiba Instruments, Kyoto, Japan). The instrument uses a 5 mW red laser diode (λ = 650 nm) and a 3 mW blue light emitting diode (LED) (λ = 405 nm). LD is a powerful tool that has a much wider detection range (20 nm to 2,000 µm) and is a better choice for lipid nanoparticles in the upper nanometre and micrometre size ranges than DLS (Keck and Müller, 2008). The two combined are often used to give a complete particle size distribution from ultra-small to large particles.
The operational principle of LD is based on the complex patterns derived due to Fraunhofer, Mie and Rayleigh scattering from an illuminated particle. These patterns are dependent on the particle size of the sample to be analysed. The particle radius is based on the correlation between the angle of diffraction and the particle radius. The light scattered from an illuminated particle is detected by an array of detectors in a laser
63 Chapter 3 Experimental Section diffractometer which determines its angular distribution. Large particles predominantly scatter laser light in the forward direction. Smaller particles give a more spherical distribution of scattered light. Thus, the particle size is determined from the geometric distribution of the scattered light. The intensity of the scattered light is also influenced by the particles sizes, and weakens with the cross sectional area of the particle. It can thus be concluded that larger particles scatter light at contracted angles (with higher intensities) as against small particles that scatter light at broader angles (with lower intensities) (Müller et al., 2000). The Fraunhofer approximation is used to ascertain the diameters of particles in the micrometre and millimetre size ranges. The particle size can be calculated using Mie theory which is a complex combination of optical parameters and angle of scatter. This technique is well suited for characterisation of large microparticles. An LD analysis also gives a reasonable estimation of polydispersity of particles. The LD data is often reported in terms of d(x) which represents diameter of x% of particles below the reported value.
The use of LD also presents limitations. The main drawback of this theory is that its application to nanoparticles requires knowledge of optical parameters (the real and imaginary real refractive indices at the wavelength of measurements) of samples. The technique is less useful in samples containing several populations of variable particle sizes (i.e. highly polydisperse populations). Uncertainties can develop in instances where particles are non-spherical. It should also be acknowledged that LD and DLS both use light scattering effects to estimate the particle size rather than directly measuring the particle size.
3.2.4 Shimadzu UFLC system
The determination and quantification of drug in the samples was performed by high performance liquid chromatography (HPLC) analysis on a UFLC system (Shimadzu, Kyoto, Japan). A schematic depiction of the HPLC setup is given in Figure 3.3. The specification of the UFLC system used in this study is given in Table 3.1.
64 Chapter 3 Experimental Section
Figure 3.3 A schematic representation of a HPLC setup.
Table 3.1 The specifications of UFLC system
Component Specifications
Controller CBM-20A Prominence Communications Bus Module
Pump LC-20AT Prominence LC double reciprocating plunger pump
Autosampler SIL-20A HT Prominence Auto Sampler
Column oven CTO-20A Prominence Column Oven
Detector SPD-M20A Prominence Diode Array Detector
3.2.5 2920 Modulated DSC
The thermal characteristics of samples were investigated by differential scanning calorimetry (DSC) on a 2920 Modulated DSC (TA Instruments, Delaware, USA). A cutaway view of a DSC cell is shown in Figure 3.4. An empty pan is taken as a reference. In comparison to the reference, samples need to have a higher heat capacity. Samples are also expected to undergo thermal transitions (such as melting, recrystallisation, etc.) when heated. Such thermal transitions require large amounts of heat. The Universal
65 Chapter 3 Experimental Section
Analysis 2000 software (TA Instruments, Delaware, USA) allows the user to study the thermal behaviour by plotting the heat flow (on the abscissa) and temperature (on the ordinate). These plots provide valuable information about the samples such as their heat capacity and different phase transitions which is further processed to extract information about the samples such as crystallinity, polymorphism, melting point, etc.
Figure 3.4 A cutaway view of a standard DSC cell.
3.2.6 D8 Advance Diffractometer
The diffraction analysis of samples was performed by X-ray diffraction (XRD) on a D8 Advance diffractometer (Bruker, Germany). The XRD provides additional but limited information about the crystallinity of samples. The XRD works on the principle of Bragg’s Law which can be described by Equation 3.3,
λ = 2d sin θ … Equation 3.3 where λ is the wavelength of X-rays, d is the inter-planar distance between two crystals and θ is the angle between the incident ray and the sample stage (or the scattering plane)
Since the wavelength is fixed, the X-ray source and the detector must move along the measurement circle to achieve necessary θ angles for constructive interference. Constructive interference can be seen only in the presence of crystalline materials; in the absence of crystallinity the diffraction is random with destructive interference. A diffraction pattern is generated by plotting diffraction intensity (on the abscissa) and the
66 Chapter 3 Experimental Section diffraction 2θ angles (on the ordinate). Any crystalline material generates a diffraction pattern distinctive for its structure. The loss of crystallinity either due to incorporation of drug molecules and/or surfactants or due to preparation technique may reduce the crystallinity of the samples as compared to their bulk counterparts. Thus, XRD analysis may provide useful information on reduced crystallinity of samples.
Figure 3.5 A schematic representation of an X-ray diffractometer.
67 Chapter 3 Experimental Section
3.3 Methods
The general methods used throughout the thesis are listed and described here. The readers are directed to specific chapters for modifications (if any) and/or any other methods specific to those chapters.
3.3 A Production, physicochemical characterisation and in vitro release studies
3.3.1 Production of solid lipid nanoparticles (SLNs)
The SLNs were prepared by a novel microwave-assisted microemulsion technique using a 2.45 GHz Discover LabMate microwave system (see Section 3.2.1). The microwave conditions were set during the preparation of SLNs using Synergy™ software. The “Fixed Power Control” method was chosen for preparation of SLNs. This option allows for control and monitoring of the microwave conditions during the preparation of SLNs. The software allows the user to program:
The maximum microwave power to be applied during the reaction. The maximum run time (i.e. time during which microwave energy is constantly supplied to the ingredients). The maximum temperature set point (i.e. temperature above which microwave energy ceases to be supplied).
The fixed power control option applies the desired maximum power until the temperature set point is reached after which the feedback loop modulates the amount of power to maintain the temperature set point.
Accurately weighed quantities of ingredients (i.e. lipid, surfactant and water) were taken in a 10 mL thick walled Pyrex reactor tube, tightly sealed with a septa cap and heated in the microwave system with constant stirring. Unless otherwise specified, stearic acid (100 mg) and Tween®20 (150 µL) in water (1.35 mL) were used to prepare SLNs in this research. The microwave temperature set point was 80 - 85C (above the melting point of stearic acid) with microwave power not exceeding 10 W. A continuous supply of cooling gas (nitrogen) and the self-tuning capability in the microwave cavity maintained the reactor tube at the temperature set point of 80 - 85C for 10 min. The pressure throughout the run time was 0 psi. The software allows the user to release the reaction product at elevated temperatures. The release temperature was set above the melting
68 Chapter 3 Experimental Section point of stearic acid. This process constitutes a single-pot synthesis of an o/w microemulsion which is then cooled to form an SLN.
In order to encapsulate drugs into the SLNs, accurately weighed quantities of drug (5% of lipid mass) was added to the ingredients in the reactor tube prior to subjecting the ingredients to microwave heating. This was done to facilitate solubilising of the drug in the molten lipid material.
The microwave-assisted preparation of SLNs is based upon the principle of creating a microemulsion at high temperature and generating SLNs from microemulsion droplets as the temperature is lowered. The hot o/w microemulsion obtained from the microwave reactor was immediately injected and dispersed into cold water (50 mL, held at 2 - 4C) under constant magnetic stirring to generate dispersions of SLNs.
3.3.2 Particle characterisation
3.3.2.1 Dynamic light scattering (DLS)
In order to assess the suitability of the prepared SLN formulations, particle size analyses were performed on the day of their production. Detection of SLNs and particle size measurements were performed by DLS using a BIC-90Plus Particle analyser (see Section 3.2.2). Dynamic light scattering is the most widely used method to determine the mean particle size in terms of effective diameter (or z-average or mean hydrodynamic diameter) and the width of particle size distribution expressed as the polydispersity index (PI) (Obeidat et al., 2010).
Prior to particle size measurement, each sample was diluted with distilled water to obtain a weak opalescent dispersion, in order to eliminate multiple scattering and viscosity effects caused by the concentrated SLN dispersions. Such dilution may cause instability in the SLN dispersion and is an inherent problem with light scattering-based particle size determinations. To check for experiment induced instability, test samples were routinely diluted by differing amounts whilst remaining within the desired concentration range for the instrument. The particle size of these test samples were unaffected by the dilution ratio (data not shown), and so it was assumed that dilution was a suitable method for preparing these SLNs for particle size measurement. The viscosity (0.8937 cp) and refractive index (RI, 1.33) of water at 25C were used for all measurements.
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Unless otherwise specified, three consecutive measurements (of ten runs each) were performed and averaged. The results are presented as DLS diameter which is an intensity- weighted mean diameter and PI values.
3.3.2.2 Laser diffraction (LD)
In selected cases, the samples were also analysed by LD using a Partica LA-950V2 (see Section 3.2.3). The DLS and LD combined are often used to give a complete particle size distribution from ultra-small to large particles and also to provide self-validation of results. Prior to measurements, like in DLS, each sample was diluted with distilled water to obtain a weak opalescent dispersion in order to eliminate multiple scattering and viscosity effects caused by the concentrated SLN dispersions. The viscosity (0.8937 cp) and RI (1.33) of water at 25C were used for all measurements. The sample was constantly stirred to avoid particle aggregation during the measurement. Unless otherwise specified, five consecutive measurements were performed and averaged.
Hu et al (2014) argue that Mie theory is useful to estimate the correct size of particles in the expected size range of 20 nm to 4 µm. The estimation of particle size using Mie theory often requires the user to input specific optical parameters such as the real and imaginary refractive indices of the materials. The determination of these indices is difficult because of two reasons:
(1) These indices are compound-specific (therefore, not known without previous experimentation) and (2) Changes in temperature and wavelength of the measurement changes the refractive indices of the compound (Keck and Müller, 2008).
Most of the published measurements, therefore, “consider” a suitable value for these indices and make measurements accordingly.
The results are analysed as volumetric distribution and are often expressed as d(0.5) and d(0.9) indicating the volume percentage of particles with diameters equal to or lower than the given value of particle size. Thus, for example, a value of 250 nm for d(0.5) means that 50%, by volume, of particles have a diameter equal to, or smaller, than 250 nm.
In the case of stearic acid-based SLNs, the requirements for a known RI is problematic. Whilst the dependence of calculated particle sizes on temperature and wavelength is
70 Chapter 3 Experimental Section easily accounted for by measuring and controlling those parameters, the correct value for RI is problematic. The commonly accepted values of 1.456 (RI) and 0.010 (imaginary RI) (Hommoss, 2011; Obeidat, 2012) have been questioned as they relate to nanoemulsions at room temperatures (where the nanoemulsion is a liquid) (Hu et al., 2014; Keck and Müller, 2008; Keck et al., 2014b; Kübart and Keck, 2013). It is questionable as to how well this reflects a surfactant coated solid dispersion of small particle size. To determine the influence of RI on the calculated particle size, the instrument software was used to methodically calculate particle size from a test case varying the inputed RI. The results are given in Figure 3.6 as volume diameters of a drug- free SLN sample as a function of real RI. The imaginary RI was kept constant at 0.010.
300
250
200
150
d(0.5)(nm) 100
50
0 1.38 1.40 1.42 1.44 1.46 1.48 Real refractive index (a)
12
10
8
m) 6
d(0.9)( 4
2
0 1.38 1.40 1.42 1.44 1.46 1.48 Real refractive index (b) Figure 3.6 Influence of real refractive index on the diameters of drug-free SLNs. In the graphs, (a) d(0.5) and (b) d(0.9) diameters are plotted as a function of real RI. The imaginary RI was assumed to be 0.01.
71 Chapter 3 Experimental Section
The results in Figure 3.6 clearly illustrate that particle size is dependent on the value of real RI of particles. The d(0.5) diameters decreased with increasing values of real RI (Figure 3.6 (a)). By contrast, the real RI did not strongly influence d(0.9) diameters until the real RI was set to 1.43 or higher. At this point, there was a significant and dramatic increase in the particle size (Figure 3.6 (b)). The now very different particle sizes generated from the choice of RI is of concern and may reflect either:
(1) The presence of small amounts of very large particles, or (2) An unrealistic choice of values greater than 1.43 as the real RI.
None of the samples were sonicated prior to or during the measurement in order to avoid any destruction of possible aggregates within the SLN samples. The instrument is sensitive to such aggregates and these may strongly affect the d(0.9) values as also seen here. Note that it would take very few particles of very large diameter to represent an important percentage of the total volume, even though the number of particles is very small. Thus if only 10%, by volume, of the particles are very large, then the d(0.9) value would be very large – the value is not an average particle size, it is the largest diameter measured in the bottom 90% (by size) of the sample.
The DLS measurements and SEM imaging of this sample revealed particle sizes below 300 nm and the absence of any large particles, suggesting that the reason for the very large d(0.9) values at high RI is most probably an error in the chosen RI, and not the presence of large particles or large aggregates. However the measurement of correct real and imaginary refractive indices of solid materials such as the SLNs used in this theory is cumbersome and out of the scope of this thesis. For this reason, d(0.9) values are not discussed in this thesis, and the results were analysed using Mie theory with the default real and imaginary refractive indices assumed to be 1.456 and 0.010 respectively based on previously published literature (Hommoss 2011; Keck et al., 2014b; Obeidat, 2012). Only d(0.5) values were then analysed and discussed throughout the thesis. The simulation in Figure 3.6 indicates that this could result in absolute errors of as much as 50% depending on the true RI, an error which has also been noted as common in the literature by Keck and Müller (2008). Whatever the error is, it is assumed however to be constant. The justification for accepting this approach is thus:
(1) The real RI used is the one most commonly quoted in the literature. (2) Determining a better RI is outside the scope of this thesis.
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(3) Values are used as comparators, rather than absolute, i.e. does the value change with time, indicating instability. This observation should not be affected by any systematic error in the determination of particle size. (4) The results, at d(0.5) were consistent with DLS suggesting that any error in the true real RI may be counterbalanced by any error arising from the choice of d(0.5) (i.e. 50% point) as representing the average particle size of relevance to DLS measurements.
Further work in this area could definitely involve determination of the true real RI of Tween® 20 coated stearic acid lipid nanoparticles (and any influence of that on the incorporation of various drugs of interest), however for the purpose of this thesis and these measurements the current literature value is deemed suitable for the analysis undertaken.
3.3.2.3 Zeta potential
The zeta potential was determined by the measurement of electrophoretic mobility using a BIC-90Plus Particle Analyser (see Section 3.2.2). The electrophoretic mobility of samples was determined by combining laser Doppler anemometry and PALS. The palladium electrode used to measure electrophoretic mobility was initially conditioned to a conductivity of greater than 30,000 S/cm with 0.9% potassium chloride solution.
Prior to measurement, samples were appropriately diluted with distilled water. The pH of distilled water during the measurements was 6.0 ± 0.5. Unless otherwise specified, each sample was analysed in triplicate and averaged. The mean zeta potential was calculated from electrophoretic mobility using freely available software “Zeta for Windows” (Kosmulski, 2002).
3.3.2.4 Scanning laser microscopy (SEM)
The shape and particle size of the SLNs was also investigated using the field emission scanning electron microscopy (FESEM) on a SUPRA™ 40VP (Carl Zeiss Microscopy GmbH, Jena). Prior to SEM analysis, the SLNs were diluted appropriately in distilled water. Diluted aqueous SLN dispersions were placed and allowed to spread on an
73 Chapter 3 Experimental Section aluminium plate and left to dry for 30 min. The air-dried SLN samples were sputter- coated with gold using an Emitech K975X Turbo-pumped evaporator in the sputtering configuration. High resolution images were taken at 3 kV by FESEM at 12,500×, 25,000×, 40,000× and 60,000× magnifications. It is worth appreciating here that although many researchers have used SEM to study the morphology of SLNs, the SLNs may not maintain their integrity and solid state during SEM analysis due to the high energy electrons used in the analysis and the vacuum applied in the SEM chamber. The results obtained here, therefore, should be considered qualitative and not an absolute estimation of the actual shape and size of the particles.
3.3.2.5 Measurements of pH
The pH measurements were performed using a smartCHEM-LAB multi-parameter laboratory analyser (TPS, Brisbane, Australia). Prior to pH measurements of SLN dispersions, the pH analyser was calibrated with standard solutions of pH 4.0 and pH 7.01. All the pH measurements were conducted at 25C.
3.3.3 Encapsulation efficiency (EE) and Loading capacity (LC) measurements
The EE and LC (see Equations 3.4 and 3.5) refer to the amount, expressed as a percentage, of drug encapsulated by the nanoparticles. EE is expressed as the amount encapsulated compared to the amount of drug added, whilst LC refers to the amount encapsulated compared to the amount of lipid used.
The measurement of EE of most nanoparticles, including SLNs, typically requires a method that can efficiently and rapidly cause physical separation of nanoparticles from their surrounding dispersion medium to assist real-time estimation of free drug. For large particles, separation can be achieved by simple filtration. Most methods rely on separation of free drugs from the nanoparticles to indirectly measure the nanoparticle- bound drug. However, the small size of nanoparticles often presents challenges during separation. A few methods are reported in the literature including ultracentrifugation (Ricci et al., 2006; Singh et al., 2014), centrifugal ultrafiltration (Das et al., 2012; Lu et al., 2014; Teeranachaideekul et al., 2007) and pressure ultrafiltration (Boyd, 2003; Cui et al., 2006; Magenheim et al., 1993).
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The EE and LC of SLNs in this research were determined by the centrifugal ultrafiltration method. This method has several advantages: rapid separation (in minutes), low centrifugal forces (4000 – 4500 g) and negligible application of pressure. The EE and LC of SLNs were determined by the method described by Das et al. (2012) with some modification. In brief; any unencapsulated, undissolved free drug (if present) was initially filtered out using cellulose filter paper (Grade 42, Whatman, USA). This will also remove any SLN material which became aggregated following drug incorporation. An appropriate volume of filtered SLN dispersion (0.5 mL) was diluted with methanol (9.5 mL). The dispersion-methanol mixture was vortexed carefully to facilitate extraction of encapsulated drug from the lipid into the methanol. The mixture was then subjected to centrifugation (4200 g, 15 min) to separate any large insoluble particles of lipids. The amount of drug was determined in the supernatant, and the other fractions described later in this section, by HPLC analysis (see Section 3.3.6). The amount of drug in the supernatant was assumed to be the “filtered” amount. Unfiltered SLN dispersions were used as a control and assumed to be the drug “loaded” amount (as opposed to the amount of drug added to the formulation which we refer to as the “drug loading”). Analysis of the amount of drug in both the filtered and unfiltered formulations gives the amount of drug lost to filtration and is assumed to be the amount of “free” drug.
In addition to free drug, a small amount of unencapsulated drug may be dissolved in the aqueous phase. The amount of unencapsulated “soluble” drug was determined by an ultrafiltration method using centrifugal filter units with a 10 kDa molecular weight cut- off (Amicon® Ultra-4; Millipore, Germany). The SLN dispersion was placed in the centrifugal filter unit and subjected to centrifugation (4200 g, 20 min). The amount of drug in the aqueous phase (ultra-filtrate) was determined by HPLC analysis and assumed to be the “soluble” amount.
EE and LC were calculated from the amounts of drug determined by the HPLC analysis using the following equations,
[amount (loaded) - amount (free) - amount (soluble)] EE (%) = × 100 amount (drug loading)
… Equation 3.4 [amount (loaded) - amount (free) - amount (soluble)] LC (%) = × 100 amount of lipid added to the formulation
… Equation 3.5
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3.3.4 Separation effectiveness of centrifugal ultrafiltration
The separation effectiveness of centrifugal ultrafiltration was assessed by the method described by Wallace et al. (2012). This was done by detection of SLNs in the ultra- filtrate samples that may have escaped during centrifugal ultrafiltration. In the absence of SLNs, scattering of light by filtrate samples are expected to be comparable to scattering of pure dispersant (here, distilled water). In contrast, filtrate samples that contain just a few SLNs still scatter a significant amount of light that can be quantified by DLS. The BIC software is equipped with MAS option which allows maximisation of the incident power settings. This option is used only when determining the intensity (in counts per second) vs. particle concentration relationship. The light scattered is directly proportional to the size and number of particles present in the sample. This principle can be used to measure the absolute light scattering, expressed as derived count rate, to detect the presence of particles in the filtrate and hence the effectiveness of separation. The absolute scattering is different for different nanoparticle systems under study. It is, therefore, necessary to prepare calibrations curves for each system under study.
A calibration curve of particle count rate against particle concentration was established. This was done by preparing a 1% (v/v) SLN dispersion. A series of standards were prepared at concentrations up to 0.0625% (v/v) by serial dilution of 1% (v/v) SLN dispersion in water. The derived count rate, expressed in kilo counts per second (kcps), was recorded during particle size measurements. A calibration curve (derived count rate vs. particle concentration) for SLNs was established. The light scattered by distilled water ranged from 450 - 500 counts per second (cps) and this serves as the count rate corresponding to zero SLN particles. The presence, and quantitative value if present, of SLNs which “escaped” the centrifugal filtration was measured using this calibration graph.
3.3.5 In vitro drug release studies
Numerous techniques have been used to study the release of drugs from nanoparticulate systems including pressure ultrafiltration (Boyd, 2003; Magenheim et al., 1993; Wallace et al., 2012), ultracentrifugation (Martins et al., 2012b; Sun et al., 2013) and dialysis techniques including sac dialysis (or dialysis bag) method (Gomes et al., 2014; Hua et al., 2014; Li et al., 2008; Luo et al., 2006; Zhang et al., 2012a, 2012b, 2013), side-by-
76 Chapter 3 Experimental Section side dialysis (Henricksen et al., 1995; Johnston et al., 2008) and reverse dialysis (Muthu and Singh, 2009).
In this thesis, the dialysis bag method was used for studying the drug release kinetics from drug-loaded SLNs. The dialysis bag technique is the most commonly used in the literature for drug release measurements. However, the appropriateness of this technique in estimation of drug release form SLNs has been questioned by various researchers (Boyd, 2003; Rosenblatt et al., 2007). The drug concentration in the release medium may not always reflect the true free drug concentration in the dialysis bags. The membrane transport affects that mask the true drug release from the SLNs also dictates the passage of free drug across the membrane. However, the membrane pore size, as in this study (10 - 12 kDa), is large enough to allow easy diffusion of free drug. Moreover, the method can be used, as in this study, where only comparative values (not absolute values) of drug release are required. The dialysis bag method is also cost effective as opposed to other methods which require sophisticated equipment.
The release studies were performed at pH 7.4 and 37C (i.e. conditions mimicking the physiological pH and temperature respectively) to evaluate the drug release profile at the conditions that may be encountered by the formulation when applied in vivo. A 100 mM phosphate buffered saline solution (PBS, see Section 3.4 A for preparation of PBS) at pH 7.4 and supplemented with Tween® 20 was used as the release medium. The solubility of drug in the release medium can directly affect the drug diffusion rate and consequently influence the release of drug from the SLNs. The drugs used in this research are poorly soluble in water resulting in slow diffusion from SLNs. Surfactants like Tween® 20 can improve the solubility of such drugs by micellar solubilisation. Thus, 1% Tween® 20 was used in this study to maintain sink conditions.
The dialysis bag (molecular weight cut off: 12 - 14 kDa, Livingstone International, Australia) was soaked in distilled water for 12 h prior to use. A 2 mL aliquot of a drug- loaded SLN dispersion was placed in the dialysis bag which was sealed at both ends. The dialysis bag was immersed in an amber coloured glass bottle containing 50 mL of release medium. The bottles were placed in a thermostatic shaker at 37°C and 150 rpm. Five millilitres of release medium was withdrawn at predetermined time points (0, 1, 2, 4, 6, 8, 12 and 24 h) and replaced with an equal volume of fresh release medium to maintain the sink conditions. The drug content in the aliquot was determined by HPLC analysis (see Section 3.3.6).
77 Chapter 3 Experimental Section
3.3.6 Determination of drug by high performance liquid chromatography (HPLC)
The determination of drug in samples (from EE, LC and drug release studies) was performed by HPLC analysis using a Shimadzu UFLC (see Section 3.2.4) attached to a reversed-phase C18 column (PrevailTM C18 column, 150 mm x 4.6 mm, 5m; Alltech, USA).Unless otherwise specified, the solvents and reagents used in HPLC analysis were of HPLC grade.
The mobile phase employed in the HPLC analysis was methanol and 25 mM sodium dihydrogen phosphate solution (adjusted to pH 2.5 with 0.1 M HCl). The preparation of solvents for HPLC analysis may result in bubble formation. Prior to HPLC analysis, both methanol and sodium dihydrogen phosphate solution were subjected to vacuum degassing (ultrafiltration though 0.22 µm membrane filter) followed by sonication using an ultrasonic bath. The column temperature was set at 30°C. The injection volume was 5 µL for all standards and samples.
A standard stock solution (5 µL) of drug was initially injected and analysed between 190 and 800 nm covering the entire UV-visible wavelength. This was particularly useful to determine the absorbance maxima (λmax) and the retention time (time between injection and detection of sample in HPLC). The detection wavelength during analysis of samples was set depending on the absorbance maxima of the drug.
To estimate the amount of drug in the samples, a calibration curve relating to standard concentrations of drugs was established. A serial dilution of drugs from 0 - 100 µg/mL was injected into the column and area under curves was determined from HPLC data. A calibration curve of area under curves vs. concentration of drugs was established and the amount of drug samples was determined by interpolation. The experiments were conducted in triplicate.
3.3.7 Differential scanning calorimetry (DSC) analysis
The crystallinity and solid nature of SLNs was investigated by assessing their thermal behaviour by DSC on a 2920 Modulated DSC (see Section 3.2.5). Samples (~ 4 mg) of bulk stearic acid, drug and SLNs were weighed in 40 µL aluminium pans and sealed. The sealed pans were kept under isothermal conditions at 25°C for 10 min. Unless otherwise specified, the DSC curves for the bulk stearic acid and the SLNs were recorded from 25
78 Chapter 3 Experimental Section
- 80°C at a heating rate 10°C/min, and then cooled to 25°C in an inert nitrogen gas atmosphere. An empty sealed aluminium pan was used as a reference. The melting enthalpy (ΔH) was obtained by integration of the area under the transition peak using the Universal Analysis 2000 software (TA Instruments, Delaware, USA). The degree of crystallinity, or crystallinity index (CI), was determined by Equation 3.6,
∆HSLN CI (%) = × 100 ∆Hbulk lipid × Concentration of lipid phase (%) … Equation 3.6
3.3.8 X-ray diffraction (XRD) analysis
The crystallinity of SLNs was also investigated by studying the diffraction patterns obtained by XRD on a D8 Advance diffractometer (see Section 3.2.6). Unless otherwise specified, samples were placed on glass sample holders and scanned from 3.5° to 50° with an angular scan speed of 0.75° per minute. The operating voltage was 40 kV and the current was 40 mA. The diffraction patterns of bulk stearic acid and SLNs were collected using primary monochromatic radiation. Characteristic peaks for stearic acid were identified. Comparison in terms of reduced intensity and positions of characteristic peaks was made between the diffraction patterns of SLNs and stearic acid to investigate the crystallinity of SLNs.
3.3 B In vitro cell culture studies
3.3.9 Thawing of cells
The cryogenic vial containing the frozen cells was placed in a warm water bath (37C) for a very short period (< 1 min). The thawing procedure is stressful to frozen cells, and so care was taken to thaw the cells rapidly. The thawed cells were diluted with pre- warmed media (37C). The cell freezing media (see Section 3.4.2) often contains 10% DMSO which may prove toxic once warmed above 4C. Immediate dilution of thawed cells with pre-warmed media ensures that a high proportion of the cells survive the thawing procedure. The cell suspension was then subjected to centrifugation (1000 g, 5 min, 4C) to collect the cells. The supernatant was discarded and the cell pellet was resuspended in fresh medium (5 mL). The cell suspension was placed in disposable 25
79 Chapter 3 Experimental Section
2 cm culture flasks and incubated at 37C in a humidified atmosphere containing 5% CO2 (Heraeus BB15 Function Line, Thermo Electron Corporation, Australia).
3.3.10 Subculturing of cells
The cells were regularly cultivated as monolayers in disposable 25 cm2 culture flasks in complete DMEM (see Section 3.4.1). The cells were passaged when 80 - 90% confluent (most likely every 2 - 3 days). The culture medium was carefully aspirated from the culture flasks (taking care not to disturb the confluent cells) using a sterile pipette. The cells were washed twice with approximately 5 mL of sterile PBS solution (see section 3.4 A for preparation of PBS). A 0.25% trypsin/EDTA solution (2 mL) was added to the culture flask to cover the cell monolayer and incubated at 37C in 5% CO2 atmosphere for 3 - 4 min to allow the cells to detach. Fresh media (3 mL) was added to the culture flasks to resuspend the detached cells. FBS in culture medium neutralises the action of trypsin. The cell suspension was aspirated from the flasks and subjected to centrifugation (1000 g, 5 min, 4C) to collect the cells. The supernatant was discarded and the cell pellet was resuspended in fresh medium (5 mL). Cells were counted after appropriate dilution of cell suspension. Cells were seeded at a density of 1.5 × 105 cells per flask and incubated at 37C in 5% CO2 atmosphere until next passage.
3.3.11 Cryopreservation of cells
To prepare cells for storage, a confluent monolayer of cells was detached from the culture flask with 0.25% trypsin/EDTA solution as described in Section 3.3.10. The cell suspension was subjected to centrifugation (1000 g, 5 min, 37C). The supernatant was discarded and the cell pellet was resuspended in cell freezing media (see Section 3.4.2). A cell count was performed to divide the cell suspensions into aliquots of 1 × 106 cells per cryogenic storage vial using a sterile pipette. The vials were packed in cotton wool and placed on ice or in a refrigerator (4C). The cryogenic vials were then cooled at -20C for 2 h and then transferred to -80°C for gradual freezing overnight. The vials were transferred in liquid nitrogen on the next day for long term storage.
80 Chapter 3 Experimental Section
3.3.12 Cell viability assay
The cells were seeded into 96-well plates at a seeding density of 1 × 104 cells per well, in complete DMEM (200 L), and allowed to attach for 24 h. Following 24 h incubation, the media were aspirated, followed by addition of drug-free and drug-loaded SLN dispersions (100 L) diluted in DMEM (two-fold dilutions, ranging from 3.125 - 100 g/mL). An equal volume (100 L) of complete DMEM was then added to each well and incubated for 24 h at 37C in 5% CO2 atmosphere. A 0.1% Triton-X 100 solution was taken as a positive control. The untreated cells (without any sample) were considered to be a negative control.
The viability of cells following exposure to samples was measured using MTT assay. Following 24 h incubation, the medium with the samples was aspirated and 170 l MTT solution (5 mg/mL MTT in sterile PBS, pH 7.4) was added to the DMEM in the well
(final concentration of 0.32 mg/mL) and incubated for 2 h at 37C in 5% CO2 atmosphere. The medium with MTT solution was discarded and formazan crystals were solubilised using 150 L DMSO. The plates were further incubated for 15 min at room temperature and in the dark. Absorbance at 570 nm (directly proportional to cellular metabolism) was measured using a POLARstar microplate reader (Omega, BMG LabTech). Cell viability was calculated using Equation 3.7,
Absorbance of treated cells Cell viability (%) = × 100 Absorbance of control cells … Equation 3.7
Equation 3.7 assumes the Beer-Lambert law is obeyed (i.e. absorbance is directly proportional to concentration). This is true provided absorbance < 1 which was true in all cases.
3.2.13 Statistical analysis
Except where otherwise stated, experiments were performed in triplicate. The data are presented as mean ± standard deviation (mean ± SD) unless otherwise stated. The statistical significance was evaluated using a Student’s t test and analysis of variance (ANOVA) tests. A p value of <0.05 was considered statistically significant.
81 Chapter 3 Experimental Section
3.4 Preparation of buffers and media
3.4 A Phosphate buffer saline (PBS), pH 7.4
The reagents given in Table 3.2 were accurately weighed and dissolved in 800 mL of distilled water. A 100 mM HCl solution was added to adjust the pH to 7.4 and volume made up to 1 L with distilled water. PBS solution was autoclaved for 16 min at 121C and 15 psi on a liquid cycle.
Table 3.2 Composition of phosphate buffered saline (pH 7.4)
Ingredients Amount to be added Final concentration
NaCl 8 g 137 mM
KCl 0.2 g 2.7 mM
Na2PO4 1.44 g 10 mM
KH2PO4 0.24 g 1.8 mM
The concentration of PBS (in molarity) was adjusted as per the requirements of the studies for e.g. a 100 mM PBS was used for drug release studies.
3.4 B Cell culture
All cell culture media were prepared in a biological safety cabinet class II to maintain aseptic conditions.
3.4.1 Complete DMEM
Complete DMEM was used for maintenance of cell lines, subculturing of cells, and preparing the cells for the various in vitro assays conducted in this research. Table 3.3 shows the concentration of each ingredient in the complete DMEM (in % v/v).
82 Chapter 3 Experimental Section
Table 3.3 Composition of complete DMEM used in cell culture
Ingredients Concentration (% v/v)
DMEM 89
FBS 10
Antibiotic solution (contains penicillin G sodium, 10,000 U/mL and Streptomycin, 10,000 µg/mL) 1
3.4.2 Cell freezing media
The cells were prepared in cell freezing media for storage in liquid nitrogen (suitable for long storage of cells). Table 3.4 shows the concentration of each ingredient with their concentrations (in % v/v) used in the preparation of cell freezing media.
Table 3.4 Composition of cell freezing medium used in cryopreservation of cells
Ingredients Concentration (% v/v)
DMEM 10
FBS 80
DMSO 10
3.4.3 Potassium-free medium
The cells were incubated in a potassium-free medium (Table 3.5) to inhibit the clathrin- mediated endocytosis (see Chapter 9).
Table 3.5 Composition of potassium-free medium
Ingredient Concentration
NaCl 140 mM
CaCl2 1 mM
MgCl2 1 mM
4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) 20 mM
D-glucose 5.55 mM
83 Chapter 3 Experimental Section
3.4 C Antimicrobial assays
Dehydrated microbiological media were purchased from Oxoid (Australia). Media were prepared using distilled water and sterilised by autoclaving at 121°C for 16 min unless otherwise stated. 1.5% (w/v) bacteriological agar (Micromedia) was used as a solidifying agent for preparing solid culture media. The various microbiological media used in this thesis are listed in Table 3.6 with quantities (in g) required to make up a 1 L solution and an approximate pH value of their solutions.
Table 3.6 Microbiological media used in this study
Medium g/L of water pH
Brain Heart Infusion (BHI) broth 37.0 7.4 ± 0.2
Nutrient broth 13.0 7.4 ± 0.2
Sabouraud Dextrose broth 50.0 7.3 ± 0.2
3.4 D Simulated gastrointestinal (GI) fluids
The simulated GI fluids used for stability studies (see Chapter 10) were prepared according to Zimmermann and Muller (2001). The composition of the simulated GI fluids is given in Table 3.7.
Table 3.7 Composition of simulated GI fluids
pH 1.1 pH 3.5 pH 7.4
68 g NaH2PO4.H2O 12 mL HCl (32%) Solution 1: 150 mL 15.6 g NaOH 1188 mL distilled water Solution 2: 100 mL 10 L distilled water
Solution 1 contains: 10.5 g citric acid + 100 mL NaOH (1 M) + 395.5 mL distilled water Solution 2 contains: HCl (0.2 M)
Each of these simulated GI fluids was adjusted to iso-osmolarity with NaCl (i.e. 0.9 g/100 mL)
84 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique 4
Introduction and Optimisation of A Novel Microwave-assisted Microemulsion Technique for Production of Solid Lipid Nanoparticles (SLNs)
85 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
Abstract
A thorough understanding of the influence of lipid and surfactant composition on stability, particle size and zeta potential plays an important role in designing solid lipid nanoparticles (SLNs) for applications in drug delivery. The in vitro stability and in vivo delivery of the encapsulated drug molecules is often influenced by the physicochemical properties of the SLNs. To find a suitable formulation for developing the novel microwave-assisted microemulsion technique (reported for the first time in this thesis) as an appropriate production methodology for SLNs, ninety formulations with varying combinations of lipids (stearic acid, Imwitor® 900K, Dynasan® 114, Compritol® 888 ATO, cetyl palmitate and Witepsol® E85) and surfactants (Tween® 20, Tween® 80 and Cremophor® EL) were investigated by 22 factorial designs (with one centre point). The influence of varying the concentrations of these components on particle size, size distribution and zeta potential was investigated. To avoid unnecessary complications in this development stage, only single lipid-surfactant systems were systematically trialled. Future work (started in this thesis) involving multiple surfactants should produce even more stable and robust systems.
Formulations with smaller particles, a narrow size distribution and larger zeta potential magnitude are the goals for further development of the microwave-assisted technique. Stearic acid-based and Imwitor® 900K-based formulations exhibited promising results. Stearic acid is inexpensive, inert and readily available. Often used to mask bitter taste, it has been used recently as an encapsulation medium and is of GRAS status. Therefore, a stearic acid-based formulation was selected for further experimentation throughout the thesis. Stearic acid-based SLNs exhibited optimal size with narrow distribution of particles and good zeta potentials.
In addition to this, the influence of electrolytes, co-emulsifiers, solvents and sstabilisers on particle characteristics was also investigated.
86 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
4.1 Introduction
Solid lipid nanoparticles (SLNs) have recently emerged as an attractive alternative to more traditional colloidal drug carriers. In theory, SLNs combine the advantages of emulsions, polymeric nanoparticles and other traditional carriers whilst overcoming the limitations inherent to those colloidal systems. The application of SLNs as drug delivery vehicles, therefore, appears promising. Most of the approaches employed in the production of SLNs appear to be a two-step process (see Chapter 1, Section 1.6): (1) creation of an oil-in-water (o/w) microemulsion and (2) generation of SLNs by subsequent solidification of the dispersed lipid droplets.
The SLN particle size is presumed equivalent to the emulsion droplet size prior to solidification. The emulsion droplet size is influenced by a number of factors such as the shear forces that are exerted on its surface, interfacial tension, viscosity of dispersed lipid phase and viscosity of the dispersion medium. Different emulsification (and variants thereof) efforts that have been reported in SLN production have focused on strategies that reduce the interfacial tension and viscosity, increasing the shear forces imparted on the emulsion droplets (see Chapter 1, Section 1.5, Table 1.4).
The production of SLNs from emulsions has several significant challenges. Most of the techniques that are employed produce emulsions with polydisperse droplets (a considerable proportion of emulsions droplets exceed the desired submicron threshold), and are thus polydisperse SLNs on solidification. The precursor emulsions are often subjected to large mechanical forces (such as in high pressure homogenisation, or high sheer homogenisation or ultrasonication) to overcome issues related to polydispersity and undesirably large emulsion droplets (see Chapter 1, Section 1.5, Table 1.4). The high energy inputs involved in such approaches increase operating costs, increase the risk of metal contamination and may degrade mechanically and thermally sensitive drug molecules (Triplett and Rathman, 2009). Solvent-based techniques (such as solvent evaporation, solvent diffusion and solvent injection) have been pursued to avoid application of large mechanical energy (see Chapter 1, Section 1.5, Table 1.4). However, toxicity of organic solvents used in SLN production limits their use.
Despite the inherent challenges of emulsion-based approaches, they are worth pursuing and the current study has made considerable advances in the production of SLNs from emulsions. In an effort to avoid large mechanical energy input and improve the
87 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique production of SLNs from microemulsion templates, the use of microwave energy (or heating) has been employed. By offering a novel, innovative, energy-conserving, ecologically-friendly and time-saving technology, the microwave-assisted microemulsion technique may provide a promising approach in SLN production.
For the present work, some of the lipids (stearic acid, Imwitor® 900K, Dynasan® 114, Compritol® 888 ATO, cetyl palmitate and Witepsol® E85) and surfactants (Tween® 20, Tween® 80 and Cremophor® EL) that have been previously used in the production of SLNs were selected. The lipid, itself, is the main ingredient of SLNs that influence their drug loading capacity, their stability and the sustained release behaviour of the formulations. Most of these lipids, with the notable exception of cetyl palmitate, are approved as generally-recognised-as-safe (GRAS) and are physiologically well- tolerated. Surfactants form the other critical component of the SLN formulations. Surfactants used in the preparation of SLNs play two quite distinct and important roles: (a) dispersing the lipid melt in the aqueous phase during the production process and (b) stabilising the SLNs in dispersions after cooling. In this chapter, a systematic strategy for optimisation of formulation parameters was applied.
88 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
4.2 Chapter Aims
The aim of this chapter is to optimize a formulation that will then be used throughout the thesis for investigating the efficiency of the novel microwave-assisted microemulsion technique to produce SLNs.
The specific aims of this chapter:
To introduce the use of microwave heating in the production of microemulsions and SLNs. To investigate the effect of varying combinations of lipids and surfactants on particle characteristics of SLNs. To select an optimised SLN formulation that can then be employed as a possible candidate to encapsulate various drug molecules. To investigate the effect of acid, base or salt addition on particle characteristics. To understand the effect of co-emulsifiers and stabilisers on SLN characteristics. To characterise SLNs prepared from microemulsions employing different organic solvents.
89 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
4.3 Methods
4.3.1 Preparation of solid lipid nanoparticles (SLNs) and solid lipid microparticles (SLMs)
The SLNs and SLMs were prepared by the microwave-assisted microemulsion technique (see Section 3.3.1). In brief, the composition ingredients (lipid, surfactant and water) were heated above the melting point of the lipid material in a microwave reactor tube with constant stirring to produce an o/w emulsion. The microwave reaction temperature was set to 85C with a variable microwave power of (but not exceeding) 10 W and the reaction was maintained at the set temperature for 10 min. The hot o/w microemulsion was then dispersed immediately into cold water (50 ml, 2 - 4C), under constant magnetic stirring to generate dispersions of lipid particles.
4.3.2 Particle characterisation
The intensity weighted mean hydrodynamic diameter and the polydispersity index (PI) of the SLN dispersions were determined by DLS at 25C as described in Section 3.3.2.1.
The zeta potential measurements were carried out as described in Section 3.3.2.3. The zeta potential of the SLN dispersions was determined by measurement of the electrophoretic mobility.
4.3.3 Selection of Formulation
Prior to encapsulation of active ingredients into SLNs and their extensive characterisation, an attempt was made to systematically evaluate all relevant combinations of lipids and surfactants in terms of their effects on key particle characteristics. All formulations were subjected to particle size analysis and zeta potential measurements.
4.3.3.1 Design of Experiment (DoE)
The basic experimental design consists of a set of 2-level factorial designs where one factor from each of two categories, lipid and surfactant, was selected. One of the six lipids, stearic acid (SA), Imwitor® 900K (I900K), Dynasan® 114 (D114), Compritol®
90 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
888 ATO (C888), cetyl palmitate (CP) and Witepsol® E85 (WE85), was investigated in combination with one of the three surfactants, Tween® 20 (T20), Tween® 80 (T80) and Cremophor® EL (CEL). For each combination of lipid and surfactant (two factors or variables), a 22 factorial design with one centre point was carried out, testing different concentrations (high and low levels and one centre point) of the two variables. The values for the high and low points were decided by comparison with literature formulations. The experiments were performed in a random order to avoid any systematic bias in the results. All DoE and modelling of contour plots were performed using Minitab® version 17 (Minitab Inc., USA).
Table 4.1 illustrates the investigated factors used in this chapter. In total, ninety SLN formulations were screened in preliminary experimentation to understand the effect of lipids and surfactants on the particle characteristics.
Table 4.1 DoE: Factors and levels for 22 factorial designs
Level Factors Low Centre High
Lipid content (mg) 50 75 100
Surfactant content (µL) 100 125 150
Categories
Lipid type I900, D114, C888, CP, SA, WE85
Surfactant type T20, T80, CEL
4.3.3.2 Formulation annotation
The SLN formulations were identified on the basis of their quantitative composition. A unique code was assigned to each SLN formulation. The formulation code consists of an abbreviation for the lipid type and its amount (a number as a subscript) followed by an abbreviation for the surfactant type and its amount (a number as a subscript). e.g. ® ® I90050T20100 denotes a formulation containing Imwitor 900K (50 mg) and Tween 20 (100 µL).
91 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
The formulation composed of stearic acid and Tween® 20 in water was found to have lower particle size and least PI value amongst the others (see Results and Discussion, Section 4.4.2 and 4.4.3) and was, therefore, used in subsequent experiments unless mentioned otherwise and was treated as the control.
4.3.4 Influence of solvents for preparation of SLNs
To evaluate the influence of solvents, water in the original formulation (control) was replaced with different solvents, including methanol, ethanol, 2-propanol, 2-butanol, acetone, ethylene glycol and ethyl acetate.
4.3.5 Evaluation of formulation parameters
4.3.5.1 Influence of excipients
Influence of lipid and surfactant concentration
A full factorial design of experiments was used to prepare SLNs with varying amounts of stearic acid and Tween® 20. The amount of stearic acid and the concentration of Tween® 20 were the two variables investigated at three levels (coded as low, centre and high) (Table 4.2). The experiments were performed in a random fashion to avoid any systematic bias in the results.
Table 4.2 DoE: Factors and levels for full factorial designs
Levels Variables Low Centre High
Mass of stearic acid (mg) 50 75 100
Volume of Tween® 20 (µL) 75 100 125
Nine stearic acid-based formulations were prepared based on this DoE. The composition and code of each of these formulations is given in Table 4.3.
92 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
Table 4.3 Composition of stearic acid-based SLNs
Formulation code Amount of stearic acid (mg) Amount of Tween® 20 (µl)
F1 50 75
F2 50 100
F3 50 125
F4 75 75
F5 75 100
F6 75 125
F7 100 75
F8 100 100
F9 100 125
Influence of acid, base and salt
To evaluate the influence of an acid, base or a salt on the formulation as an excipient, formulations with the addition of 100 µl 0.1 M NaOH, 0.1 M HCl or 0.1 M NaCl were evaluated.
Influence of co-emulsifiers
To evaluate the influence of the co-emulsifiers soy lecithin, Span® 20, Span® 80, 1- butanol and 2-propanol, formulations with and without these co-emulsifiers were evaluated. The total volume of emulsifiers (with co-emulsifiers) was 125 µL. The proportion of emulsifier and co-emulsifier was based on the hydrophilic-lipophilic balance (HLB) system (Pasquali et al., 2008; Pasquali and Helguera, 2013).
Influence of stabilisers
To evaluate the influence of the stabiliser, Lutrol® F68, formulations with and without the stabiliser were evaluated. The volume of Tween® 20 was 125 µl and the concentration of the stabiliser was 1% (w/v).
93 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
4.3.5.2 Short-term storage stability
The initial particle size analysis of the SLN dispersions was performed on the day of production (See section 4.3.2.1). The SLN formulation with and without NaOH was divided into three sample sets, one stored at 4C (in a refrigerator), the second stored at 25C and the third stored at 37C (both in temperature-regulated incubators). All samples were stored in colourless sealed glass vials. Samples were removed after 4, 15, 30, 45 and 60 days and subjected to particle size measurements.
94 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
4.4 Results and Discussion
4.4.1 Preparation of SLNs
Conventionally, the microemulsion technique for preparing SLNs is a two-step procedure: (1) synthesis of a microemulsion by mixing the heated composition ingredients and (2) subsequent dispersion in cold water for generation of SLNs. In the microwave-assisted method reported in this thesis, however, preparation of the microemulsion is a “single-pot” step wherein all the composition ingredients are heated together in controlled microwave reaction conditions. The principle behind microwave- ingredient interaction (microwave theory) was described earlier (see Chapter 1, Section 1.8).
4.4.2 Selection of the formulation
The rationale was to select a fatty acid (SA), a monoglyceride (I900), a diglyceride (C888), a triglyceride (D114) and some waxes or low melting point lipids (CP and WE85). These lipids in combination with each of the three surfactants, T20, T80 and CEL, were used in the production of lipid particles.
4.4.2.1 Assessment of particle size and polydispersity index (PI)
The primary criterion used to decide on the best dispersion was a small particle size, as this parameter has been reported in the literature to be reflective of a stable dispersion (Heurtault et al., 2003). The particle size also influences the properties of the materials, and decides the fate of particles in a biological system (Wu et al., 2011). Therefore, particle size was selected as the most important response parameter in selection of lipids and surfactants for further optimisation of lipid particles as drug carriers. The PI value that estimates the breath of the particle size distribution in dispersions was used as a secondary parameter in selection of formulation ingredients. The particle size analysis was also used to confirm the production of particles in the nanometre size (or submicron) range.
Two lipid materials, namely Imwitor® 900K (I900) and stearic acid (SA), in combination with any of the three surfactants – T20, T80 or CEL, produced particles in the nanometre size range. The results for I900-based and SA-based SLNs stabilised with T20, T80 and
95 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
CEL are summarised in Tables 4.4, 4.5 and 4.6 respectively. The particle characteristics of particles produced from other lipids (in combination with the three surfactants) are summarized in Table 4.7. These formulations produced large particles and were deemed unsuitable for this thesis, and therefore, will not be discussed further. The results, however, indicate that the size of particles produced was considerably influenced by the lipid and surfactant used in their production. No correlation between the chemistry of the lipids and particle size was observed.
Table 4.4 Particle characteristics of SLNs stabilised with Tween® 20
Formulation code pH Diameter (nm) PI
I90050T20100 5.3 71 ± 12 0.30 ± 0.04
I90050T20150 5.5 31 ± 1 0.23 ± 0.02
I90075T20125 5.2 369 ± 59 0.46 ± 0.07
I900100T20100 5.4 697 ± 145 0.42 ± 0.05
I900100T20150 5.5 398 ± 49 0.36 ± 0.04
SA50T20100 5.2 169 ± 14 0.17 ± 0.05
SA50T20150 5.2 105 ±5 0.23 ± 0.04
SA75T20125 5.2 195 ± 16 0.19 ± 0.05
SA100T20100 5.2 247 ± 16 0.19 ± 0.07
SA100T20150 5.2 206 ± 10 0.22 ± 0.07
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Table 4.5 Particle characteristics of SLNs stabilised with Tween® 80
Formulation code pH Diameter (nm) PI
I90050T80100 4.7 167 ± 16 0.34 ± 0.03
I90050T80150 4.2 76 ± 4 0.30 ± 0.02
I90075T80125 4.1 165 ± 7 0.28 ± 0.03
I900100T80100 4.6 234 ± 23 0.29 ± 0.04
I900100T80150 4.1 175 ± 8 0.29 ± 0.03
SA50T80100 4.7 272 ± 11 0.23 ± 0.05
SA50T80150 4.2 230 ± 17 0.22 ± 0.05
SA75T80125 4.1 380 ± 61 0.28 ± 0.07
SA100T80100 4.8 396 ± 43 0.35 ± 0.03
SA100T80150 4.2 236 ± 11 0.23 ± 0.05
Table 4.6 Particle characteristics of SLNs stabilised with Cremophor® EL
Formulation code pH Diameter (nm) PI
I90050CEL100 5.2 178 ± 16 0.29 ± 0.04
I90050CEL150 5.7 75 ± 5 0.30 ± 0.03
I90075CEL125 5.3 201 ± 15 0.31 ± 0.03
I900100CEL100 5.5 448 ± 68 0.35 ± 0.05
I900100CEL150 5.8 247 ± 20 0.31 ± 0.05
SA50CEL100 5.5 259 ± 15 0.20 ± 0.07
SA50CEL150 5.6 232 ± 16 0.23 ± 0.05
SA75CEL125 5.5 229 ± 13 0.22 ± 0.06
SA100CEL100 5.4 250 ± 11 0.23 ± 0.07
SA100CEL150 5.6 230 ± 11 0.21 ± 0.07
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Table 4.7 Particle characteristics of lipid particle dispersions prepared using other lipid-surfactant combinations
Formulation code pH Diameter (nm) PI
D11450T20100 4.4 1605 ± 272 0.37 ± 0.09
D11450T20150 4.2 1423 ± 434 0.42 ± 0.06
D11475T20125 4.0 2033 ± 510 0.51 ± 0.14
D114100T20100 4.7 2809 ± 476 0.33 ± 0.16
D114100T20150 4.1 2023 ± 524 0.32 ± 0.12
D11450T80100 5.4 918 ± 145 0.36 ± 0.06
D11450T80150 5.6 264 ± 33 0.38 ± 0.04
D11475T80125 5.1 866 ± 243 0.39 ± 0.08
D114100T80100 5.3 1338 ± 285 0.30 ± 0.06
D114100T80150 5.6 561 ± 128 0.36 ± 0.07
D11450CEL100 5.6 > 10 µm NA
D11450CEL150 5.8 > 10 µm NA
D11475CEL125 5.6 > 10 µm NA
D114100CEL100 5.6 > 10 µm NA
D114100CEL150 5.7 > 10 µm NA
C88850T20100 4.7 663 ± 167 0.30 ± 0.03
C88850T20150 4.1 1962 ± 519 0.43 ± 0.06
C88875T20125 4.0 1426 ± 260 0.35 ± 0.06
C888100T20100 4.7 1320 ± 233 0.36 ± 0.06
C888100T20150 4.2 2193 ± 481 0.51 ± 0.05
C88850T80100 5.3 324 ± 101 0.35 ± 0.05
C88850T80150 5.4 47 ± 9 0.25 ± 0.03
C88875T80125 5.0 905 ± 128 0.35 ± 0.10
C888100T80100 5.2 1587 ± 309 0.32 ± 0.08
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Formulation code pH Diameter (nm) PI
C888100T80150 5.4 394 ± 303 0.27 ± 0.12
C88850CEL100 5.5 26 ± 2 0.15 ± 0.04
C88850CEL150 5.6 24 ± 1 0.16 ± 0.04
C88875CEL125 5.5 40 ± 3 0.21 ± 0.04
C888100CEL100 5.5 67 ± 2 0.26 ± 0.03
C888100CEL150 5.8 34 ± 2 0.17 ± 0.03
CP50T20100 4.7 > 10 µm NA
CPS50T20150 4.1 > 10 µm NA
CP75T20125 4.0 > 10 µm NA
CP100T20100 4.8 > 10 µm NA
CP100T20150 4.1 > 10 µm NA
CP50T80100 5.4 1428 ± 462 0.48 ± 0.06
CP50T80150 5.6 1479 ± 274 0.44 ± 0.09
CP75T80125 5.3 1419 ± 386 0.46 ± 0.07
CP100T80100 5.5 1839 ± 483 0.33 ± 0.11
CP100T80150 5.6 768 ± 333 0.47 ± 0.13
CP50CEL100 5.8 > 10 µm NA
CP50CEL150 5.8 > 10 µm NA
CP75CEL125 5.8 > 10 µm NA
CP100CEL100 5.8 > 10 µm NA
CP100CEL150 5.8 > 10 µm NA
WE8550T20100 4.7 3139 ± 1051 0.36 ± 0.11
WE8550T20150 4.2 3120 ± 1153 0.36 ± 0.06
WE8575T20125 4.0 4571 ± 1928 0.37 ± 0.11
WE85100T20100 4.7 4425 ± 1450 0.41 ± 0.08
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Formulation code pH Diameter (nm) PI
WE85100T20150 4.2 4410 ± 1741 0.39 ± 0.19
WE8550T80100 5.5 450 ± 58 0.32 ± 0.07
WE8550T80150 5.7 254 ± 12 0.22 ± 0.05
WE8575T80125 5.1 1775 ± 560 0.50 ± 0.06
WE85100T80100 5.5 1858 ± 435 0.36 ± 0.11
WE85100T80150 5.7 1373 ± 342 0.46 ± 0.07
WE8550CEL100 5.8 > 10 µm NA
WE8550CEL150 5.9 > 10 µm NA
WE8575CEL125 5.7 > 10 µm NA
WE85100CEL100 5.7 > 10 µm NA
WE85100CEL150 5.9 > 10 µm NA
From the results summarised in Tables 4.4 - 4.6, all I900-based and SA-based formulations produced particles in the nanometre size range and therefore, are discussed here. The other lipids were less successful and were not pursued. Future studies may involve optimisation of these less successful lipids using, for example, HLB derived surfactant mixtures rather than single surfactants.
The results were further analysed using contour plots. The contour plots for particle size characteristics of I900-based and SA-based SLNs stabilised with T20, T80 and CEL are depicted in Figures 4.1, 4.2 and 4.3 respectively.
100 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
100 100 600 220 (a) 400 (b) 240
90 90
) 500
g 180
)
g
m
(
m
80 ( 80
K
d
0
i
0 c
a
9
r c
i o
r 200
t a i 200
70 e 70 w
300 t
S m I 140
60 60
100 160 120 50 50 100 110 120 130 140 150 100 110 120 130 140 150 Tween 20 (µl) Tween 20 (µl)
Figure 4.1 Contour plots from particle size analysis of SLNs stabilised with Tween® 20. The SLNs were prepared from (a) Imwitor® 900K and (b) stearic acid.
100 100 175 (a) 225 (b) 400 375 325 275
90 90
)
g
)
g
m
(
m
80 ( 80
K 200
d 0
i 350
0 c
a
9
r c
125 i
o
r
t
a i
70 e 70
w
t
S
m I
60 60
300 150 100 50 50 100 110 120 130 140 150 100 110 120 130 140 150 Tween 80 (µl) Tween 80 (µl)
Figure 4.2 Contour plots from particle size analysis of SLNs stabilised with Tween® 80. The SLNs were prepared from (a) Imwitor® 900K and (b) stearic acid.
101 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
Figure 4.3 Contour plots from particle size analysis of SLNs stabilised with Cremophor® EL. The SLNs were prepared from (a) Imwitor® 900K and (b) stearic acid.
From the particle size results (Table 4.4), all except one SLN formulation (I900100T20100) prepared from either lipids and stabilised with Tween® 20 revealed submicron particle sizes. However, all of the stearic acid-based SLNs exhibited small particle sizes (200 - 250 nm). The PI values of Imwitor® 900K-based SLNs were between 0.20 and 0.50. Stearic acid-based SLNs exhibited PI values slightly lower, generally < 0.25. Particle dispersions with PI values ≤ 0.10 reflect excellent monodispersity, while values ≤ 0.25 indicate narrow size distribution (Martins et al., 2012c). PI values > 0.50 indicate polydispersed populations (Kaur et al., 2008). The results, therefore, indicate a narrow size distribution of stearic acid-based SLNs. The combined effects of Imwitor® 900K (or stearic acid) and Tween® 20 was also investigated (Figure 4.1). Irrespective of the lipid ® matrix, SLNs stabilised with Tween 20 show similar trends. The results indicate that the size of SLNs is lipid concentration-dependent. Particle size increases when the amount of lipid is higher, and decreases with increasing surfactant content.
® For SLNs stabilised with Tween 80 (Table 4.5), particle sizes for all SLNs were in the submicron range. Unlike Tween® 20, stearic-acid based SLNs had larger particle sizes ® compared to Imwitor 900K-based SLNs. The PI values of all SLNs were between 0.20 and 0.35 indicating slightly monodispersed to polydispersed populations. Nevertheless, the PI values were ≤ 0.50 and therefore, considered acceptable. The combination of Imwitor® 900K and Tween® 80 had similar effects as when stearic acid was combined with Tween® 80. In both the cases, the particle sizes of the SLNs increased with
102 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique increasing amount of lipid used. In contrast, particle sizes of the SLNs decreased when smaller amounts of Tween® 80 were used. Figure 4.2 depicts the combined influence of lipid and Tween® 80 on the particle sizes of SLNs.
® Table 4.6 summarises the particle characteristics of stearic acid-based and Imwitor ® 900K-based SLNs stabilised with Cremophor EL. The particle sizes of SLNs, irrespective of the lipid material, were within submicron ranges. Depending on the ® ® concentration of Cremophor EL used in the preparation, particle sizes of Imwitor 900K-based SLNs ranged between 70 and 450 nm with PI values ≤ 0.35. In contrast, particle sizes of stearic-acid-based SLNs were within a narrow range of 220 – 260 nm and PI values ≤ 0.25. The results indicate that stearic acid-based SLNs have a slightly more monodispersed population. The combined effect of lipid and surfactant showed a similar trend to the earlier combinations of lipids and surfactants. Particle sizes of SLNs, irrespective of lipid material, increased with an increase in the amount of lipid and a decrease in the amount of surfactant (Figure 4.3). However, the combined effect of stearic acid and Cremophor® EL was more linear (which can be observed in Figure 4.3 (b)) than any other formulation discussed here.
4.4.2.2 Assessment of zeta potential
The pH of a formulation intended for in vivo administration is an important parameter that can interfere with the stability of the excipients and/or drug substances in the formulation. The results (Tables 4.4 – 4.7) show that Tween® 80 contributed to a lower pH with values between 4 and 5. Tween® 20 and Cremophor® EL contributed to pH values of 5 – 5.5 and 5.5 – 6, respectively. Amongst all the formulations prepared in this study, there was no one pH value at which all formulations were found to produce particles with similar sizes.
Zeta potential can be used as a measure of the degree of electrostatic repulsion between charged particles. It is particularly relevant here since the SLNs are solid in nature, unlike the liquid drops of conventional emulsions, and thus more likely to be genuinely charge stabilised. These forces of repulsion can be responsible for preventing particle aggregation and therefore can serve as a useful indicator of the physical stability of the formulation. The zeta potential values of all stearic acid-based and Imwitor® 900K-based formulations discussed earlier are summarised in Table 4.8.
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Table 4.8 Zeta potential of stearic acid-based and Imwitor® 900K-based SLNs stabilised with surfactants
Formulation Zeta Formulation Zeta Formulation Zeta code potential code potential code potential (mv) (mV) (mV)
I90050T20100 -10.7 ± 0.7 I90050T80100 -14.0 ± 0.4 I90050CEL100 -7.7 ± 1.1
I90050T20150 -17.4 ± 0.6 I90050T80150 -16.6 ± 0.7 I90050CEL150 -6.7 ± 1.4
I90075T20125 -11.7 ± 0.7 I90075T80125 -12.1 ± 0.7 I90075CEL125 -18.2 ± 1.2
I900100T20100 -13.4 ± 1.1 I900100T80100 -15.7 ± 1.0 I900100CEL100 -13.3 ± 0.3
I900100T20150 -15.0 ± 0.5 I900100T80150 -13.7 ± 0.2 I900100CEL150 -12.3 ± 1.5
SA50T20100 -22.5 ± 1.1 SA50T80100 -24.3 ± 0.7 SA50CEL100 -14.1 ± 1.8
SA50T20150 -23.8 ± 1.0 SA50T80150 -17.1 ± 0.7 SA50CEL150 -15.8 ± 1.2
SA75T20125 -20.0 ± 1.8 SA75T80125 -19.5 ± 0.6 SA75CEL125 -12.5 ± 2.2
SA100T20100 -19.3 ± 1.1 SA100T80100 -20.9 ± 0.3 SA100CEL100 -13.8 ± 0.7
SA100T20150 -19.9 ± 1.1 SA100T80150 -21.2 ± 0.9 SA100CEL150 -10.7 ± 1.2
The zeta potential values were ~ -20 mV for stearic acid-based SLNs stabilised with Tween® 20 and Tween® 80. For all other formulations, the values were between |5| and |20| mV. A minimum zeta potential of ~ |20| mV is desirable for systems stabilised by both electrostatic and steric stabilisation (Mitri et al, 2011; Tamjidi et al., 2013). However, the surfactants used in this study are non-ionic surfactants which may be steric stabilisers (see Chapter 10). There is no required value for zeta potential in systems stabilised by steric stabilisers alone (Bunjes and Siekmann, 2005). Although, therefore, there may not be a requirement for zeta potential to be optimised it is still prudent to choose systems where the absolute value approaches the ~ |20| limit discussed above. Future studies may deal with systems where the zeta potential is totally inadequate to impart any significant degree of electrostatic stabilisation.
Based on the particle size characteristics and zeta potential values, the formulation composed of stearic acid (75 mg) and stabilised with Tween® 20 (125 µl) was selected for further study on evaluation of formulation excipients and solvents (see Sections 4.4.3 and 4.4.4), as it exhibited low particle size and high zeta potential. It is also
104 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique biocompatible, inexpensive, inert and readily available. For example, stearic acid has been used to mask the taste of bitter drugs (Waters et al., 2011) in other formulations and has been recently applied as an encapsulation medium (Waters and Pavlakis, 2007; Waters et al., 2011). It has been accorded generally-recognised-as-safe (GRAS) status by the US Food and Drug Administration (2014). In view of all these considerations, and results obtained from screening studies, stearic acid was selected for preparation of SLNs in this research. It must, however, be appreciated that combinations of others lipids and surfactants (not used in this study) may produce smaller and more stable particles. Gullapalli and Sheth (1999) in their research on emulsions suggested that the emulsion stability is affected by the structural similarity between the hydrocarbon moieties of the oil phase and the surfactant. The hydrocarbon moiety of Tween® 20 (lauric acid) is structurally similar to stearic acid, and therefore, selection of Tween® 20 seems appropriate.
In this chapter, the effects of other selected excipients (see Section 4.4.3.1) and solvents (see Section 4.4.3.2) were investigated. The primary objective of this thesis was to develop a novel microwave-assisted technique and investigate its suitability in encapsulating representative model drug substances, rather than continue a search for optimized lipid and surfactant mixtures. Therefore, only formulations containing stearic ® acid and Tween 20 will be used throughout the remainder of this research.
4.4.3 Influence of solvents
The dielectric properties of solvents (dielectric constant, loss tangent, dielectric loss) play an important role determining how well it will absorb microwave energy (see Chapter 1, Section 1.8.3). Solvents that are better at absorbing the microwave energy may deliver more thermal energy to the microemulsion, potentially resulting in smaller particle sizes. The dielectric properties of solvents tested are summarised in Table 4.9.
105 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
Table 4.9 Dielectric properties of solvents relevant to this study (Hayes, 2004)
Solvent Dielectric constant (εʹ) Loss tangent (tan ô) Dielectric loss (εʹʹ)
Water 80.4 0.123 9.889
Methanol 32.6 0.659 21.483
Ethanol 24.3 0.941 22.866
2-propanol 18.3 0.799 14.622
2-butanol 15.8 0.447 7.063
Acetone 20.7 0.054 1.118
Ethylene 37.0 1.350 49.950 glycol
Ethyl acetate 6.0 0.059 0.354
While the presence of other ingredients in a formulation may increase or decrease the absorbing power of the solvents, this effect is deemed to be negligible since the bulk of the formulation ingredients consist of the dispersion medium (i.e. the solvent). The influence of solvents on particle characteristics was studied by replacing water (original formulation) with these other organic solvents. The solvents were chosen largely on the basis that they have been used by other researchers in preparation of SLNs by other techniques (see Chapter 1, Section 1.5). The particle size characteristics of SLNs prepared using these solvents as dispersion medium are depicted in Figure 4.4.
106 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
Particle size (nm) Polydispersity index 2000 1.0
1750 0.9 0.8 index Polydispersity 1500 0.7 1250 0.6 1000 0.5
750 0.4 0.3
Particlesize (nm) 500 0.2 250 0.1
0 *** 0.0
Water
Ethanol
Acetone
Methanol
2-butanol
2-propanol
Ethyl acetate Ethylene glycol Ethylene
Figure 4.4 Effect of solvents on particle characteristics of SLNs. The bars in the graph denote particle sizes (in nm) and the dots denote PI. *** Particle size of SLNs prepared in ethyl acetate was > 20 µm.
The results (Figure 4.4) demonstrate that the choice of solvent significantly influences the particle size of the SLNs. Amongst the solvents used as a dispersion medium in this study, ethylene glycol (and water) produced the smallest particles and ethyl acetate produced the largest particles (> 20 µm). The SLNs in ethylene glycol had similar particle size as those produced in water. There was no correlation observed between the particle sizes and any individual dielectric property, indicating that the solvents affect on the emulsion itself is more important that it’s affect on microwaving. It is recognised, however, that a more complex investigation may find an influence from the dielectric properties if the other salvation effects could be factored out.
The PI values for SLNs prepared using water were the smallest (~ 0.11) followed by ethylene glycol (PI ≤ 0.20), denoting narrow size distributions. PI values for all other formulations, except SLNs with ethyl acetate, were ≤ 0.50. Ethyl acetate gave PI values of ~ 0.60 indicating very broad size distribution which was also evident in its particle size measurements.
107 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
Based on these results, the SLNs produced in water as the dispersion medium gave optimal particle size and PI values. Therefore, water was selected as the dispersion medium for further experimentation in this thesis. The results for ethylene glycol, however, showed that should there be a requirement, in specific applications, to change the solvent, then this may be possible.
4.4.4 Evaluation of formulation excipients
4.4.4.1 Influence of the amount of stearic acid and Tween® 20
Figure 4.5 depicts a plot of particle size characteristics as a function of lipid and surfactant quantity on particle size.
Particle size (nm) Polydispersity index 400 0.35
350 0.30
300 index Polydispersity 0.25 250 0.20 200 0.15 150
Particlesize (nm) 0.10 100
50 0.05
0 0.00 F1 F2 F3 F4 F5 F6 F7 F8 F9
Figure 4.5 Particle characteristics of stearic acid-based SLNs stabilised with Tween® 20. The bars in the graph denote particle sizes (in nm) and the dots denote PI. Refer to Table 4.3 for formulation codes
When the amount of surfactant was kept constant, the SLNs with larger diameters were produced when using greater amounts of stearic acid. These results indicate that the amount of stearic acid had a significant influence on the particle size. This probably be due to a lack of sufficient surfactant to cover the particle surface. This increases the probability of increasing the particle-particle interactions resulting in particle aggregates and thus increased particle size (Ghadiri et al., 2012; Keck et al., 2014b). A larger amount
108 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique of lipids may also increase the viscosity of the emulsion and affect the sheering capacity of the stirrer used to mix the formulation constituents during production, again leading to increased particle size (Araujo et al., 2010).
Keeping the amount of stearic acid constant, smaller particles were produced at larger amounts of surfactants. Higher concentrations of surfactant allow better stabilisation of the smaller lipid droplets and thus prevent them from coalescing into larger droplets (Kovačević et al., 2011). At higher concentrations, sufficient surfactant present at the surface of the SLN reduced the surface tension between the two phases and enabled SLN formation when the hot microemulsion was rapidly injected into the cold water (Martins et al., 2012c).
4.4.4.2 Influence of acid, base and salt
The influence of addition of an acid (0.1 N HCl) or a base (0.1 N NaOH) or a salt (0.1 N NaCl) was investigated to check the pH range at which the SLNs may remain stable. The effects of these changes on particle characteristics are shown in Figure 4.6.
500 0.35
0.30 400
Polydispersity index Polydispersity 0.25 Particle size (nm) 300 Polydispersity index 0.20
200 0.15
Particlesize (nm) 0.10 100 0.05
0 0.00 Control Acid Base Salt
Figure 4.6 Particle characteristics of SLNs on addition of acid, base and salt. The bars in the graph denote particle sizes (in nm) and the dots denote PI.
The results demonstrate that the particle size of the formulations increased after the addition of each of these excipients (Figure 4.6). One possible explanation is that the
109 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique addition of such solutions introduces ions into the system which depletes the surfactant layer covering the surface of the SLNs, thereby increasing the particle-particle interactions and leading to increased particle sizes. Gavish and Promislow (2012) studied the influence of salt on dielectric properties of water. Presence of salt in water was reported to cause “dielectric decrement”, i.e. decrease in dielectric constant of water. The influence of salt in water may have an influence on the size of the particles. The results show that particle size increased on addition of salt, acid and base. The “standard” formulation, therefore, will not involve any addition of such excipients. The effect of acid, base and salt will be further investigated in Chapter 10.
The PI values, however, showed an opposing trend (Table 4.6). Addition of acid or salt to the system increased the PI value while addition of base decreased the PI values as compared to the control formulation. In the case of zeta potential, the zeta potential of control formulation was -14.6 ± 0.8 mV. Addition of base increased the zeta potential (- 40.2 ± 1.4 mV) while addition of acid lowered the zeta potential (-9.0 ± 0.1 mV), which correlates with the higher PI values observed in these formulations. Addition of salt had a small effect on zeta potential (-12.8 ± 1.2 mV). Notwithstanding increased particle size, formulation to which a base was added was selected for further excipient optimisation.
4.4.4.3 Influence of co-emulsifiers
The effects of co-emulsifiers such as Span® 20 (HLB = 8.6), Span® 80 (HLB = 4.3), 1- butanol (HLB = 7) and 2-propanol (HLB = 7.4) were also investigated. Matching the HLB of the emulsifier (with or without co-emulsifiers) to the required HLB of the lipid material used theoretically assists in the preparation of finely dispersed and physically stable formulations. A combination of emulsifiers with their combined HLB value matching the required HLB value usually gives a more stable product (Chen et al., 2010).
The required HLB value of stearic acid used in this study is 15. Based on the HLB system, and matching the HLB value to the required value of 15, combinations of Tween® 20/Span® 20 (79:21), Tween® 20/Span® 80 (86.25:13.75), Tween® 20/1-butanol (82.5:17.5) and Tween® 20/2-propanol (81.75:18.5) were added to the system. Figure 4.7 outlines the results of particle size analysis after addition of a co-emulsifier. Surprisingly, the particle size was found to increase after the addition of all co-emulsifiers, although generally there was the expected reduction seen in the PI values. Despite the same HLB
110 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique of mixtures of emulsifiers investigated in this study, there was a considerable difference in the particle sizes of SLNs. These results are in agreement with the explanation provided by Gullapalli and Sheth (1999). In their research on stability of emulsions, Gullapalli and Sheth (1999) suggested that mixtures of emulsifiers all adjusted to the same HLB would result in emulsions with varying degrees of stability and the stability of emulsions would then depend on the structural similarity between the emulsifiers and the lipid phase. Nevertheless, there is a wealth of emulsion experience which suggests that using multiple surfactants generally gives a better result than a single surfactant. Further experimentation, optimising all conditions (e.g. pH, total volume of surfactant, etc.) may result in a more promising particle size, however given that this was not forthcoming in some simple experimentation it was not felt appropriate to continue down that line at this stage. The situation may be very complex in these emulsions (as explained in Chapter 10) as the origin of the stability may be due to adsorption of surfactant micelles at the surface, so future experimentation with co-surfactants may need focus on micelle formation rather than HLB matching as initially thought.
500 0.35
0.30 Particle size (nm) 400 Polydispersity index Polydispersity Polydispersity index 0.25
300 0.20
200 0.15
Particlesize (nm) 0.10 100 0.05
0 0.00
Control
Span 20 Span 80 Span
1-butanol 2-propanol
Figure 4.7 Effect of co-emulsifiers on particle characteristics of SLNs. The bars in the graph denote particle sizes (in nm) and the dots denote PI.
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4.4.4.4 Influence of stabilisers
The effect of adding two different stabilisers to the dispersion medium was evaluated. Matching the HLB of the stabiliser with that of the internal lipid phase is expected to give a product with greater stability. The HLB value of Lutrol® F68 is ~ 28. Figure 4.8 depicts the particle size characteristics of SLNs with stabilisers. The results reveal an increase in particle size and PI value when Lutrol® F68 was added to the formulation. This may be due to the large difference between the HLB values. The higher molecular weight of Lutrol® F68 (~ 12.6 kDa) could be another reason for increased particle size. The results obtained in this thesis are consistent with the explanation provided by Martins et al. (2012c). In their study, Martins et al. (2012c) concluded that presence of a larger surfactant molecule such as poloxamer on the SLN surface may contribute to an increased SLN size. The lower zeta potential also suggests that the use of Lutrol® F68 as a stabiliser yields a less stable formulation (relative to the control formulation).
500 0.35 Particle size (nm) 0.30 Polydispersity index 400
Polydispersity index Polydispersity 0.25
300 0.20
200 0.15
Particlesize (nm) 0.10 100 0.05
0 0.00 Control Lutrol F68
Figure 4.8 Effect of stabiliser on particle characteristics of SLNs. The bars in the graph denote particle sizes (in nm) and the dots denote PI.
4.4.4.5 Short-term stability
The formulations containing the co-emulsifiers and stabilisers as an excipient were found to be unstable on the day following production (in contrast to the control which remained stable for at least several days). The SLNs were found to sediment at the bottom of the vial and therefore, were considered unsuitable for short-term stability assessment. The
112 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique instability of these formulations may be due to the combination of NaOH and the excipients which may lead to some untoward interactions between the components leading to particle aggregation.
The formulation with or without base as the only excipient in addition to stearic acid and Tween® 20 was selected for short-term stability studies. The physical stability of the optimised formulation was evaluated at 4C, 25C and 37C for 60 days by particle size measurements. Figure 4.9 depicts the short-term stability of SLNs stored at 4C.
500 with NaOH 400 without NaOH
300
200 Particlesize (nm) 100
0 0 4 15 30 45 60 Storage (days)
Figure 4.9 Short-term stability of SLNs stored at 4C.
The SLNs with or without NaOH stored at 25C resulted in sedimentation of a few particles. The particle size of SLNs with and without NaOH on day 0 was ~ 340 nm and ~ 225 nm respectively. Particle analysis of these samples revealed that the particle size increased to ~ 714 nm and ~ 480 nm after 4 days of storage, indicating poor long term stability at room temperature. The SLNs stored at 37C were found to sediment completely within 4 days, indicating even worse long term stability. These results indicate that the samples were unstable when stored at 25C or 37C, and therefore, were not analysed further. On the other hand, the SLNs stored under refrigerated conditions were stable over a period of 2 months with only slight sedimentation at the end of this time. There was negligible increase in particle size. The SLN dispersions could,
113 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique therefore, remain of potential commercial interest providing consumers were prepared to keep the product cold (not uncommon in pharmaceutical products).
The observed increases in particle size at the higher temperatures is also not unexpected. Similar findings have been reported earlier by Freitas and Muller (1998). Their findings indicated that increased temperature may reduce the micro-viscosity of the emulsifier and induce destabilisation of the system. An increased kinetic energy of the SLNs at higher temperatures is sufficient to overcome the electrostatic repulsion and may result in aggregation of particles.
114 Chapter 4 Introduction and Optimisation of Novel Microwave-assisted technique
4.5 Conclusions
In this chapter, a novel microemulsion technique based on the use of microwave heating was introduced. Ninety formulations were prepared using varying compositions of lipids and surfactants. The type and quantity of lipid and surfactant were identified as having a major influence on the particle characteristics of SLNs.
From the lipids tested in this study, at least two lipids, stearic acid and Imwitor® 900K were able to produce submicron (or nanometre range) particles in combination with all three surfactants. It was observed that a combination of stearic acid and Tween® 20 produced the smallest particles with a narrow size distribution and desirable zeta potential values. Therefore, this formulation was selected for further study.
Addition of ingredients such as an acid, base or salt also influenced the particle size, but was not considered to be beneficial. Addition of co-emulsifiers produced larger particles with high zeta potential values. The use of stabilisers in the formulation increased the size of the SLNs. The solvent used as a dispersion medium during microwave heating had a major influence on particle characteristics of SLNs. Since the main objective of the thesis was to develop the microwave technique for the production of SLNs, further experimentation with these ingredients was not pursued in this thesis. The SLNs were found to remain stable when stored in refrigerated conditions.
115
Chapter 5 Microwave-assisted technique vs. Conventional technique 5
Physicochemical Characteristics of Solid Lipid Nanoparticles (SLNs):
Microwave-assisted microemulsion technique
Versus
Conventional microemulsion technique
117 Chapter 5 Microwave-assisted technique vs. Conventional technique
Abstract
Solid lipid nanoparticles (SLNs) produced by conventional microemulsion techniques using thermal heat have specific limitations (e.g. high polydispersity, instability and low encapsulation). Replacing thermal heat with microwave heat may produce SLNs which overcome some of these limitations. Stearic acid-based SLNs prepared with Tween® 20 as the emulsifier were chosen as the optimum formulation to encapsulate and potentially deliver the antibacterial model drug tetracycline.
All formulations were characterised by their particle size, zeta potential, encapsulation efficiency, loading capacity, thermal and diffraction analyses. Microwave heating helps to overcome several disadvantages associated with thermal heating (non-uniform, inefficient and slow) and results in improved particle characteristics. The particle sizes of microwave-produced SLNs were in the desired nanometre range (200 - 250 nm) with both lower size and lower polydispersity than SLNs produced by the conventional method. These properties indicate improved stability; however, zeta potential measurements were not different, indicating similar stability.
Short-term stability and in vitro drug studies were also performed. Physical stability testing (visual observation with time) showed that the microwave-produced SLNs were more stable, particularly when refrigerated after four weeks. The microwave-produced SLNs also demonstrated improved encapsulation efficiency and loading capacity. Thermal and diffraction analysis confirmed lowered crystallinity of stearic acid with successful incorporation of tetracycline into the SLNs. In vitro release studies indicated that, after an initial burst release, SLNs could provide prolonged release of tetracycline, suggesting a core-shell model of SLNs.
The effects of SLNs on the viability of human lung adenocarcinoma A549 cells were also evaluated. The cell viability assay suggested that the SLNs were non-toxic. Antimicrobial susceptibility testing was performed against E. coli and S. aureus. The presence of tetracycline and non-toxicity of carriers towards microbes was confirmed by antimicrobial susceptibility tests. Overall, the results suggest that SLNs produced by the microwave method demonstrate the potential for new opportunities in the development of colloidal drug carriers and specifically with the anti-bacterial drug, tetracycline.
118 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.1 Introduction
Recent advances in drug discovery and development have led to the production of a variety of drug (or therapeutic) molecules with high potency. The ability of many newly discovered drug candidates, and some established drug molecules, to reach their target and treat diseases is often limited, however, by poor aqueous solubility, low membrane permeability and poor metabolic stability (Williams et al., 2013). The use of colloidal carriers such as micelles, nano-emulsions, liposomes and polymeric nanoparticles has been actively looked upon as a promising strategy to overcome these challenges. However, specific drawbacks including particle aggregation, drug leakage and polymer or solvent toxicity have restricted their use as carrier systems (Bunjes and Siekmann, 2005; de Mendoza et al., 2010). In recent years, solid lipid nanoparticles (SLNs) have aroused particular interest as alternative colloidal carriers to encapsulate drugs including those having limited water solubility.
SLNs have been produced by a variety of procedures (see Chapter 1, Section 1.6); high pressure homogenisation and microemulsion techniques being the two most widely employed (Silva et al., 2011). Each procedure has specific disadvantages (see Chapter 1, Table 1.4) such as the risk of metal contamination when ultrasound is used, the presence of microparticles in microemulsion techniques, high energy inputs in homogenisation- based techniques, difficulty of solvent removal in solvent-based techniques, particle aggregation and membrane clogging (Puglia et al., 2008; Silva et al., 2011; Yoon et al., 2013).
The microemulsion technique of SLN production was first documented in 1993 (Gasco, 1993). The microemulsion technique, referred to as the conventional microemulsion technique henceforth, is a two-step procedure: (1) preparation of a hot o/w microemulsion and (2) dispersing the hot microemulsion in cold water to generate SLNs. The o/w microemulsion in itself is a two-step process: (1) heating of lipid and aqueous phases to the same temperature simultaneously and (2) vigorous mixing of both phases at the same temperature to generate SLNs. The conventional technique employs a thermal mode of heating for preparation of the microemulsion. A microemulsion is a thermodynamically stable system composed of water and oil and stabilised by surfactants (McClements and Li, 2010). Rapid solidification of the hot microemulsion on dispersing in cold water results in lipid crystallisation and is possibly the mechanism of particle formation.
119 Chapter 5 Microwave-assisted technique vs. Conventional technique
The present study investigates the application of microwave heating to prepare SLNs; the process will be referred to as the microwave-assisted microemulsion technique. Microwave-assisted techniques have been extensively investigated in recent years (See Chapter 1, Section 1.8). Whilst microwave chemistry is a well-established technique in syntheses, its use in pharmaceutical formulation has not yet reached its full potential, with only a few reported successes (An et al., 2006; Bergese et al., 2003; Waters et al., 2011). To our knowledge, this is the first research that considers the use of microwave heating for formulation of a microemulsion which can be subsequently solidified to generate SLNs.
In this chapter, tetracycline was selected as a “drug of choice” since it is a very common antibacterial agent and the bioassay to test its activity is simple and widely accepted. Tetracycline is a broad spectrum antimicrobial agent that binds to the 30S ribosomal subunit of bacteria, and inhibits protein biosynthesis (Xu et al., 2011). Tetracycline and its derivatives find extensive use in the prophylaxis and therapy of human and veterinary infections and for agricultural purposes. It has been found to exhibit antimicrobial activity against a number of bacteria, mycoplasmas, rickettsia and chlamydia (Daghrir and Drogui, 2013).
Tetracycline (free base form) is a polyketide comprising of a naphthacene ring structure. It is an amphoteric compound. The tetracycline molecule comprises three functional groups: tricarbonylamide, phenolic diketone and dimethylamine imparting pH- dependent speciation and lipophilicity. Tetracycline has three pKa values; 3.30, 7.68 and 9.68 (Zhang et al., 2009). The solubility (231 mg/L – 52 g/L) and lipophilicity (-1.97 to -0.47) of tetracycline are pH-dependent (Gu et al., 2007). Tetracycline free base is very slightly soluble in water (231 mg/L) and its partition coefficient is very low (log P = - 1.3). Figure 5.1 depicts the chemical structure of tetracycline.
120 Chapter 5 Microwave-assisted technique vs. Conventional technique
dimethylamino group N pK = 9.68 HO a3
OH
OH tricarbonylamide NH2 pKa1 = 3.3
OH O OH O O
phenolic diketone
pKa2 = 7.68
Figure 5.1 Chemical structure of tetracycline
121 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.2 Chapter Aims
The main objective of this chapter is to compare a conventional microemulsion technique of SLN production to the novel microwave-assisted microemulsion technique of SLN production developed in this research (see Chapter 4).
The specific aims of this chapter
To study the influence of microwave heating (novel microwave-assisted microemulsion technique) in preparation of SLNs and compare it to SLNs prepared using thermal heating (conventional microemulsion technique)
To demonstrate the suitability of the novel microwave-assisted microemulsion technique to encapsulate a “choice of drug”, namely tetracycline
To characterise and compare the SLNs prepared by conventional microemulsion and microwave-assisted microemulsion techniques
To study and compare the drug release patterns of tetracycline from SLNs prepared by the conventional microemulsion and novel microwave-assisted microemulsion techniques in phosphate buffered saline (pH 7.4) by the dialysis bag method
To evaluate the antimicrobial activity of tetracycline-loaded SLNs against E. coli and S. aureus
To evaluate the cytotoxicity of tetracycline-loaded SLNs against human A549 cells
122 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.3 Methods
5.3.1 Screening of lipids
The screening of lipids was performed by evaluating the solubility of tetracycline (5– ® ® 15% (w/w) with respect to lipid mass) in different lipids: Imwitor 900 K, Dynasan 114, ® ® ® Compritol 888 ATO, Precirol ATO 5, Softisan 142, cetyl palmitate and stearic acid. The physical mixtures of lipid and tetracycline were heated to 90C, and the melts were observed to verify the presence or absence of insoluble drug crystals.
5.3.2 Preparation of SLNs
SLNs were prepared by two production techniques: the conventional microemulsion method and the novel microwave-assisted microemulsion method. The composition of both the drug-free (DF) and drug-loaded (DL) SLNs produced by both heating techniques are presented in Table 5.1. Tetracycline was used as a “drug of choice” at a concentration, referred to as drug loading, of 5%, 10% and 15% (w/w) with respect to stearic acid, and the resultant formulations designated as DL A, DL B and DL C, respectively.
Table 5.1 Composition of drug-free and tetracycline-loaded SLNs
Formulations (% w/w) Composition DF DL A DL B DL C
Stearic acid 7.5 7.5 7.5 7.5
Tween® 20 12.5 12.5 12.5 12.5
Water 80.0 80.0 80.0 80.0
Tetracycline* - 5.0 10.0 15.0
DF: drug-free SLNs, DL: tetracycline-loaded SLNs, * mass of tetracycline with respect to the mass of stearic acid
5.3.2.1 Conventional microemulsion technique
SLNs were prepared by a conventional microemulsion method according to the procedure described by Gasco (1993) with some modifications. To summarise: two ® separate phases, an aqueous (mixture of water and Tween 20) phase and a lipid (stearic acid) phase were separately heated to the same temperature (85C). Under constant
123 Chapter 5 Microwave-assisted technique vs. Conventional technique stirring, at 85C, the hot aqueous phase was then added to the molten lipid phase in order to produce a hot o/w microemulsion. A dispersion of SLNs was then obtained by dispersing the hot o/w microemulsion in cold water (50 mL, 2 - 4C). For DL SLNs, tetracycline and stearic acid were heated together to solubilise the drug in the lipid, prior to formation of the initial microemulsions which were subsequently cooled, now containing the drug tetracycline.
5.3.2.2 Novel microwave-assisted microemulsion technique
SLNs were also prepared by the novel microwave-assisted microemulsion technique as ® described in Section 3.3.1. In brief, a mixture of stearic acid, Tween 20 and water was heated above the melting point of stearic acid in a microwave reactor tube with constant stirring using a microwave synthesiser to produce an o/w microemulsion. The microwave reaction temperature was set to 85C with a variable microwave power of (maximum) 10 W and the reaction was maintained at the temperature set point for 10 min. The hot o/w microemulsion was then dispersed immediately into cold water (50 mL, 2 - 4 C), under constant magnetic stirring to generate SLN dispersions. For DL SLNs, tetracycline ® was added to the physical mixture of stearic acid, Tween 20 and water prior to formation of the initial microemulsion. The entire mixture was then subjected to microwave heating to form the microemulsions which were subsequently cooled, now containing the drug tetracycline.
It should be noted that the microwave-assisted preparation of solid lipid nanoparticles occurs at low microwave power (not exceeding 10 W) and is more rapid than the conventional technique. It is thus unlikely that the microwave process employed here produces free-radicals or other reactive species during the preparation, or causes degradation of drug which would either lead to toxic effects or loss of activity. Cytotoxicity studies (see Section 5.3.10) and antimicrobial susceptibility tests (see Section 5.3.9) were performed to evaluate such changes.
124 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.3.3 Particle characterisation
5.3.3.1 Determination of hydrodynamic diameter and polydispersity index (PI)
The intensity weighted mean hydrodynamic diameter and the PI of the SLN dispersions were determined by DLS at 25C as described in Section 3.3.2.1.
5.3.3.2 Zeta potential measurements
The zeta potential measurements were carried out as described in Section 3.3.2.3. The zeta potential of the SLN dispersions was determined by measurement of the electrophoretic mobility.
5.3.4 Determination of tetracycline by high performance liquid chromatography (HPLC)
Quantification of tetracycline was performed by HPLC analysis. The column and mobile phase used and the conditions set were as given in Table 5.2. Tetracycline was eluted at 3.6 min. The calibration curve for the quantification of tetracycline was linear (see Appendix, Figure A.5.1) over the range 0 - 100 µg/mL with a correlation coefficient (R2) of 0.9989.
Table 5.2 HPLC method for analysis of tetracycline
Specifications
Column Reversed-phase Prevail™ C18 column, 5 µm, 150 mm × 4.6 mm
Mobile phase A: 25 mM NaH2PO4.H2O B: Methanol
Isocratic 90% B
Flow rate 0.75 mL/min
Injection volume 5 µL
Column temperature 30C
Detection wavelength 358 nm
125 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.3.5 Encapsulation efficiency and loading capacity measurements
Encapsulation efficiency (EE) and loading capacity (LC) (see Equations 5.1 and 5.2) refer to the amount of drug encapsulated by the nanoparticles, expressed as a percentage. EE indicates the amount encapsulated compared to the amount of drug added to the system, whilst LC refers to the amount encapsulated compared to the amount of lipid used. The EE and LC of the SLNs were determined by the centrifugal ultrafiltration method described in Section 3.3.3. The amounts of tetracycline in “filtered”, “loaded”, “free” and “soluble” fractions were determined by HPLC analysis (see Section 5.3.2.5). EE and LC were calculated from the amounts of drug determined by HPLC analysis using the following equations,
[amount (loaded) - amount (free) - amount (soluble)] EE (%) = × 100 amount (drug loading) … Equation 5.1 [amount (loaded) - amount (free) - amount (soluble)] DL (%) = × 100 amount of lipid added to the formulation … Equation 5.2
5.3.6 Crystallinity of SLNs
The crystallinity of SLNs was investigated from their thermal and diffraction characteristics. The thermal behaviour of SLNs was studied by differential scanning calorimetry (DSC) analysis of bulk tetracycline, bulk stearic acid and the SLNs using a 2920 Modulated DSC (TA Instruments, Delaware, USA) as described in Section 3.3.7. The melting enthalpy (ΔH) was obtained by integration of the area under the transition peak and crystallinity index (CI) was determined by Equation 5.3,
∆HSLN CI (%) = × 100 ∆Hbulk lipid × Concentration of lipid phase (%) … Equation 5.3
The X-ray diffraction (XRD) patterns were obtained using a D8 Advance diffractometer (Bruker, Germany) as described in Section 3.3.8. The XRD data were analysed in conjunction to DSC data to investigate the changes in crystallinity of stearic acid used in preparation of SLNs.
126 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.3.7 Short-term stability of SLN dispersions
In addition to zeta potential measurements, the short-term stability of the SLN dispersions was evaluated by two methods: (a) effect of centrifugation (at 600 g for 15 minutes) on SLN dispersions to check for any phase separation, and (b) effect of storage of SLN dispersions in sealed amber coloured glass vials at ambient temperature (25C) and under refrigerated conditions (4C) for a period of four weeks. In both cases, short term stability was assessed as any change, over time, to particle size and/or particle size distribution.
5.3.8 In vitro drug release studies
The drug release from tetracycline-loaded SLNs was performed in phosphate buffered saline (PBS; 100 mM, pH 7.4) using the dialysis bag method as described in Section 3.3.5. In brief, a 2 mL aliquot of SLN dispersion was sealed in a dialysis bag (soaked in distilled water for 12 h prior to use) and placed in release medium (50 mL) in amber coloured glass bottles. The bottles were placed in a thermostatic shaker at 37C and 150 rpm. A 5 mL aliquot of release medium was withdrawn at pre-determined time points and replaced immediately with the same volume of fresh PBS to maintain the sink conditions. The amount of drug in the aliquot was determined at 358 nm.
5.3.9 Investigation of antimicrobial susceptibility of the tetracycline-loaded SLNs
Bacteria. Overnight cultures of a gram-positive bacterium Staphylococcus aureus (ATCC 12600) and a gram-negative bacterium Escherichia coli K12 (ATCC 23716) in nutrient broth were adjusted to match a 0.5 McFarland standard (approximately 1 × 108 CFU/mL) and used for antimicrobial susceptibility testing of SLN dispersions.
Assay. The SLNs (1 mg) were accurately weighed and dissolved in absolute ethanol. Sterile paper discs (6 mm diameter) were overlaid with 10 L of ethanol solution solubilised with SLNs, air dried to remove ethanol and placed over Brain Heart Infusion (BHI, Oxoid) agar plates previously inoculated with S. aureus and E. coli. The BHI plates were incubated at 37C for 18 h.
127 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.3.10 Evaluation of cell viability of SLN dispersions
The viability of human lung A549 cells following their exposure to tetracycline-loaded SLNs was evaluated by measuring the metabolic activity of cells using the MTT assay as described in Section 3.3.12. Cell viability was expressed as a percentage of untreated cells (used as negative control).
128 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.4 Results and Discussions
5.4.1 Screening of lipids
Assessing the solubility of a drug in the lipid material is the first step in the selection of appropriate lipids for the formulation of SLN dispersions. Seven lipids with different physicochemical properties were selected, as listed in Table 5.3. For most of the lipids, tetracycline did not solubilise or solubilised at only 5% (w/w). No drug crystals were observed when tetracycline and stearic acid were heated together (for all three concentrations tested).
Table 5.3 Screening of lipids based on solubility of tetracycline
Solubility (mg tetracycline / 100 mg lipid) Lipid 5 10 15
Imwitor® 900K + - -
Dynasan® 114 - - -
Precirol® ATO 5 + - -
Compritol® 888 ATO - - -
Softisan® 142 - - -
Stearic acid + + +
Cetyl palmitate - - -
+ denotes solubility pf tetracycline and – denotes insolubility of tetracycline
Optimisation of the microwave-assisted technique (see Chapter 4) also indicated that for the materials tested, stearic acid is the most appropriate lipid material for preparation of SLNs. This is, indeed, fortunate, since stearic acid is also shown here to be the most compatible with the first test drug of choice. Being inexpensive, inert and readily available, stearic acid is a suitable ingredient for drug delivery vehicles and has already been used to mask the taste of bitter drugs (Waters et al., 2011). Stearic acid has been recently applied as an encapsulation medium (Waters and Pavlakis, 2007; Waters et al., 2011). It has been accorded GRAS status by the US Food and Drug Administration (2014). In view of all of these considerations, and results obtained from screening studies,
129 Chapter 5 Microwave-assisted technique vs. Conventional technique stearic acid was selected for preparation of SLNs in this research, including the remaining drugs.
5.4.2 Preparation of SLNs
In conventional thermal heating, energy that is generally supplied from an external source is driven through the walls of the vessel to the surface of the material by conduction, convection and radiation (Hayes, 2004). In contrast, microwave heating arises from the direct coupling of microwaves with a material, rather than via heat transfer (National Research Council, 1994). Microwave heating presents several advantages over conventional thermal heating. Microwave heating is a rapid and efficient process that is dependent on the dielectric properties of the materials. The dielectric properties of the materials, namely ionic conduction or dipole rotation, are important parameters that determine the extent to which a material is heated when exposed to microwave radiation. Thermal heating, on the contrary, is a slow and inefficient process of transferring energy that mainly depends on the thermal conductivity of the materials (Hayes, 2004). Thermal equilibrium between the formulation vessel and actual formulation is achieved only after sufficient time has elapsed. By contrast, microwave heating involves direct coupling of microwaves with the molecules of the materials leading to a rapid increase in the temperature. Since microwave heating is not limited by the thermal conductivity of the reaction vessel in use, there is instantaneous localised heating of the sample (Nüchter et al., 2004). Microwaves penetrate into the materials with heat generated throughout the volume of materials, resulting in more uniform heating (Tompsett et al., 2006).
The results presented in this work indicate that microwave heating could be a good alternative to thermal heating particularly due to the ease with which the temperature can be monitored and controlled throughout the formulation and across the entire formulation vessel. An illustrative example of a report generated by the Synergy® software that controls and monitors the microwave reaction conditions is given in Appendix (see Figure A.5.2)
130 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.4.3 Particle characterisation
Comparison of the two microemulsion techniques for SLN production was performed using extensive particle characterisation. Production of nanometre-sized SLNs was confirmed by particle size analyses. The mean hydrodynamic diameters and particle size distribution (indicated by PI) of the SLN dispersions produced using the novel microwave-assisted and conventional microemulsion techniques are presented in Figure 5.2 and Figure 5.3, respectively.
700 Conventional 600 Technique
500 Novel Technique
400
300
200 Particlesize (nm)
100
0 DF DL A DL B DL C Figure 5.2 Particle size of drug-free and tetracycline-loaded SLNs. DF: drug-free SLNs; DL A: SLNs loaded with 5% (w/w) tetracycline (relative to stearic acid); DL B: SLNs loaded with 10% (w/w) tetracycline (relative to stearic acid); DL C: SLNs loaded with 15% (w/w) tetracycline (relative to stearic acid)
The results indicate that particle size was significantly (p < 0.05) influenced by the mode of heating (Figure 5.2). The conventional technique produced SLNs in the range of 350 - 600 nm whereas the novel technique produced particles in the range of 200 - 250 nm. The results in Figure 5.3 indicate that the novel technique produced particles with low PI values (~0.15) and the conventional technique produced particles with higher PI values (~0.30). Production of nanoparticles with narrow dispersity using microwave heating has been previously reported by An et al. (2006) and the current results support these earlier findings. Moreover, it is clearly evident that the concentration of drug significantly (p < 0.05) increased the size of particles produced by conventional thermal heating (Figure 5.2) but did not influence the size of particles produced by microwave heating.
131 Chapter 5 Microwave-assisted technique vs. Conventional technique
0.5 Conventional Technique 0.4 Novel Technique
0.3
0.2
Polydispersityindex 0.1
0.0 DF DL A DL B DL C Figure 5.3 Polydispersity index of drug-free and tetracycline-loaded SLNs. DF: drug- free SLNs; DL A: SLNs loaded with 5% (w/w) tetracycline (relative to stearic acid); DL B: SLNs loaded with 10% (w/w) tetracycline (relative to stearic acid); DL C: SLNs loaded with 15% (w/w) tetracycline (relative to stearic acid)
Zeta potential can be used as a measure of the degree of electrostatic repulsion between charged particles and is particularly relevant here since the nanoparticles are solid in nature, unlike the liquid drops of conventional emulsions, and are thus more likely to be genuinely charge-stabilised. These forces of repulsion are responsible for preventing particle aggregation and are therefore a useful indicator of the physical stability of the formulation.
The zeta potential can be used as an indicative tool to predict physical stability of SLN dispersions. As a general rule, zeta potential values above |30| mV provide good stability and above |60| mV provide excellent physical stability. Limited flocculation (short-term stability) can be observed between |5| and |30| mV. Zeta potentials below |5| mV often result in irreversible particle aggregation (Heurtault et al., 2003; Wu et al., 2011a). Whilst this is true for low molecular weight surfactants and/or for pure electrostatic stabilisation, a minimum zeta potential of approximately |20| mV is still satisfactory for dispersions stabilised by a combined steric and electrostatic effect (Mitri et al., 2011; Tamjidi et al., 2013). Zeta potential values of only |20| mV or lower can provide sufficient physical stability for systems stabilised with high molecular weight surfactants that mainly act by steric stabilisation (Bunjes and Siekmann, 2005).
132 Chapter 5 Microwave-assisted technique vs. Conventional technique
-40 Conventional Technique -30 Novel Technique
-20
-10 Zetapotential (mV)
0 DF DL A DL B DL C Figure 5.4 Zeta potential of drug-free and tetracycline-loaded SLNs. DF: drug-free SLNs; DL A: SLNs loaded with 5% (w/w) tetracycline (relative to stearic acid); DL B: SLNs loaded with 10% (w/w) tetracycline (relative to stearic acid); DL C: SLNs loaded with 15% (w/w) tetracycline (relative to stearic acid)
The zeta potential values of all formulations produced by both procedures are summarised in Figure 5.4. The zeta potential values were greater than |20| mV for all SLN dispersions prepared by either of the two techniques. The surfactant used in this study (Tween® 20) is non-ionic and is traditionally known to induce steric stability (see Chapter 10 for further discussion on this). The results in Figure 5.4, thus, indicate that almost all SLN dispersions produced in this study are expected to provide sufficient stability. This was further verified by stability studies (see Section 5.3.7). The zeta potential of SLN dispersions is most likely to originate from dissociation of stearic acid either in the aqueous dispersion medium or from the particle surface. The pKa of stearic acid is ~4.9, and the pH of SLN dispersion was 5.0 ± 0.5, close to the pKa of stearic acid.
The zeta potential of most SLNs was very similar. The non-loaded and 5% loaded conventional SLNs showed the highest value, around 30 mV, whilst all other SLNs had a zeta potential around 25 mV. At first sight, this would indicate that the novel technique did not produce an advantage over the conventional technique, and that all emulsions were similar. However, the particle size of the novel SLNs were considerably smaller than the conventional SLNs, meaning that a much larger quantity of charge must be present in order to result in similar zeta potentials, i.e. smaller particles equates to higher surface area which equates to more charged material to maintain the same charge density. Speculatively, the zeta potential of SLNs may, in fact, be the controller of particle size,
133 Chapter 5 Microwave-assisted technique vs. Conventional technique remembering that the first step is to form a microemulsion (at high temperatures). When particles in the microemulsion are first formed, they are fluid, can divide and can coalesce, and their particle size will change until a stable condition has been reached. If more charge is generated in the novel technique, then particles can become smaller and remain stabilised by that charge. The resultant particle size may simply reflect a constant charge density (and thus constant zeta potential), with the novel technique generating more charge and thus allowing smaller particles whilst maintaining the required charge density.
The above process then changes as soon as the particles are cooled and a solid dispersion is formed. Once formed, the dispersion now cannot change size other than by instability resulting from flocculation or coagulation. For this reason, particle size changes are now a good indicator of an unstable dispersion.
5.4.4 Encapsulation efficiency and loading capacity of SLNs
The encapsulation efficiency (EE) of SLNs is defined as the fraction of drug added in the process of SLN manufacture that is associated with the SLNs. Centrifugal ultrafiltration was used to separate the dispersion medium and the SLNs. The measurement of EE or the SLN-associated fraction of drug can be performed indirectly by quantification of free drug in the dispersion medium (Magenheim et al., 1993). Table 5.4 gives the results for EE measurements for the SLNs produced by both the methods.
Table 5.4 Encapsulation efficiency and loading capacity of tetracycline-loaded SLNs
Formulation EE (%) LC (%)
Novel Conventional Novel Conventional technique technique technique technique
DL A 50.4 ± 0.8 24.9 ± 2.2 2.5 ± 0.1 1.2 ± 0.1
DL B 48.9 ± 0.7 18.6 ± 0.7 4.9 ± 0.1 1.9 ± 0.1
DL C 47.5 ± 0.9 15.9 ± 0.4 7.1 ± 0.1 2.4 ± 0.1
DL A: SLNs loaded with 5% (w/w) tetracycline (relative to stearic acid); DL B: SLNs loaded with 10% (w/w) tetracycline (relative to stearic acid); DL C: SLNs loaded with 15% (w/w) tetracycline (relative to stearic acid)
134 Chapter 5 Microwave-assisted technique vs. Conventional technique
The results in Table 5.4 show that a significantly higher EE was attained with the novel technique. Not surprisingly, the drug concentration had a negative influence on the EE of SLNs, with EE decreasing with increasing drug concentration in both cases. The decrease was more pronounced in SLNs prepared using the conventional technique (15 - 25%) than those prepared using microwave heating (50 – 47%). A similar effect of drug concentration on EE was reported by Das et al. (2011). The results from EE measurements were further confirmed by the loading capacity (LC) measurements. The SLNs produced using the novel technique achieved a higher drug loading (2.5 - 7 %) as compared to those produced using the conventional technique (1 - 2.5 %). The results in Table 5.4 indicate that the LC increased with an increase in drug concentration. It should again be noted that LC was greater in the case of microwave-produced formulations, and this may be attributed to a greater lipid-drug interaction, which in turn may be attributed to the use of microwave energy. It is also worth noting that the LCs of SLNs produced using the novel technique were twice that of the LCs from the conventional technique.
5.4.5 Crystallinity of SLNs
Both preparation techniques employed here require heating of stearic acid (lipid) above the melting point, thus forming a hot microemulsion which solidifies after dispersion in the aqueous phase. However, the mode of heating responsible for melting the stearic acid is different in both cases and, therefore, the occurrence of different crystalline and polymorphic modifications of lipids is a possible outcome. Thermal and diffraction analysis of the SLNs was performed to assess the influence of the mode of heating on the crystallinity of the SLNs. Figure 5.5 (a) depicts the differential scanning calorimetry (DSC) profile of bulk stearic acid which shows a melting transition at 72.6C. Figures 5.5 (b) and 5.5 (c) show the DSC profiles of SLNs produced using conventional thermal and microwave heating procedures, respectively. The DSC data obtained from the DSC curves are summarised in Table 1.5.
135 Chapter 5 Microwave-assisted technique vs. Conventional technique
(a)
(b)
(c)
Figure 5.5 DSC analysis of drug-free and tetracycline-loaded SLNs. DSC profiles for (a) bulk stearic acid, (b) SLNs produced using conventional technique and (c) SLNs produced using novel technique
136 Chapter 5 Microwave-assisted technique vs. Conventional technique
Table 5.5 DSC data of tetracycline-loaded SLNs
Technique Sample Tonset (C) Tmax (C ) ΔH (J/g)
Stearic acid 69.2 72.6 228.5
DF 57.1 64.2 51.8
DL A 58.0 64.6 52.5 Novel microemulsion DL B 57.9 64.7 58.0
DL C 57.9 64.9 58.2
DF 54.7 61.8 29.7
DL A 54.6 61.2 19.6 Conventional microemulsion DL B 55.9 62.1 23.7
DL C 54.1 62.1 34.5
DF: drug-free SLNs; DL A: SLNs loaded with 5% (w/w) tetracycline (relative to stearic acid); DL B: SLNs loaded with 10% (w/w) tetracycline (relative to stearic acid); DL C: SLNs loaded with 15% (w/w) tetracycline (relative to stearic acid)
The dispersion of hot microemulsion in cold water generates SLNs. However, in many cases lipids may not crystallise in a colloidally dispersed state, and may be regarded as “emulsions of supercooled melts”. The presence of a melting transition in Figures 5.5 (b) and 5.5 (c) indicates the absence of any such supercooled melts (Bunjes and Unruh, 2007; Kuntsche and Mäder, 2010).
The DSC data in Table 5.5 suggest that the melting transition (Tmax) of all SLNs, irrespective of method of preparation, were lower compared to bulk stearic acid. Only one transition was observed indicating no further transitions, for example, glass transitions, were observed and it is not possible to distinguish whether or not this particular peak is a glass transition or a melting transition. The endotherm of the SLNs is broadened and shifted to lower temperatures. In addition to possible reduction due to the adsorbed emulsifier molecules, the Gibbs-Thomson, or the “small size”, effect can be expected since all the formulations are in the nanometre range. The high surface energy associated with the nanometre-sized particles (larger surface area-to-volume ratio) creates an energetically suboptimal state that lowers the melting point of the lipid in the SLN formulation. Similar “small size” effects of SLNs on DSC curves have been
137 Chapter 5 Microwave-assisted technique vs. Conventional technique demonstrated earlier (Hou et al., 2003; Keck et al., 2014b; Kovačević et al., 2011, 2014). This may also be due to the surfactants that generate surface tension near the particle surface which shifts the melting and onset temperature towards lower values (Bunjes and Siekmann, 2005; Kovačević et al., 2014).
The melting onset temperatures (Tonset) were all still above 40C, which is a pre-requisite for the SLNs to be used successfully as drug carrier systems that can remain solid at normal body and room temperatures. Similar findings have been previously reported by de Souza et al. (2012).
On comparing the DSC curves of SLNs, produced by the two different techniques (Figures 5.5 (b) and 5.5 (c)), a difference in the position and shape of the signal representing the melting event can be observed. The novel microwave-assisted technique consistently produced SLNs with higher melting onset and transition temperatures. Broadening of peaks can be attributed to the presence of polydispersed nanoparticles. Since the formulations contain particles with different dimensions, the occurrence of a series of melting transitions can be observed. From the data in Figures 5.5 (b) and 5.5 (c) and Table 5.5, it can be observed that formulations prepared by microwave heating have a lower polydispersity. Higami et al. (2003) have reported similar findings which are consistent with the PI values reported in Figure 5.3.
The melting temperature of tetracycline was 191.6 C. The DSC profiles of SLNs did not show any endothermic peak at this temperature. The absence of peaks indicates incorporation of tetracycline into an amorphous or molecularly dispersed state in the lipid phase during SLN preparation. Similar findings have also been reported elsewhere (Anantachaisilp et al., 2010; Chen et al., 2006; Vivek et al., 2007). The presence of tetracycline (SLN-associated fraction) was investigated by performing antimicrobial susceptibility tests of all SLN formulations (see Section 5.3.9).
Incorporation of tetracycline in the lipid matrix increases the number of imperfections in the crystal structure of the lipid and contributes to the decrease of its melting enthalpy in the SLN formulation (Vivek et al., 2007). These changes were also be reflected by changes in the melting enthalpy (∆퐻). The crystallinity index (CI) was used to investigate the interaction of tetracycline with stearic acid. The results in Table 5.5 suggest that the crystallinity of SLNs was approximately 10 - 25% and 35 - 40% for SLNs prepared by conventional thermal and microwave heating, respectively. SLNs with lower CI can
138 Chapter 5 Microwave-assisted technique vs. Conventional technique expected to exhibit higher EE. This was evident in formulations prepared by both modes of heating wherein the EE reduced with increased CI values (Table 5.4).
The results also indicate that, when compared to microwave heating, conventional thermal heating produces SLNs with a lower RI, indicating the presence of more unstable polymorphic forms of the lipid (Silva et al., 2011). It can be expected that EE of SLNs prepared by conventional thermal heating should have higher EE than those prepared by microwave heating. However, the EE was higher for SLNs prepared by microwave heating. This may be because of the direct coupling of materials with electromagnetic radiations that increases the interactions between the drug and the lipid rather than simple dissolution of drug into lipid as in conventional thermal heating.
The DSC analysis of SLNs was supported with X-ray diffraction (XRD) analysis to investigate the crystallinity of SLNs. Figure 5.6 shows the XRD patterns of SLNs prepared by both the techniques and of bulk stearic acid. The XRD pattern of stearic acid (Figure 5.6 (a)) shows three distinct peaks at 2 = 6.4, 21.5 and 24.1. Corresponding peaks, but of lower intensities with a slight shift to lower angle, were also found in the XRD patterns of SLNs produced by both heating techniques (Figures 5.6 (b) and 5.6 (c)). These results indicated that there has been a decrease in the degree of crystallinity of stearic acid during the production process. The interaction of crystalline stearic acid with the surfactant and/or tetracycline used in the production is a probable explanation for these observations.
When compared to microwave heating (Figure 5.6 (c)), the diffraction peaks in the XRD patterns of the SLNs obtained by thermal heating (Figure 5.6 (b)) were slightly less intense. This again suggests that lipids processed by thermal heating have a lower degree of crystallinity. These results are in agreement with the DSC data (Table 5.5).
139 Chapter 5 Microwave-assisted technique vs. Conventional technique Arbitrary unitsArbitrary
0 10 20 30 40 50 (a) 2
DL C
DL B
DL A Arbitrary unitsArbitrary
DF
0 10 20 30 40 50 (b) 2
DL C
DL B
DL A Arbitrary unitsArbitrary
DF
0 10 20 30 40 50 (c) 2
Figure 5.6 XRD analysis of drug-free and tetracycline-loaded SLNs. XRD patterns for (a) bulk stearic acid, (b) SLNs produced using conventional technique and (c) SLNs produced using novel technique.
140 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.4.6 Short-term stability studies
As previously indicated from zeta potential measurements (see Section 5.3.3, Figure 5.4), all of the SLN dispersions were expected to be physically stable, at least in the short term. The short-term stability, however, should still be directly measured and long term effects studied. This was achieved by examining the effect of centrifugation and storage temperature on stability of SLNs.
Following centrifugation, SLN dispersions produced using the conventional technique showed signs of sedimentation; however, particles could be easily redispersed by mechanical shaking. One might expect stearic acid nanoparticles and aggregates to remain suspended due to the difference in densities between stearic acid and water. However, sedimentation was observed for SLNs prepared by the conventional technique. The observed sediment is probably a mixture of stearic acid and Tween® 20 (stearic acid nanoparticles surface-tailored with Tween® 20 molecules) whose density is likely to be higher than that of water. By contrast, SLN dispersions produced using the novel technique did not sediment. From these results, it is clear that microwave-produced SLNs were more stable compared to those produced under thermal heating. These results indicate that the samples can maintain structural integrity over time, with microwave heating providing more favourable physical stability.
Physical stability was also assessed by examining changes in the particle size of SLNs stored at ambient (25C) and refrigerated conditions. For samples stored at 25C, samples were found to sediment immediately within 24 h. Particle size data was not determined for such cases since all formulations were unstable according to these visual observations.
A change in particle size of SLNs is widely accepted as an indicator of formulation instability (Heurtault et al., 2003) and was relevant to the refrigerated samples. Figure 5.7 shows the changes in particle sizes of refrigerated samples after 28 days of storage.
141 Chapter 5 Microwave-assisted technique vs. Conventional technique
700 Day 0 600 Day 28
500
400
300
200 Particlesize (nm)
100
0 DF DL A DL B DL C (a)
700 Day 0 600 Day 28
500
400
300
200 Particlesize (nm)
100
0 DF DL A DL B DL C (b)
Figure 5.7 Short-term stability studies of SLNs dispersions at 4°C. Particle size of SLNs produced using (a) conventional technique and (b) microwave-assisted technique.
The results from Figure 5.7 indicate that the particle sizes of SLNs produced by either technique increased only slightly when stored at refrigerated conditions and that the microwave-produced formulations retained its low particle size. This again illustrates that microwave-produced SLNs have favourable stability, and show suitable stability at low temperatures. Any influence of kinetic energy, such as temperature, can lead to particle growth. Freitas and Müller (1998) have reported the influence of various kinetic parameters such as temperature and light on particle growth and have shown that many pharmaceutical products are very sensitive to these parameters. It is also, therefore, quite
142 Chapter 5 Microwave-assisted technique vs. Conventional technique common for pharmaceutical products to be kept refrigerated, or at least to be kept in a cool storage area.
5.4.7 In vitro drug release studies
The amount of tetracycline released from the SLNs was determined by an in vitro dialysis bag technique. This is the most widely used method reported in the literature to estimate drug release from the SLNs. Due to the solid core at body temperature, drug release from the SLNs was expected to be very slow. Figure 5.8 shows the release profile of tetracycline from SLNs prepared by both techniques. A biphasic release profile was observed for both formulations, as demonstrated by an initial burst release within three hours followed by a prolonged release. The initial burst release of tetracycline can be attributed to the rapid release of the drug incorporated into the shell. Tetracycline loaded into the SLN core leaches out gradually through two different mechanisms, dissolution and diffusion. Similar results and interpretations were reported by Grassia et al. (2003a, 2003b) and Xu et al. (2011).
100 Conventional 90 Technique 80 Novel Technique 70 60 50 40 30
20 Cumulative Release Cumulative (%) 10 0 0 1 2 3 4 5 6 7 8 9 10 11 12 Time (h) Figure 5.8 Drug release profiles of tetracycline-loaded SLNs in phosphate buffered saline (PBS, pH 7.4) at 37°C.
Approximately 80% of the tetracycline was released from the SLNs produced using the novel technique within 12 h compared to 90% from SLNs produced using the conventional technique. These results indicate that tetracycline incorporated into the
143 Chapter 5 Microwave-assisted technique vs. Conventional technique
SLNs is likely to remain associated with the nanoparticle. The release medium should be physiologically relevant and should have enough volume to quantify a drug when it is released and dissolved in the release medium. Almost double the amount of tetracycline loaded into the SLNs produced by the novel technique (Table 1.4) being released into the same volume of release medium might result in the absence of proper sink conditions. The absence of proper sink conditions during the drug release studies may be a reason for lower drug release. Similar results that suggest slower drug release due to increased drug loading have been reported by Das et al. (2012).
5.4.8 Antimicrobial susceptibility studies
Antimicrobial susceptibility testing of SLN dispersions and inertness of stearic acid was evaluated by performing the disc diffusion assay (Table 5.6). The antimicrobial activities of the drug-free SLNs and drug-loaded SLNs were determined against two bacteria, S. aureus and E. coli. A clear zone of inhibition was seen around drug-loaded SLNs produced by both methods, indicating that drug-loaded SLNs produced by either method were active against the microbes. However, SLNs were more active against S. aureus than E. coli. It is also worth noting that drug-free SLNs produced by either technique did not exhibit antimicrobial activity, which suggests that SLNs as carriers are non-toxic towards microbes, and exhibit no inherent antimicrobial activity.
Table 5.6 Anti-microbial activity of SLNs
Zone of inhibition (mm)
S. aureus E. coli Formulation Microwave- Conventional Microwave- Conventional assisted technique assisted technique
DF - - - -
DL A 25 22 9 8
DL B 28 24 12 10
DL C 30 26 16 14
Tetracycline# 29 24
DF: drug-free SLNs; DL A: SLNs loaded with 5% (w/w) tetracycline (relative to stearic acid); DL B: SLNs loaded with 10% (w/w) tetracycline (relative to stearic acid); DL C: SLNs loaded with 15% (w/w) tetracycline (relative to stearic acid), # commercially available tetracycline discs (30 g) were used
144 Chapter 5 Microwave-assisted technique vs. Conventional technique
Table 5.6 gives the antimicrobial activity of SLNs in terms of diameters (mm) of zones of inhibition. Tetracycline-loaded SLNs produced using the novel technique showed greater activity compared to those produced using the conventional technique. The antimicrobial activity was due to the tetracycline that was released into the culture medium over a period of time. This suggests that there was no chemical degradation of tetracycline. In other word, tetracycline retained chemical stability during SLN production.
5.4.9 Cell viability after exposure to SLNs
The cytotoxicity of SLNs was evaluated by assessing the viability of A549 cells after exposure to DF SLNs and DL SLNs for 24 h. The viability of cells was determined using the MTT assay that measures the metabolic activity of viable cells and thus establishes the concentration of SLNs below which they can be considered to be non-toxic to the proliferating cells. The results presented in Figure 5.9 depict that, after 24 h of contact with a series of SLN concentrations, cell viability was concentration-dependent. The results in Figure 5.9 suggest that the cytotoxic concentration (CC50) values for all SLNs were more than the highest concentration tested (i.e. 100 µg/mL).
150 Drug-free SLNs 125 Tetracycline-loaded SLNs 100
75
50 Cell(%) viability 25
0 1 10 100 Concentration of SLNs (g/mL) Figure 5.9 Viability of A549 cells measured by MTT assay for tetracycline-loaded SLNs.
145 Chapter 5 Microwave-assisted technique vs. Conventional technique
5.5 Conclusions
A novel and facile strategy for controlled formulation of a microemulsion, and hence SLNs, is reported here. Specifically, SLNs prepared from stearic acid and surface- tailored with Tween® 20 as the emulsifier were successfully prepared and used to encapsulate tetracycline, an antibacterial drug. Although previously used in pharmaceutical formulation, we believe that this is the first research that reports the use of microwave energy in the formulation of a microemulsion which is then used to form an SLN.
The use of controlled microwave reaction parameters is the key to the development of the formulation strategy. Firstly, it was confirmed that replacement of the conventional thermal heating process with a unique temperature-controlled microwave heating process produces SLNs with smaller particle sizes, narrow polydispersity, higher encapsulation efficiency and loading capacity, increased physical stability and the capacity for more prolonged release of drugs. Thermal and diffraction data, analysed by DSC and XRD, respectively, confirmed lowered crystallinity of SLNs with successful incorporation of tetracycline.
Based on drug release studies, the apparent initial burst release of tetracycline strongly suggests a core-shell structure of tetracycline-loaded SLNs, similar to comparable structures reported in the literature. Inhibition of growth of E. coli and S. aureus when treated with tetracycline-loaded SLNs indicated the retention and therefore, chemical stability of tetracycline during SLN production. The cell viability assays showed that cytotoxic concentration (CC50) of SLNs was more than 100 µg/mL.
146 Chapter 6 Incorporation of NSAIDs into SLNs 6
Incorporation of Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) into SLNs
147 Chapter 6 Incorporation of NSAIDs into SLNs
Abstract
Non-steroidal anti-inflammatory drugs (NSAIDs) are frequently used in the treatment of inflammatory disorders such as rheumatoid arthritis and other mild to moderate chronic pain. They are also known to have analgesic and anti-pyretic effects. However, the acidic characteristics and poor water solubility of NSAIDs have limited their use. Solid lipid nanoparticles (SLNs), such as the stearic acid-based SLNs reported in this study, have the ability to overcome most of these limitations by protecting the drugs from the acidic environment of the gastrointestinal tract and improving the transport of drugs through encapsulation. The aim of the present study was to evaluate SLNs as nanoparticulate drug delivery systems for NSAIDs (indomethacin, ketoprofen and nimesulide). The SLNs were produced by the recently reported microwave-assisted microemulsion procedure. These SLNs had a particle size within the nanometre range with a negative zeta potential and high EE and LC depending on the encapsulated drug. The cytotoxic concentration
(CC50) values of drug-loaded SLNs were >100 µg/mL as evaluated by cell viability assays. The drug-loaded SLNs reduced interleukin (IL)-6 and IL-8 secretion in lipopolysaccharide (LPS)-induced A549 alveolar epithelial cells. All of the above findings suggest that SLNs are a promising drug carrier system for NSAIDs.
148 Chapter 6 Incorporation of NSAIDs into SLNs
6.1 Introduction
In the previous chapter, the physicochemical characteristics of tetracycline-loaded SLNs prepared by two techniques (a novel microwave-assisted microemulsion technique and the conventional microemulsion technique) were compared. In this chapter, the suitability of the microwave-assisted technique in the production of SLNs loaded with drugs from a different class – non-steroidal anti-inflammatory drugs (NSAIDs) – will be investigated. The use of NSAIDs has increased considerably over the past two decades. These are the most commonly prescribed preparations and are also available as over-the- counter medications. They have prominent analgesic, antipyretic and anti-inflammatory properties (Beetge et al., 2000), and are frequently used in the treatment of inflammatory disorders such as inflammatory bowel disease, rheumatoid arthritis, osteoarthritis, low back pain and joint diseases (Okyar et al., 2012).
Inflammation is the immediate immune response to infection and injury. Prostaglandins (PGs) play a key role in the promotion as well as resolution of the inflammatory response (Ricciotti and FitzGerald, 2011). PGs are lipid autocoids derived from arachidonic acid by the activity of prostaglandin-endoperoxide synthases (PTGS), colloquially known as cyclooxygenase (COX) enzymes (Ricciotti and FitzGerald, 2011; Suleyman et al. 2010). The COX enzymes are bifunctional enzymes that exhibit both peroxidase and cyclooxygenase activities. These exist in two isoforms, COX-1 and COX-2. COX-1 is a constitutive enzyme that is involved in the biosynthesis of PGs. These are also important in platelet aggregation and protection and homeostasis of gastric mucosa (Dubois et al., 1998). In contrast, COX-2 is an inducible enzyme responsible for pro-inflammatory cytokines and glucocorticoids that have been associated with responses such as inflammation, rheumatoid arthritis, and ischemia and in some cases, seizures (Schuschke et al., 2009; Warner and Mitchell, 2004). In addition to PGs, thromboxane A2 (TXA2) is also derived from arachidonic acid by the action of COX enzymes. The PG production pathway is depicted in Figure 6.1.
149 Chapter 6 Incorporation of NSAIDs into SLNs
Figure 6.1 Biosynthesis of prostaglandins and thromboxane (adapted from Ricciotti and FitzGerald, 2011). : Site of action of NSAIDs
The mechanism of action of NSAIDs is based on their ability to inhibit COX enzymes. The usage of NSAIDs often results in gastric irritation due to frequent asymptomatic inflammation, gastric ulcers, erosions and changes in mucosal permeability (Perron et al., 2013). These adverse effects also stem from the ability of NSAIDs to inhibit biosynthesis of prostaglandins as a result of non-selective inhibition of COX-1 (Delaney et al., 2007; Willoughby et al., 2000). The inhibition potencies of NSAIDs on the two isoforms of COX enzymes are, however, different (Simon, 1999). Whilst COX-2 appears to be a target for the anti-inflammatory effect of NSAIDs, COX-1 appears to be a target for their side effects (Suleyman et al., 2010).
There is a need to improve the therapeutic efficacy of NSAIDs while reducing the severity of the adverse effects. Encapsulation of NSAIDs in drug vehicles is one of the few approaches that have been investigated in overcoming the aforementioned disadvantages. NSAIDs have been successfully encapsulated into polymeric particles (Arida and Al-Tabakha, 2007; del Gaudio et al., 2009; Graves et al., 2008; Kluge et al., 2009), liposomes (Maestrelli et al., 2005, 2006; Refuerzo et al., 2015; Srinath et al., 2000), dendrimers (Murugan et al., 2014) and microemulsions (Rhee et al., 2001). These studies suggest that NSAIDs are well accepted in encapsulation studies and their drug delivery is well characterized. The selection of NSAIDs in encapsulation studies such as the one in this thesis seems appropriate, before more problematic drugs are attempted.
150 Chapter 6 Incorporation of NSAIDs into SLNs
Moreover, although there has been great success in encapsulating NSAIDs, each of the drug carriers used (as above) still suffer from some limitations (see Chapter 1, Section 1.2). The SLNs may, therefore, prove to be a viable alternative drug carrier.
In order to investigate the suitability of the microwave-assisted technique in the production of NSAID-loaded SLNs, three traditional NSAIDs were selected as model drugs: indomethacin, ketoprofen and nimesulide. These drugs have been widely used for their anti-inflammatory, analgesic and anti-pyretic properties in the treatment of inflammation, rheumatism and pain. However, due to their low water solubility and good membrane permeability, each of these drugs is categorised as Class II according to the Biopharmaceutical Classification System. Table 6.1 summarises some of the physicochemical properties of these NSAIDS relevant to this study.
151
Table 6.1 Physicochemical properties of non-steroidal anti-inflammatory drugs employed as model drugs in this study
Physicochemical properties Indomethacin Ketoprofen Nimesulide
Structure O O O CH3 SO2CH3 HN OH
HO O N
O NO2
Cl 152
Chemical name 1-(4-chlorobenzyl)-5-methoxy-2- 2-(3-benzoylphenyl) propionic acid N-(4-nitro-2-phenoxyphenyl) methylindol-3-yl) acetic acid methane sulphonamide
Molecular weight 357.8 254.3 308.3
pKa 4.5 4.6 6.5
log P 3.4 0.97 2.38
Water solubility 25 µg/mL 95 µg/mL 10 µg/mL
Inada et al., 2013; Nagai et al., del Gaudio et al., 2009 Murugan et al., 2014 2014; Sprunk et al., 2013
Chapter 6 Incorporation of NSAIDs into SLNs
6.2 Chapter Aims
The main objective of this chapter was to investigate the suitability of the novel microwave-assisted microemulsion produced solid lipid nanoparticles for the encapsulation of non-steroidal anti-inflammatory drugs
The specific aims of this chapter:
To demonstrate the suitability of the novel microwave-assisted microemulsion technique to encapsulate non-steroidal anti-inflammatory drugs (indomethacin, ketoprofen and nimesulide). To characterise the drug-loaded SLNs in terms of their physicochemical characteristics, crystallinity and encapsulation capacities. To evaluate the cytotoxicity of drug-loaded SLNs against human A549 cell line by determining its mitochondrial activity following exposure to SLNs. To evaluate the anti-inflammatory effect of drug-loaded SLNs on lipopolysaccharide-induced A549 cells using ELISA assays.
153 Chapter 6 Incorporation of NSAIDs into SLNs
6.3 Methods
6.3.1 Preparation of SLNs
SLNs were prepared by the novel microwave-assisted microemulsion technique described earlier (see Section 3.3.1). In brief, a mixture of stearic acid (100 mg), Tween® 20 (150 µl) and water (1.35 mL) was heated above the melting point of stearic acid in a microwave reactor tube with constant stirring using a microwave synthesiser to produce an o/w microemulsion. The microwave reaction temperature was set to 80C with a variable microwave power not exceeding 18 W and the reaction was maintained at the set temperature for 10 minutes. The hot o/w microemulsion from the microwave was dispersed immediately into cold water (50 mL, 2 - 4C) under constant magnetic stirring to generate SLN dispersions. For drug-loaded SLNs, drug (5% w/w with respect to lipid) was added to the mixture of stearic acid and Tween® 20 before the mixture was subjected to microwave heating.
6.3.2 Particle characterisation
Determination of hydrodynamic diameter and polydispersity index (PI) using DLS
The intensity weighted mean hydrodynamic diameter and the PI of the SLN dispersions were then determined by DLS at 25C as described in Section 3.3.2.1.
Determination of particle diameter using LD
In addition to DLS, particle size measurement was also conducted by LD at 25 C as described in Section 3.3.2.2.
Zeta potential measurements
The zeta potential measurements were carried out as described in Section 3.3.2.3. The zeta potential of the SLN dispersions was determined by measurement of the electrophoretic mobility. Conversion of the electrophoretic mobility to zeta potential was performed on “Zeta for Windows” (Kosmulski, 2002).
Scanning electron microscopy (SEM)
The size and shape of particles were estimated by SEM analysis as described in Section 3.3.2.4.
154 Chapter 6 Incorporation of NSAIDs into SLNs
6.3.3 Determination of NSAIDs by high performance liquid chromatography (HPLC)
HPLC analysis was performed to determine the amount of NSAIDs as described in Section 3.3.6. The column and mobile phase used and the conditions set for HPLC analysis of NSAIDs are given in Table 6.2. Indomethacin, ketoprofen and nimesulide were eluted at 5.2 min, 4.2 min and 4.1 min, respectively (see Appendix, Figure A.6.1 (a), A.6.2 (a) and A.6.3 (a)). The assay was linear (R2 > 0.99) for each of the three drugs over the concentration range of 0 – 100 µg/mL (see Appendix, Figure A.6.1 (b), A.6.2 (b) and A.6.3 (b)).
Table 6.2 HPLC method for analysis of NSAIDs
Specifications
Column Reversed-phase Prevail™ C18 column, 5 µm, 150 mm × 4.6 mm
Mobile phase A: 25 mM NaH2PO4.H2O (pH 2.5) B: Methanol
Isocratic 90% B
Flow rate 0.75 mL/min
Injection volume 5 µL
Column temperature 30C
Detection 318 nm (for indomethacin) wavelength 254 nm (for ketoprofen) 295 nm (for nimesulide)
6.3.4 Encapsulation efficiency and loading capacity measurements
The EE and LC refer to the percentage of drug encapsulated by the nanoparticles. EE is expressed as the amount encapsulated compared to the amount of drug added, whilst LC refers to the amount encapsulated compared to the amount of lipid used. The EE and LC of the SLNs were determined by the centrifugal ultrafiltration method described in Section 3.3.3. The separation effectiveness of centrifugal filters was performed using the method described in Section 3.3.4. The amount of NSAIDs in “filtered”, “loaded”, “free”
155 Chapter 6 Incorporation of NSAIDs into SLNs and “soluble” fractions were analysed by HPLC analysis (see Section 6.3.3). EE and LC were calculated from the amounts of drug determined by the HPLC analysis using the following equations (see Equations 6.1 and 6.2),
[amount (loaded) - amount (free) - amount (soluble)] EE (%) = × 100 amount (drug loading)
… Equation 6.1 [amount (loaded) - amount (free) - amount (soluble)] LC (%) = × 100 amount of lipid added to the formulation
… Equation 6.2
6.3.5 Crystallinity of SLNs
The crystallinity of SLNs was investigated from their thermal and diffraction characteristics. Thermal behaviour of SLNs was studied by differential scanning calorimetry (DSC) analysis as described in Section 3.3.7. The melting enthalpy (∆H) was obtained by integration of the area under the transition peak and crystallinity index (CI) was determined by Equation 6.3,
∆HSLN CI (%) = × 100 ∆Hbulk lipid × Concentration of lipid phase (%) … Equation 6.3
The X-ray diffraction (XRD) analysis was performed as described in Section 3.3.8. The XRD data were analysed in conjunction with DSC data to investigate the changes in crystallinity of stearic acid used in preparation of SLNs.
6.3.6 Evaluation of cell viability of SLN dispersions
The viability of human A549 and mouse 3T3-L1 cells following their exposure to drug- loaded SLNs was evaluated by measuring the metabolic activity of cells using the MTT assay as described in Section 3.3.12. Cell viability (Equation 6.4) was expressed as a percentage of untreated cells (used as negative control).
Absorbance of treated cells Cell viability (%) = × 100 Absorbance of control cells … Equation 6.4
156 Chapter 6 Incorporation of NSAIDs into SLNs
6.3.7 Evaluation of anti-inflammatory activity of drug-loaded SLNs on lipopolysaccharide (LPS)-induced A549 cells
The A549 cells were seeded in 12-well plates and allowed to adhere for 24 h. The cells were exposed for 4 h to the following formulations: (i) drug-loaded SLNs, (ii) drug-free SLNs (iii) drug solutions (concentration of drug equivalent with drug-loaded SLNs). The incubation medium was then removed and replaced with fresh medium supplemented with 10 g/mL of LPS to induce inflammation. Cell-free supernatants were harvested 24 h later and stored at −20°C for cytokine quantitation. TNF-α, IL-1β, IL-6, IL-8 and IL-12 were assayed using human ELISA kits as per manufacturer’s instructions (ELISAKit.com, Australia). The optical density was measured at 570 nm (with a background correction at 450 nm) using a microplate reader. The concentration of cytokines was measured in the samples.
157 Chapter 6 Incorporation of NSAIDs into SLNs
6.4 Results and discussion
6.4.1 Preparation of solid lipid nanoparticles
The drug-free and drug-loaded SLNs were successfully prepared using stearic acid as the lipid core material by the microwave-assisted microemulsion technique. Based on previous results (see Chapter 4 and 5), the particles were expected to be in the nanometre range, solid and non-toxic with high EE and LC. Extensive particle characterisation including particle sizing, zeta potential, thermal studies and cell culture studies was performed to confirm, or otherwise, these expected features.
6.4.2 Particle characterisation
The determination of particle size was conducted in order to confirm production of particles in the nanometre range. The particle characteristics (size, PI and zeta potential) of SLNs are outlined in Table 6.3. The results indicate that the SLNs are within the nanometre range with narrow size distribution and moderate zeta potential values.
Table 6.3 Particle characteristics of SLNs loaded with NAIDs
Particle size Zeta DLS LD SLNs potential Diameter PI d(0.5) (nm) (mV) (nm)
Drug-free SLNs 244 ± 6 0.13 ± 0.01 153.0 ± 0.2 -28.0 ± 1.9
Indomethacin-loaded SLNs 274 ± 8 0.11 ± 0.02 164.1 ± 0.1 -23.8 ±1.7
Ketoprofen-loaded SLNs 254 ± 15 0.14 ± 0.02 159.9 ± 0.3 -20.6 ± 1.2
Nimesulide-loaded SLNs 288 ± 23 0.26 ± 0.02 165.0 ± 0.2 -22.0 ± 1.1
The effect of encapsulation of drug molecules in SLNs on particle properties was investigated by comparing them to drug-free SLNs (taken as control in these experiments). The particle size of drug-free SLNs was smaller than any of the drug-loaded SLNs (Table 6.3). On comparison, it was found that there was a significant increase (p < 0.05) in the size of the SLNs when incorporated with drugs. These results indicate that the particle size was influenced by drug encapsulated into the SLNs. Similar results have
158 Chapter 6 Incorporation of NSAIDs into SLNs been obtained by other researchers (Esposito et al., 2013; Mulik et al., 2010; Silva et al., 2011, 2012a). However, amongst the drug-loaded SLNs, there was no significant difference in the particle sizes (p > 0.05). The incorporation of drugs into the SLNs also causes a slight reduction in the magnitude of the zeta potential which may be indicative of disruption of the packing at the surface which in turn increases the particle size.
Amongst the drug-loaded SLNs, nimesulide-loaded SLNs were the biggest and ketoprofen-loaded SLNs were the smallest. However, there was no correlation between the chemistry of the encapsulated drug molecules and the particle size of the SLNs.
The DLS and LD data show similar trends but the d(0.5) data are smaller than the DLS data (Table 6.3). The d(0.5) data were significantly (p < 0.05) lower than those of DLS. Though the presence of microparticles cannot be excluded in the SLN dispersions, it should be acknowledged that a very small portion of microparticles in the dispersion may cause large changes in the mean values of diameters. The results obtained by these techniques rely on different measurement principles, and hence differences in results are not unexpected. DLS determines the particle size in terms of hydrodynamic diameters which are usually larger than the actual solid diameter of the spherical particles (Jores et al., 2004).
The width of the particle size distribution expressed as PI is given in Table 6.3. The PI values for SLNs, with the exception of nimesulide-loaded SLNs, are below 0.2. The PI of nimesulide-loaded SLNs was below 0.3. PI values ≤ 0.2 indicate a narrow distribution of particles, however PI values ≤ 0.3 are still considered optimal, and a PI value < 0.5 is often acceptable (Das et al., 2012).
159 Chapter 6 Incorporation of NSAIDs into SLNs
The shape of the SLNs laden with NSAIDs was assessed by SEM imaging. Figures 6.2 - 6.5 depict the SLNs investigated in this chapter.
Figure 6.2 SEM image of drug-free SLNs viewed at 60,000× magnification. The scale bar represents 200 nm.
Figure 6.3 SEM image of indomethacin-loaded SLNs viewed at 60,000× magnification. The scale bar represents 200 nm.
Figure 6.4 SEM images of ketoprofen-loaded SLNs viewed at 60,000× magnification. The scale bar represents 200 nm.
160 Chapter 6 Incorporation of NSAIDs into SLNs
Figure 6.5 SEM image of nimesulide-loaded SLNs viewed at 40,000× magnification. The scale bar represents 200 nm.
While SEM is rarely used for measuring the size of SLNs, the SEM images here clearly demonstrate that the SLNs reported in this chapter are well within the submicron (or nanometre) size range. Moreover, it was also observed that the SLNs are not always spherical and different morphologies (oval-shaped, spherical, and/or irregular) were observed. However, these shapes may not be true representatives of the actual particle shapes of the SLNs because the sample preparation involved in the SEM analysis are harsh, and may affect the physical nature of particles leading to uncertainties in the experimental observations (Dubes et al., 2003). Assuming that the sample preparation does not alter the nature of the particles, it was observed that most of the SLNs with or without drug have similar size ranges (250 - 300 nm). These particle diameters are smaller compared to the DLS diameters (Table 6.3). Neves et al. (2013) argue that the DLS measures the hydrodynamic diameters of the particles (i.e. in their hydrated states) which are slightly greater compared to the actual solid diameter (i.e. in their non-hydrated states) which is assumed to be measured with SEM analysis.
The surface charge of the SLN dispersions is an important characteristic (Keck et al., 2014b), however it is more appropriate to measure the associated potential, as this is often a major controller of the stability behaviour as particles approach each other (Kuo and Ko, 2013). Unlike liquid droplets in conventional emulsions, the nanoparticles prepared in this work are solid in nature. Solid particles are likely to be genuinely charge stabilised, or at least partially charge stabilised, and thus zeta potential is particularly relevant in this context. The zeta potential values of all formulations with and without encapsulated drug are also shown in Table 6.3. The zeta potential values were greater than |20| mV for all formulations. The negative zeta potential may be attributed to functional groups on the
161 Chapter 6 Incorporation of NSAIDs into SLNs surface of SLNs (which could be residual stearic acid) or due to the dissociation of stearic acid in the aqueous medium and subsequent adsorption of the anion. The incorporation of drugs into the SLNs causes a slight reduction in the magnitude of their zeta potential indicating that the drug molecules had only minor influence on surface properties. This leads to speculation that the drugs are mostly incorporated into the SLNs (core) rather than adsorbed to the surface (shell), however is not proof thereof.
Zeta potential values of about |20| mV are deemed desirable for systems stabilised by combinations of steric and electrostatic stabilisers (Mitri et al., 2011; Tamjidi et al., 2013). The SLNs prepared in this study were surface-tailored with Tween® 20, a non- ionic surfactant, which is expected to impart some steric-like stability (see Chapter 10, Section 10.4). All SLNs, therefore, retain a zeta potential appropriate for stability, regardless of whether or which drug was incorporated. Similar to the particle size results, the incorporation of drug of any kind had a significant lowering (p < 0.05) of the zeta potential magnitude, however there was no significance between the drugs tested nor any pattern with their chemical structure, nor any pattern with the particle size of the SLNs.
6.4.3 Separation of SLNs and encapsulation studies
The EE and LC of SLNs were studied by the centrifugal ultrafiltration method using centrifugal filter units. For this technique, it is first necessary to determine the effectiveness of separation of nanoparticles from the aqueous dispersion medium. For this purpose, concentration curves using highly diluted SLN dispersions were prepared. The calibration curve for nimesulide-loaded SLNs is shown in Figure 6.6 as an illustrative example. The calibration curves for indomethacin-loaded and ketoprofen-loaded SLNs are shown in Appendix (see Figure A.6.4 (a) and A.6.4 (b) respectively). The calibration curves showed an almost linear relationship between SLN concentration and the amount of light scattered, presented in kilo counts per second (kcps) (R2 > 0.99). The detection of SLNs in diluted samples by DLS was highly sensitive, detecting SLNs as low as 0.0625% (v/v).
The amount of light scattered by the aqueous portion (ultra-filtrate) after centrifugal ultrafiltration was lower than or equal to the amount of light scattered by MilliQ water (0.4 - 0.5 kcps). These results indicate that the aqueous portion contained a negligible amount of nanoparticles. Centrifugal ultrafiltration was effective in separating the SLNs
162 Chapter 6 Incorporation of NSAIDs into SLNs from the aqueous dispersion medium. Determination of the drug content in this portion was, therefore, a measure of the amount of unencapsulated drug (available as “soluble” drug).
500
400
300
200
100 Derived countDerived rate (kcps)
0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Concentration of nimesulide-loaded SLNs (% v/v)
Figure 6.6 Light scattering of nimesulide-loaded SLNs in water (R2 = 0.996).
The results for EE and LC of drug-loaded SLNs are summarised in Table 6.4. The result show that most of the drug added has been encapsulated, with EE ranging from 71% - 92% and the LC ranging from 3.6 - 4.6% (the theoretical maximum values for LC was 5% for all three drugs). The LC results are consistent with the EE results, i.e. the EE results match with an equivalent proportion of theoretical maximum values of LC.
Table 6.4 Encapsulation efficiency and loading capacity of SLNs loaded with NSAIDs (in increasing order of EE corresponding to decreasing order of aqueous solubility)
SLNs EE (%) LC (%)
Ketoprofen-loaded SLNs 71.5 ± 1.3 3.6 ± 0.1
Indomethacin-loaded SLNs 82.6 ± 3.8 4.1 ± 0.2
Nimesulide-loaded SLNs 92.4 ± 1.2 4.6 ± 0.1
The EE and LC decreased in the order: nimesulide-loaded SLNs > indomethacin-loaded SLNs > ketoprofen-loaded SLNs. The results indicate that the EE and LC of SLNs are significantly influenced by the drug encapsulated within the SLNs. This may be due to
163 Chapter 6 Incorporation of NSAIDs into SLNs the interplay of physical properties of the drug such as aqueous solubility and partition coefficient. Ketoprofen has the highest water solubility amongst the model drugs used in this study. The aqueous solubility decreases in the order: ketoprofen (95 µg/mL) > indomethacin (25 µg/mL) > nimesulide (10 µg/mL). These results indicate that higher EE and LC may be expected for SLNs encapsulating drugs of lower water solubility, however with only three drugs tested this correlation remains relatively speculative.
6.4.4 Crystallinity of SLNs
The heating (or melting) of stearic acid and cooling (or recrystallisation) of the hot microemulsion into SLNs can lead to changes in the crystallinity and polymorphic form of stearic acid. An extensive characterisation by DSC analysis was performed to investigate the crystallinity of stearic acid in SLNs. Figure 6.7 illustrates the DSC profiles (or curves) of bulk stearic acid and SLNs. The DSC profiles often depict thermal behaviour of samples which is influenced by its crystallinity. The DSC data analysed from DSC profiles are summarised in Table 6.5.
Table 6.5 DSC data of SLNs loaded with NSAIDs
Samples Tonset (°C) Tmax (°C) ΔH (J/g) CI (%)
Stearic acid 66.9 71.5 173.0 100
Drug-free SLNs 54.5 64.4 59.6 91
Indomethacin-loaded SLNs 55.0 64.1 53.4 83
Ketoprofen-loaded SLNs 54.6 63.4 44.9 70
Nimesulide-loaded SLNs 54.1 63.1 39.9 62
164 Chapter 6 Incorporation of NSAIDs into SLNs
a. Stearic acid Drug-free SLNs b. Indomethacin-loaded SLNs c. Nimesulide-loaded 64.4 SLNs d. Ketoprofen-loaded 64.1 SLNs e. 63.4
Heatflow (W/g) 63.1
71.5
25 30 35 40 45 50 55 60 65 70 75 80 °C
Figure 6.7 DSC analysis of SLNs loaded with NSAIDs. DSC profiles of (a) bulk stearic acid, (b) drug-free SLNs, (c) indomethacin-loaded SLNs, (d) ketoprofen-loaded SLNs and (e) nimesulide-loaded SLNs.
One of the prominent features that may influence the release properties of SLNs is their solid nature. The DSC analysis of SLNs was performed to confirm the solid nature of the SLNs. The results (Figure 6.7) demonstrate the presence of a melting endotherm in the DSC profiles of SLNs. These results indicate the absence of any supercooled melts (lipids not crystallised in a colloidally dispersed state) that may form during the preparation of SLNs (Noack et al., 2012). The DSC profile of bulk stearic acid shows a sharp melting transition (also represented as Tmax in Table 6.5) at 71.5°C. On comparison with the bulk stearic acid, the melting transition of SLNs was observed at lower temperatures (Table 6.5). This reduction of the melting transition for stearic acid in SLNs may be due the adsorbed surfactant on the particle surface. From the results, it can also be observed that the melting transition of drug-loaded SLNs reduced further (compared to the drug-free SLNs). These results indicate that there is a slight reduction in melting transitions due to incorporation of drug molecules.
All SLNs, both drug-free and drug-loaded, prepared in this study were in the nanometre size range (Table 6.3). An energetically suboptimal state was created due the high surface energy associated with nanoparticles. This caused a reduction in the melting point of the lipid due to the “Gibbs-Thomson” or “small size” effect. Similar findings have been reported by other researchers (Kovačević et al., 2014).
165 Chapter 6 Incorporation of NSAIDs into SLNs
Though the melting transitions of all SLNs were lower than the melting transition of bulk stearic acid, the onset temperatures of melting, represented as Tonset, were still above 40C. The SLNs can, thus, remain solid at normal body temperature. Similar results have been previously reported by other researchers (Silva et al., 2011, 2012a).
The melting points of pure indomethacin, ketoprofen and nimesulide were found to be 161.6C, 95.8C and 150.3C, respectively. Peaks corresponding to the melting points of drugs were absent in corresponding drug-loaded SLNs. This indicated the incorporation of the drugs into the lipid phase in a solubilised or dispersed state during preparation of the SLNs. Analysis of both, melting transitions and relative melting enthalpies, confirmed that the drugs were successfully incorporated into the SLNs (Table 6.5). Similar findings have been previously reported (Anantachaisilp et al., 2010).
Incorporation of a drug into the lipid matrix increases the number of imperfections in the crystal structure of the lipid. Melting of the lipid matrix with more imperfections requires less energy. Thus, increasing in number of imperfections in the lipid matrix contributes to a decrease in melting enthalpy (ΔH) of the SLNs. From the results (Table 6.5), it can be seen that incorporation of the drug lowers the melting enthalpies of the SLNs.
The crystallinity of SLNs was represented in terms of the crystallinity index (CI). The CI of SLNs decreased in the order: drug-free SLNs > indomethacin-loaded SLNs > ketoprofen-loaded SLNs > nimesulide-loaded SLNs. Lower CI values indicate a higher number of imperfections in the SLN structure. According to Hou et al. (2003), SLNs with a perfect crystal lattice will result in drug expulsion whilst those with imperfections will accommodate proportionately more drug molecules. Therefore, a higher EE and LC would be expected with a lower CI. Based on this theory, the EE and LC of nimesulide- loaded SLNs should be the highest. The EE and LC results (Table 6.4) are consistent with this argument. It should also be expected that the EE and LC of ketoprofen-loaded SLNs should be higher than the EE and LC of indomethacin-loaded SLNs. However, the results for these two drugs are the opposite. This may be due to the difference in partition coefficients (log P) of ketoprofen (0.97) and indomethacin (3.4). Hou et al. (2003) suggested that higher drug loading can be achieved with high solubility of drug in the lipid melt. The higher partition coefficient of indomethacin suggests that it is more soluble in the lipid phase compared to ketoprofen. Based on these deliberations, it can be concluded that the EE and LC results (Table 6.4) align with the DSC data.
166 Chapter 6 Incorporation of NSAIDs into SLNs
XRD analysis was also performed to complement the DSC analysis and further investigate the reduced crystallinity of stearic acid in SLNs. Figure 6.8 depicts the XRD patterns of bulk stearic acid and SLNs prepared in this study.
21.7 Bulk stearic acid Drug-free SLNs Indomethacin-loaded 6.7 24.3 SLNs 20.6 Ketoprofen-loaded 11.1 36.4 a. SLNs
b. Nimesulide-loaded SLNs c. Intensity(AU) d. e.
5 10 15 20 25 30 35 40 2 Figure 6.8 XRD analysis of SLNs loaded with NSAIDs. XRD patterns of (a) bulk stearic acid, (b) drug-free SLNs, (c) indomethacin-loaded SLNs, (d) ketoprofen-loaded SLNs and (e) nimesulide-loaded SLNs
The XRD pattern of bulk stearic acid revealed one sharp peak at 2 = 21.7, three medium-intensity peaks at 2 = 6.7, 20.6 and 24.3 and two intensity peaks at 11.1 and 36.4. The intensity of characteristic peaks of stearic acid was reduced and/or shifted to low diffraction angles, and the other low- and medium-intensity peaks were not observed in the XRD of SLNs which is an indicative of reduced crystallinity in SLNs. This XRD data supports the findings of the DSC data (Table 6.5).
6.4.5 In vitro cell culture studies
6.4.5.1 Cell viability assay
To select a non-toxic concentration of SLNs, the cell viability of drug-loaded SLNs was determined using the MTT assay on proliferating human A549 cells and mouse 3T3-L1 cells. The cell viability was evaluated upon exposure to both drug-free and drug-loaded SLNs (Figure 6.9).
167 Chapter 6 Incorporation of NSAIDs into SLNs
The results presented in Figure 6.9 depict that, after 24 h of contact with a series of SLN concentrations, cell viability was concentration-dependent. The cytotoxic concentration
(CC50) values for all SLNs were more than the highest concentration tested (i.e. 100 µg/mL). Based on these results, the appropriate concentration of SLNs tested (i.e. 100 µg/mL) was selected for further in vitro cell culture assays. Similar trends were observed in 3T3-L1 cells after 24 h of contact with SLNs (Figure 6.10).
150 Drug-free SLNs 125 Indomethacin-loaded SLNs 100 Ketoprofen-loaded SLNs 75 Nimesulide-loaded SLNs 50 Cell(%) viability 25
0 1 10 100 Concentration of SLNs (g/mL)
Figure 6.9 Viability of A549 cells measured by MTT assay for SLNs loaded with NSAIDs.
150 Drug-free SLNs 125 Indomethacin-loaded SLNs 100 Ketoprofen-loaded SLNs 75 Nimesulide-loaded SLNs 50 Cell(%) viability 25
0 1 10 100 Concentration of SLNs (g/mL)
Figure 6.10 Viability of 3T3-L1 cells measured by MTT assay for SLNs loaded with NSAIDs.
168 Chapter 6 Incorporation of NSAIDs into SLNs
6.4.5.2 Anti-inflammatory activity by inhibition of IL-6 and IL-8 in LPS-induced A549 cells
Activated epithelial cells such as alveolar cells play an important role in inflammatory responses via activation of pathways that lead to pro-inflammatory mediators and production of cytokines. The LPS-induced cell injury model is a reasonably simple, rapid and reproducible method to screen novel anti-inflammatory compounds. In this study, human alveolar epithelial cells were used as they have been implicated in the inflammatory response to LPS induction (Cabrera-Benitez et al., 2012). Bacterial LPS, also termed “endotoxin”, is a major component of the outer membrane of gram negative bacteria, and in most cases causes activation of epithelial cells. LPS can cause inflammatory responses in human alveolar epithelial A549 cells (Wu et al., 2011b). LPS is recognised by the toll-like receptors (TLRs) on the epithelial the mitogen-activated protein kinases (MAPK) such as p38 MAPK, ERK1/2 and JNK triggering host defense responses including production of inflammatory cytokines (Chow et al., 2015). Epithelial cells generate immune effectors including chemokines, cytokines as well as antimicrobial peptides in response to such inflammatory stimuli (Larsson et al., 1999; Strieter et al., 2002). The LPS-induced A549 cell injury model was used in this study to evaluate anti- inflammatory activity of drug-loaded SLNs because this model has been the most used, acceptable, validated and suitable model to study cell injury (Cabrera-Benitez et al., 2012).
In this study, the influence of cell treatment with drug-loaded SLNs on IL-1β, IL-6, IL-8, IL-12 and TNF-α expression was investigated in LPS-induced A549 cells. No significant production of IL-1β, IL-12 and TNF-α was observed and hence the affect of drug-loaded SLNs on production of these cytokines could not be established. Though many researchers have reported production of IL-1β and TNF-α by A549 cells in response to stimulation by LPS (Song et al., 2013), there are several studies which report an absence or negligible amounts of these cytokines in supernatants of LPS-induced A549 cells (Thorley et al., 2007; Tsutsumi-Ishii and Nagaoka, 2003). The current results are in alignment with these latter studies.
The current results suggest that LPS stimulation induces inflammatory response in A549 cells and triggers release of cytokines such as IL-6 and IL-8 (Capasso et al., 2014; Corsini et al., 2013; Hara et al., 2011; Song et al., 2013; Yasutake et al., 2013;). The
169 Chapter 6 Incorporation of NSAIDs into SLNs concentrations of IL-6 and IL-8 released into the cultured supernatants after LPS stimulation were measured by ELISA.
IL-6 and IL-8 protein expression increased significantly (p < 0.05) after LPS stimulation. Co-cultures of A549 cells with LPS and drug solutions (not encapsulated in SLNs) or drug-loaded SLNs significantly (p < 0.05) reduced IL-6 protein secretion (Figure 6.11), while only a weak suppression of IL-8 protein secretion was found (Figure 6.12). Drug- free SLNs also showed a reduction in IL-6 and IL-8 secretion, suggesting that the SLN carrier has inherent anti-inflammatory properties. This is not unexpected given that stearic acid is known to exhibit anti-inflammatory activity (Pan et al., 2010). However, reduced secretion was greater for the loaded SLNs than the drug-free SLNs, confirming the activity of the NSAIDs. While there was a slightly increased suppression of IL-6 and IL- 8 in the presence of drug solutions (not encapsulated in SLNs) compared to drug-loaded SLNs, the difference between them was not significant (p > 0.05). The results demonstrated that drug-loaded SLNs can suppress secretion of pro-inflammatory cytokines (and would thus be expected to exhibit anti-inflammatory activity).
50
40
30
20 IL-6secretion (pg/mL) 10
0 A B C D E F G H I
Figure 6.11 Inhibition of IL-6 expression in LPS-induced A549 cells by SLNs loaded with NSAIDs. A: control, B: LPS control, C: drug-free SLNs, D: indomethacin-loaded SLNs, E: indomethacin drug solution, F: ketoprofen-loaded SLNs, G: ketoprofen drug solution, H: nimesulide-loaded SLNs and I: nimesulide drug solution.
170 Chapter 6 Incorporation of NSAIDs into SLNs
800
700
600 g/mL) 500
400
300
IL-8secretion ( 200
100
0 A B C D E F G H I
Figure 6.12 Inhibition of IL-8 expression in LPS-induced A549 cells by SLNs loaded with NSAIDs. A: control, B: LPS control, C: drug-free SLNs, D: indomethacin-loaded SLNs, E: indomethacin drug solution, F: ketoprofen-loaded SLNs, G: ketoprofen drug solution, H: nimesulide-loaded SLNs and I: nimesulide drug solution.
171 Chapter 6 Incorporation of NSAIDs into SLNs
6.5 Conclusions
SLNs encapsulated with non-steroidal anti-inflammatory drugs were successfully prepared by the microwave-assisted microemulsion method. The drug-loaded SLNs were within the nanometre range (250 - 300 nm) and showed a negative zeta potential above |20| mV, entrapment efficiency of 70 - 90% and loading capacity of 3.5 - 4.5% (w/w). The DSC and XRD data suggested a decrease in crystallinity of stearic acid formulated as SLNs.
The SLNs were found to be non-toxic using an in vitro cell viability assay. The small size of SLNs is suitable for their uptake into epithelial cells. The anti-inflammatory activity of the drug-loaded SLNs was shown by reduced secretion of IL-6 and, to a lesser extent, IL-8 in LPS-induced alveolar A549 cells. It can thus be concluded that SLNs can encapsulate NSAIDs, and may act as potential carriers of these drugs for the treatment of inflammatory disorders.
172 Chapter 7 Incorporation of anti-fungal drugs into SLNs 7
Incorporation of anti-fungal drugs into SLNs
173 Chapter 7 Incorporation of anti-fungal drugs into SLNs
Abstract
The aim of the present work was to assess the suitability of solid lipid nanoparticles (SLNs) for the encapsulation of the anti-fungal drugs: clotrimazole, miconazole nitrate and econazole nitrate. The microwave-assisted microemulsion technique was used for the production of anti-fungal drug-loaded, stearic acid-based SLNs. The particle sizes of all SLNs prepared were in the nanometre range with moderate zeta potential values, high enough to predict good physical stability. High encapsulation efficiency (EE) and loading capacity (LC) of drug-loaded SLNs demonstrated their high encapsulation capabilities. Physicochemical characterisation of SLNs and bulk stearic acid, performed by differential scanning calorimetry (DSC) and X-ray diffraction (XRD), indicated decreased crystallinity of stearic acid, a factor that influences incorporation and release of drug. The biocompatibility studies performed on A549 cell lines showed a cytotoxic concentration (CC50) value > 100 µg/mL. The anti-fungal efficacy of drug-loaded SLNs was evaluated against Candida albicans. These encouraging results suggest that SLNs can be considered as efficient carriers for encapsulation of anti-fungal drugs.
174 Chapter 7 Incorporation of anti-fungal drugs into SLNs
7.1 Introduction
A novel microwave-assisted microemulsion technique was reported in Chapter 4 of this thesis. Based on the optimisation results in Chapter 4, stearic acid (lipid) and Tween® 20 (surfactant) were selected as appropriate ingredients for production of SLNs. In Chapter 5, the novel microwave-assisted technique was compared with a conventional microemulsion for the production of SLNs loaded with a model antibacterial agent, tetracycline. The results from Chapter 5 clearly demonstrated the advantages of using microwave heating over conventional thermal heating in terms of particle size, stability, encapsulation efficiency and drug release. In Chapter 6, the suitability of the microwave- assisted technique for the production of SLNs loaded non-steroidal anti-inflammatory drugs (NSAIDs) was investigated using selected. The results from Chapter 6 indicated that irrespective of drug chemistry, small SLNs (< 300 nm) with a moderate zeta potential (|20| - |30| mV) and good encapsulation efficiency were produced by the microwave- assisted technique. The EE and LC was influenced by the physical properties of the drugs. The study also suggested that the incorporation of NSAIDs within the SLNs did not lessen the anti-inflammatory activity of the drugs. In the current chapter, these studies are further extended to selected anti-fungal drugs encapsulated within the SLNs by the novel microwave-assisted technique.
The formulation of anti-fungal drugs is becoming of increasing interest and importance. There has been, for example, a significant increase in the incidence of serious invasive mycoses due to new and emerging opportunistic fungal pathogens over the past two decades (Ravani et al., 2013). These opportunistic pathogens colonize the mucosal linings, including oral and vaginal mucosae, that otherwise are characterised by complex bacterial microbiota which make the host less susceptible to infections (Esposito et al., 2013).
Candida albicans is a normal member of the gastrointestinal tract (GIT) microbiota in healthy humans. C. albicans is a commensal organism that colonizes various sites in and on the body including the skin, the GIT (normally present in the mouth, throat, in the stomach, colon and rectum) and reproductive tract (vagina) (Naglik et al., 2014). C. albicans can act as an opportunistic fungal pathogen during host immunosuppression or disruption of the bacterial microbiota (Mason et al., 2012). Dissemination of C. albicans deteriorates the mucosal surfaces and serves as a source of future infections ranging from relatively trivial conditions such as oral and genital thrush to serious super-infections
175 Chapter 7 Incorporation of anti-fungal drugs into SLNs leading to infertility and sterility (Esposito et al., 2013). Candida usually invades deeper tissues and blood in immunocompromised people and may lead to severe life-threatening forms of candidiasis. In recent years, there has been increased interest in Candida infections, particularly C. albicans, due to its causative role in life-threatening infections (Verma and Pathak, 2012).
A number of anti-fungal medications are now in use and applied for topical treatment of severe skin fungal infections. In this study, widely studied anti-fungal drugs, namely clotrimazole, miconazole nitrate and econazole nitrate, have been used as model drugs. They are all imidazole type synthetic broad-spectrum anti-fungal drugs.
Clotrimazole has been used in the treatment of skin and mucus diseases (including tinea pedis, tinea crusis, vulvovaginal and oral candidiasis and genitourinary mycosis) (Das et al., 2012). It is a promising agent in the treatment of cancer (Furtado et al., 2012), sickle cell anaemia (Brugnara et al., 1993) and rheumatoid arthritis (Wojtulewski et al., 1980a, 1980b). Clotrimazole is available as topical preparations (such as creams, lotions, solutions and inserts). Oral administration of clotrimazole is also possible. However, when administered orally, large differences in bioavailability are observed due to the drug’s poor water solubility and slow dissolution in water (Prabagar et al., 2007). Oral administration can also lead to side effects including hepatic toxicity and, very occasionally, neurologic disorders (Brugnara et al., 1993; Yong et al., 2007). Moreover, the plasma half-life of 3 - 6 h indicates that clotrimazole needs to be administered frequently (Ning et al., 2005a, 2005b). In order to overcome these limitations, researchers have attempted to incorporate clotrimazole in mucoadhesive gels (Chang et al., 2002), liposomes and niosomes (Ning et al., 2005b), microemulsions (Hashem et al., 2011), microemulsion-based gels (Bachhav and Patravale, 2009) and inclusion complexes with-cyclodextrin (Bilensoy et al., 2006; Prabagar et al., 2007).
Miconazole nitrate is clinically administered for the management of buccal, dermal and vaginal candidiasis, dermatophytoses, superficial mycoses and mixed infections (Ahmed et al., 2012). It is often administered as a 2% (w/w) topical suspension in the treatment of dermatophytoses, mycoses and other mixed fungal infections and as an oral gel for oral candidiasis (Peira et al., 2008). Oral administration of miconazole nitrate is limited due to its poor water solubility and lack of absorption (Aggarwal and Katare, 2002). Poor skin penetration of miconazole nitrate makes it a poor candidate for topical administration (Elmoslemany et al., 2012). Strategies such as encapsulating miconazole
176 Chapter 7 Incorporation of anti-fungal drugs into SLNs nitrate into liposomes (Elmoslemany et al., 2012), microemulsions (Ofokansi et al., 2012) and mucoadhesive buccal patches (Nafee et al., 2003) have been investigated with varying degrees of success.
Econazole nitrate has been used to treat a variety of dermatological and other mycotic disorders such as dermatophytoses, superficial mycoses and other mixed infections (Verma and Pathak, 2012). The currently available commercial products containing econazole nitrate are creams and pessaries. The self-cleansing action of the vagina resulting from mucus secretion often requires increasing the dosing frequency of such vaginal formulations (Albertini et al., 2009). Salting out of econazole nitrate frequently results in physical instability (phase separation) in creams containing econazole nitrate (Ge et al., 2014). A number of strategies have been employed to overcome these issues including the use of drug carriers such as microspheres (Albertini et al., 2009), nanosponges (Sharma and Pathak, 2011), solid lipid microparticles (Passerini et al., 2009) and ethosomes (Verma and Pathak, 2012)
The successful encapsulation of clotrimazole, miconazole nitrate and econazole nitrate into various drug delivery vehicles demonstrate that their selection for encapsulation into the SLNs is appropriate. In this chapter, the suitability of the microwave-assisted microemulsion method to encapsulate the model anti-fungal drugs (clotrimazole, miconazole nitrate and econazole nitrate) into SLNs is investigated. Table 7.1 is a summary of some relevant physicochemical properties of the model drugs used in this chapter.
177
Table 7.1 Physicochemical properties of anti-fungal drugs employed as model drugs in this study
Physicochemical Clotrimazole Miconazole nitrate Econazole nitrate properties
- - Structure O O HN O O HN N+ N+
N N O O Cl
O O N Cl
Cl Cl Cl N Cl Cl Cl
178 Chemical name 1-[(2-chlorophenyl) 1-[2-(2, 4-dichlorophenyl)-2-[(2, 4- 1-[2-(4-chlorophenyl) methoxy]-2-[(2, diphenylmethyl]-1H-imidazole dichlorophenyl) methoxy] ethyl]-1H- 4-dichlorophenyl) ethyl]-1H-imidazole, imidazole, mononitrate mononitrate
Molecular 344.8 479.1 444.7 weight
pKa 5.8 6.7 6.65
log P 5.9 - 6.26 6.25 5.2
Water solubility 0.5 µg/mL 100 µg/mL 800 µg/mL
Bachhav and Patravale, 2009; Bhalekar et al., 2009; Jain et al., 2010b Bachhav et al., 2011 Hreinsdôttir, 2006; Loftsson and Ravani et al., 2013
Chapter 7 Incorporation of anti-fungal drugs into SLNs
7.2 Chapter Aims
The main objective of this chapter was to investigate the suitability of the novel microwave-assisted microemulsion technique for the production of solid lipid nanoparticles encapsulating anti-fungal drugs.
The specific aims of this chapter
To demonstrate the suitability of the novel microwave-assisted microemulsion technique to encapsulate anti-fungal drugs (clotrimazole, miconazole nitrate and econazole nitrate) into the SLNs.
To characterise the drug-loaded SLNs in terms of their physicochemical characteristics, crystallinity and encapsulation capacities.
To evaluate the cytotoxicity of drug-loaded SLNs against human A549 cell line by determining their mitochondrial activity following exposure to SLNs.
To evaluate the anti-fungal activity of drug-loaded SLNs against Candida albicans.
179 Chapter 7 Incorporation of anti-fungal drugs into SLNs
7.3 Methods
7.3.1 Preparation of SLNs
SLNs were prepared by the novel microwave-assisted microemulsion technique described earlier (see Section 3.3.1). In brief, a mixture of stearic acid (100 mg), Tween® 20 (150 µl) and water (1.35 mL) was heated above the melting point of stearic acid in a microwave reactor tube with constant stirring using a microwave synthesizer to produce an o/w microemulsion. The microwave reaction temperature was set to 80C with a variable microwave power not exceeding 18 W and the reaction was maintained at the set temperature for 10 minutes. The hot o/w microemulsion from microwave was dispersed immediately into cold water (50 mL, 2 - 4 C) under constant magnetic stirring to generate SLN dispersions. For drug-loaded SLNs, drug (5% w/w with respect to lipid) was added to the mixture of stearic acid and Tween® 20 before the mixture was subjected to microwave heating.
7.3.2 Particle characterisation
Determination of hydrodynamic diameter and polydispersity index (PI) using DLS
The intensity weighted mean hydrodynamic diameter and the PI of the SLN dispersions were then determined by DLS at 25C as described in Section 3.3.2.1.
Determination of particle diameter using LD
In addition to DLS, particle size measurements were also conducted by LD at 25 C as described in Section 3.3.2.2.
Zeta potential measurements
Zeta potential measurements were carried out as described in Section 3.3.2.3. The zeta potential of the SLN dispersions was determined by measurement of the electrophoretic mobility. Conversion of the electrophoretic mobility to zeta potential was performed using “Zeta for Windows” (Kosmulski, 2002).
Scanning electron microscopy (SEM)
The shape and particle sizes were estimated by SEM imaging as described in Section 3.3.2.4.
180 Chapter 7 Incorporation of anti-fungal drugs into SLNs
7.3.3 Determination of anti-fungal drugs by high performance liquid chromatography (HPLC)
HPLC analysis was performed to determine and quantify the anti-fungal drugs as described in Section 3.3.6. The column and mobile phase used, and the conditions set, for HPLC analysis are given in Table 7.2. Clotrimazole, miconazole nitrate and econazole nitrate were eluted at 5.8 min, 7.5 min and 6.0 min, respectively (see Appendix, Figure A.7.1 (a), A.7.2 (a) and A.7.3 (a)). The assay was linear (R2 > 0.99) for the three drugs, each over the concentration range of 0 – 100 µg/mL (see Appendix, Figure A.7.1 (b), A.7.2 (b) and A.7.3 (b)).
Table 7.2 HPLC method for analysis of anti-fungal drugs
Specifications
Column Reversed-phase Prevail™ C18 column, 5 µm, 150 mm × 4.6 mm
Mobile phase A: 25 mM NaH2PO4.H2O (pH 2.5) B: Methanol
Isocratic 90% B
Flow rate 0.75 mL/min
Injection volume 5 µL
Column temperature 30C
Detection wavelength 210 nm (for clotrimazole) 230 nm (for miconazole nitrate) 200 nm (for econazole nitrate)
7.3.4 Encapsulation efficiency (EE) and loading capacity (LC) measurements
The EE and LC refer to the percentage of drug encapsulated by the nanoparticles. EE is expressed as the amount encapsulated compared to the amount of drug added, whilst LC refers to the amount encapsulated compared to the amount of lipid used. The EE and LC of the SLNs were determined by the centrifugal ultrafiltration method described in Section 3.3.3. The separation effectiveness of centrifugal filters was performed using the method described in Section 3.3.4. The amounts of anti-fungal drugs in “filtered”,
181 Chapter 7 Incorporation of anti-fungal drugs into SLNs
“loaded”, “free” and “soluble” fractions were analysed by HPLC analysis (see Section 7.3.3). EE and LC were calculated from the amounts of drug determined by the HPLC analysis using the following equations (see Equations 7.1 and 7.2 respectively),
[amount (loaded) - amount (free) - amount (soluble)] EE (%) = × 100 amount (drug loading)
… Equation 7.1 [amount (loaded) - amount (free) - amount (soluble)] LC (%) = × 100 amount of lipid added to the formulation
… Equation 7.2
7.3.5 Crystallinity of SLNs
The crystallinity of SLNs was investigated from their thermal and diffraction characteristics. Thermal behaviour of SLNs was studied by differential scanning calorimetry (DSC) analysis of bulk anti-fungal drugs, bulk stearic acid and the SLNs. DSC analysis was performed as described in Section 3.3.7. The melting enthalpy (ΔH) was obtained by integration of the area under the transition peak and crystallinity index (CI) was determined by Equation 7.3,
∆HSLN CI (%) = × 100 ∆Hbulk lipid × Concentration of lipid phase (%) … Equation 7.3
The X-Ray diffraction (XRD) analysis was performed as described in Section 3.3.8. The XRD data were analysed in conjunction with DSC data to investigate the changes in crystallinity of stearic acid used in preparation of SLNs.
7.3.6 Evaluation of cell viability of SLN dispersions
The viability of human A549 and mouse 3T3-L1 cells following their exposure to SLNs was evaluated by measuring the metabolic activity of cells using the MTT assay as described in Section 3.3.12. Cell viability expressed as a percentage of untreated cells (used as negative control) was determined using Equation 7.4,
182 Chapter 7 Incorporation of anti-fungal drugs into SLNs
Absorbance of treated cells Cell viability (%) = × 100 Absorbance of control cells … Equation 7.4
7.3.7 Evaluation of anti-fungal activity of drug-loaded SLNs on Candida albicans
Yeasts. Candida albicans was used to assess the anti-candidal activity of the formulations. The yeasts were cultured and maintained on Sabouraud dextrose agar (Oxoid, Australia) for 24 - 48 h at 30C.
Assay. The anti-fungal efficacy of the drug-loaded SLNs was initially screened against C. albicans. For this purpose, a yeast suspension was prepared in saline (0.9% sodium chloride solution), with an optical density equivalent to a 0.5 McFarland standard (106 – 5 × 106 yeasts/mL). The yeast suspension was then diluted 1:1000 (v/v) in DMEM to obtain a final concentration of 1 × 103 – 5 × 103 yeasts/mL. A 3 mL aliquot of this suspension was incubated with 3 mL of dispersions containing the SLNs 30C for 24 h. Drug-free SLNs were taken as a negative control and corresponding drug solutions were taken as positive controls. Yeast cells (without any sample) treated with medium alone were taken as a negative control.
The anti-fungal susceptibility of the fungal samples was performed using broth microdilution method described by the Clinical and Laboratory Standards Institute (CLSI) (Fothergill, 2012) using DMEM as the medium. Two-fold serial dilutions of clotrimazole solution, clotrimazole-loaded SLNs, miconazole nitrate solution, miconazole nitrate-loaded SLNs, econazole nitrate solution and econazole nitrate-loaded SLNs were performed in 96-well microplates filled with DMEM, with initial and final drug concentrations of 40 µg/mL and 8 × 10−2 µg/mL, respectively. The yeast suspension (100 µL), prepared as described earlier, was then inoculated in each well of the 96-well microplates. The microplates were incubated at 30 C for 24 h and the results were analysed visually. The minimum inhibitory concentration (MIC) was defined as the lowest concentration at which the growth of yeast cells was completely inhibited.
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7.4 Results and discussion
7.4.1 Preparation of solid lipid nanoparticles
The drug-free and drug-loaded SLNs composed of stearic acid (as the solid lipid core) and surface-tailored with Tween® 20 were successfully prepared by the microwave- assisted microemulsion technique. As discussed in previous chapters, rapid crystallisation of microemulsion droplets generates SLNs. Based on previous results (see Chapter 4, 5 and 6) the particles are expected to be small (nanometre range), solid and non-toxic with a high EE and LC. Extensive particle characterisation including particle sizing, zeta potential, thermal studies and cell culture studies was performed to investigate these features when incorporated with anti-fungal model drugs.
7.4.2 Particle characterisation
The production of SLNs in the nanometre range was evaluated by determination of particle diameter. The particle characteristics of SLNs (including particle diameter, PI and zeta potential) as determined by DLS and LD are summarised in Table 7.3.
Table 7.3 Particle characterisation of SLNs loaded with anti-fungal drugs
Particle size Zeta DLS LD SLNs potential Diameter (mV) PI d(0.5) (nm) (nm)
Drug-free SLNs 257 ± 4 0.13 ± 0.01 153.1 ± 0.3 -27.9 ± 0.5
Clotrimazole-loaded SLNs 274 ± 2 0.18 ± 0.01 160.5 ± 0.3 -21.3 ± 3.2
Miconazole nitrate-loaded 286 ± 3 0.12 ± 0.02 161.7 ± 0.5 20.9 ± 0.8 SLNs
Econazole nitrate-loaded SLNs 301 ± 3 0.15 ± 0.02 165.0 ± 0.2 12.4 ± 0.8
From the results (Table 7.3), drug-free SLNs had the smallest particle size. Investigation of DLS data indicated a significant (p < 0.05) increase in particle diameters of drug-loaded SLNs. This is not unexpected, as seen earlier (see Chapter 6, Section 6.4.2), there is an increase in the particle diameter when SLNs are laden with drug molecules. The order of
184 Chapter 7 Incorporation of anti-fungal drugs into SLNs
SLNs in terms of their particle sizes (from smallest to largest) was as follows: drug-free SLNs < clotrimazole-loaded SLNs < miconazole nitrate-loaded SLNs < econazole nitrate-loaded SLNs. Similar to the case of SLNs loaded with NSAIDs (see Chapter 6), there was no apparent correlation between the drug chemistry and the particle size of SLNs incorporating those drugs.
LD measurements were performed to detect the presence of microparticles in the SLNs. The DLS and LD data show similar trends, but the d(0.5) is significantly (p < 0.05) smaller than the DLS data (Table 7.3). Such differences in particle diameters are not unexpected, and can be attributed to different measurement principles involved in particle sizing by these techniques. Nonetheless, the trend observed in DLS measurements aligns well with the LD data. Although this trend was difficult to assess by SEM analysis, it was observed that the SLNs produced in this chapter were in the submicron size range, and approximately spherical. Figure 7.1 – 7.3 depict SEM images of SLNs loaded with anti- fungal drugs.
Figure 7.1 SEM image of clotrimazole-loaded SLNs viewed at 60,000× magnification. The scale bar represents 200 nm.
Figure 7.2 SEM image of miconazole nitrate-loaded SLNs viewed at 60,000× magnification. The scale bar represents 200 nm.
185 Chapter 7 Incorporation of anti-fungal drugs into SLNs
Figure 7.3 SEM image of econazole nitrate-loaded SLNs viewed at 60,000× magnification. The scale bar represents 200 nm.
The determination of PI was essential to confirm the narrow distribution of particles. The PI results of drug-free and drug-loaded SLNs are given in Table 7.3. The PI values for all SLNs were below 0.2 which indicates a narrow size distribution of particles (Das et al., 2012).
Surface charge is an important characteristic; however, it is more appropriate to measure the associated zeta potential. Zeta potential has been used as a measure of the degree of repulsion between particles in dispersion; therefore, it is often used as a major indicator of stability behaviour. As discussed earlier in the thesis, the solid core of the nanoparticles prepared in this study may prevent particles from coalescing compared to liquid emulsion droplets, presumably also prevent charged entities from moving away from the zone of impact during particle collision, and hence charge-stabilisation may play a particularly important role (Lee et al., 2007) in SLNs. The zeta potential measurements of the different SLNs are summarised in Table 7.3.
The zeta potential results in Table 7.3 show that the zeta potentials of all SLNs were above |20| mV with the notable exception of econazole nitrate-loaded SLNs. The zeta potential of drug-free SLNs is significantly higher than the anti-fungal drug-loaded SLNs. The encapsulation of NSAIDs into SLNs also resulted in a reduction of zeta potential as reported in the previous Chapter. The reduction in the magnitude of the zeta potential may be attributed to disruption of surfactant packing at the particle surface. Any such disruption should also increase the particle size. Increased particle size of drug-loaded SLNs supports this argument (Table 7.3).
The results in Table 7.3 show that the zeta potential of two SLN formulations – miconazole nitrate-loaded SLNs and econazole nitrate-loaded SLNs – was positive.
186 Chapter 7 Incorporation of anti-fungal drugs into SLNs
Interestingly, these are the only two (ionic) drugs used in this study that have positive charge at the pH of the dispersion. The fact that the SLN dispersions show positive zeta potential (i.e. acquire positive charge) suggests that the drug is the origin of that charge, and that a significant portion of the drug was adsorbed at the surface or within the shell of the nanoparticle. Whether or not the (positively charged) drug needs to be in excess of, or simply displaces, the negative charge (presumed to be due to stearic acid) of the drug-free SLNs is not clear and is beyond the scope of this thesis.
Amongst all SLNs characterised in this study, econazole nitrate-loaded SLNs had a significantly lower zeta potential (~ 13 mV) and therefore, potentially less stable. The zeta potential is a good measure of electrostatic stability and for the other SLNs were sufficiently high to indicate that electrostatic stability may be at least partially responsible for stability. The stability of the econazole system, however, shows that electrostatic stability is not necessarily the controlling source of stability. This will be discussed more fully in Chapter 10.
7.4.3 Separation of SLNs and encapsulation studies
Prior to determination of EE and LC, the effectiveness of centrifugal filter units to separate the nanoparticles from the aqueous dispersion medium for better estimation of EE and LC was investigated. This was done by determining the amount of light scattered by serial dilutions of SLNs. The calibration curve prepared for clotrimazole-loaded SLNs is depicted in Figure 7.4. Similar calibration curves for miconazole nitrate- and econazole nitrate-loaded SLNs are shown in Appendix (Figure A.7.4 (a) and A.7.5 (b)).
187 Chapter 7 Incorporation of anti-fungal drugs into SLNs
500
400
300
200
100 Derived countDerived rate (kcps)
0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Concentration of clotrimazole-loaded SLNs (% v/v)
Figure 7.4 Light scattering of clotrimazole-loaded SLNs in water (R2 = 0.999).
The calibration curve showed a linear relation (R2 > 0.999) between the concentration of clotrimazole-loaded SLNs in water and the amount of light scattered. The amount of light scattered by the ultra-filtrate (i.e. aqueous portion), after centrifugation, was approximately equal to the amount of light scattered by MilliQ water (0.4 to 0.5 kcps) indicating effective separation of nanoparticles and the aqueous dispersion medium. These results indicate that any drug content in the ultra-filtrate is most probably the encapsulated drug available as “soluble” drug.
The results for EE and LC of drug-loaded SLNs are summarised in Table 7.4. The EE and LC of the SLNs were influenced by the drug encapsulated. The EE and LC of the drug-loaded SLNs decreased in the order: clotrimazole-loaded SLNs > miconazole nitrate-loaded SLNs > econazole nitrate-loaded SLNs. As discussed earlier (see Chapter 6, Section 6.4.3), the physical properties of drugs such as water solubility and partition coefficients may be an explanation for this behaviour of the drug-loaded SLNs. The aqueous solubility of drugs used in this study decreased in the order: econazole nitrate (800 µg/mL) > miconazole nitrate (100 µg/mL) > clotrimazole (0.5 µg/mL). The EE of the SLNs would be expected to be in the reverse order. The EE and LC results align well with this theory.
188 Chapter 7 Incorporation of anti-fungal drugs into SLNs
Table 7.4 Encapsulation efficiency and loading capacity of SLNs loaded with anti-fungal drugs (in decreasing order of EE corresponding to increasing order of aqueous solubility)
SLNs EE (%) LC (%)
Clotrimazole-loaded SLNs 88.3 ± 0.8 4.4 ± 0.1
Miconazole nitrate-loaded SLNs 86.6 ± 0.7 4.3 ± 0.1
Econazole nitrate-loaded SLNs 72.8 ± 5.0 3.6 ± 0.3
7.4.4 Crystallinity of SLNs
The preparation of SLNs involves heating (or melting) of stearic acid with subsequent cooling (recrystallisation) of the hot microemulsion into SLNs. Such processes can often lead to crystallinity and polymorphic changes in stearic acid and these, in turn, can influence the drug release properties of SLNs. Thermal analysis was conducted on drug- free and drug-loaded SLNs to investigate the crystallinity changes in stearic acid and influence of drug loading on SLNs. The DSC data for bulk stearic acid and the SLNs prepared in this study are given in Figure 7.5 and the critical points deduced from them are summarised in Table 7.5.
a. Stearic acid Drug-free SLNs b. Clotrimazole-loaded c. SLNs d. 64.4 Miconazole nitrate-loaded SLNs e. 63.7 Econazole nitrate-loaded SLNs 63.3 Heatflow (W/g) 62.6 71.5
25 30 35 40 45 50 55 60 65 70 75 80 Temperature (°C)
Figure 7.5 DSC analysis of SLNs loaded with anti-fungal drugs. DSC profiles of (a) bulk stearic acid, (b) drug-free SLNs, (c) clotrimazole-loaded SLNs, (d) miconazole nitrate- loaded SLNs and (e) econazole nitrate-loaded SLNs.
189 Chapter 7 Incorporation of anti-fungal drugs into SLNs
Table 7.5 DSC data of SLNs loaded with anti-fungal drugs
SLNs Tonset (°C) Tmax (°C) ΔH (J/g) CI (%)
Stearic acid 66.9 71.5 173.0 100
Drug-free 54.5 64.4 59.6 91
Clotrimazole-loaded SLNs 58.9 63.7 57.5 88
Miconazole nitrate-loaded 62.1 63.3 52.2 80 SLNs
Econazole nitrate-loaded SLNs 55.5 62.6 58.2 89
The DSC profiles in Figure 7.5 demonstrate the presence of a melting transition endotherm (presented as Tmax in Table 7.5) in all cases, suggesting that supercooled melts were not formed in any of the cases, and that the SLNs produced in this study are genuinely solid in nature. The solid nature of SLNs imparts controlled-release properties to the system.
A sharp melting transition was observed for stearic acid at 71.5C. However, the corresponding melting transitions in SLNs was observed at lower temperatures (Table 7.5) and were less sharp. These results indicate that although the stearic acid was crystalline in all cases, the degree of crystallinity was reduced from that of free stearic acid. The melting transition of drug-loaded SLNs was observed at temperatures marginally below that of drug-free SLNs and well below that of stearic acid, further suggesting an influence of incorporation into SLNs on the solid state nature of stearic acid. Adsorption of surfactant on the surface of SLNs and/or incorporation of drug molecules may have caused such a reduction in crystallinity of stearic acid (Anantachaisilp et al., 2010).
The particle characterisation (Table 7.3) reveals that the particle diameters of the SLNs prepared in this study were in the nanometre (or submicron) range. Small particles have high surface energies that often create an energetically suboptimal state. Such particle contributions, often termed the “small size” or “Gibbs-Thomson” effect, may also cause a reduction in the melting point of stearic acid in the SLNs. The DSC data (Table 7.5) also revealed that the onset temperatures of melting (Tonset) were all above 40C indicating that they would probably remain solid at body temperature.
190 Chapter 7 Incorporation of anti-fungal drugs into SLNs
The melting transitions of pure clotrimazole, miconazole nitrate and econazole nitrate were 146.2C , 187.4C and 163.3C, respectively. The DSC profiles of corresponding drug-loaded SLNs did not exhibit peaks at these temperatures. These results, in addition to reduced melting enthalpy data from Table 7.5, indicate that drug was successfully incorporated into the lipid phase in a solubilised or dispersed state during preparation of the SLNs.
The results (Table 7.5) suggest that the crystallinity calculated in terms of CI increased in the following order: econazole nitrate-loaded SLNs < miconazole-loaded SLNs < clotrimazole-loaded SLNs < drug-free SLNs. Reduced crystallinity is often related with increased EE and LC (see Chapter 6, Section 6.4.4). The EE and LC results (Table 7.4) are consistent with this theory. While it was observed that the physical properties of the drugs (such as aqueous solubility and partition coefficient) influence the EE, LC and CI of SLNs, a specific property which influences these observations cannot be singled out.
XRD analysis was also performed in parallel to DSC analysis to investigate the reduced crystallinity of SLNs. The XRD patterns of bulk stearic acid and the SLNs prepared in this study are depicted in Figure 7.6.
21.7 Bulk stearic acid Drug-free SLNs Econazole 6.7 24.3 nitrate-loaded SLNs 20.6 11.1 36.4 Miconazole a. nitrate-loaded SLNs b. Clotrimazole-loaded
c. SLNs Intensity(AU) d. e.
5 10 15 20 25 30 35 40 2
Figure 7.6 XRD analysis of SLNs loaded with anti-fungal drugs. XRD patterns of (a) bulk stearic acid, (b) drug-free SLNs, (c) clotrimazole-loaded SLNs, (d) miconazole nitrate-loaded SLNs and (e) econazole nitrate-loaded SLNs.
The XRD pattern of bulk stearic acid revealed one sharp peak at 2 = 21.7, three medium-intensity peaks at 2 = 6.7, 20.6 and 24.3 and two intensity peaks at 11.1 and
191 Chapter 7 Incorporation of anti-fungal drugs into SLNs
36.4. The intensity of characteristic peaks of stearic acid was reduced and/or shifted to low diffraction angles, and the other low- and medium-intensity peaks were not detected in the XRD of SLNs suggesting reduced crystallinity in SLNs. These changes in the crystallinity may be attributed to production and formulation parameters such as heating/cooling processes, surfactants and/or drugs. These data are in agreement with the DSC data (Table 2).
7.4.5 Cell viability assay
The biocompatibility of SLNs was investigated by conducting cell viability assays on proliferating A549 and 3T3-L1 cells. The cell viability was evaluated by determining mitochondrial activity (directly proportional to viable cells) using MTT assays. Figure 7.7 depicts the viability of A549 cells after being exposed to SLNs for 24 h. The results indicate that the viability of cells was concentration-dependent. The cells exhibited reduced viability at higher concentrations, but more than 50% cells were viable at all concentrations of SLNs tested in this study. The cytotoxic concentration (CC50) values for all SLNs were concluded to be greater than the highest concentration of SLNs tested (100
µg/mL). If CC50 is assumed to be an indicator of non-toxicity as in the earlier chapters, these results indicate that SLNs are non-toxic at all concentrations tested in this study (0.3125 - 100 µg/mL). Similar trends were observed in 3T3-L1 cells exposed to SLNs for 24 h (Figure 7.8).
150 Drug-free SLNs 125 Clotrimazole-loaded SLNs 100 Miconazole nitrate-loaded SLNs 75 Econazole nitrate-loaded SLNs 50 Cell(%) viability 25
0 1 10 100 Concentration of SLNs (g/mL)
Figure 7.7 Viability of A549 cells measured by MTT assay for SLNs loaded with anti- fungal drugs.
192 Chapter 7 Incorporation of anti-fungal drugs into SLNs
150 Drug-free SLNs 125 Clotrimazole-loaded SLNs Miconazole 100 nitrate-loaded SLNs Econazole nitrate-loaded 75 SLNs
50 Cell viability (%)Cell viability 25
0 1 10 100 Concentration of SLNs (g/mL)
Figure 7.8 Viability of 3T3-L1 cells as measured by MTT assay for SLNs loaded with anti-fungal drugs.
7.4.6 Anti-fungal activity on C. albicans
The initial screening of drug-loaded SLNs for anti-fungal activity was performed against C. albicans in broth culture medium. Compared to fungi-only controls, the medium which included drug-loaded SLNs remained clear or only slightly turbid. These preliminary results suggested that the anti-fungal activity of drugs when incorporated into SLNs was retained. The culture medium containing the drug-free SLNs showed comparable growth (relative to control), eliminating any intrinsic anti-fungal activity from the SLNs (or any component used in the preparation of SLNs). Therefore, the activity exhibited by drug- loaded SLNs was due to the retention of activity of the drug after incorporation within the SLNs. In order to determine the MIC of drug-loaded SLNs, the yeast cells were exposed to serial concentrations of SLNs in culture medium. The results of anti-fungal activity of SLNs are summarised in Table 7.6.
Table 7.6 Anti-Candida albicans activity of SLNs loaded with anti-fungal drugs
Sample MIC range (µg/mL)
Drug-free SLNs No activity
Clotrimazole-loaded SLNs 0.31 - 0.63
Miconazole nitrate-loaded SLNs 2.50 - 5.00
Econazole nitrate-loaded SLNs 2.50 - 5.00
193 Chapter 7 Incorporation of anti-fungal drugs into SLNs
The result presented here show that clotrimazole-loaded SLNs have a greater inhibitory effect than miconazole nitrate-loaded SLNs and econazole nitrate-loaded SLNs which were found to have similar effects. This could be due to strong association of miconazole nitrate and econazole nitrate with the lipid matrix which may lower the rate at which the drugs are released into the culture medium. Drug release studies (see Chapter 8, Section 8.4 B) also reveal that more drug was released from clotrimazole-loaded SLNs after 24 hours, and the release of miconazole nitrate and econazole nitrate is slow. However, it should be appreciated that the incorporated drugs maintain their inhibitory activity and further studies may be required to increase the anti-fungal activities of drug-loaded SLNs.
194 Chapter 7 Incorporation of anti-fungal drugs into SLNs
7.5 Conclusions
The lipophilic anti-fungal model drugs, clotrimazole, miconazole nitrate and econazole nitrate, used in this study were successfully incorporated into SLNs by a microwave- assisted microemulsion method. Physicochemical characterisation demonstrated that SLNs with small particle sizes (250 - 300 nm), moderate zeta potentials (|12| - |28| mV), high EE (72 - 88%) and LC (3.6 - 4.4%) were produced. The DSC data, supported with XRD analysis, suggest decreased crystallinity of stearic acid in SLNs, conducive to increased loading capacities of SLNs.
The biocompatibility experiments suggested that the viability of cells was concentration- dependent. More than 50% of the cells were viable at concentrations tested in this study. The susceptibility of C. albicans to drug-loaded SLNs suggested that the anti-fungal activity of drugs was maintained when incorporated into the SLNs. All these findings suggest that SLNs can be used as potential carriers of anti-fungal drugs in the treatment of candidal infections.
195
Chapter 8 Drug release kinetics of SLNs 8
In vitro Drug Release Properties of SLNs
197 Chapter 8 Drug release kinetics of SLNs
Abstract
The SLNs prepared by the microwave-assisted microemulsion technique have been shown to exhibit excellent physicochemical properties. However, it is important to investigate the release of drugs from drug-loaded SLNs. A number of factors regulate the release of drug from drug carriers, such as the nature of the drug, the carrier and the carrier’s physicochemical characteristics. The solid nature of the SLNs prepared in this thesis is expected to demonstrate slow and sustained release of drugs. The release of drugs from various drug-loaded SLNs was investigated in this chapter by the dialysis bag technique in phosphate buffered saline (pH 7.4) containing Tween® 20 to facilitate solubilisation of encapsulated drugs which are otherwise poorly water soluble. The drug- loaded SLNs exhibited a biphasic release of drugs. SLNs loaded with non-steroidal anti- inflammatory drugs (NSAIDs) exhibited a high initial release followed by a sustained release of drugs and SLNs loaded with anti-fungal drugs exhibited a slow, sustained but an incomplete release of drugs. Based on these observations, a drug-enriched shell and drug-enriched core model was suggested for SLNs-loaded with NSAIDs and anti-fungal drugs respectively.
The drug release data is fitted into various mathematical kinetic models of drug release and the model with best fit was selected on the basis of three criteria - adjusted coefficient 2 of determination (R adjusted), the Akaike information criterion (AIC) and the model selection criterion (MSC). Model fitting suggested that release of NSAIDs was governed by Fickian diffusion and release of anti-fungal drugs by non-Fickian diffusion. The dissimilarity in profiles (attributed to difference in the physicochemical properties of the drugs i.e. water solubility and partition coefficients) was evaluated by profile comparison techniques such as the pairwise procedure and bootstrap f2 methods.
198 Chapter 8 Drug release kinetics of SLNs
8.1 Introduction
The SLNs are looked upon as potential candidates for drug delivery; therefore, the success of SLNs should be evaluated in terms of their drug release properties. The SLNs are expected to exhibit several advantages which are relevant to their drug release properties (Siepmann and Siepmann, 2011): (a) provide controlled release of drugs – due to their solid nature, and (b) increase apparent solubility of drugs – due to their small size. It is hoped that the SLNs produced in this research will exhibit each of these benefits. In previous chapters, drug substances belonging to different therapeutic classes were encapsulated with high efficiency into the SLNs. The controlled release of drugs may help overcome the issue of frequent administration (due to short half-lives of drugs) and increasing the apparent solubility of drug will overcome the classic solubility issue of some poorly soluble yet potent drugs.
Depending on the chemistry of drug(s), types and amounts of excipient(s), production technique, geometry and dimension of the drug carriers and the environmental conditions during release of drug from the carriers, one or more mechanisms can be involved in release of drug from carriers. An extensive account of release mechanisms has been reported elsewhere (Siepmann and Siepmann, 2008). A few of these mechanisms that are relevant to most delivery systems are (Crank, 1975; Cussler et al., 2009; Faisant et al., 2003; Frenning and Strømme, 2003; Guse et al., 2006; Lao et al., 2011; Lee, 2011; Narasimhan, 2001; Narasimhan and Peppas, 1996; Sackett and Narasimhan, 2011; Zygourakis and Markenscoff, 1996):
Wetting of surface with water Diffusion (or penetration) of water into the system Diffusion of drugs and/or excipients out of the system Diffusion of drugs and/or excipients through the liquid unstirred layer that forms the interface between the system and the release medium Dissolution of drugs and/or excipients Degradation of drugs and/or excipients Changes in the micro-environmental conditions such as the ionic strength, pH and presence of counter ions Matrix former erosion
199 Chapter 8 Drug release kinetics of SLNs
In most lipid systems, diffusion seems to be the predominant step in release of drug release (Siepmann and Siepmann, 2011). A study by Bidah et al. (1992) suggested that release of sodium salicylate from Gelucire 46/07-based spherical beads was diffusion- controlled. However, a clear distinction between water-diffusion and drug-diffusion could not be made. Koennings et al. (2007a) showed that protein release out of the lipid implants and water penetration into the implants are closely related. In another study, Koennings et al. (2007b) showed that increased water penetration due to surface wetting in presence of surfactants play a rate-determining role in release of lysozymes from lipid implants. The release of propranolol hydrochloride from (higher concentrations of) Precirol® ATO 5 and Dynasan® 120 was expected to be predominantly due to the limited drug solubility effects and/or matrix former erosion (Kreye et al., 2011).
The structure of the SLNs (see Chapter 1, Section 1.11) such as the drug-enriched shell, drug-enriched core, homogenous matrix or a mixed system, is often considered to contribute a critical role in the release of drugs from the SLNs (Müller et al., 2002a). The release of drug from SLNs like most of the other lipid systems can, therefore, be expected to be predominantly diffusion-controlled with or without any matrix erosion and/or limited drug solubility effects. Based on Noyes-Whitney and Nernst-Brunner theories and based on Fick’s Law of diffusion (see Chapter 1, Section 1.12), different mathematical equations have been proposed. These mathematical equations provide an indication of underlying mechanism of drug mechanism. In order to determine the mechanism of drug release from the SLNs prepared in this thesis, the following mathematical models were used:
Zero-order model. The zero-order model describes the dissolution of drug from pharmaceutical devices. The pharmaceutical device slowly releases the drug into the surrounding medium without losing its integrity (i.e. without disaggregation) and is independent of the drug concentration in the device. Equation 8.1 gives the mathematical expression that describes the zero-order kinetics.
F = k0t
… Equation 8.1
200 Chapter 8 Drug release kinetics of SLNs where F is the fraction of drug dissolved in time t and k0 is the apparent dissolution rate constant or zero-order rate constant. The fraction of dissolved drug F can be calculated using the Equation 8.2,
Q F = 1 - t Q0 … Equation 8.2 where is Qt is the amount of drug dissolved in time t and Q0 is the initial amount of drug in the formulation.
This is deemed to be the most ideal method drug release in order to achieve a prolonged pharmacological effect (Costa and Lobo, 2001). The zero-order relation is often used for describing the dissolution of modified release pharmaceutical systems such as transdermal drug delivery systems, matrix tablets with low soluble drugs, osmotic drug delivery systems, etc. (Varelas et al., 1995).
First-order model. The first-order model is based on the Noyes-Whitney rule and the Nernst-Brunner theory (see Chapter 1, Section). The rate of drug release from a pharmaceutical device is dependent on the concentration of the drug remaining in the device at each definite time (Mulye and Turco, 1995). Equation 8.3 can be used to express the first-order kinetics model,
F = 100 × [1 - e-k1t]
… Equation 8.3 where F is the fraction of drug dissolved in time t and k1 is the first-order rate constant.
While it is difficult to hypothesize the first-order release mechanism from a hypothetical basis, this kinetics model has been used to describe the pharmacokinetics (adsorption and/or elimination) of several drugs (Costa and Lobo, 2001). The application of first- order kinetics model, and variants thereof, to drug dissolution studies have been previously proposed (Gibaldi and Feldman, 1967; Gibaldi and Perrier, 1982; Kitazawa et al., 1975, 1977; Wagner, 1969).
201 Chapter 8 Drug release kinetics of SLNs
Higuchi model. Takeru Higuchi developed several theoretical models to study the release of water soluble and poorly water soluble drugs from semi-solid and solid pharmaceutical dosage forms (Higuchi, 1961, 1963). The Higuchi model describes the release of drug from a non-eroding homogenous matrix. The Higuchi model is based on the Fick’s law of diffusion, and is square root time-dependent. The mathematical expression that best describes the Higuchi model is given in Equation 8.4,
1/2 F = kHt … Equation 8.4 where F is the fraction of drug dissolved in time t and kH is the Higuchi release constant.
The Higuchi model is, however, based on a few assumptions (Siepmann and Siepmann, 2008, 2011, 2012, 2013): (a) perfect sink conditions are maintained throughout the experiments; (b) the initial drug concentration in the pharmaceutical dosage form (or the system) is much higher than the drug solubility in the wetted system; (c) the drug is finely dispersed within the system i.e. the size of the drug particles is much smaller than the thickness of the drug delivery device; (d) the drug is homogenously distributed throughout the drug delivery device; (e) the diffusion coefficient of the drug within the drug delivery system is constant and is independent of the time and the position within the device; (f) the drug delivery system does not swell or dissolve during the drug release.
Korsmeyer-Peppas model. The Korsmeyer- Peppas release model, also referred to as the Power law, is a semi-empirical model based on theories proposed by Korsmeyer et al. (1983) and Peppas (1985). The Korsmeyer-Peppas model has been described using Equation 8.5,
n F = kKPt
… Equation 8.5 where kKP is the Korsmeyer-Peppas constant and n is the diffusional or release exponent.
The value of release exponent n has been used as an indicative of the drug release mechanism - Fick’s diffusion, anomalous transport, swelling (or case-II transport) or super case-II transport (Zuo et al., 2014). Different n values for different geometries have been recommended (Table 8.1). Garg and Singh (2011) and Silva et al. (2012a) used the value of n to describe release mechanisms from lipid systems.
202 Chapter 8 Drug release kinetics of SLNs
Table 8.1 Release exponents and release mechanisms from polymeric dosage forms
Release exponent (n) Drug release mechanism Slab Cylinder Sphere
0.5 0.45 0.43 Fickian diffusion
0.5 < n < 1.0 0.45 < n < 0.89 0.43 < n < 0.85 Anomalous transport
1.0 0.89 0.85 Case-II transport
More than 1.0 More than 0.89 More than 0.85 Super case-II transport
Hixson-Crowell model. Noyes-Whitney and Nernst-Brunner in their experimental studies intentionally avoided any time-dependent changes in the surface area of the substance exposed to the fluids. Hixson and Crowell (1931a, 1931b and 1931c) addressed the fact that the surface of the dissolving substances often changes with time, for e.g. the radius of spherical surfaces decrease with time in well-agitated bulk fluids. Equation 8.6 gives the mathematical expression that describes the Hixson-Crowell model,
3 F = 100 × [1 - (1- kHt) ]
… Equation 8.6 where F is the fraction of drug dissolved in time t and kHC is the Hixson-Crowell release constant.
It was also found that the regular area of the particles was proportional to the cube root of their volume. Based on these observations, a mathematical expression was derived to describe the drug dissolution from dosage forms (Equation 8.7) which is the well-known “cube-root law”,
3 3 √Mt = √M0 - kt
… Equation 8.7 where M0 and Mt are the initial and remaining amounts of drug in the pharmaceutical dosage forms at time 0 and t respectively.
The Hixson-Crowell model is often applied to systems that erode over time (Azadi et al., 2013). The classical Hixson-Crowell or the cube-root law are based on a few assumptions (Siepmann and Siepmann, 2013): (a) the concentration of drug dissolved in the bulk
203 Chapter 8 Drug release kinetics of SLNs fluids remains does not change significantly (when perfect sink conditions are maintained during the experiments); (b) the dissolving dosage form has a spherical shape which does not change with time; (c) the particles do not disaggregate during dissolution.
Hopfenberg model. Hopfenberg (1976) proposed a semi-empirical model to correlate the drug released from surface eroding polymer and the surface area of the device. The assumption made in this model was that the surface area of the device remains constant throughout the drug release period. Based on this assumption, the mathematical equation (Equation 8.8) that describes the release of drug following this model is,
n F = 100 × [1 - (1- kHBt) ]
… Equation 8.8 where F is the fraction of drug dissolved in time t, kHB is the Hopfenberg release constant and n is the shape factor.
Baker-Lonsdale model. The Baker-Lonsdale model is a semi-empirical model developed from the Higuchi model in 1974 (Baker and Lonsdale, 1974). It has been used to describe the release of drug (by diffusion) from spherical matrices. The mathematical equation describing the drug release following Baker-Lonsdale model is given by Equation 8.9,
3 F 2/3 F × [1 - (1 - ) ] - = k t 2 100 100 BL
… Equation 8.9 where F is the fraction of drug dissolved in time t and kBL is the Baker-Lonsdale release constant.
Makoid-Banakar model. Makoid-Banakar is a less commonly used semi-empirical model of drug release (Zhang et al., 2010). The mathematical expression that described the release of drug according to this model is given by Equation 8.10,
m -ct F = kMBt e
… Equation 8.10
204 Chapter 8 Drug release kinetics of SLNs where F is the fraction of drug dissolved in time t, kMB is the Makoid-Banakar release constant and n and k are empirical model parameters.
Weibull model. Although rarely used, the Weibull model of drug release has been used to describe the drug dissolution process, and therefore more commonly applied in erosion-based drug release systems. Equation 8.11 has been used to describe the release of drugs following Weibull model,
tb - F = 100 × [1 - e a ]
… Equation I.8.11 where F is the fraction of drug dissolved in time t, a is the scale parameter and b is the shape parameter.
The shape parameter b characterizes the shape of the drug release curve; when b = 1 the curve is sigmoidal or S-shaped, for b > 1 the curve is parabolic (i.e. upward curvature followed by a turning point) and when b < 1 the curve has a higher initial slope followed by a consistent exponential phase (Zhang et al., 2010). The scale parameter is useful in determining the time required for the 63.2% of drug in the formulation to be released (Costa and Lobo, 2003).
In this chapter, an investigation of drug release from the SLNs was undertaken to provide a better understanding of the release properties of the SLNs, and also to speculate on the probable structure of SLNs when incorporated with different drug molecules used in this study. The drug release data was analysed by fitting the drug release data to different mathematical models to evaluate the release behaviour of the SLNs. Some of these mathematical equations are empirical or semi-empirical and are therefore descriptive rather than mechanistic. Although the predictive power of such models is low, these may find use, for example, in comparing release profiles on the basis of a specific parameter. By contrast, other mathematical equations rely on mechanistic models are often based on real phenomena (e.g. dissolution, diffusion, erosion, precipitation, swelling and/or degradation) (Siepmann and Siepmann, 2008). The selection of a suitable model that fits the release data is necessary for quantitative evaluation of release characteristics of the system and for comparison of release profiles in model-dependent approaches.
205 Chapter 8 Drug release kinetics of SLNs
8.2 Chapter Aims
The main objective of this chapter was to study the release kinetics of selected non- steroidal anti-inflammatory drugs and anti-fungal drugs from SLNs.
The specific aims of this chapter are:
To study the drug release behaviour of SLNs loaded with NSAIDs employed in this thesis (indomethacin, ketoprofen and nimesulide). To investigate the kinetics of release of NSAIDs from SLNs by fitting the release data with various mathematical models. To study the drug release behaviour of SLNs loaded with anti-fungal drugs employed in this thesis (clotrimazole, miconazole nitrate and econazole nitrate). To investigate the kinetics of release of anti-fungal drugs from SLNs by fitting the release data with various mathematical models. To speculate on the structure of the SLNs loaded with drugs based on their release behaviour. To compare the drug release profiles of a representative from each drug class
using profile comparison methods (such as the pairwise procedure or bootstrap f2 methods).
206 Chapter 8 Drug release kinetics of SLNs
8.3 Methods
8.3.1 Determination of drugs by HPLC analysis
HPLC analysis was performed to determine the concentration of drug in release medium. The column and mobile phase used, and the conditions set, for HPLC analysis are given in Table 8.2. Indomethacin, ketoprofen, nimesulide, clotrimazole, miconazole nitrate and econazole nitrate were eluted at 5.2 min, 4.2 min, 4.1 min, 5.8 min, 7.5 min and 6.0 min respectively (see Appendix, Figure A.6.1 (a), A.6.2 (a), A.6.3 (a), A.7.1 (a), A.7.2 (a) and A.7.3 (a)). The assay was linear (R2 > 0.99) for the six drugs, each over the concentration range of 0 – 100 µg/mL (see Appendix, Figure A.6.1 (b), A.6.2 (b), A.6.3 (b), A.7.1 (b), A.7.2 (b) and A.7.3 (b)).
Table 8.2 HPLC method for analysis of drugs encapsulated in SLNs
Specifications
Column Reversed-phase Prevail™ C18 column, 5 µm, 150 mm × 4.6 mm
Mobile phase A: 25 mM NaH2PO4.H2O (pH 2.5) B: Methanol
Isocratic 90% B
Flow rate 0.75 mL/min
Injection volume 5 µL
Column temperature 30C
Detection wavelength 318 nm (for indomethacin) 254 nm (for ketoprofen) 295 nm (for nimesulide) 210 nm (for clotrimazole) 230 nm (for miconazole nitrate) 200 nm (for econazole nitrate)
8.3.2 In vitro drug release studies
The drug release kinetics from drug-loaded SLNs was studied by the dialysis bag technique described in Section 3.3.5. Briefly, a 5 mL aliquot of a drug-loaded SLN
207 Chapter 8 Drug release kinetics of SLNs dispersion was placed in the dialysis bags (soaked in distilled water for 12 h prior to use) and sealed at both ends. The dialysis bag was immersed in an amber coloured glass bottle containing 50 mL of release medium (0.1 M PBS, pH 7.4, containing 1% Tween® 20). The bottles were placed in a thermostatic shaker at 37 ± 0.5°C and 150 rpm. A 1 mL aliquot of release medium was withdrawn at predetermined time points (0, 1, 2, 4, 6, 8, 12, 24 h) and replaced with an equal volume of fresh release medium to maintain the sink conditions. The drug content in the aliquot was determined by HPLC analysis (Section 8.3.1).
8.3.3 Drug Release data modelling
The drug release data was synchronised with mathematical equations that fit this data under various kinetic models. In addition to zero order and first order kinetic models, mechanistic models (such as Higuchi, Korsmeyer-Peppas and Hixson-Crowell models) and empirical models (such as Hopfenberg, Baker-Lonsdale, Makoid-Banakar and Weibull models) were used to fit the drug release data. Model fitting was performed in order to select the model that best describes the drug release profiles from SLNs, and predict the in vivo release mechanisms. The equations and the parameters for each model 2 are summarised in Table 8.2. The adjusted coefficient of determination (R adjusted), the Akaike information criterion (AIC) and the model selection criterion (MSC) were used as indicators of the best fit of the data for each model (Zhang et al., 2010).
8.3.4 Evaluation of release profile comparison
A comparison of drug release profiles is often performed to evaluate changes in the release profiles of a newly developed product when compared to the release profiles of a previously approved product. Several approaches (including statistical, model-dependent and model-independent approaches) have been proposed for comparison of drug release profiles (Zhang et al., 2010). In this study, drug release profile comparison was carried out by model-independent approaches (determination of similarity and difference factors, determination of Rescigno indices and the bootstrap f2 method) (Moore and Flanner, 1996; Rescigno, 1992; Vertzoni et al., 2003).
208 Chapter 8 Drug release kinetics of SLNs
The drug release profiles were compared to achieve a preliminary indication of the SLN structure (with respect to drug localisation). The structure of nanomaterials often dictates the drug release behaviour. It must, however, be acknowledged that these methods are generally used for comparison of two products – an approved product and a “changed” product. Therefore, the results here can only be used as an indicator of similar drug release profile, and hence, SLN structure – not proof of that structure.
8.3.5 Data fitting and statistical analysis
The drug release data modelling and comparison of drug release profiles was performed using the freely available DDSolver® Program. This is a computer program compiled by Zhang et al. (2010) that works as an add-in with Microsoft® Excel.
209 Chapter 8 Drug release kinetics of SLNs
8.4 Results and Discussion
8.4.1 Drug release studies of SLNs loaded with non-steroidal anti-inflammatory drugs
The drug-loaded SLNs prepared and characterised previously (see Results, Chapter 6 – Section 6.4) were employed to investigate the in vitro release of drugs from the SLNs.
8.4.1.1 Indomethacin-loaded SLNs
The indomethacin-loaded SLNs used for drug release studies had a small diameter (274 ± 8 nm) with a low PI value (0.11 ± 0.02) and a negative zeta potential (-23.8 ± 1.7 mV) (see Chapter 6, Section 6.4.2). The EE (83 ± 4%) and LC (4.1 ± 0.2%) of indomethacin- loaded SLNs were high (see Chapter 6, Section 6.4.3). The indomethacin release profile from SLNs into the surrounding phosphate buffered solution (pH 7.4) containing 1% Tween® 20 at 37°C over 24 h is shown in Figure 8.1.
100 90 80 70 60 50 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.1 In vitro drug release of indomethacin from SLNs.
The release of indomethacin from SLNs was found to increase exponentially in the first 5 h followed by a sustained release over 24 h. Most researchers have described similar drug release behaviour as “biphasic” release (Basha et al., 2015; Bose et al., 2013; Kelidari et al., 2015; Nayak et al., 2010; Silva et al., 2012b; Wang et al., 2012). The
210 Chapter 8 Drug release kinetics of SLNs indomethacin release is, therefore, consistent with a biphasic release profile. A schematic diagram showing the biphasic release of drugs from SLNs is depicted in Figure 8.2.
Figure 8.2 Schematic diagram showing biphasic release of drugs from SLNs.
Phase I: The indomethacin-loaded SLNs showed an initial phase of fast or burst release (up to 5 h)
Indomethacin is a poorly water-soluble drug; however, at high temperature, solubility of indomethacin may increase and lead to its repartitioning from the molten stearic acid (lipid phase) to the hot water phase. Rapid cooling of hot o/w microemulsion accelerates lipid crystallisation at the core with concomitant increase in drug concentration in the outer liquid lipid. Complete cooling of microemulsion droplets may cause precipitation of any drug-enriched shell. The burst release of indomethacin may be due to the short diffusion path of indomethacin molecules encapsulated within the shell of the SLNs. Bose et al. (2013), in their study on quercetin-loaded SLNs, proposed a drug-enriched shell model of quercetin-loaded SLNs based on a similar drug release profile. In addition, an initial burst due to release to release of adsorbed drug molecules has
211 Chapter 8 Drug release kinetics of SLNs
also been reported by other researchers (Nayak et al., 2010; Reddy and Murthy, 2005; Singh et al., 2010). Bhandari and Kaur (2013), in their study on isoniazid- loaded SLNs, suggested that the initial burst release may be due to:
a. Presence of unencapsulated (or free) drug molecules in the SLN dispersion b. Release of adsorbed drug molecules from the surface of the SLNs or release from precipitated drug molecules within the shell of the SLNs c. Passage of a few small nanoparticles (~ 10-15 nm) that may have passed across the dialysis membrane
Based on these arguments, the presence of free indomethacin molecules and release of adsorbed indomethacin and/or from precipitated indomethacin within the shell may explain the initial burst release of indomethacin. The possibility of passage of small nanoparticles through dialysis membranes is quite low as light scattered (particle size measurements) by release medium was low (similar to water) indicating the absence of any SLNs in the drug release medium.
Phase II: The initial burst release phase was followed by a more sustained release phase (post 5 h)
The sustained release of indomethacin suggested homogenous encapsulation of indomethacin throughout the lipid matrix (Paliwal et al., 2009). The remaining drug incorporated into the core of the SLNs leached out by diffusion (Grassi et al., 2003a, 2003b). A slow release was expected due to the solid nature of the SLNs and the lipophilicity of stearic acid used in the preparation of SLNs. Approximately 10% of drug remained associated with the SLNs after Phase II (Figure 8.1). The remaining drug was recovered from the dialysis bag after 24 h.
The drug release data were fitted with release kinetic models and the results obtained from data fitting are summarised in Table 8.3.
212 Chapter 8 Drug release kinetics of SLNs
Table 8.3 Model fitting of indomethacin release profiles
2 Model Parameters R adjusted AIC MSC
Zero order k0 = 0.10 -0.57 76.7 -1.5
First order k1 = 0.01 0.95 48.8 2.0
Higuchi kH = 3.24 0.64 64.9 0.0
Korsmeyer-Peppas kKP = 17.71 0.91 54.8 1.3 n = 0.24
Hixson-Crowell kHC = 0.00 0.79 60.5 0.6
Hopfenberg kHB = 0.00 0.94 50.8 1.8
Baker-Lonsdale kBL = 0.00 0.92 53.0 1.5
Makoid-Banakar kMB = 4.40 0.99 41.0 3.0 n = 0.53
c = 0.00
Weibull a = 35.82 0.98 44.0 2.6 b = 0.68
In this study, goodness of fit of each model was performed based on three selection 2 criteria: R adjusted, the AIC and the MSC values. The best model would have a high 2 R adjusted, a low AIC and a high MSC value. Mathematically, the expression that best 2 describes the indomethacin release from SLNs is the Makoid-Banakar model (R adjusted = 2 0.99). The R adjusted results are supported by AIC and MSC values. The Makoid-Banakar model had the smallest AIC value (41.0) and highest MSC value (3.0). The Makoid- Banakar model is, by far, the most complex model to calculate (Costa and Lobo, 2003), and its success may be, in part, due to that complexity. The curvilinear nature of the cumulative percent indomethacin released depicted that the drug release profile followed 2 first-order kinetics (R adjusted = 0.95), which was prominent in the first few hours (~ 5 h). These results suggested that release of indomethacin from SLNs diminished every unit of time.
2 The R adjusted value obtained for Korsmeyer-Peppas model was 0.91. This result showed that the Korsmeyer-Peppas model provided a good fit for indomethacin release. The
213 Chapter 8 Drug release kinetics of SLNs value of release exponent n obtained from Korsmeyer-Peppas model was 0.24. The value of release exponent n gives an indication of the drug release mechanism. Many researchers describe the release mechanism to be diffusion-controlled for spherical particles when n ≤ 0.43 (Huang et al., 2012; Krstić et al., 2014; Silva et al., 2012b). Based on these findings, the release of indomethacin from the SLNs was assumed to be based on Fick’s laws of diffusion. In simple words, diffusion of indomethacin probably takes place because of concentration gradient of indomethacin.
While the Weibull model is an empirical model and cannot adequately characterize the release properties of the drug, the applicable parameters have been used to describe the 2 release profile. The R adjusted value obtained for Weibull model was 0.98. These results suggested a good fit of release data to Weibull model. The model parameters viz. shape parameter, b, and scale parameter, a, were 0.68 and 35.82 respectively. Al-Zoubi et al. (2015) and Franek et al. (2014) used these parameters to describe the shape of the release curve and to estimate the time required (Td) for the device to release 63.2% of encapsulated drugs into the release medium. The results suggested an initial burst release of indomethacin slowing gradually to reach a plateau (slow and sustained release) and the Td was calculated to be 3.2 h.
All these results suggested that release of indomethacin from SLNs was a diffusion- controlled process with an initial burst release followed by a sustained release of indomethacin.
8.4.1.2 Ketoprofen-loaded SLNs
The ketoprofen-loaded SLNs used for drug release studies had a small diameter (254 ± 15 nm) with a low PI value (0.14 ± 0.02) and a negative zeta potential (-20.6 ± 1.2 mV) (see Chapter 6, Section 6.4.2). The EE (72 ± 1%) and LC (3.6 ± 0.1%) of ketoprofen- loaded were lower than indomethacin-loaded SLNs but still acceptable (see Chapter 6, Section 6.4.3). The in vitro release profile of ketoprofen from SLNs obtained by the dialysis bag technique in phosphate buffered saline (pH 7.4) containing 1% Tween® 20 is shown in Figure 8.3.
214 Chapter 8 Drug release kinetics of SLNs
100 90 80 70 60 50 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.3 In vitro drug release of ketoprofen from SLNs.
Similar to indomethacin release (Section 8.4.1), the release of ketoprofen from SLNs showed biphasic release behaviour (Figure 8.3).
An initial phase of burst release (up to 4 h) A sustained release phase
A high initial burst followed by a sustained release of ketoprofen resembled a drug- enriched shell of ketoprofen-loaded SLNs (i.e. more drug within the shell and less in the lipid core)
The drug release data were fitted with release kinetic models and the results obtained from data fitting are summarised in Table 8.4.
215 Chapter 8 Drug release kinetics of SLNs
Table 8.4 Model fitting of ketoprofen release profiles
2 Model Parameters R adjusted AIC MSC
Zero order k0 = 0.09 -1.34 78.4 -2.3
First order k1 = 0.01 0.83 57.3 0.3
Higuchi kH = 3.20 0.32 68.5 -1.1
Korsmeyer-Peppas kKP = 31.48 0.95 49.0 1.4 n = 0.15
Hixson-Crowell kHC = 0.00 0.46 66.7 -0.9
Hopfenberg kHB = 0.00 0.81 59.3 0.1
Baker-Lonsdale kBL = 0.00 0.77 59.8 0.0
Makoid-Banakar kMB = 13.80 0.99 35.9 3.0 n = 0.32
c = 0.00
Weibull a = 6.39 0.97 43.8 2.0 b = 0.38
Similar to indomethacin release from SLNs, the release of ketoprofen was also a diffusion-controlled process. Important observations for ketoprofen release from SLNs:
Release data fitted well to the Korsmeyer-Peppas model and Weibull model 2 (since R adjusted > 0.85) Makoid-Banakar model was the mathematical expression that best described the 2 ketoprofen release from SLNs (since R adjusted = 0.99, AIC = 35.9 and MSC = 3.0) Release of ketoprofen from SLNs followed Fickian diffusion mechanism (since release exponent n from Korsmeyer-Peppas model < 0.43) Release data for ketoprofen suggested an initial burst release (high initial slope) slowing gradually to reach a plateau (slow and sustained release) (since shape parameter b from Weibull model < 1) 63.2% of ketoprofen was released within 2.1 h
216 Chapter 8 Drug release kinetics of SLNs
8.4.1.3 Nimesulide-loaded SLNs
The nimesulide-loaded SLNs used for drug release studies had a small diameter (288 ± 23 nm) with a low PI value (0.26 ± 0.02) and a negative zeta potential (-22.0 ± 1.1 mV) (see Chapter 6, Section 6.4.2). The EE (92 ± 1%) and LC (4.6 ± 0.1%) of nimesulide- loaded were high (see Chapter 6, Section 6.4.3). The in vitro release profile of nimesulide from SLNs obtained by the dialysis bag technique in phosphate buffered saline (pH 7.4) containing 1% Tween® 20 is shown in Figure 8.4.
100 90 80 70 60 50 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.4 In vitro drug release of nimesulide from SLNs.
From Figure 8.4, the release of nimesulide from SLNs also exhibited a similar biphasic release behaviour which includes
An initial phase of burst release in the first 4 h A sustained release phase (post 4 h). Based on these observations, the nimesulide-loaded SLNs resembled drug-enriched shell type of SLNs.
The nimesulide release data were fitted with release kinetic models and the results deducted from release data fitting are summarised in Table 8.5.
217 Chapter 8 Drug release kinetics of SLNs
Table 8.5 Model fitting of nimesulide release profiles
2 Model Parameters R adjusted AIC MSC
Zero order k0 = 0.09 -0.29 74.6 -1.1
First order k1 = 0.00 0.93 51.1 1.8
Higuchi kH = 2.98 0.71 62.4 0.4
Korsmeyer-Peppas kKP = 12.8 0.88 54.7 1.1 n = 0.28
Hixson-Crowell kHC = 0.00 0.84 57.3 1.1
Hopfenberg kHB = 0.00 0.92 53.1 1.6
Baker-Lonsdale kBL = 0.00 0.92 52.4 1.7
Makoid-Banakar kMB = 2.19 0.98 42.3 2.9 n = 0.66
c = 0.00
Weibull a = 51.98 0.95 49.2 2.1 b = 0.69
Important observations for nimesulide release from SLNs:
Release of nimesulide from SLNs followed first-order kinetics i.e. amount of drug released diminished per unit time Release data fitted well to the Hopfenberg, Baker-Lonsdale and Weibull models 2 (since R adjusted > 0.85) Makoid-Banakar model was the mathematical expression that best described the 2 nimesulide release from SLNs (since R adjusted = 0.98, AIC = 42.3, MSC = 2.9) Release of nimesulide from SLNs followed Fickian-diffusion mechanism (since release exponent n from Korsmeyer-Peppas model < 0.43) Release data for ketoprofen suggested a parabolic curve i.e. an initial burst release (high initial slope) slowing gradually to reach a plateau (slow and sustained release) (since shape parameter b from Weibull model < 1) 63.2% of ketoprofen was released within 5.1 h
218 Chapter 8 Drug release kinetics of SLNs
8.4.2 Summary of release of NSAIDs from SLNs
The release profiles of NSAIDs (Figures 8.1, 8.3 and 8.4, Section 8.4.1) from SLNs show that release of NSAIDs is biphasic. Mathematical modelling of release data suggest that release of drugs was governed by Fickian diffusion. Although their release from SLNs is diffusion-controlled and governed by Fickian transport mechanism, there were subtle differences in this pattern. Figure 8.5 shows an overlay of release profiles of the NSAIDs discussed in this thesis. Table 8.6 gives a comparative summary of model parameters.
100 90 80 70 60 Indomethacin-loaded SLNs Ketoprofen-loaded SLNs 50 Nimesulide-loaded SLNs 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.5 Overlay of drug release profiles of NSAIDs from SLNs.
The results in Figure 8.5 showed that NSAIDs had similar release profiles. The amount of drug release in first 4 h followed the trend: ketoprofen > indomethacin > nimesulide. This initial burst release of drug may be attributed to the release of drug present in the shell and/or adsorbed on the surface of SLNs. This was followed by a slow and sustained release during the remaining period of the assay. Based on these observations, the structure of SLNs loaded NSAIDs can be speculated to resemble that of drug-enriched shell type.
219 Chapter 8 Drug release kinetics of SLNs
Table 8.6 Comparative summary of parameters for release of NSAIDs from SLNs
Parameter Indomethacin- Ketoprofen-loaded Nimesulide-loaded loaded SLNs SLNs SLNs
Model of best fit Makoid-Banakar Makoid-Banakar Makoid-Banakar 2 2 2 R adjusted = 0.99 R adjusted = 0.99 R adjusted = 0.98 AIC = 41.0 AIC = 35.9 AIC = 42.3 MSC = 3.0 MSC = 3.0 MSC = 2.9
Release Fickian diffusion Fickian diffusion Fickian diffusion mechanism n = 0.24 n = 0.15 n = 0.28
Shape of the curve Exponential Exponential Exponential b = 0.68 b = 0.38 b = 0.69
Time required (Td) ~ 3.2 h ~ 2.1 h ~ 5.1 h to release 63.2% of a = 35.82 a = 6.39 a = 51.98 drug
The release exponent n for all SLNs was less than 0.43 indicating that diffusion may be the mechanism of drug release from the SLNs. The scale parameters calculated from the Weibull model suggested that all three profiles were parabolic. Despite these similarities, there were subtle differences amongst them. For example, the time necessary to release 63.2% drug encapsulated within the SLNs was lowest for ketoprofen (~ 2.1 h) followed by indomethacin (~ 3.2 h) and nimesulide (~ 5.1 h).
8.4.3 Drug release studies of SLNs loaded with anti-fungal drugs
The drug-loaded SLNs prepared and characterised in the earlier studies (see Results, Chapter 7 – Section 7.4) were employed to investigate the in vitro release of anti-fungal drugs from the SLNs.
8.4.3.1 Miconazole nitrate-loaded SLNs
The miconazole nitrate-loaded SLNs used for drug release studies had a small diameter (286 ± 3 nm) with a low PI value (0.12 ± 0.02) and a positive zeta potential (20.9 ± 0.8 mV) (see Chapter 7, Section 7.4.1). The EE (87 ± 1%) and LC (4.3 ± 0.1%) of miconazole nitrate-loaded were high (see Chapter 7, Section 7.4.2). The in vitro release profile of
220 Chapter 8 Drug release kinetics of SLNs miconazole nitrate from SLNs obtained by the dialysis bag technique in phosphate buffered saline (pH 7.4) containing 1% Tween® 20 is shown in Figure 8.6.
100 90 80 70 60 50 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.6 In vitro drug release of miconazole nitrate from SLNs.
The miconazole nitrate-loaded SLNs, as observed in Figure 8.6, exhibited a controlled- release profile over 24 h. Similar to other drugs encapsulated in this thesis (see Section 8.4.1), the release of miconazole nitrate was assumed to be biphasic. However, the release of miconazole nitrate from SLNs was slow and sustained (with ~ 50% of encapsulated drug released) after 24 h as compared to fast initial followed by sustained release in case of NSAIDs (with ~ 90% of encapsulated drug released, see Section 8.4.1). A very small amount (~ 20%) of miconazole nitrate was released within 6 h, followed by an additional ~ 30% in the next 18 h. Approximately 50% of drug was retained within the SLNs after 24 h which was recovered by extracting with methanol.
The initial release may be attributed to the presence of unencapsulated (or free) miconazole nitrate, including that adsorbed on the SLN surface or precipitated from the shell of the SLNs. The gradual but an incomplete release of miconazole nitrate from SLNs after 24 h suggests that most of the drug was encapsulated within the lipid core during SLN generation. This resembles to the structure of a drug-enriched core model reported previously by other researchers (Venishetty et al., 2012; Venkateswarlu and
221 Chapter 8 Drug release kinetics of SLNs
Manjunath, 2004). In this type of model, drug crystallises prior to lipid crystallisation. Due to the high partition coefficient (property of drug which makes it more oil-soluble), drug is solubilised in the lipid melt closer to its saturation solubility. Rapid cooling of lipid melt causes super-saturation of drug in the lipid melt. As a result, drug crystallises prior to lipid recrystallisation. Additional cooling causes formation of lipid membrane around the drug-enriched core (Müller et al., 2002b). The controlled-release of miconazole nitrate from SLNs may be attributed to the increased diffusional distance and increased hindrance from the surrounding lipid shell. Similar explanation was reported by Venishetty et al. (2012) for their carvedilol-loaded SLNs.
The drug release data from the miconazole nitrate-loaded SLNs were fitted with release kinetic models and the results obtained from data fitting are summarised in Table 8.7.
Table 8.7 Model fitting of miconazole nitrate release profiles
2 Model Parameters R adjusted AIC MSC
Zero order k0 = 0.04 0.89 44.7 1.8
First order k1 = 0.00 0.97 33.5 3.3
Higuchi kH = 1.20 0.94 40.4 2.4
Korsmeyer-Peppas kKP = 0.36 0.98 30.1 3.6 n = 0.68
Hixson-Crowell kHC = 0.00 0.96 37.7 2.7
Hopfenberg kHB = 0.00 0.97 35.1 3.0
Baker-Lonsdale kBL = 0.00 0.92 42.7 2.1
Makoid-Banakar kMB = 0.06 1.00 15.3 5.5 n = 1.03
c = 0.00
Weibull a = 616.14 0.99 24.1 4.4 b = 0.83
The best fit of release data from miconazole nitrate-loaded SLNs was the Makoid- 2 Banakar model. It exhibited the largest R adjusted, smallest AIC and largest MSC values 2 amongst all the mathematical models fitted to the release data. Considering the R adjusted
222 Chapter 8 Drug release kinetics of SLNs values from Table 8.7, the miconazole nitrate release data seems to fit adequately to the Higuchi model. These results suggested that miconazole nitrate release was diffusion- controlled. In a study by Jose et al. (2014), the release data for resveratrol-loaded SLNs fitted well to the Higuchi model. They concluded that release of resveratrol from SLNs was diffusion-controlled. The release data obtained for miconazole nitrate was also found to fit well to Baker-Lonsdale model. Based on Higuchi model, these findings from Baker- Lonsdale model indicate that diffusion may be one of the major mechanisms of miconazole release (Zuo et al., 2014). The cumulative percent miconazole nitrate 2 released depicted that drug release profile follows first-order kinetics (R adjusted = 0.97) indicating that the amount of drug released depends on the concentration of drug remaining within the device at that point of time.
The release data from miconazole nitrate-loaded SLNs fitted well to the Korsmeyer- 2 Peppas model (since R adjusted = 0.98). Further analysis of Korsmeyer-Peppas model revealed that the release exponent n was 0.68. Based on the n values (0.43 < n < 0.85, Table 8.1), Jose et al. (2014) and Azadi et al. (2013) in their studies on resveratrol-loaded SLNs and methotrexate-loaded chitosan nanogels respectively suggested the mechanism of drug release to be due to non-Fickian diffusion or anomalous transport. The results obtained in this study, therefore, indicate that the release of miconazole nitrate from SLNs was due to anomalous transport or non-Fickian diffusion mechanisms. The release of drug from SLNs occurs mainly by a combination of mechanisms – drug diffusion, water diffusion and/or surface as well as bulk erosion. Good fitting to the Hopfenberg and the Hixson-Crowell models further support findings from Korsmeyer-Peppas model that in addition to diffusional mass transport, erosion may be responsible in release of miconazole nitrate. Hixson-Crowell model and Hopfenberg model are used to describe drug release due to surface and bulk erosion respectively (Zuo et al., 2014).
The release data was also fitted with an empirical model – the Weibull model which is often used to characterize the shape of the release profile and to estimate the time necessary to release ~ 63.2% of drug (i.e. Td). The shape parameter for miconazole nitrate release profile was 0.83 which characterizes the curve as parabolic i.e. one with a steeper initial slope (b < 1) (Costa and Lobo, 2003). The scale parameter was calculated to be ~ 616 which indicate that 63.2% of miconazole nitrate may be predicted to be released after ~ 37 h.
223 Chapter 8 Drug release kinetics of SLNs
8.4.3.2 Econazole nitrate-loaded SLNs
The econazole nitrate-loaded SLNs used for drug release studies had a small size (301 ± 3 nm) with a low PI value (0.13 ± 0.01) and a positive zeta potential (12.4 ± 0.8 mV) (see Chapter 7, Section 7.4.1). The EE (73 ± 5%) and LC (3.6 ± 0.3%) of econazole nitrate- loaded were lower than other SLNs loaded with anti-fungal agents (see Chapter 7, Section 7.4.2). The in vitro release profile of econazole nitrate from SLNs obtained by the dialysis bag technique in phosphate buffered saline (pH 7.4) containing 1% Tween® 20 is shown in Figure 8.7.
100 90 80 70 60 50 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.7 In vitro drug release of econazole nitrate from SLNs.
Similar to miconazole nitrate-loaded SLNs, the econazole nitrate-loaded SLNs exhibited a slow and sustained but an incomplete release of econazole nitrate (Figure 8.7). The release of miconazole nitrate can be assumed to biphasic with
Approximately 20% of econazole nitrate released in 4 h Approximately 55% of econazole nitrate was released at the end of 24 h
Based on these findings, the econazole nitrate-loaded SLNs may resemble drug-enriched core type of SLNs.
224 Chapter 8 Drug release kinetics of SLNs
The drug release data from the econazole nitrate-loaded SLNs were fitted with release models and the results obtained from data fitting are summarised in Table 8.8.
Table 8.8 Model fitting of econazole nitrate release profiles
2 Model Parameters R adjusted AIC MSC
Zero order k0 = 0.05 0.71 55.7 0.8
First order k1 = 0.00 0.90 47.1 1.8
Higuchi kH = 1.51 0.92 45.4 2.1
Korsmeyer-Peppas kKP = 0.99 0.92 46.4 1.9 n = 0.57
Hixson-Crowell kHC = 0.00 0.86 50.2 1.5
Hopfenberg kHB = 0.00 0.89 49.1 1.6
Baker-Lonsdale kBL = 0.00 0.91 46.3 2.0
Makoid-Banakar kMB = 0.04 0.99 31.8 3.8 n = 1.24
c = 0.00
Weibull a = 261.2 0.94 43.5 2.3 b = 0.75
Important observations for release of econazole nitrate from SLNs:
Release of econazole nitrate from SLNs followed first-order kinetics i.e. the amount of drug released diminished per unit time, prominent in first 12 h
2 Econazole nitrate release data fitted adequately to the Higuchi model (R adjusted > 0.85) suggesting that release of drug was diffusion-controlled Good fitting of release data to Baker-Lonsdale and Makoid-Banakar models further supported earlier observations that diffusion may be one of the mechanisms responsible for econazole nitrate release from SLNs Makoid-Banakar model was the mathematical expression that best described the econazole nitrate release from SLNs
225 Chapter 8 Drug release kinetics of SLNs
Korsmeyer-Peppas release exponent (n = 0.57) suggested non-Fickian diffusion i.e. combination of drug diffusion, water diffusion and/or erosion (drug dissolution) in release of econazole nitrate Release data fitted well to the Hixson-Crowell and Hopfenberg models which indicated that surface and bulk erosion (i.e. drug dissolution) may be the other mechanisms of drug release Release data for econazole nitrate suggests a parabolic shape of release profile (since shape parameter b < 1 from Weibull model) 63.2% of econazole nitrate was predicted to be released after ~ 29 h
8.4.3.3 Clotrimazole-loaded SLNs
The clotrimazole-loaded SLNs used for drug release studies had a small diameter (274 ± 2 nm) with a low PI value (0.13 ± 0.01) and a negative zeta potential (-21.3 ± 3.2 mV) (see Chapter 7, Section 7.4.1). The EE (88 ± 1%) and LC (4.4 ± 0.1%) of clotrimazole- loaded were high (see Chapter 7, Section 7.4.2). The in vitro release profile of clotrimazole from SLNs obtained by the dialysis bag technique in phosphate buffered saline (pH 7.4) containing 1% Tween® 20 is shown in Figure 8.8.
100 90 80 70 60 50 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.8 In vitro drug release of clotrimazole from SLNs.
226 Chapter 8 Drug release kinetics of SLNs
The release profile of clotrimazole-loaded SLNs, as observed in Figure 8.8, exhibited a slow and sustained release of clotrimazole. The clotrimazole release was assumed to be biphasic.
The clotrimazole-loaded SLNs show a clotrimazole release of ~ 25% (up to 4 h) Approximately 70% of clotrimazole was released at the end of 24 h
The slow and sustained release profile of clotrimazole suggests that the clotrimazole- loaded SLNs may resemble drug-enriched core type of structure.
The drug release data from the clotrimazole-loaded SLNs were fitted with release kinetic models and the results obtained from data fitting are summarised in Table 8.9.
Table 8.9 Model fitting of clotrimazole release profiles
2 Model Parameters R adjusted AIC MSC
Zero order k0 = 0.05 0.85 51.6 1.5
First order k1 = 0.00 0.96 38.4 3.1
Higuchi kH = 1.65 0.94 45.2 2.3
Korsmeyer-Peppas kKP = 0.68 0.97 39.5 3.0 n = 0.65
Hixson-Crowell kHC = 0.00 0.94 42.6 2.6
Hopfenberg kHB = 0.00 0.95 40.4 2.9
Baker-Lonsdale kBL = 0.00 0.91 48.1 1.9
Makoid-Banakar kMB = 0.40 0.97 39.4 3.0 n = 0.82
c = 0.00
Weibull a = 573.64 0.97 37.9 3.2 b = 0.87
Important observations for release of clotrimazole from SLNs:
Release of clotrimazole from SLNs followed first-order kinetics i.e. the amount of drug released diminished per unit time
227 Chapter 8 Drug release kinetics of SLNs
2 Clotrimazole release data fitted adequately to the Higuchi model (R adjusted > 0.85) suggesting that release of drug was diffusion-controlled Good fitting to the Baker-Lonsdale and Makoid-Banakar models supported role of diffusion in clotrimazole release Korsmeyer-Peppas release exponent (n = 0.65) suggested non-Fickian diffusion i.e. combination of drug diffusion, water diffusion and/or erosion (drug dissolution) in release of clotrimazole The release data fitted well to the Hixson-Crowell and the Hopfenberg models which indicated the role of surface and bulk erosion in clotrimazole release Weibull model was the mathematical expression that best describes the clotrimazole release from SLNs Release data for clotrimazole suggested a parabolic shape of release profile (since shape parameter b < 1) 63.2% of clotrimazole was predicted to be released after ~ 25 h
8.4.4 Summary of release of anti-fungal drugs from SLNs
The release profiles of anti-fungal drugs (Figures 8.6, 8.7 and 8.8, Section 8.4.3) from SLNs show that the release is slow and sustained but incomplete within the time-scale (1 day) of the experiment. Mathematical modelling of the release data suggested that their release from SLNs was governed by non-Fickian transport mechanism i.e. both diffusion- and dissolution-controlled. Figure 8.9 shows an overlay of release profiles of the anti-fungal drugs discussed in this thesis.
The results in Figure 8.9 show that anti-fungal drugs have similar release profiles. The amount of drug release in first hour follows the trend: clotrimazole > econazole nitrate > miconazole nitrate. The slow, sustained but an incomplete release of anti-fungal drugs from SLNs suggested that the SLNs encapsulated with these drugs had a drug-enriched core structure.
228 Chapter 8 Drug release kinetics of SLNs
100 90 80 70 60 Clotrimazole-loaded SLNs Miconazole 50 nitrate-loaded SLNs 40 Econazole nitrate-loaded SLNs 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.9 Overlay of drug release profiles of anti-fungal drugs from SLNs.
Table 8.10 gives a comparative summary of some of subtle differences in model parameters obtained after mathematical modelling of release data of anti-fungal drugs used in this thesis. The release exponent n for all SLNs was between 0.43 and 0.85 indicating that non-Fickian diffusion may be the mechanism of drug release from the SLNs. The scale parameters calculated from the Weibull model suggested that all three profiles were parabolic. Despite these similarities, there were subtle differences amongst them. For example, the time necessary to release 63.2% drug encapsulated within the SLNs was lowest for clotrimazole (~ 25 h) followed by econazole nitrate (~ 29 h) and miconazole nitrate (~ 37 h).
229 Chapter 8 Drug release kinetics of SLNs
Table 8.10 Comparative summary of parameters for release of anti-fungal drugs from SLNs
Parameter Miconazole nitrate- Econazole nitrate- Clotrimazole- loaded SLNs loaded SLNs loaded SLNs
Model of best fit Makoid-Banakar Makoid-Banakar Weibull 2 2 2 R adjusted = 1.00 R adjusted = 0.99 R adjusted = 0.97 AIC = 15.3 AIC = 31.8 AIC = 37.9 MSC = 5.5 MSC = 3.8 MSC = 3.2
Release Non-Fickian Non-Fickian Non-Fickian mechanism diffusion diffusion diffusion n = 0.68 n = 0.57 n = 0.65
Shape of the curve Exponential Exponential Exponential b = 0.83 b = 0.75 b = 0.87
Time required (Td) ~ 37 h ~ 29 h ~ 25 h to release 63.2% of a = 616.14 a = 261.20 a = 573.64 drug (predicted)
8.4.5 Drug release comparison
The results in Section 8.4.2 and 8.4.4 indicated that two types of drug release profiles were observed for SLNs prepared in this thesis:
An initial burst release followed by a sustained release of drugs – in case of NSAIDs A slow, sustained but an incomplete release of drugs – in case of anti-fungal drugs
To further elucidate the difference between the release profiles, a representative from each class of drugs – indomethacin (from NSAIDs) and miconazole nitrate (from anti- fungal drugs) was selected. These formulations were selected as representative from their respective groups based on their particle sizes and encapsulation efficiency as both are similar for the two formulations. The difference in the release pattern is evident in Figure 8.10 which is an overlay of release profiles of indomethacin and miconazole nitrate.
230 Chapter 8 Drug release kinetics of SLNs
100 90 80 70 60 Indomethacin-loaded SLNs Miconazole 50 nitrate-loaded SLNs 40 30
Cumulative drug release drug Cumulative (%) 20 10 0 0 5 10 15 20 25 Time (h)
Figure 8.10 Comparison of release of indomethacin (acidic) and miconazole nitrate (basic) from SLNs.
This may be due to the difference in physicochemical properties of the drugs:
The NSAIDs are weakly acidic (due to presence of carboxylic acid functional groups in indomethacin and ketoprofen) or neutral (due to presence of sulphonamide functional group in nimesulide) and have low partition coefficients The anti-fungal drugs are basic (due to presence of imidazole ring in clotrimazole, miconazole nitrate and econazole nitrate) and have high partition coefficients
This behaviour of SLNs may be attributed to the location of the drug within the SLNs. The SLNs encapsulated with NSAIDs were suggested to resemble the drug-enriched shell type of structure. In contrast, SLNs encapsulated with anti-fungal drugs were suggested to resemble drug-enriched core type of structure. Due to the difference in their partition coefficients, drugs with lower partition coefficients (i.e. NSAIDs in this case) may probably, in perspective, form the shell (i.e. drug-enriched shell model) and the drugs with higher partition coefficients (i.e. anti-fungal drugs in this drugs) should be easily solubilised in the molten lipid and crystallise within the lipid core (i.e. drug- enriched core model). This may influence the release of drugs from the SLNs. Interestingly, the release of NSAIDs was found to be governed by a Fickian transport
231 Chapter 8 Drug release kinetics of SLNs mechanism and release of anti-fungal drugs was shown to be controlled by a non-Fickian transport mechanism. These findings support the hypothesis that the NSAIDs that are primarily present in the shell are released as a “burst” and are diffusion-controlled. In contrast, anti-fungal drugs that are predominantly present in the lipid core are controlled by dissolution and diffusion.
Table 8.11 summarises the results obtained after profile comparison by model- independent approaches. The indomethacin release data was considered to be the “reference” and miconazole nitrate data was considered to be the “test” formulations. The comparison was done by determination of similarity and difference factors, Rescigno indices and Bootstrap f2 method. Such methods of profile comparison are often used to compare a “changed” form to an already “approved” product and rarely used to compare release profiles of different drugs from similar drug carriers, as in this study. Hence, the difference should be seen as a proof-of-concept and not as an absolute difference.
Table 8.11 Comparison of release profiles of indomethacin (reference) and miconazole nitrate (test) by model-independent approaches
Parameter Value Accept or Reject
Difference factor (f1) 68.9 Reject Similarity factor (f2) 16.7
Rescigno index (ξ1) 0.41 Reject Rescigno index (ξ2) 0.43
Bootstrap f2 16.706 (16.156 – 17.308) Reject
The difference factor f1 is a measure of the relative error between two release profiles, while the similarity factor f2 is a measure of the similarity in the percent of drug release between two release profiles. For the profiles to be considered “similar”, f1 should be less than 15 (i.e. f1 ∈ [0, 15]) and f2 should be greater than 50 (i.e. f2 ∈ [50, 100]) according to current Food and Drug Administration guidelines for comparison of “changed” and “approved” products (FDA, 1997). The results in Table 8.11 show that none of these criteria are met which is an indication that the release profiles of indomethacin and miconazole nitrate from SLNs are dissimilar.
232 Chapter 8 Drug release kinetics of SLNs
The results from difference and similarity factors were consistent with the results obtained by another pairwise procedures of profile comparison; determination of Rescigno indices. The Rescigno indices take on values from zero (indicating no difference between the reference and test formulations) to one (indicating complete release from one formulation before the other begins to release the drug). The results (Table 8.11) indicate that the profiles were not similar (since the Rescigno indices were ~ 0.4 > 0).
The bootstrap f2 method was used to compare the release profiles. The release profiles are similar, at a 0.05 significance level, if the 90% lower confidence limit of f2 is greater than 50. The results (Table 8.11) indicate that the 90% lower confidence limit (i.e. 16.156) is less than 50, and therefore, the release profiles are dissimilar.
All these findings suggest that the release profiles of indomethacin and miconazole nitrate are dissimilar.
233 Chapter 8 Drug release kinetics of SLNs
8.5 Conclusions
The release of drugs from drug-loaded SLNs was investigated in this chapter using the most commonly employed technique – the dialysis bag technique. The drug-loaded SLNs were found to exhibit biphasic release behaviour; phase I being initial release of free drug molecules and/or drug molecules adsorbed on the SLN surface and, phase II being release of encapsulated drug molecules. The SLNs loaded with NSAIDs (i.e. indomethacin, ketoprofen and nimesulide) exhibited a high initial burst release followed by a sustained release of drugs. Such drug release patterns are indicative of drug-enriched shell type structures. The release patterns of these drugs were found to be governed by Fickian diffusion. The drug release data fitted most suitably to the Makoid-Banakar model.
In contrast, the SLNs loaded with anti-fungal drugs (i.e. miconazole nitrate, econazole nitrate and clotrimazole) exhibited a slow and sustained but an incomplete release of drugs after 24 h. Such drug release patterns are indicative of drug-enriched core type structures. Although the release of drugs followed non-Fickian diffusion, the drug release data fitted very well to the Makoid-Banakar model (exception clotrimazole-loaded SLNs which fitted very well to the Weibull model) like SLNs loaded with non-steroidal anti- inflammatory drugs.
The difference in the drug release patterns was attributed to the difference in the chemical structures of the drugs and/or location of the drug within the SLNs. The drug release patterns of one representative drug from each drug class was compared using pairwise procedures (determination of similarity and difference factors and determination of
Rescigno indices) and the bootstrap f2 method. The release of these two drugs was found to be dissimilar by these methods. Further investigation to confirm the drug-enriched shell or the drug-enriched core structure may be necessary to ascertain the position of the drug in the SLNs. The drug release data fitted most suitably to the Makoid-Banakar model.
234 Chapter 9 Cellular uptake of SLNs 9
An Investigation of the Uptake Mechanism and Pathway of SLNs Used as Intracellular Drug Transporters
235 Chapter 9 Cellular uptake of SLNs
Abstract
An understanding of transport of drug carriers, as much as the drug molecule itself, is an important consideration for improving drug absorption and bioavailability. The mechanisms by which drug carriers enter target cells can differ depending on their size, surface properties and components. Solid lipid nanoparticles (SLNs) are the drug carriers of interest in this thesis. They are known to breach the cell-membrane barrier and have been actively sought to transport biomolecules such as drugs, human gene products and proteins into cells. In this study, SLNs were prepared by the microwave-assisted microemulsion technique and had a small size (< 300 nm) and negative zeta potential (~ -20 mV). The aim of this work was to systematically analyse the cellular internalisation mechanisms and pathways for SLNs in human lung A549 and cervical HeLa epithelial cell lines using pharmacologic inhibitors (sucrose, potassium-free buffer, filipin and cytochalasin B) of specific pathways. Imaging techniques and flow cell cytometry were used to assess the cellular uptake of fluorescent SLNs using Rhodamine 123 as a fluorescent probe. The findings suggested that cell uptake of SLNs is an energy- dependent process and the endocytosis of SLNs is mainly dependent on clathrin- mediated pathways. The establishment of entry mechanism of SLNs is of fundamental importance for future facilitation of SLNs as biological or drug carriers.
236 Chapter 9 Cellular uptake of SLNs
9.1 Introduction
In previous chapters, a microwave-assisted microemulsion method used in the production of SLNs was described. An optimised composition scheme was selected for preparation of drug-loaded SLNs. The SLNs were found to be suitable for encapsulation of drug substances from at least three drug categories investigated in this thesis – antibacterial, antifungal and non-steroidal anti-inflammatory drugs. Extensive particle characterisation indicated the colloidal nature and high encapsulation capabilities of SLNs. These findings indicate that SLNs may be looked upon as potential drug carriers. In this chapter, the mechanisms and pathways that may be involved in cellular internalisation of SLNs are investigated.
One of the major considerations in the development of SLNs as drug carriers in disease therapy is to ensure that the SLNs can easily enter target cells. The transport of most nanomaterials into the cells depends upon the characteristics of nanoparticles (such as particle structure, particle shape, particle size and surface charge, particle hydrophobicity and coating material) and the interactions between the cells and the nanoparticles (Sahay et al., 2010).
Traversal through numerous barriers, such as epithelial tissue, the natural biological barrier, is one of the major challenges in drug development and delivery (Peer et al., 2007). The epithelial tissue is a protective lining on major organs of the body that not only hinders absorption of exogenous substances but also protects against microbial invasion (Chai et al., 2014). The epithelial tissue is extensively distributed in the gastrointestinal tract (GIT) and forms the biological barrier that dictates the passage of drug molecules across the cell membrane when administered orally. Any reduced absorption negatively affects the bioavailability and therapeutic efficacy of drugs. Such behaviour is more pronounced in drugs with limited aqueous solubility and membrane permeability (Pouton, 2006). These challenges are particularly important in drug development sciences, and presents limitations to their satisfactory and irrefutable exploitation.
Transport through the cell membranes is critical for the SLNs to be able to perform their therapeutic functions in vivo. The cell membrane is a biological barrier that segregates the intracellular milieu (cytoplasm) from the extracellular milieu. It is a selectively permeable membrane that maintains the intracellular homeostasis by regulating the
237 Chapter 9 Cellular uptake of SLNs transport of exogenous materials into the cells (i.e. by the process termed “cellular uptake”) (Zhao et al., 2011). The application of nanostructured drug carriers, such as SLNs, is looked upon as one of the most potent approaches to overcome these barrier difficulties (Alonso, 2004).
Our basic knowledge of the biological fate of SLNs, however, lacks a coherent understanding of the underlying mechanisms involved in their cellular uptake. Hence, an investigation into the mechanisms of cellular uptake of SLNs is considered critical. Previous studies have investigated SLN uptake by different cell types (Miglietta et al., 2000; Sun et al., 2013; Teskač and Kristl, 2010; Yuan et al., 2008). However, few studies have investigated the mechanism of cellular entry of SLNs into human cells (Chai et al., 2014; Martins et al., 2012a; Xu et al., 2009;). Furthermore, these studies have focused on human hepatocellular carcinoma, glioma and macrophage cell lines and canine epithelial cells. To the best of the author’s knowledge, there is lack of knowledge about the transport mechanism for uptake of SLNs by human epithelial cells.
The cellular uptake of exogenous substances can be accelerated by overcoming the membrane barrier through multiple mechanisms which can be categorised into endocytic or non-endocytic. Non-endocytic mechanisms often allow trafficking of molecules either by Fickian diffusion (i.e. passive diffusion of small molecules such as oxygen, carbon dioxide and amino acids) or the action of integral proteins and ion channels located in the cell membrane for sugars and ions (Verma and Stellacci, 2010). Macromolecules including nanoparticles and other molecular assemblies, however, can traverse the membrane in small membrane-enclosed sacs - “vesicles” derived by invagination or “pinching off” segments of membranes. This process is called endocytosis (Yan et al., 2012; Conner and Schmid, 2003).
Endocytosis is an energetically driven process fundamentally used by cells to internalise molecules and macromolecules. Endocytosis is not limited to uptake of nutrients alone. It plays a key role in several other biological functions including surface receptor regulation (including antigen presentation), control of several signalling cascades, mitosis and cell motility. Bacteria and virus enter human cells via endocytosis (Canton and Battaglia, 2012).
Endocytosis is responsible for intracellular trafficking of most engineered nanomaterials including liposomes, polymeric micelles, polymeric nanoparticles, dendrimers and
238 Chapter 9 Cellular uptake of SLNs carbon nanotubes (Chou et al., 2011). Depending on the cell type and properties of nanomaterials, endocytosis may occur either by phagocytosis (i.e. cellular uptake of large particles) or by pinocytosis (i.e. cellular uptake of solutes and fluids). Phagocytosis is performed by a few specialised cells such as macrophages, monocytes, neutrophils, mast cells and dendritic cells. These are professional phagocytic cells and can engulf particles as large as 5-10 µm (Canton and Battaglia, 2012). By contrast, pinocytosis is a general entry pathway that occurs in all cells, and by at least four basic mechanisms: clathrin- mediated endocytosis, caveolae-mediated endocytosis, clathrin- and caveolae- independent endocytosis and macropinocytosis. These four mechanisms were classified on the basis of proteins and lipids involved in the actual uptake pathway (Canton and Battaglia, 2012; Conner and Schmid, 2003; Sahay et al., 2010), and is the preferred classification system used here. Other systems of classification based on material- membrane interactions have also been proposed. The origin and the function of the cell type dictate the mechanism of pinocytosis involved in the cellular uptake (Sahay et al., 2010). There is no specific size cut-off for molecules which can gain entry via pinocytosis, however, it has been suggested that particles smaller than 5 µm are internalised by this mechanism (Huang et al., 2002).
Clathrin-mediated endocytosis exists in all mammalian cells. Uptake of essential nutrients such as cholesterol and iron is carried out by clathrin-mediated endocytosis (Doherty and McMahon, 2009). Caveolae-mediated endocytosis of extracellular substances is dependent on the presence of cholesterol domains on the cellular membranes. Due to the abundance of caveolae (rich in cholesterol) in selected types of mammalian cells such as adipocytes, fibroblasts, endothelial cells and adipocytes, caveolae-mediated endocytosis is the preferred route of entry into these cells (Kam et al., 2006). Macropinocytosis may be present in any mammalian cell type with a few exceptions such as macrophages and brain microvessel endothelial cells (Mercer and Helenius, 2012).
In this chapter, a systematic investigation of mechanism and pathway for cellular uptake of SLNs in human epithelial cell lines is presented. The deciphering of mechanism of cellular uptake of SLNs was done by exclusion of specific endocytic pathway using pharmacologic inhibitors. Figure 9.1 depicts a schematic diagram of major endocytic pathways that may be involved in cellular uptake of nanomaterials (and possibly SLNs).
239 Chapter 9 Cellular uptake of SLNs
Figure 9.1 Major endocytic pathways of uptake in cells (reprinted with permission from Conner and Schmid, 2003)
Rhodamine 123 (R123) was used as a model drug and fluorescent probe in this study. R123 [6-Amino-9- (2-methoxycarbonyl-phenyl)-xanthen-3-ylidene-ammonium] is a lipophilic cationic fluorescent dye (Figure 9.2) with high quantum yield. R123 has been previously used to stain mitochondria (it accumulates into the mitochondria due to the negatively charged membrane potential across the inner membrane of mitochondria) (Jouan et al., 2014). Additionally, commercial availability, low cost and non-invasive detection of R123 makes it a good biological tracer. Another advantage of using R123 in imaging studies is that it does not interfere with underlying metabolic processes (Jouan et al., 2014).
H2N O NH2
COOCH3
Figure 9.2 Chemical structure of Rhodamine 123
240 Chapter 9 Cellular uptake of SLNs
9.2 Chapter Aims
The main objective of this chapter was to investigate if SLNs enter human epithelial cells, and to systematically decipher the mechanism and pathway of their traversal into epithelial cells.
The specific aims of this chapter:
To encapsulate a fluorescent probe (i.e. Rhodamine 123) and characterise the SLNs prior to cell culture studies. To evaluate the cytotoxicity of SLNs on human epithelial cell lines, A549 and HeLa. To investigate the energy-dependency of epithelial cells in cellular uptake of SLNs.. To decipher the mechanism of cellular uptake of SLNs by flow cell cytometry and imaging techniques.
241 Chapter 9 Cellular uptake of SLNs
9.3 Methods
9.3.1 Preparation of Solid Lipid Nanoparticles
SLNs were prepared by the novel microwave-assisted microemulsion technique described earlier (see Section 3.3.1). In brief, a mixture of stearic acid (100 mg), Tween® 20 (150 µl) and water (1.35 mL) were heated above the melting point of stearic acid in a microwave reactor tube with constant stirring using a microwave synthesiser to produce an o/w microemulsion. The microwave reaction temperature was set to 80C with a variable microwave power not exceeding 18 W and the reaction was maintained at the set temperature for 10 minutes. The hot o/w microemulsion from the microwave was dispersed immediately into cold water (50 mL, 2 - 4 C) under constant magnetic stirring to generate SLN dispersions. For R123-loaded SLNs, referred to as “fluorescent SLNs” henceforth, R123 (0.03%) was added to the mixture of stearic acid and Tween® 20 before the mixture was subjected to microwave heating. The SLNs without R123 are referred to as non-fluorescent SLNs.
9.3.2 Particle Characterisation
Determination of hydrodynamic diameter and polydispersity (PI) index using DLS
The intensity weighted mean hydrodynamic diameter and the PI of the SLN dispersions were then determined DLS at 25C as described in Section 3.3.2.1.
Determination of particle diameter using LD
In addition to DLS, particle size measurement was also conducted by LD at 25C as described in Section 3.3.2.2.
Zeta potential measurements
The zeta potential measurements were carried out as described in Section 3.3.2.3. The zeta potential of the SLN dispersions was determined by measurement of the electrophoretic mobility. Conversion of the electrophoretic mobility to zeta potential was performed on “Zeta for Windows”.
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9.3.3 Crystallinity of SLNs
The crystallinity of SLNs was investigated from their thermal and diffraction characteristics. Thermal behaviour of SLNs was studied by DSC analysis of bulk stearic acid and the SLNs. The DSC analysis was performed as described in Section 3.3.7. The melting enthalpy (ΔH) was obtained by integration of the area under the transition peak and crystallinity index (CI) was determined by Equation 9.1,
∆HSLN CI (%) = × 100 ∆Hbulk lipid × Concentration of lipid phase (%) … Equation 9.1
The X-ray diffraction (XRD) analysis was performed as described in Section 3.3.8. The XRD data were analysed in conjunction to DSC data to investigate the changes in crystallinity of stearic acid used in preparation of SLNs.
9.3.4 Evaluation of cell viability of SLN dispersions
In addition to human lung A549 epithelial cells used in previous chapters, another human epithelial cells - cervical HeLa cells – were used in this work. The investigation of cell viability was performed using MTT assay as described in Section 3.3.12.
In brief, the cells were seeded into 96-well plates at a seeding density of 2.5 × 104 cells per well in complete DMEM (200 L) and allowed to attach for 24 h at 37C in a 5%
CO2 atmosphere. Following 24 h incubation, the media were aspirated, followed by addition of non-fluorescent and fluorescent SLN dispersions (100 L) diluted in DMEM (two- fold dilutions, ranging from 3.9 - 1000 g/mL). An equal volume (100 L) of complete DMEM was then added to each well and incubated for 24 h at 37C in a 5%
CO2 atmosphere. A 0.1% Triton-X 100 solution was taken as the positive control. The untreated cells (without any sample) were considered as a negative control. Following 24 h incubation, samples (including medium) were aspirated and 170 L MTT solution (5 mg/mL MTT in sterile PBS, pH 7.4) was added to the DMEM in the well (final concentration of 0.32 mg/mL) and incubated for 2 h at 37C in a 5% CO2 atmosphere. The medium with MTT solution was discarded and formazan crystals were solubilised using 150 L DMSO. The plates were further incubated for 15 min at room temperature and in the dark. Absorbance at 570 nm (directly proportional to cellular metabolism) was
243 Chapter 9 Cellular uptake of SLNs measured using a POLARstar microplate reader (Omega, BMG LabTech). Cell viability compared to untreated cells (control) was calculated using Equation 9.2,
Absorbance of treated cells Cell viability (%) = × 100 Absorbance of control cells … Equation 9.2
According to ISO 10993-5, a reduction of cell viability by more than 30% is considered a cytotoxic effect (ISO, 2009). A stricter criterion to define cytotoxicity was used for the current studies where cell viability values greater than 80% were considered to indicate suitable viability (non-toxic), values between 20% and 80% were considered to have reduced viability, and values below 20% indicated complete loss of viability (Petersen et al, 2011). The experiment was performed in triplicate (with each sample measured thrice). The results are presented as mean values with corresponding standard deviation (SD).
9.3.5 Fluorescence Microscopy
The cellular uptake of SLNs by epithelial cells was investigated by fluorescence microscopy. The fluorescent SLNs were used for this investigation. Centrifugal ultrafiltration using centrifugal filter units (Amicon® Ultra-4, 10 kDa molecular weight cut-off, Millipore, Germany) was carried out to separate the fluorescent SLNs from unencapsulated R123.
The cells were seeded into 8-well plates at a seeding density of 1 × 105 cells per well in complete DMEM medium (300 µL) and incubated for 24 h at 37C in a 5% CO2 atmosphere to allow them to adhere. Adherent cells were then incubated with fluorescent SLNs (100 µg/mL) diluted in DMEM medium for 2 h. The cells were washed with Dulbecco’s PBS, and stained with CellMask® Deep Red solution diluted in DMEM (300 µL, excitation/emission maxima ~ 647/659 nm) for 10 min at 37C. The cells were washed with Dulbecco’s PBS to remove excess stain and fixed in 4% (w/v) paraformaldehyde solution at 37C. The cells were then imaged with a Nikon Eclipse 50i fluorescence microscope equipped with digital camera and processed using ImagePro® software. The wavelengths selected were suitable for imaging of R123 (470 - 490 nm, green) and CellMask® Deep Red (520 - 550 nm, red). The cells incubated with non- fluorescent (i.e. R123-free) SLNs were used as controls to test the inherent fluorescence
244 Chapter 9 Cellular uptake of SLNs due to SLNs. Care was taken to protect the stained cells from light by covering the plates with aluminium sheets so as to avoid fluorescent quenching, if any.
9.3.6 Fluorescence-assisted cell sorting (FACS) or flow cell cytometry
The cellular uptake of SLNs was further investigated using FACS, commonly referred to as flow cell cytometry, using a BD FACSAria™ II flow cell cytometer (BD Biosciences, USA). The fluorescent SLNs were used for this investigation. Centrifugal ultrafiltration using centrifugal filter units (Amicon® Ultra-4, 10 kDa molecular weight cut-off, Millipore, Germany) was carried out to separate the fluorescent SLNs from unencapsulated R123.
The cells were seeded into 12-well plates at a seeding density of 1 × 106 cells per well in complete DMEM medium and allowed to adhere for 24 h at 37C in a 5% CO2 atmosphere. The adherent cells were then incubated with fluorescent SLNs (100 µg/mL) for 2 h at 37C in a 5% CO2 atmosphere. Upon incubation, the cells were washed with Dulbecco’s PBS. Adherent cells were detached from the surface by trypsinisation and re- suspended in ice cold Dulbecco’s PBS. Propidium iodide (10 mM, 0.2%) was added to the cell suspension and immediately analysed with BD FACSAria™ II flow cell cytometer using a 488 nm laser for excitation of R123. A total of 10000 events were counted, gating on epithelial cells using forward scatter/side scatter (FSC/SSC) plots to exclude the debris and non-internalised SLNs and was read at 488 nm. Cells that were stained with propidium iodide (corresponding to naturally occurring dead cells) were excluded from the data analysis. The FACS data were further analysed to remove the events associated with non-fluorescent SLNs and untreated cells (controls used in this study). From the filtered data, the mean fluorescence intensity of cells exposed to the various formulations was determined using a BD FACSDiva software package (version 6.1.3).
9.3.7 Confocal Laser Scanning Microscopy (CLSM)
The cellular uptake of SLNs by cells was also investigated by CLSM. The cells were treated as described in Section 9.3.5 for fluorescence microscopy. Briefly, cells were seeded in 8- well plates at a density of 1 × 105 cells per well in complete DMEM medium
245 Chapter 9 Cellular uptake of SLNs and allowed to adhere for 24 h at 37C in a 5% CO2 atmosphere. The adherent cells were incubated with fluorescent SLNs diluted in DMEM medium (100 µg/mL) for 2 h. The cells were then washed with Dulbecco’s PBS and simultaneously stained with CellMask® Deep Red solution (excitation/emission maxima ~ 647/659 nm) and DAPI (excitation/emission maxima ∼ 358/461 nm) diluted in DMEM for 10 minutes at 37 C. The cells were washed with Dulbecco’s PBS to remove excess stain and fixed in 4% (w/w) paraformaldehyde solution at 37C. The cells were then imaged with a FLUOVIEW FV10i confocal laser scanning microscope system equipped with digital camera and processed using FluoView FV software package (version 7.0). The wavelengths suitable for imaging of R123 (473 nm, green), DAPI (365-375 nm, blue) and CellMask® Deep Red (649 nm, red) were selected for this study. Care was taken not to expose the plates to light in order to prevent fluorescent quenching.
9.3.8 Investigation of SLN uptake by human epithelial cells
The cellular incubations with the fluorescent SLNs were carried out as described above with some modifications (see below) to carry out a systematic investigation of cellular uptake by epithelial cells. The cells incubated with fluorescent SLNs at 37C in a CO2 atmosphere served as positive control in these experiments.
Inhibition of endocytosis
In order to evaluate the role of endocytosis, cellular incubations were carried out at low temperature (4C) instead of the regular incubation temperature of 37C. In addition to incubation at 4C, the cells were also pre-incubated in ATP-depleted medium. Prior to regular incubation for 2 h, the cells were incubated in PBS supplemented with sodium azide (10 mM) and deoxy-D-glucose (50 mM) to deprive cells of ATP.
To elucidate exact endocytic pathway of SLN uptake, cells were pre-incubated with specific pharmacologic inhibitors (Table 9.1).
Inhibition of clathrin-mediated endocytosis
In order to inhibit clathrin-mediated endocytosis of SLNs, the cells were pre-incubated in a hypertonic solution or a potassium-depleted buffer for 30 min followed by regular incubation of cells with fluorescent SLNs for 2 h at 37C.
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Inhibition of caveolae-mediated endocytosis
The cells were pre-incubated with specific drug solutions (i.e. DMEM medium supplemented with fipilin III) for 30 min prior to their incubation with fluorescent SLNs for 2 h at 37C.
Inhibition of macropinocytosis
The inhibition of SLN uptake by macropinocytosis was achieved by incubating the cells in DMEM medium supplemented with cytochalasin B for 30 min followed by regular incubation with fluorescent SLNs for 2 h at 37C.
Table 9.1 Pharmacologic inhibitors of specific endocytosis pathway
Pathway Treatment Pharmacologic inhibitor Concentration
Clathrin-mediated Hypertonic Sucrose 0.45 M endocytosis treatment
Potassium- Potassium-free buffer which depletion includes - NaCl 0.14 M CaCl2 1 mM MgCl2 1 mM HEPES 20 mM D-glucose 6 mM
Caveolae-mediated Filipin Filipin III 7.64 µM endocytosis treatment
Macropinocytosis Cytochalasin Cytochalasin B 20.85 µM and phagocytosis treatment
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9.4 Results and Discussion
9.4.1 Preparation and Characterisation of SLNs
The SLNs were produced by the microemulsion technique and characterised in terms of effective mean diameter, polydispersity index and zeta potential. Fluorescent SLNs (i.e. R123-loaded SLNs) with a mean diameter of ~ 275 nm, low polydispersity index of ~ 0.20 and with zeta potential values of approximately ~ 18 mV were produced (Table 9.2). Non -fluorescent SLNs were also produced to evaluate the influence of incorporation of the fluorescent probe R123 on SLN characteristics. Non-fluorescent SLNs with a mean diameter of ~ 250 nm, low polydispersity index of ~0.17 and with zeta potential values of approximately -25 mV were produced (Table 9.2). Fluorescent SLNs had a slightly increased diameter and a slightly decreased zeta potential. These results indicated that incorporation of R123 had minimal influence on the characteristics of SLNs.
Table 9.2 Physical characteristics of SLNs used in cellular uptake studies
SLNs Particle Size Measurements Zeta potential DLS LD (mV)
Diameter PI d(0.5) (nm) d(0.9) (nm) (nm)
Non-fluorescent 253 ± 12 0.17 ± 0.05 152.6 ± 0.1 260.6 ± 0.6 -25.6 ± 1.2 SLNs
Fluorescent 273 ± 18 0.19 ± 0.05 157.1 ± 0.3 286.3 ± 4.3 -18.3 ± 1.1 SLNs
The size of nanomaterials has been significantly found to influence their cellular uptake. The SLNs generated in this study have a small size (< 300 nm) that seems to be suitable for drug delivery use, as they are likely to be taken up easily by cells through endocytosis (Canton and Battaglia, 2012). Many researchers have postulated the importance of having a small size for successful delivery of cargos via the endocytic pathway (Blechinger et al., 2013; de Mendoza et al., 2011; Li et al., 2014; Verma and Stellacci, 2010; Vranic et al., 2013).
The particle sizes determined by LD were in agreement with the DLS data (Table 9.2). The d(0.9) was < 300 nm for both non-fluorescent and fluorescent SLNs used in this
248 Chapter 9 Cellular uptake of SLNs study. The results obtained by these techniques rely on different measurement principles, and hence differences in results are not unexpected. DLS determines the particle size in terms of hydrodynamic diameters which are usually larger than the actual solid diameter of the spherical particles (Jores et al., 2004). The LD measurements are more applicable for larger particles (> 700 nm), and hence particle sizing analysis solely on the basis of DLS seems insufficient (Noack et al., 2012).
The surface charge of the SLNs is an often quoted, important characteristic (Keck et al., 2014b), however it is more appropriate to measure the associated potential, as this is often a major controller of the stability behaviour as particles approach each other (Kuo and Ko, 2013). The SLNs produced in this study had a slight negative zeta potential (Table 2). Dispersions with zeta potential values of ~ |20| mV are expected to be physically stable (Mitri et al., 2011), especially when there is likely to be some steric- like forces also operative (see Chapter 10). The negative zeta potential may be attributed to the functional groups on the surface of the SLNs (i.e. presence of residual stearic acid on the lipid nanoparticle surface) or due to the dissociation of stearic acid in the aqueous dispersion medium. Similar attribution of zeta potential has been previously reported (Alex et al., 2011). The incorporation of R123 into the SLNs causes a slight reduction in the magnitude of their zeta potential indicating that whilst R123 may displace some of the charged groups at the surface, the effect is minimal and most of the R123 is probably internalised.
Charged functional groups on nanoparticle play an important role in cell interactions. Neutral functional groups avoid any unwanted nanoparticle-biological interaction. The nanoparticles produced in this study are negatively charged, and their interaction with the negatively charged cell membrane may be electrostatically unfavourable. However, there is evidence that shows cellular uptake of negatively charged particles despite such unfavourable interactions (Cho et al., 2009). These results also indicate that despite being negatively charged, SLNs interact with cells which are considered unfavourable due to the negative charges on the cell membrane. This may be due to specific binding and/or non-specific binding on clusters of cationic sites on cell membranes which may later be engulfed by the cells by endocytosis (Verma and Stellacci, 2010). It may also indicate large “patches” of uncharged surface corresponding to non-ionic surfactant, possibly micellar adsorption.
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9.4.2 Crystallinity of SLNs
The thermal behaviour of bulk stearic acid and stearic acid-based SLNs was assessed by DSC. The DSC studies were performed to investigate the solid nature and crystallinity of the SLNs (Das et al., 2012). The DSC profile and the DSC data computed from these curves are depicted in Figure 9.3 (a) and Table 9.3, respectively.
A single thermal transition was observed when bulk stearic acid was heated from 25C to 80C. The endothermic peak observed at 71.5C corresponds to the melting point of stearic acid. Similarly, a single thermal transition was detected with both non-fluorescent and fluorescent SLNs. Irrespective of whether or not R123 was encapsulated, the thermal transition was observed at similar temperatures (Figure 9.3). These results indicate that the loading of R123 into the SLNs has no influence on the crystallinity and the solid nature of the SLNs.
The single thermal transitions corresponding to melting transitions in DSC profiles were, however, shifted to a lower temperature compared to the melting transition of stearic acid (Table 9.3). This can be explained by the presence of surfactant molecules on the surface of SLNs, the “Gibbs-Thomson” effect and the high surface energy associated with the nano-sized SLNs (Hou et al., 2003). A similar effect has been previously reported in lipid nanoparticles (Kovačević et al., 2014).
Table 9.3 DSC analysis of SLNs used in cellular uptake studies
Sample Tonset (C) Tmax (C) ΔH (J/g) CI (%)
Stearic acid 66.9 71.5 165.5 100
Non-fluorescent SLNs 54.5 64.4 59.6 95
Fluorescent SLNs 60.5 64.1 47.22 76
The presence of a melting endotherm in the DSC curve is an indication of the solid state of SLNs generated in this study. The melting onset temperature and the melting temperature are above 40C (Table 9.3) which supports the assumption that these drug carriers can remain in the solid state at ambient temperature and the experimental conditions (similar to body temperature) used in these studies. Similar findings have been reported in the literature (de Souza et al., 2012).
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(a)
i. Stearic acid Non-fluorescent SLNs ii. Fluorescent SLNs iii.
64.4
64.1 Heatflow (W/g)
71.5
25 30 35 40 45 50 55 60 65 70 75 80 Temperature (°C)
(b)
Bulk stearic acid Non-fluorescent SLNs 21.7 Fluorescent SLNs
6.7 24.3 20.6 11.1 36.4
i. Intensity(AU) ii.
iii.
5 10 15 20 25 30 35 40 2
Figure 9.3 Crystallinity of SLNs conducted using (a) Differential scanning calorimetry (DSC) studies and (b) X-ray diffraction (XRD) analysis. The DSC and XRD profiles of (i) bulk stearic acid, (ii) non-fluorescent SLNs and (iii) fluorescent SLNs.
As shown in Table 9.3, the reduced melting points and melting enthalpies of SLNs (relative to bulk stearic acid) indicate that SLNs with lower crystallinity were produced (Anantachaisilp et al., 2010). The crystallinity index (CI) of SLNs was determined by comparison of the melting enthalpies of bulk stearic acid and SLN dispersions. DSC analysis revealed that the SLNs were in the solid state and the CI value was found to be between 90 and 100%. The reduced CI values indicated an increased number of
251 Chapter 9 Cellular uptake of SLNs imperfections in the crystal structure, the latter of which is caused by incorporation of biomolecules.
XRD analysis was also performed to complement DSC analysis and further investigate the reduced crystallinity of stearic acid in SLNs. Figure 9.3 (b) depicts the XRD patterns of bulk stearic acid and SLNs prepared in this study. The XRD pattern of bulk stearic acid revealed one sharp peak at 2 = 21.7, three medium-intensity peaks at 2 = 6.7, 20.6 and 24.3 and two intensity peaks at 11.1 and 36.4. The intensity of characteristic peaks of stearic acid was reduced and/or shifted to low diffraction angles, and the other low- and medium-intensity peaks were not observed in the XRD of SLNs which is again indicative of reduced crystallinity in SLNs. These results show that XRD data align well with the DSC data (Table 9.3).
9.4.3 Cell viability of SLN dispersions
One of the major concerns regarding the application of nanomaterials is their potential toxicity. This also arises from their ability to enter cells due to their nanoparticulate nature. They may cause adverse effects due to their small size, large surface area and high reactivity (Cheng et al., 2013). Due to their small size, nanoparticles may readily penetrate into areas which are otherwise difficult to access, including cells, tissues and organs and may pose a greater risk to humans than their bulk counterparts. Cell viability (MTT) studies, based on metabolic activity of viable cells, were therefore performed. Figures 9.4 and 9.5 depict the cell viability of non-fluorescent and fluorescent SLNs on both epithelial cell lines.
As expected, cell viability was concentration-dependent with viability increasing with decreased concentrations of SLNs in both the cell lines. However, there was no significant difference (p > 0.05) between the viability of cells treated with non- fluorescent SLNs or fluorescent SLNs. The effect of SLNs was comparable in both the cell lines. SLNs were well tolerated at low concentrations (< 125 µg/mL) indicating that the SLNs were non-toxic at concentrations < 150 µg/mL in both cell lines. The viability of HeLa cells was slightly reduced (relative to A549 cells) when incubated at higher concentrations of SLNs. These results indicate that the HeLa cells were more susceptible to SLNs above 125 µg/mL compared to A549 cells. It was clear from the results that the
252 Chapter 9 Cellular uptake of SLNs cells were viable when incubated at 125 µg/mL, and hence a concentration slightly lower than this (100 µg/mL) was selected for other in vitro experiments.
150 Non-fluorescent SLNs 125 Fluorescent SLNs
100
75
50 Cell viability (%)Cell viability 25
0 1 10 100 1000 Concentration of SLNs (g/mL) Figure 9.4 Viability of A549 cells as measured by MTT assay for SLNs investigated in uptake studies.
150 Non-fluorescent SLNs 125 Fluorescent SLNs
100
75
50 Cell viability (%)Cell viability 25
0 1 10 100 1000 Concentration of SLNs (g/mL) Figure 9.5 Viability of HeLa cells as measured by MTT assay for SLNs investigated in uptake studies.
9.4.4 Investigation of cellular uptake pathways
In order to investigate the cellular uptake of SLNs, the cells were incubated with fluorescent SLNs and analysed using microscopic imaging and flow cell cytometry. Figures 9.6 and 9.7 depict the fluorescence images of A549 and HeLa cell lines, respectively, when incubated under various experimental conditions. The results were
253 Chapter 9 Cellular uptake of SLNs supported by flow cell cytometry analysis as depicted in Figures 9.8, 9.9, 9.12 and 9.13. The CLSM imaging of A549 and HeLa cells incubated under various experimental conditions are given in Figures 9.10 and 9.11, respectively.
R123 CellMask Deep Red Combination (a)
(b)
(c)
(d)
(e)
254 Chapter 9 Cellular uptake of SLNs
R123 CellMask Deep Red Combination (f)
(g)
(h)
Figure 9.6 Uptake of SLNs by A549 cells as investigated by fluorescence imaging. Fluorescence images of A549 cells incubated with (a) free R123 (b) non-fluorescent SLNs (c) fluorescent SLNs at 37C (positive control) (d) fluorescent SLN at low temperature (4C) (e) pre-incubated in hypertonic medium, 0.45 M sucrose (f) pre- incubated in potassium-depleted medium (g) pre-incubated with filipin and (h) pre- incubated with cytochalasin B. The scale bars in the images represent 100 µm.
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R123 Deep Red Combination (a)
(b)
(c)
(d)
(e)
256 Chapter 9 Cellular uptake of SLNs
R123 Deep Red Combination (f)
(g)
(h)
Figure 9.7 Uptake of SLNs by HeLa cells as investigated by fluorescence imaging. Fluorescence images of HeLa cells incubated with (a) free R123 (b) non-fluorescent SLNs (c) fluorescent SLNs at 37C (positive control) (d) fluorescent SLN at low temperature (4C) (e) pre-incubated in hypertonic medium, 0.45 M sucrose (f) pre- incubated in potassium-depleted medium (g) pre-incubated with filipin and (h) pre- incubated with cytochalasin B. The scale bars in the images represent 100 µm.
Although R123 was assumed to be encapsulated within SLNs, there is a possibility that R123 at least partially adsorbs to the surface of SLNs and could easily desorb to become freely solubilised. Thus, the absence of free R123 molecules during cellular uptake cannot be guaranteed. To eliminate any discrepancies related to interference by free R123, cells were incubated with free R123 solution and fluorescent SLNs under similar culture conditions and analysed by fluorescence imaging. Cells incubated with free R123 showed no or negligible fluorescence in both the cell lines (Figures 9.6 (a) and 9.7 (a)).
The cells were then incubated with fluorescent SLNs at 37C in order to confirm cellular uptake of particles. Figures 9.6 (c) and 9.7 (c) depicts the fluorescence images of A549
257 Chapter 9 Cellular uptake of SLNs and HeLa cells, respectively, incubated with fluorescent SLNs at 37C. These results indicate that the fluorescent SLNs were easily taken up by both the cells. The CLSM images Figures 9.10 (b) and 9.11 (b) also aligned well with these observations. Figure 9.8 (a) illustrates the FACS data which also demonstrate cellular uptake of fluorescent SLNs by A549 cells. Similar results were observed in HeLa cells (Figure 9.9 (a)). The cells incubated with fluorescent SLNs at 37C served as a positive control.
It was also possible that fluorescence was due inherent fluorescence of the cells or the SLNs themselves rather than encapsulated R123. In order to evaluate this, the cells were treated with medium alone (or untreated cells) and non-fluorescent SLNs under similar conditions. Post incubation, FACS analysis of untreated A549 cells and A549 cells treated with non-fluorescent SLNs did not exhibit fluorescence (Figure 9.8 (a)). This was further supported by fluorescence and CLSM images (Figures 9.6 (b) and 9.10 (a), respectively). Similar results were observed in HeLa cells treated with similar samples under similar conditions (Figures 9.7 (b), 9.11 (a) and 9.12 (a)). These results indicate that neither untreated cells (which served as negative control in further experiments) nor SLNs exhibit inherent fluorescence. All these results suggest that the cells and SLNs are devoid of any inherent fluorescence. Based on all these findings, it can now be assumed that the results observed henceforth due to incubation of cells with fluorescent SLNs are due to R123 loaded into the SLNs.
The cells were incubated at low temperature (4C) to investigate whether or not the cellular uptake was an energy-dependent mechanism, as active transport of SLNs would be inhibited due to increased membrane rigidity by this treatment (Thurn et al., 2011). Internalisation within the internal cell components usually takes place by energy- dependent processes. Figures 9.6 (d) and 9.10 (c) depict the cellular uptake of SLNs by A549 cells under low temperature conditions. The images show negligible fluorescence in A549 cells when incubated at 4C. The FACS data (Figure 9.8 (b)) also reveal a noticeable reduction in the mean fluorescence intensity of cells incubated at 4 C. Similar results were obtained HeLa cells incubated under similar conditions (Figures 9.7 (d), 9.11 (c) and 9.12 (b)). These results suggest that the cellular uptake of SLNs was an energy- dependent process in both the epithelial cell lines, and this serves as an indication that endocytosis was the underlying mechanism responsible for the cellular uptake of SLNs. These results are consistent with previous studies on lipid nanoparticles (Chai et al., 2014; Martins et al., 2012a).
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(b) Figure 9.8 FACS data showing cellular uptake of non-fluorescent SLNs at 37C and fluorescent SLNs at 4C and 37C by A549 cells. (a) Uptake of non-fluorescent SLNs relative to fluorescent SLNs and (b) Inhibition of energy-dependent endocytosis mechanism.
259 Chapter 9 Cellular uptake of SLNs
(a)
(b) Figure 9.9 FACS data showing cellular uptake of non-fluorescent SLNs at 37C and fluorescent SLNs at 4C and 37C by HeLa cells. (a) Uptake of non-fluorescent SLNs relative to fluorescent SLNs and (b) Inhibition of energy-dependent endocytosis mechanism.
260 Chapter 9 Cellular uptake of SLNs
R123 Deep Red Combination (a)
(b)
(c)
(d)
(e)
261 Chapter 9 Cellular uptake of SLNs
R123 Deep Red Combination (f)
(g)
Figure 9.10 Uptake of SLNs by A549 cells as investigated by CLSM imaging. CLSM images of A549 cells when incubated with (a) non-fluorescent SLNs (b) fluorescent SLNs at 37C (positive control) (c) fluorescent SLN at low temperature (4C) (d) pre- incubated in hypertonic medium, 0.45 M sucrose (e) pre-incubated in potassium-depleted medium (f) pre-incubated with filipin and (g) pre-incubated with cytochalasin B. The scale bars in the images represent 50 µm.
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R123 Deep Red Combination (a)
(b)
(c)
(d)
(e)
263 Chapter 9 Cellular uptake of SLNs
R123 Deep Red Combination (f)
(g)
Figure 9.11 Uptake of SLNs by HeLa cells as investigated by CLSM imaging. CLSM images of HeLa cells when incubated with (a) non-fluorescent SLNs (b) fluorescent SLNs at 37 C (positive control) (c) fluorescent SLN at low temperature (4C) (d) pre- incubated in hypertonic medium, 0.45 M sucrose (e) pre-incubated in potassium-depleted medium (f) pre-incubated with filipin and (g) pre-incubated with cytochalasin B. The scale bars in the images represent 50 µm.
The endocytosis of SLNs probably occurs either by pinocytosis or by phagocytosis. Since epithelial cells were used in this study, the possibility of involvement of phagocytosis in the internalisation is very low. The endocytosis of SLNs into the cells may be, however, due to one or more pathways. Uptake can occur by one of the forms of pinocytosis – clathrin-mediated endocytosis, caveolae-mediated endocytosis, clathrin- and caveolae- independent endocytosis or macropinocytosis.
A systematic investigation of pathways was performed on epithelial cell lines by excluding specific endocytosis mechanisms through the use of pharmacologic inhibitors (Iversen et al., 2011) (see Table 9.1). This is a distinct and influential tool used in the elucidation of endocytosis pathways. In order to investigate the cellular uptake of SLNs, the cells were treated with fluorescent SLNs and incubated with various pharmacologic inhibitors and analysed using fluorescence and CLSM microscopy. These experiments were supported by FACS analysis.
264 Chapter 9 Cellular uptake of SLNs
The classical route of cellular entry is receptor-mediated endocytosis. Clathrin-mediated endocytosis is by far the most common of these mechanisms. Extracellular substances such as nanoparticles localise on the cell membrane and trigger the formation of clathrin- coated pits. Extracellular substances are trapped into clathrin-coated pits, which pinch off from the cell membranes and develop into vesicles. The extracellular substances are eventually internalised along with the coated pits as vesicles (Doherty and McMahon, 2009).
The role of clathrin in the internalisation of SLNs was assessed by incubating the cells in hypertonic (0.45 M sucrose) or potassium-depleted medium, prior to exposure to SLNs. These two treatments disrupt the formation of clathrin-coated pits on the cell membranes and inhibit the cellular uptake of SLNs (Kam et al., 2006). Figures 9.6 (e), 9.10 (d) and 9.12 (a) depict reduced fluorescence of HeLa cells due to hypertonic treatment. This is an indication that the endocytosis and cellular uptake of SLNs was inhibited by hypertonic treatment of HeLa cells. Additionally, a drastic reduction in the fluorescence intensity of HeLa cells was also observed when the cells were incubated in potassium-depleted medium (Figures 9.6 (f), 9.10 (e), 9.12 (b)). The inhibition of clathrin-mediated endocytosis was less pronounced in A549 cells but followed a similar pattern to HeLa cells (Figures 9.7 (e), 9.7 (f), 9.10 (d), 9.10 (e), 9.13 (a) and 9.13 (b)). These results indicate that the endocytosis of SLNs was mediated by clathrin-coated pits.
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(b) Figure 9.12 FACS data showing inhibition of clathrin-mediated endocytosis in A549 cells at 37 C. Clathrin-mediated endocytosis was inhibited by (a) hypertonic treatment and (b) potassium-depletion in medium at.
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(a)
(b) Figure 9.13 FACS data showing inhibition of clathrin-mediated endocytosis in HeLa cells at 37C. Clathrin-mediated endocytosis was inhibited by (a) hypertonic treatment and (b) potassium-depletion in medium.
The endocytosis of many extracellular substances may occur by mediation of caveolae or lipid-rafts via specific or non-specific interactions. Caveolae or lipid-rafts are flask- shaped invaginations on the cellular membrane rich in cholesterol and sphingomyelin (Doherty and McMahon, 2009). To assess the role of caveolae-mediated endocytosis in the cellular uptake of SLNs, cells were incubated with filipin prior to exposure to SLNs. Filipin is a cholesterol binding agent that interferes with the cholesterol present in the cell membranes increasing the membrane fluidity (Billiet et al., 2012). Filipin specifically blocks caveolae-mediated endocytosis without interfering with the functioning of coated-pits (Kheirolomoom and Ferrara, 2007).
Figures 9.6 (g) and 9.10 (f) depict the fluorescence and CLSM images, respectively, of A549 cells incubated with filipin. There was no reduction in the fluorescence of cells demonstrating that the filipin treatment did not inhibit cellular uptake of SLNs. These results indicate that endocytosis of SLNs by A549 cells was not mediated by caveolae or
267 Chapter 9 Cellular uptake of SLNs lipid rafts. Similar results were obtained with HeLa cells (Figures 9.7 (g) and 9.11 (f)). However, the viability of the cells was affected, possibly by increased membrane fluidity, as indicated by the greater uptake of potassium iodide during FACS experiments (data not shown).
Cellular entry may be due to other endocytic mechanisms which are independent of both clathrin- and caveolae, such as macropinocytosis. Growth factors activate the receptor tyrosine kinases, which are responsible for the initiation of macropinocytosis. Receptor activation facilitates a signalling cascade which causes changes to the actin cytoskeleton. This further triggers formation of ruffles in the membrane which protrude to engulf fluids and nutrients present in the external milieu of the cells (Mercer and Helenius, 2012). These protrusions form macropinosomes which are large (0.5-10 µm) and different from other vesicles that are formed during receptor-mediated endocytosis. Macropinocytosis may serve as a non-specific entry pathway for cells which lack phagocytosis and can internalise larger submicron particles.
To assess whether cellular uptake of SLNs was mediated by macropinocytosis, cells were treated with cytochalasin B. Cytochalasin B is known to depolymerise the actin filaments, thereby inhibiting the formation of membrane ruffles and cellular uptake (Linares et al., 2014). Cytochalasin B treatment did not inhibit the uptake of SLNs in either of the cell lines (Figures 9.6 (h), 9.7 (h), 9.10 (g) and 9.11 (g)) which indicates that macropinocytosis is not a preferred pathway for cellular uptake of SLNs.
From all of the experimental data above, it is shown that clathrin-mediated endocytosis is the main mechanism for entry of fluorescent SLNs into epithelial cells.
268 Chapter 9 Cellular uptake of SLNs
9.5 Conclusions
In conclusion, SLNs were prepared using the novel microwave-assisted microemulsion technique. The small particle size (< 300 nm), low polydispersity index (< 0.2) and negative zeta potential (~ -20 mV) of SLNs produced in this study are suitable for them to be taken up by epithelial cells. Studies also suggest that small particles with slight negative charge can easily move through tumour tissue in animal models (Nomura et al., 1998). These findings indicate that SLNs such as the ones produced in this study are potential candidates for drug delivery in animal models. The SLNs produced by this technique had lower crystallinity compared to bulk stearic acid and remain solid at room and body temperature. These results were consistent with the findings presented in previous Chapters.
The SLNs were found to have no cytotoxic effects on both of the human epithelial cells, lung A549 and cervical HeLa, used in this study. The SLNs laden with a fluorescent, model drug (Rhodamine 123) were readily transported into human epithelial cells. The cellular entry takes place by endocytosis, an energy-dependent process. A detailed dissection of the intracellular internalisation process was performed by microscopic and cell flow cytometry techniques. The epithelial cells take up SLNs through mediation of clathrin-coated pits in their cellular membranes rather than caveolae or lipid rafts or phagocytosis. These results were consistent with previous experiments using other lipid nanoparticle formulations (Chai et al., 2014; Martins et al., 2012a).
These findings increase knowledge of the cellular uptake of SLNs by epithelial cells. The data may assist future development of SLNs as potential candidates in drug delivery applications.
269
Chapter 10 A pH-dependent study on the stability of SLNs 10
A pH-dependent study on the stability of SLNs
271 Chapter 10 A pH-dependent study on the stability of SLNs
Abstract
The SLNs prepared by the microwave-assisted technique have been shown to exhibit promising physicochemical characteristics, encapsulation efficiency and drug release capabilities, and have the ability to be internalised by human cells.
In practice, SLNs may have to be able to tolerate some, or all, of the various conditions experienced in the human body. Consequently, the influence of pH, electrolytes and simulated gastrointestinal (GI) fluids on the physical stability of the SLNs was investigated. The influence of pH on the particle characteristics of the SLNs was determined by addition of hydrochloric acid and sodium hydroxide to the SLN dispersions after their original manufacture.
The particle size of the SLNs increased slightly at low pH levels, remained relatively constant at moderate pH levels and increased dramatically at high pH levels. The effect of electrolytes (simulated GI fluids) was evaluated and found that SLNs were stable at low pH levels if the electrolyte concentration was high. Particle sedimentation, however, was seen within 4 h of incubation at high pH levels.
The electrostatic and steric stabilisation mechanisms responsible for the physical stability of the SLNs under different pH and electrolyte conditions are discussed. A preliminary study was undertaken to assess the effect of pH on the encapsulation efficiency of the SLNs.
The results suggest that the SLNs can be considered as potential drug carriers for oral and/or topical administration under a wide range of physical conditions providing they do not involve extremes of pH.
272 Chapter 10 A pH-dependent study on the stability of SLNs
10.1 Introduction
In previous chapters, SLNs were prepared using the microwave-assisted microemulsion technique. A number of different drugs were successfully encapsulated within the SLNs. Short-term stability studies over a few weeks showed that the particles remained stable under refrigeration (Chapters 5-7) but not necessarily stable at room temperature.
Particle size, or at least a change in particle size, is often regarded as an indicator of physical stability (Heurtault et al., 2003). In addition to this, zeta potential measurements are often undertaken to assist in predicting the physical stability of colloidal systems and providing more information regarding the mechanism of stability. The drug-free and the drug-loaded SLNs prepared in this thesis had a solid lipid core composed of stearic acid and were surface-tailored with Tween® 20 to impart stability to the SLNs (the SLNs were formulated as dispersions here). A summary of the zeta potential results from previous chapters is shown in Table 10.1.
Table 10.1 Zeta potential of SLNs from previous chapters (see Section 6.4.2 and 7.4.2) (pH was the native pH of the dispersion as formed)
SLNs Zeta potential pH (mV)
Drug-free SLNs -28.0 ± 1.9 4.5 ± 0.1
Indomethacin-loaded SLNs -23.8 ± 1.7 4.5 ± 0.1
Ketoprofen-loaded SLNs -20.6 ± 1.2 4.4 ± 0.1
Nimesulide-loaded SLNs -22.0 ± 1.1 4.6 ± 0.1
Clotrimazole-loaded SLNs -21.3 ± 3.2 4.4 ± 0.1
Miconazole nitrate-loaded SLNs +20.9 ± 0.8 4.3 ± 0.1
Econazole nitrate-loaded SLNs +12.4 ± 0.8 4.3 ± 0.1
All SLNs had a negative zeta potential, with the exceptions of the miconazole nitrate- loaded SLNs and econazole nitrate-loaded SLNs. The probable origin of the negative potential is due to the stearic acid at the surface of the SLNs dissociating in the surrounding aqueous dispersion, leaving negatively charged stearate ions at the particle/water interface. In both cases where a positive zeta potential is observed, the
273 Chapter 10 A pH-dependent study on the stability of SLNs incorporated drugs are cationic in nature and are almost certainly responsible for the positive charge.
Electrostatic and/or steric stabilisation plays an important role in the stabilisation of SLNs (Heurtault et al., 2003). The stability can be due to the charge present at the surface of the SLNs (see Section 10.1.1) or due to the surfactant Tween® 20 (non-ionic surfactant) contributing “steric stabilisation” (see Section 10.1.2) or a contribution of both.
10.1.1 Electrostatic stabilisation
A short description of the electrostatic stabilisation mechanisms was given in Section 1.11.1 (see Chapter 1). Stearic acid is primarily a saturated, free fatty acid with a carboxylic acid (RCOOH) functional group. As with other carboxylic acids, when placed + in water, stearic acid undergoes hydrolysis to form hydronium ions (H3O ) and its conjugate base (stearate ions, RCOO-) (Equation 10.1). The stearate ions in the dispersions provide the electrostatic repulsion necessary for assisting in the potential stabilisation of the dispersions, arising due to overlap of electrical double layers of identical SLNs.
- + CH3(CH2)16COOH + H2O ⇄ CH3(CH2)16COO + H3O
… Equation 10.1
The fractions of stearic acid molecules and stearate ions in the dispersion are pH dependent. Figure 10.1 depicts a schematic representation of the fraction of stearic acid molecules and stearate ions as a function of pH. At pH values less than the pKa (4.9), the + concentration of H3O increases, shifting the equilibrium (Equation 10.1) towards the left. Hence, more neutral stearic acid molecules are present. At pH values above the pKa, the concentration of stearate ions increases due to the equilibrium shifting to the right.
274 Chapter 10 A pH-dependent study on the stability of SLNs
Stearic acid Stearate anions Fraction of molecular species
0 1 2 3 4 5 6 7 8 9 10 pH
Figure 10.1 A schematic diagram of the fraction of stearic acid and stearate ions in solution as a function of pH. The pKa of stearic acid (~ 4.95) is the pH at which the fraction of both the molecular species in solution – stearic acid and stearate ions – are nearly equal.
10.1.2 Steric stabilisation
A short description of steric stabilisation mechanisms is given in Section 1.11.2 (see Chapter 1). Steric stabilisation can be induced by polymeric material, but large molecular non-ionic surfactants are more commonly used for stabilising SLNs. The surfactant used in this thesis was Tween® 20 which is a low molecular weight non-ionic surfactant. Therefore, it was not necessarily expected to result in significant steric stabilisation. It is also not charged, so does not directly contribute to the negative zeta potential of the SLNs. However, Tween® 20 forms a protective layer around the SLNs which contributes to the overall stability of the SLNs, either through an unusual charge generation (such as negative ion adsorption) (Hsu et al., 2003; Marinova et al., 1996) or through an unusual steric stabilisation (such as micellar adsorption) (Dimitrova and Leal-Calderon, 1999, 2000). The exact stabilising mechanism of Tween® 20 is therefore not clear and will be debated in this chapter.
The stabilizing mechanism of non-ionic surfactants is often attributed to solvation effects. The non-polar segment of the non-ionic surfactant strongly interacts with the
275 Chapter 10 A pH-dependent study on the stability of SLNs dispersed SLNs, while the stabilising polar ends of the surfactant extends into the bulk solution and are strongly solvated to provide the desired repulsive solvation forces, preventing particle aggregation.
276 Chapter 10 A pH-dependent study on the stability of SLNs
10.2 Chapter Aims
The main objective of this chapter was to investigate the effect of both pH and the electrolyte conditions of simulated gastrointestinal fluids on the stability of the SLNs.
The specific aims of this chapter are:
To investigate the effect of pH on the stability of the SLNs by measuring any changes in particle size and zeta potential of the SLNs. To investigate any changes in particle size and zeta potential of the SLNs incubated in simulated gastrointestinal fluids of pH 1.2, pH 3.5 and pH 7.4. To study any effects of electrolytes (present in the simulated gastrointestinal fluids) on zeta potential measurements. To investigate any effects of pH and simulated gastrointestinal fluids on SLNs incorporated with model drugs, using indomethacin and miconazole nitrate as examples. To investigate any changes in the encapsulation efficiencies and loading capacities of SLNs under different conditions of pH.
277 Chapter 10 A pH-dependent study on the stability of SLNs
10.3 Methods
10.3.1 Preparation of SLNs
The drug-free SLNs and drug-loaded SLNs were prepared by the novel microwave- assisted microemulsion technique described earlier (see Section 3.3.1). For drug-loaded SLNs, 5% drug (with respect to the lipid) was added to the mixture of stearic acid and Tween® 20 before the mixture was subjected to microwave heating.
When preparing drug-loaded SLNs, indomethacin and miconazole nitrate were selected as model drugs. These drugs were chosen based on the difference in their chemical structures. Indomethacin is an acidic water-insoluble drug with a carboxylic acid group and miconazole nitrate is a water-insoluble drug with an imidazole-based chemistry. The SLNs incorporated with these drugs exhibited different drug release profiles and release mechanisms (see Chapter 8).
10.3.2 Particle characterisation
Determination of hydrodynamic diameter and polydispersity index (PI) using DLS
The intensity weighted mean hydrodynamic diameter and PI of the SLN dispersions were determined by DLS at 25C as described in Section 3.3.2.1.
Zeta potential measurements
Zeta potential measurements were carried out as described in Section 3.3.2.3. The zeta potential of the SLN dispersions was determined by measurement of the electrophoretic mobility and converting it to zeta potential using “Zeta for Windows”.
10.3.3 Stability studies
Effect of pH on particle size and zeta potential
The influence of pH on the stability of SLNs was evaluated primarily by considering the SLN particle size and zeta potential. The pH of the SLN dispersions was adjusted to predetermined pH levels by addition of 0.1 M hydrochloric acid or 0.1 M sodium hydroxide and monitored using a pH meter.
278 Chapter 10 A pH-dependent study on the stability of SLNs
Effect of simulated gastrointestinal (GI) fluids
Stability studies were carried out in simulated GI fluids as described by Zimmermann and Müller (2001) with some modifications. In brief; 1 mL of a SLN dispersion was added to 2 mL of simulated GI fluids. The samples were investigated for changes in particle size and zeta potential immediately after addition of simulated GI fluids (i.e. at t = 0 h) and after 4 h and 24 h incubation in GI fluids at room temperature. The simulated GI fluids used in this study were prepared as described in Section 3.4 D.
a. pH 1.1 consists of hydrochloric acid and distilled water, adjusted to iso- osmolarity with sodium chloride b. pH 3.5 consists of citric acid, sodium hydroxide, hydrochloric acid and distilled water, adjusted to iso-osmolarity with sodium chloride c. pH 7.4 consists of sodium dihydrogen monophosphate, sodium hydroxide and distilled water, adjusted to iso-osmolarity with sodium chloride
10.3.4 Encapsulation efficiency and loading capacity measurements
The EE and LC (see Equations 10.2 and 10.3) of the original SLN dispersions were determined by the centrifugal ultrafiltration method described in Section 3.3.3. In order to study the influence of pH, EE and LC of SLNs adjusted to pH 10 was also determined. The amount of drug in the “filtered”, “loaded”, “free” and “soluble” fractions were analysed by HPLC analysis (see Section 5.3.2.5).
The EE and LC were calculated from the amounts of drug determined by the HPLC analysis using the following equations,
[amount (loaded) - amount (free) - amount (soluble)] EE (%) = × 100 amount (drug loading)
… Equation 10.2 [amount (loaded) - amount (free) - amount (soluble)] LC (%) = × 100 amount of lipid added to the formulation
… Equation 10.3
279 Chapter 10 A pH-dependent study on the stability of SLNs
10.4 Results and Discussion
The stearic acid molecules on the SLN surface partially dissociate in water and most likely rearrange themselves with the carboxylic group in the polar aqueous phase and the hydrophobic aliphatic chain in the bulk solid. The negatively charged carboxylic groups at the surface could then contribute to electrostatic stabilisation of the SLNs. The electrostatic stabilisation of colloidal dispersions is based on classical DLVO theory (see Chapter 1, Section 1.11.1). The SLNs in this thesis were further stabilised with Tween® 20 which may impart steric stabilisation to the SLNs. Steric stabilisation is due to the solvation effect of Tween® 20.
A schematic depiction of the predicted outer layer of the stearic acid-based SLNs is shown in Figure 10.2. The contribution of each of these stabilisation mechanisms – electrostatic and steric – is discussed below.
Figure 10.2 A schematic diagram of the surface of the stearic acid-based SLNs.
The stearate ions (from dissociation of stearic acid on the SLN surface) impart negative charge to the SLNs which explains the production of SLN dispersions with negative zeta potential. The stearate ions and the hydroxyl group of the adjacent stearic acid molecules give rise to an ion-dipole interaction which is instrumental in providing the much needed stabilisation (Kanicky and Shah, 2002). While zeta potential values above |30| mV are deemed suitable to indicate good stability of electrostatically-stabilised colloidal systems, zeta potential values of ~ |20| mV are considered suitable for systems stabilised by a combination of electrostatic and steric forces. There is no value deemed appropriate for systems stabilised solely by steric stabilisation (Kovačević et al., 2011; Neves et al., 2013).
Tween® 20 is a low molecular weight non-ionic surfactant with a very low critical micelle concentration (CMC) of ~ 6 × 10-5 mole/L. Dimitrova and Leal-Calderon (1999) reported
280 Chapter 10 A pH-dependent study on the stability of SLNs that, for emulsions stabilised with low concentrations of Tween® 20, the stabilisation mechanism is based on classical DLVO behaviour – electrostatic repulsion. However, at very large concentrations of Tween® 20, the stabilisation mechanism is reportedly achieved through micellar condensation on the surface of emulsion droplet. Dimitrova and Leal-Calderon (1999, 2000) suggested that such effects contribute to steric-like additional effective repulsion. The SLNs in this thesis were surface-tailored with high concentrations of Tween® 20. The surfactant used in the formulation is in excess and therefore, probably form micelles on the SLN surface to impart steric-like additional repulsion.
Hingston et al. (1972, 1974) suggested that the pH-dependent adsorption of anions on a substrate is maximum at the pKa values of the anion in their studies on adsorption of anions on goethite. In their “adsorption envelope” model, Hingston (1972, 1974) reported that adsorption of anions is increased with an increase in pH until complete dissociation of the conjugate acid. However, increasing the pH past the pKa (i.e. alkaline pH) decreases the anion adsorption due to increases in the negative charge of the substrate (Bowden et al., 1973; Hingston, 1981). It should be noted here that the SLNs are prepared as emulsions first and cooled later to generate SLN dispersions. The relation between the anion adsorption (stearate ions in this case) on a substrate (Tween® 20 in this case) and pKa of the conjugate acid of the anion (stearic acid in this case) may provide an explanation to the formation of a stable emulsion and therefore, SLN dispersion. The pH of the SLN dispersions produced in this thesis was measured to be 4.5 ± 0.2, only slightly less than the pKa of stearic acid. The pKa of stearic acid when present in bulk solution as a dispersion is ~ 4.9 (Mercado et al., 2011). The anion adsorption theory can now be applied directly to this case. Maximum adsorption of stearate ions (during the preparation of the emulsion) would be expected to be greatest at the native pH of SLNs (which is close to pKa of stearic acid) and can be correlated with stability of the SLNs. The stability is probably greatest at this point.
10.4.1 Influence of pH on the physical stability of drug-free SLNs
The particle size and zeta potential of the drug-free SLNs at native pH of ~ 4.5 were approximately 240 nm and 25 mV respectively. The pH-dependent changes in particle sizes and zeta potentials was determined by addition of either hydrochloric acid or
281 Chapter 10 A pH-dependent study on the stability of SLNs sodium hydroxide to achieve the desired pH. The particle size and zeta potential of the SLNs served as indicators of particle stability. Figures 10.3 and 10.4 illustrate the particle size and zeta potential of drug-free SLNs as a function of pH respectively.
800
700
600
500
400
300
Particlesize (nm) 200
100
0 1 2 3 4 5 6 7 8 9 10 11 pH
Figure 10.3 Particle sizes of drug-free SLNs as a function of pH. The vertical red line in the graph denotes the pKa of stearic acid.
20 10 0 -10 -20 -30 -40
Zetapotential (mV) -50 -60 -70
1 2 3 4 5 6 7 8 9 10 11 pH
Figure 10.4 Zeta potentials of drug-free SLNs as a function of pH. The vertical red line in the graph denotes the pKa of stearic acid.
282 Chapter 10 A pH-dependent study on the stability of SLNs
The results in Figures 10.3 and 10.4 demonstrate that a change in the pH of the SLN dispersions influences the particle size and zeta potential of the nanoparticles. It is worth noting that the particle size of SLNs was found to be minimum, and hence, assumed to be most stable, at their native pH i.e. when pH ≈ pKa of stearic acid. This correlates well with the anion adsorption theory discussed earlier. Particle aggregation was seen at extreme acidic conditions (i.e. pH ≤ 2). No visual change in particle size was observed at pH ≤ 2. The particle sizes increased slightly at low pH levels (i.e. pH ≤ 2) and were not significantly different (p > 0.05) at moderate pH levels (i.e. 2 ≤ pH ≤ 7). However, SLN dispersions showed a glassy or gel-like appearance at alkaline conditions (i.e. pH ≥ 7). A substantial increase in particle size was observed at pH ≥ 8. A decrease in particle size of the SLNs with an increase in the pH of the dispersions has been reported earlier for other colloidal systems including liposomes, SLNs and other formulations (Shahgaldian et al., 2003a, 2003b, 2003c; Zimmermann and Müller et al., 2003; Gan et al., 2005; Sabin et al., 2006; Jiang et al., 2009).
Increasing the pH of drug-free SLNs increases the magnitude of the zeta potential. At high pH levels, the stearic acid molecules are deprotonated to form stearate ions (Kanicky and Shah, 2002). This was evident from the increased zeta potential values. It is possible that for these literature studies, the increased pH levels resulted in increased magnitudes of zeta potential and increased the stability of the particles through electrostatic stabilisation. However, in this study, this stabilisation (reduced particle size) was not seen. The results in Figure 10.3 and 10.4 showed that particle size increased dramatically at high pH levels despite increased zeta potential. This may lead to ionic repulsion of the stearate ions on the particle surface resulting in instability.
Kerwin (2008) has reviewed the chemical stability of polysorbates such as Tween® 20. Ester hydrolysis in Tween® 20 in acidic and/or basic conditions may be responsible for hydrolysis of surfactant molecules and therefore, disruption of stabilizing effect. All these findings suggest an increased instability in the system at extreme pH conditions, and consequently may lead to an increased particle size as observed in this experiment.
The zeta potential vs. pH data shown in Figure 10.4 indicates that the isoelectric point
(represented as pHiep, i.e. the pH at which net zeta potential is zero) was approximately
2. At the pHiep, a colloidal system with no other means of stabilisation is expected to flocculate. In this case, despite a net zero zeta potential, the SLNs exhibited only a slight
283 Chapter 10 A pH-dependent study on the stability of SLNs increase in particle size and no evident flocculation of particles. These observations indicate that another factor such as steric stability is a major contributor to the SLN stabilisation. Although zeta potential serves as an indicator of physical stability, it is more pronounced and meaningful for systems stabilised by electrostatic effects alone. Steric stabilisation must play an important role in maintaining the integrity of the SLNs, at least at low pH.
Figure 10.5 A schematic representation of the surface of a stearic acid-based SLN suspended in an aqueous solution (i.e. SLNs dispersion) as a function of pH. The stearic acid is present as a (a) neutral stearic molecule at pH less than pKa, (b) a strong ion- dipole interaction at pH = pKa because of equimolar concentrations of stearic acid molecules and stearate ions and (c) stearate ions at pH > pKa.
Figure 10.5 shows a schematic depiction of surface species at several pH conditions. At low pH, a larger fraction of the surface has unionised stearic acid molecules at very low pH (Kanicky and Shah, 2002). The unionised stearic acid molecules are surrounded by hydronium ions (dissociation of hydrochloric acid) which were evident from the positive zeta potential below the pH 2. Although there was slight increase in the particle size, this increase was not significantly larger than the original SLNs dispersions. At low pH, some of the stearic acid chains may “flip” on the surface. Flip-flop of fatty acid chains has been reported earlier in dynamic bilayered systems (Kamp et al., 1995; Kamp and Hamilton, 1993; Ježek et al., 1997; Pohl et al., 2000). Such flip-flop of stearic acid chains has been reported in dynamic systems such as stearic acid monolayers (Kumar et al., 2013); however, such effects have not been reported in static systems such as the SLNs. The
284 Chapter 10 A pH-dependent study on the stability of SLNs probable “flipping” of the stearic acid chains may increase the curvature of the particles, thereby increasing the particle size
In order to tackle the instability caused by the ionic repulsion of adjacent stearate ions, some of the stearic acid chains were assumed to “flip” on the surface. This may contribute to further increase in particle sizes of SLNs. While “flipping” of ionised stearic acid chains is much slower than the unionised stearic acid chains (Kamp et al., 1995; Kamp and Hamilton, 1993; Ježek et al., 1997; Pohl et al., 2000), the presence of this mechanism cannot be denied, even though they are now present in dispersions rather than monolayers.
In summary, the results indicate that the physical stability of drug-free SLNs is pH- dependent, with particles being most stable at native pH which is close to the pKa.
10.4.2 Influence of drug incorporation on pH-dependent stability of SLNs
The influence of incorporated drug molecules on the physical stability of the SLN dispersions is very likely due to their ionic properties and/or interaction with the particle surface. Further investigation of the physical stability of drug-loaded SLNs was performed under varying pH conditions. Indomethacin and miconazole nitrate were chosen as model drugs based on their chemistries and previous behaviours (see Chapters 6, 7 and 8).
Figures 10.6 and 10.7 depict particle size as a function of pH for indomethacin-loaded SLNs and miconazole nitrate-loaded SLNs respectively. The graphs depicting the zeta potentials as a function of pH for indomethacin-loaded SLNs and miconazole nitrate- loaded SLNs are shown in Figure 10.8 and 10.9 respectively.
285 Chapter 10 A pH-dependent study on the stability of SLNs
800
700
600
500
400
300
Particlesize (nm) 200
100
0 1 2 3 4 5 6 7 8 9 10 11 pH
Figure 10.6 Particle sizes of indomethacin-loaded SLNs as a function of pH. The vertical red line in the graph denotes the pKa of stearic acid.
800
700
600
500
400
300
Particlesize (nm) 200
100
0 1 2 3 4 5 6 7 8 9 10 11 pH
Figure 10.7 Particle sizes of miconazole nitrate-loaded SLNs as a function of pH. The vertical red line in the graph denotes the pKa of stearic acid.
286 Chapter 10 A pH-dependent study on the stability of SLNs
20 10 0 -10 -20 -30 -40
Zetapotential (mV) -50 -60 -70
1 2 3 4 5 6 7 8 9 10 11 pH
Figure 10.8 Zeta potential of indomethacin-loaded SLNs as a function of pH. The vertical red line in the graph denotes the pKa of stearic acid.
20 10 0 -10 -20 -30 -40
Zetapotential (mV) -50 -60 -70
1 2 3 4 5 6 7 8 9 10 11 pH
Figure 10.9 Zeta potential of miconazole nitrate-loaded SLNs as a function of pH. The vertical red line in the graph denotes the pKa of stearic acid.
The trends observed are similar to drug-free SLNs. There was a slight increase in the particle size of SLNs due to encapsulation of drug molecules.
287 Chapter 10 A pH-dependent study on the stability of SLNs
Although the presence of drug molecules influenced the absolute values of particle size and zeta potential of the SLNs, they had little effect on the optimal pH range for SLN production. The particle size of indomethacin-loaded SLNs increased slightly at low pH, remained approximately constant at pH closer to the pKa of stearic acid and increased particle sizes were observed at high pH values.
In case of miconazole nitrate-loaded SLNs, the effect of pH on the particle size was not significant at pH ≤ 7. The particle size of miconazole nitrate-loaded SLNs, like drug-free and indomethacin-loaded SLNs, increased dramatically at high pH levels, suggesting particle instability at high pH levels (despite the now high negative zeta potentials).
While the zeta potential of the original drug-free SLNs and indomethacin-loaded SLNs is negative at their native pH of ~ 4.5, the miconazole nitrate-loaded SLNs have a positive zeta potential at this pH (see Chapters 6 and 7). The positive zeta potential may be due to the presence of cationic nitrogen within the drug molecules “sticking out” from the surface of the miconazole nitrate-loaded SLNs.
Similar to drug-free SLNs, the zeta potential of both drug-loaded SLNs increased in negative magnitude with increasing pH. While the pHiep of indomethacin-loaded SLNs was similar to the pHiep of drug-free SLNs (i.e. ~ 2), the pHiep of miconazole nitrate- loaded SLNs was found to be ~ 5. The zeta potential of miconazole nitrate-loaded at pH ≤ 5 was found to be positive possibly due to protonation of the drug adsorbed on the article surface. Notwithstanding this, the change in particle size of drug-loaded SLNs was found to be insignificant and there was no immediate flocculation or other instability apparent. These results indicate that steric stabilisation and/or other mechanisms play an important role in maintaining the stability of the SLNs at low to moderate pH levels. These findings suggest that the physical stability of drug-loaded SLNs is pH-dependent. The drug-free and drug-loaded SLNs were found to have a small particle size at native pH which is close to the pKa of stearic acid and were most stable at this pH. These results indicate that they are likely to remain stable under these conditions probably due to the strong surfactant adsorption suggested by the anion adsorption theory discussed earlier in this chapter. Although the incorporation of drugs has a significant influence on the physical characteristics of the SLNs, it has a minimal influence on the stabilisation of the SLNs.
288 Chapter 10 A pH-dependent study on the stability of SLNs
The above findings indicated that the SLNs were unstable at high pH levels. Particle instability often causes a decreased EE and LC. To investigate this, a preliminary study was performed to determine the EE and loading LC of drug-loaded SLNs at the highest pH level tested i.e. pH 10.
100 pH 4.5 90 pH 10 80 70 60 50 40 30 20
Encapsulationefficiency (%) 10 0 Indomethacin-loaded SLNs Miconazole nitrate-loaded SLNs
Figure 10.10 The effect of pH on the encapsulation efficiency of SLNs. The red line depicts the theoretical maximum EE.
The comparative values of EE and LC are shown in Figure 10.10 and 10.11 respectively. These results indicate that there was a significant decrease in the EE and LC of indomethacin-loaded at pH 10. This result was expected as the SLNs were found to be unstable at high pH. The decrease in EE and LC may be due to “dislodged” indomethacin.
In contrast, despite instability at pH 10, there was no significant change in the EE and LC of miconazole nitrate-loaded SLNs. This may be due to stronger association of miconazole nitrate and stearic acid at higher pH. The results from the drug release study at pH 7.4 (see chapter 8, Section 8.4.5) also suggests that miconazole nitrate is strongly associated with the SLNs. Being positively charged miconazole nitrate may form a strong association with the negatively charged SLNs at high pH levels. Nevertheless, these findings show that pH has a significant influence on the incorporation of drugs. However, an extensive study needs to be performed on drug-loaded SLNs at various pH conditions.
289 Chapter 10 A pH-dependent study on the stability of SLNs
5 pH 4.5 pH 10 4
3
2
1 Encapsulationefficiency (%) 0 Indomethacin-loaded SLNs Miconazole nitrate-loaded SLNs
Figure 10.11 The effect of pH on the loading capacity of SLNs. The red line depicts the theoretical maximum LC.
10.4.3 Effect of simulated GI fluids
The physical stability of drug-free and drug-loaded SLNs was investigated in simulated gastrointestinal fluids by observing changes in the particle size and zeta potential values. The SLNs were considered stable if there were no significant increases in their particle sizes when incubated in simulated GI fluids after 4 h and 24 h. The changes in particle size of drug-free, indomethacin-loaded and miconazole nitrate-loaded SLNs are illustrated in Figures 10.12, 10.13 and 10.14 respectively.
1250 0 h
1000 4 h 24 h 750
500
Particlesize (nm) 250
0 pH 1.1 pH 3.5 pH 7.4
Figure 10.12 The effect of gastrointestinal fluids on the particle sizes of drug-free SLNs. Particle sedimentation was seen at pH 7.4 after 24 h.
290 Chapter 10 A pH-dependent study on the stability of SLNs
1250 0 h
1000 4 h 24 h 750
500
Particlesize (nm) 250
0 pH 1.1 pH 3.5 pH 7.4
Figure 10.13 The effect of gastrointestinal fluids on the particle sizes of indomethacin- loaded SLNs. Particle sedimentation was seen at pH 7.4 after 24 h.
1250 0 h
1000 4 h 24 h 750
500
Particlesize (nm) 250
0 pH 1.1 pH 3.5 pH 7.4
Figure 10.14 The effect of gastrointestinal fluids on the particle sizes of miconazole nitrate-loaded SLNs. Particle sedimentation was seen at pH 7.4 after 24 h.
The results in Figures 10.12 - 10.14 indicate a slight increase in the particle size of the SLNs when incubated at pH 1.1 and pH 3.5. The slight increase in the particle size may be attributed to the depletion of the electrical double layer due to the presence of salts in the simulated GI fluids (Zimmermann and Müller, 2001). The effect of electrolytes on the depletion of electrical double layer and thus zeta potential is well documented (Dukhin et al., 2005). The zeta potential of all SLNs was significantly reduced to almost neutrality (-5 to +5 mV), and were below that required for any meaningful electrostatic stabilisation. Zeta potentials below |5| mV often result in particle coagulation (Wu et al., 291 Chapter 10 A pH-dependent study on the stability of SLNs
2011a). Despite significant reduction in the zeta potential, there was no significant increase in the particle size of the SLNs in acidic conditions (i.e. pH 1.1 and pH 3.5) after 4 h and 24 h of incubation. This may be due to steric stabilisation provided by the non- ionic surfactant. Similar results were observed in the pH-dependent study reported earlier (Section 10.4.1 and 10.4.2).
There was a significant increase in the particle size when incubated at pH 7.4 after 4 h of incubation. The increased particle size may be due to (1) depletion of the electrical double layer (therefore, loss of electrostatic stabilisation) and/or (2) depletion of the non-ionic surfactant layer at high pH as observed in the pH-dependent stability study (therefore, loss of steric stabilisation).
From the results, it was observed that the particle size of drug-free SLNs and indomethacin-loaded SLNs increased considerably at lower pH (Figures 10.3 and 10.6 respectively). There was a slight increase in the particle size of miconazole nitrate-loaded SLNs (Figure 10.7) and all SLNs incubated with simulated GI fluid of pH 1.1 and 3.5 (Figure 10.12 – 10.14). These results indicated that drug-free SLNs and indomethacin- loaded SLNs had lower stability than miconazole nitrate-loaded SLNs and SLNs incubated in simulated GI fluids at lower pH. By contrast, a considerable increase in particle size of all SLNs was observed at high pH levels. Interestingly, the lowest particle size of SLNs was observed when incubated in simulated GI fluid of pH 7.4; however, particles were found to sediment within 4 h. These results suggested that the SLNs were unstable at high pH values. All these findings suggested that although pH was an important parameter clearly influencing the stability of SLNs and having an optimal value at the native pH of the dispersion, the influence of presence of electrolytes was less clear needs further investigation.
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10.5 Conclusions
The physical stability of the drug-free and drug-loaded SLNs was studied in this chapter using particle size and zeta potential as potential indicators of stability. The physical stability of the SLNs was found to be pH-dependent. The particle size was found to increase significantly under high pH conditions, and minimally increase at very low pH conditions. The lowest particle size was found at a pH that was close to the pKa of stearic acid (~ 4.9). The zeta potential values were found to increase in magnitude, becoming more “negative” in high pH conditions. It was concluded that physical stability is more related to steric stabilisation, or at least steric-like stabilisation, than electrostatic stabilisation. Preliminary results also show that EE and LC are pH-dependent.
The SLNs incubated with simulated GI fluids at low pH were found to be stable despite a slight increase in particle size. Although the SLNs were not completely stable at pH 7.4, they were stable when refrigerated and further study using different buffers with different ionic strengths and in presence of proteins/enzymes may result in a stable dispersion at room temperature as well. This could provide very useful further study. The in vivo behaviour of the SLNs may be quite different to the one observed here due to the complexity of the environment.
These encouraging results indicate that future development of SLNs may facilitate oral and/or topical administration of SLNs.
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Chapter 11 Summary and Future Perspectives 11
Summary of Conclusions and Future Perspectives
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11.1 Conclusions
11.1.1 Introduction and optimisation of a novel microwave-assisted microemulsion technique for production of solid lipid nanoparticles (SLNs)
The first specific aim of Chapter 4 was to introduce the use of microwave heating in the production of SLNs based on a “microemulsion-to-SLNs” principle. The method was successfully introduced, and henceforth referred to as the “microwave-assisted microemulsion technique”.
The second specific aim was to systematically investigate the formulation ingredients to achieve an optimized “model” SLNs formulation for further investigation. Several selected lipids and surfactants were used in varying combinations and concentrations based on a 22 experimental design (with one centre point) to produce ninety SLNs formulations. The type of lipid and surfactants had as much influence on the production as their concentration.
The selection of an optimized formulation was carefully done after performing preliminary particle characteristics measurements. The particle size served as the primary criterion for selection of an optimized formulation. Smaller particles are likely to remain more stable, and therefore, likely to encapsulate more amounts of drugs and exhibit targeted responses (Muller et al., 2002; Wissing et al., 2004). Producing small particles without generating a polydispersed sample whilst also maintaining a reasonable zeta potential has been a challenge in SLNs research. The polydispersity index and zeta potential served as secondary selection criteria.
Based on particle size characteristics, at least two of the six lipids tested in this study, stearic acid and Imwitor® 900K, were found to consistently produce particles in the desired submicron (or nanometre-size) range. It was also observed that the combination of stearic acid and Tween® 20 produced the smallest particles with narrow size distribution and reasonable zeta potential values. Therefore, this formulation was selected for future studies.
The other aim of this chapter was to investigate the influence of excipients on the formulation. The excipients that were investigated in this chapter were addition of a base, an acid, a salt, co-emulsifiers and stabilisers. The solvent used as a dispersion medium during microwave heating is a major constituent of SLNs formulations. The effect of solvents on particle characteristics of SLNs was investigated, and water was found to
296 Chapter 11 Summary and Future Perspectives produce SLNs with smallest particle size, and was therefore, selected as the dispersion medium in this thesis.
The stability of the SLNs was investigated at different storage temperatures (4C, 25C and 37C) for 60 days. An increase in particle size was seen as an indicator of particle instability (Freitas and Muller, 1998; Heurtault et al., 2003; Kovacevic et al., 2011, 2014; Vivek et al., 2007). While SLNs were found to flocculate irreversibly after first few days of storage at 25C and 37C, they were found to remain reasonably stable after 60 days when refrigerated.
Since the main objective of the thesis was to select a single formulation to understand and develop the microwave-assisted microemulsion technique in the production of SLNs, a more systematic series of experiments with additional excipients was not pursued. A simple SLN formulation composed of stearic acid and Tween® 20 was selected for future experiments.
11.1.2 Physicochemical characteristics of Solid Lipid Nanoparticles (SLNs): Microwave-assisted microemulsion technique Vs. Conventional microemulsion technique
The main objective of Chapter 5 was to compare the microwave-assisted microemulsion technique, reported for the first time in this thesis, to the conventional microemulsion technique. The specific aim was to compare and contrast microwave heating and thermal used in the microemulsion techniques.
The selected SLN formulation composed of stearic acid as the lipid core and surface- tailored with Tween® 20 as the surfactant was used for this purpose. The use of controlled microwave reaction conditions (set temperature, microwave power and holding time at the set temperature) was considered to be the key to the development of the successful formulation strategy for SLNs.
The suitability of the microwave-assisted microemulsion technique was investigated by evaluating the product quality in terms of particle characteristics. Tetracycline, an antibacterial drug, was selected as the “drug of choice” to assess the applicability of this technique to encapsulate the drug. Similar drug-loaded SLNs were prepared in parallel by the conventional microemulsion technique. An extensive physicochemical
297 Chapter 11 Summary and Future Perspectives characterisation of the SLNs formulations prepared by the two techniques was performed to realise the main objective of this chapter.
The particle characteristics of the SLNs formulations revealed that replacement of the conventional thermal heating process with a temperature-controlled microwave heating process produced SLNs with smaller particle sizes, narrow polydispersity and acceptable zeta potential values. The SLNs had a negative zeta potential possibly due to the dissociation of stearic acid. Coupled with these physical characteristics, the SLN formulations produced with microwave-assisted technique were demonstrated to achieve higher encapsulation efficiency and loading capacity.
The solid nature is one of the prominent features of SLNs which imparts controlled- release capability (Das et al., 2012). The thermal studies conducted using DSC revealed the solid nature of the particles with reduced crystallinity of stearic acid in SLNs (relative to bulk stearic acid) and successful incorporation of drugs. These results were supported by diffraction studies conducted using XRD.
The next main focus of this chapter was to evaluate and compare the short-term stability of SLNs formulations produced by the two techniques. An increased particle size of SLNs would indicate an unstable formulation. Although there was no significant increase in particle sizes of SLNs formulations produced by either technique, the particle size of SLNs produced by microwave-assisted techniques remained low at refrigerated conditions indicating production of stable SLNs formulations.
The other main focus of this chapter was to compare the release of drug from the two SLNs formulations. Although the drug release profiles appear to be similar, a greater amount of drug was released by SLNs produced by the conventional technique, suggesting a slower release of drug from SLNs produced by the microwave-assisted technique. However, based on the drug release data, the apparent initial burst release of tetracycline strongly suggests a core-shell structure of the tetracycline-loaded SLNs, comparable to similar structures reported in the literature (Grassi et al., 2003; Xu et al., 2011).
The loss of antibacterial activity due to the influence of production technique was investigated by antimicrobial susceptibility tests performed on a Gram-positive bacterium, S. aureus, and a Gram-negative bacterium, E. coli. Inhibition of growth of these bacteria suggested that that tetracycline was chemically stable during the
298 Chapter 11 Summary and Future Perspectives production. Growth of bacteria in the presence of drug-free SLNs suggested non-toxicity of SLNs formulations towards microbes.
There was a concern that production of SLNs using microwave heating may produce toxic species during the production technique. The biocompatibility of drug-loaded SLNs on human A549 cells was investigated by performing cell viability (or cytotoxicity) assays. The cell viability showed that the cytotoxic concentration (CC50) of SLNs was above the highest tested concentration i.e. 100 µg/mL. Whilst this is not a conclusive test of biocompatibility, the lack of any significant toxic response is encouraging.
11.1.3 Incorporation of non-steroidal anti-inflammatory drugs (NSAIDs) into SLNs
The main objective of Chapter 6 was to assess if the microwave-assisted microemulsion technique was suitable for production of non-steroidal anti-inflammatory drugs-loaded SLNs. To achieve this objective, three model lipophilic drugs from this category of drugs – indomethacin, ketoprofen and nimesulide – were selected.
The first specific aim was to characterise the drug-loaded SLNs produced in this study. Particle characterisation revealed that the drug-loaded SLNs were within the nanometre range (250-300 nm). Although the SLNs produced in this study had a negative zeta potential, it was concluded that incorporation of drug into the SLNs disrupted the particle surface and, therefore, they had a slightly lower zeta potential compared to drug-free SLNs. The drug-loaded SLNs had a reasonably high encapsulation efficiency of 70 - 90% and loading capacity of 3.5 - 4.5% (w/w). Prior to encapsulation studies, it was demonstrated that centrifugal ultrafiltration was an effective separation method to determine the “true” amount of drug in the dispersion medium. The values quoted in this study, therefore, are deemed to give a practical approximation. Nevertheless, the physicochemical properties of the drugs had a major influence on their encapsulation into the drug-loaded SLNs. Though the solid nature of SLNs was confirmed in the earlier studies wherein tetracycline was loaded into the SLNs, the thermal nature (referred to as crystallinity and polymorphism of lipids in SLNs) often varies with the drugs encapsulated within the SLNs. The DSC studies, supported by XRD data, indicated that the drug- loaded SLNs produced in this chapter were solid, with reduced crystallinity.
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The other major focus of this chapter was to assess the biocompatibility of the SLNs and evaluate their anti-inflammatory effect on human cells lines. The biocompatibility of the SLNs was evaluated by determining the viability of human A549 cells and mouse 3T3- L1 cells. The drug-loaded SLNs were found to be non-toxic according to these tests. Inflammation in the human A549 cells was induced with LPS and the anti-inflammatory effect of the drug-loaded SLNs was evaluated on LPS-induced A549 cells by determining the inhibition of IL-6 and IL-8 secretion. It was also concluded that TNF-α, IL-1β and IL-12 were not secreted by the A549 cells following LPS-induction, indicating that the anti-inflammatory action of the drug was not adversely affected.
All these findings indicate that SLNs can effectively encapsulate NSAIDs and suggest that the SLNs may act as potential carriers of these drugs for the treatment of inflammatory disorders.
11.1.4 Incorporation of anti-fungal agents into SLNs
In order to achieve the overall objective of this thesis (i.e. developing the novel microwave-assisted microemulsion method for SLNs production), it was considered useful to demonstrate successful (or otherwise) encapsulation of different drug molecules with different chemistries. Therefore, the main objective of Chapter 7 was to extend the study to a different class of drug – antifungal drugs that have a different chemistry. The antifungal drugs selected for this purpose – clotrimazole, miconazole nitrate and econazole nitrate – are all synthetic imidazole-type drugs.
The lipophilic model drugs selected in this study were successfully incorporated into SLNs by the microwave-assisted microemulsion method. Like SLNs loaded with NSAIDs in the earlier chapter, the physicochemical characterisation demonstrated that SLNs loaded with antifungal drugs had small particle sizes (within the desired nanometre range, i.e. 250-300 nm) with narrow size distribution. While the zeta potential of clotrimazole-loaded SLNs had a negative zeta potential (due to dissociation of stearic acid), the miconazole nitrate-loaded and econazole nitrate-loaded SLNs had a positive zeta potential (possibly due to the cationic nitrogen atom of the drug protruding from the SLN surface). The drug-loaded SLNs had acceptable encapsulation efficiencies (72 - 88%) and loading capacities (3.6 - 4.4%).
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Another focus of research was to evaluate the solid and the crystallinity nature of the lipid material post SLN production. Thermal studies conducted on the SLNs using DSC revealed that solid SLNs with reduced crystallinity were produced. The XRD analysis was in good alignment with the DSC data.
The other major focus of this chapter was to assess the biocompatibility of the SLNs. The cell viability assays performed on human A549 cells and mouse 3T3-L1 cells demonstrated that the drug-loaded SLNs were non-toxic at all concentrations tested in this study. In addition, it was also essential to confirm no loss of antifungal activity of the encapsulated drug molecules. In order to achieve this, the antimicrobial susceptibility of the drug-loaded SLNs was conducted against yeast cells, Candida albicans. Susceptibility of C. albicans to drug-loaded SLNs suggested that fungistatic activity of drugs was maintained when incorporated into the SLNs.
All these findings indicate that SLNs can be effectively used as potential carriers of antifungal drugs for the treatment of candidal infections.
11.1.5 In vitro drug release properties of SLNs
The main objective of Chapter 8 was to investigate the drug release from drug-loaded SLNs discussed in this thesis in Chapters 6 and 7. The release of drugs from SLNs into phosphate buffered saline (pH 7.4) containing Tween® 20 was performed using the most commonly employed dialysis bag technique.
The release of drugs from drug-loaded SLNs exhibited a biphasic release behaviour. The unencapsulated (or free) drug molecules, very small nanoparticles (~10-15 nm, although rare) present in the SLNs formulations escaped the dialysis bag, drug molecules adsorbed on the surface and/or encapsulated within the shell of the SLNs or within the surfactant layer were released in phase I constituting the burst release phase. The drug molecules that were encapsulated within the SLNs core were later released during phase II.
The SLNs loaded with NSAIDs exhibited an initial burst of drugs followed by a sustained release; while SLNs loaded with antifungal drugs (i.e. miconazole nitrate, econazole nitrate and clotrimazole) exhibited a slow and sustained but incomplete release of drugs after 24 h. The amount of drug released after 24 h was significantly lower than the SLNs loaded with the NSAIDs, suggesting that SLNs loaded with antifungal agents have a
301 Chapter 11 Summary and Future Perspectives different structure. Based on the release patterns, SLNs loaded with NSAIDs appear to have more drug encapsulated within the shells and less within the core, indicative of a drug-enriched shell type structure. In contrast, SLNs loaded with antifungal drugs resemble drug-enriched core type structures.
A second major focus of this chapter was to use mathematical expressions to fit the release data and investigate the mechanisms involved in the release of drugs from the SLNs. Mathematical model fitting was performed using a few selected mechanistic realistic and empirical/semi-empirical drug release kinetic models. The best fitting model was selected on the basis of model selection criteria: adjusted coefficient of 2 determination (R adjusted), the Akaike information criterion (AIC) and the model selection criterion (MSC). Models such as the Higuchi model and the Korsmeyer-Peppas model were used to determine if the drug release was due to diffusion transport mechanism and, if so, the role of Fickian or non-Fickian mechanisms was investigated. While the drug release from SLNs loaded with NSAIDs was found to be governed by Fickian diffusion, non-Fickian diffusion was responsible for release of antifungal drugs from the SLNs. These results suggested that release of NSAIDs from SLNs was diffusion-controlled and that of antifungal drugs was both – diffusion- and dissolution-controlled. However, the release profiles of all drugs fitted very well to the Weibull model, an empirical model, which aids in the predicting the time required to release about 63.2% of drug from the SLNs and also the shape (pattern) of the drug release.
The third focus of the chapter was to demonstrate that the release profiles of drugs with different drug chemistries were, or were not, dissimilar. In order to achieve this aim, the drug release patterns of one representative drug from each drug class was compared by pairwise procedures (determination of similarity and difference factors and determination of Rescigno indices) and the bootstrap f2 method. The release of these two drugs was found to be dissimilar by these methods. The difference in the release profiles was assumed to be due to the difference in the physicochemical properties of drugs such as partition coefficients. Further investigation would be necessary to confirm that those partition coefficients differ as a result of a drug-enriched shell in one case, and a drug- enriched core in the other, however this is a good working hypothesis at the moment, perhaps complicated by a third option of an homogenous matrix. Also, it must be acknowledged here that these profile comparison methods are rarely used to compare
302 Chapter 11 Summary and Future Perspectives release profiles of different drugs from similar drug carriers. Therefore, the results were treated qualitatively rather than quantitatively.
11.1.6 An investigation of the uptake mechanism and pathway of SLNs used as intracellular drug transporters
After successful encapsulation of a variety of drug molecules from three different drug classes, and with different chemistries, it was essential to demonstrate that the SLNs were well suited for transport of drug molecules into the target cells. SLNs have been actively sought as intracellular drug transporters in the recent years. The main objective of Chapter 10 was to demonstrate that the SLNs prepared using the microwave-assisted technique were internalised by the human epithelial A549 and HeLa cells.
In order to achieve this objective, SLNs loaded with Rhodamine 123 (a fluorescent probe) were prepared. The fluorescent SLNs had a small particle size (within the nanometre range, < 300 nm), narrow size distribution (PI values < 0.2) and a negative zeta potential (~ -20 mV). Most of the SLNs loaded with drugs prepared in this thesis, with exceptions of miconazole nitrate-loaded SLNs and econazole loaded-SLNs, had similar physicochemical characteristics. Therefore, it was assumed that the internalisation of drug-loaded SLNs would be very similar to fluorescent SLNs.
The small size of SLNs, like most other nanoparticles, are deemed to be suitable for cellular uptake by epithelial cells (Blechinger et al., 2013; Canton and Battaglia, 2012; de Mendoza et al., 2011; Li et al., 2014; Verma and Stellacci, 2010; Vranic et al., 2013). Studies also suggest that small particles with slight negative charge can easily move through tumour tissue in animal models (Nomura et al., 1998). These findings indicate that SLNs such as the ones produced in this study are potential candidates for drug delivery in animal models.
The next main focus of the chapter was to determine the energy-dependency of the transport mechanism. Inhibition of energy-dependent process was achieved by incubating the fluorescent SLNs-treated epithelial cells in refrigerated conditions. Imaging techniques and FACS data demonstrated that the fluorescence intensity of the cells was almost negligible. The cellular uptake of SLNs was, therefore, through endocytosis. Similar results have been reported earlier (Chai et al., 2014; Martins et al., 2012).
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The other aim of this chapter was to investigate the specific pathway that mainly contributed to the cellular uptake of SLNs. A detailed dissection of the intracellular internalisation process was conducted by the use of pharmacologic inhibitors. The various pathways of endocytosis, i.e. clathrin-mediated endocytosis, caveolae-mediated endocytosis, and macropinocytosis, were specifically inhibited to determine the role of those pathways in the cellular uptake of SLNs. It was concluded that SLN uptake by epithelial cells was mediated by the formation of clathrin-coated pits in their cellular membranes, with little or negligible caveolae, lipid rafts or phagocytosis. These results were consistent with previous experiments using other lipid nanoparticle formulations (Chai et al., 2014; Martins et al., 2012).
These findings provide increased knowledge on the cellular uptake of SLNs by epithelial cells. The data may assist future development of SLNs as potential candidates in drug delivery applications.
11.1.7 An investigation of the pH-dependence and electrolyte-dependence on the physical stability of the SLNs
The encouraging results from previous chapters established that the microwave-assisted technique was suitable to produce SLNs with improved physicochemical characteristics, drug release properties and ability to be taken up by human cells. It was, now, necessary to demonstrate that the SLNs were suitable for administration through oral and/or topical routes.
The first aim of Chapter 10 was to establish a pH-particle stability relationship. In order to achieve this aim, the physical stability of particles was evaluated as a function of pH. Particle size and zeta potential were taken as indicators of physical stability. A significant increase in particle size and/or decrease in zeta potential were considered as a measure of instability of the SLNs. Samples were also simply observed visually to ensure no obvious instability not detected by particle size or zeta potential changes. The physical integrity (or stability) of SLNs prepared in this chapter was pH-dependent. The influence of pH on physical stability of emulsions (Qian et al., 2012), titanium dioxide nanoparticles (Suttiponparnit et al., 2011) and chitosan tripolyphosphate nanoparticles (Gan et al., 2005) has been studied previously. The dependence of physical stability of
304 Chapter 11 Summary and Future Perspectives
SLNs on pH has also been reported earlier (Schwarz and Mehnert, 1999; Shahgaldian et al, 2003; Zimmermann and Muller et al., 2001).
The particle size increased slightly at very low pH and had a positive zeta potential. The particle size at the formulation pH was the smallest in the entire range of pH conditions tested. The particle size, thereafter, was found to increase with pH and zeta potential was also found to increase in magnitude. An increase in particle size despite an increase in zeta potential suggested that the SLNs were stabilised by at least a combined steric and electrostatic stabilisation mechanism, rather than simple electrostatic forces alone. Whilst it makes sense that the negatively charged stearate anions formed due to dissociation of stearic acid at the particle surface contributed to electrostatic stabilisation, it is also highly likely that the surface coverage of SLNs with excess of Tween® 20 resulted in micellar condensation which contributed to steric-like repulsion. Electrostatic stabilisation due to fatty acid dissociation (Alex et al., 2011) and steric-like repulsion due to high concentrations of non-ionic surfactant Tween® 20 (Dimitrova and Leal-Calderon 1999; 2000) have been previously reported. Note that these patterns did not significantly change when the SLNs were loaded with either of the drugs tested. The second aim of this chapter was to determine the effect of pH on encapsulation efficiency and loading capacity of drug-loaded SLNs. A preliminary study was undertaken at the highest pH tested in this chapter (i.e. pH 10). The results suggested that these parameters increased significantly in indomethacin-loaded SLNs and had minimal influence on miconazole- loaded SLNs.
The third aim of the chapter was to study the influence of simulated gastrointestinal fluids (and therefore, electrolytes) on the physical stability of the drug-free and drug-loaded SLNs. The results indicated a slight increase in particle size when incubated under acidic conditions (i.e. pH 1.1 and pH 3.5) immediately after incubation. However, the increase in particle size after 4 h and 21 h was minimal. These results suggest that the SLNs produced in this chapter were stable in simulated gastric conditions. The zeta potential, however, decreased significantly at all gastric conditions. The depletion of the electrical double layer due to the presence of salts in the gastric fluids is most probably the reason for the decrease in the zeta potential (Somasundaran et al., 2009). These results also further confirms the importance of steric-like repulsion by the non-ionic surfactant. The particles incubated at pH 7.4 were found to sediment after 4 h and were thus considered
305 Chapter 11 Summary and Future Perspectives unstable at this higher pH. Samples would need, therefore, to be kept at their native pH or lower, and not stored at higher pH values.
Overall, these results suggest that the SLNs can be considered as potential carriers of drugs through oral and/or topical route.
11.1.8 Summary of conclusions
In summary, a novel and facile microwave-assisted microemulsion method of SLN production was developed in this thesis. Small particle sizes and reasonably high encapsulation efficiency of the SLNs produced by this method make it a promising production procedure. In addition to desired physicochemical characteristics, the SLNs produce by this technique exhibited the potential to provide sustained release of drugs. The SLNs loaded with drugs were found to be biocompatible and easily taken up by epithelial cells, predominantly by endocytosis. A wide range of drugs, comprising several different classes, were all successfully loaded into the SLNs and the physical properties of those SLNs were found to be superior to those formed by conventional heating methods.
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11.2 Future Perspectives
11.2.1 Preparation of the SLNs
The research in this thesis was aimed at developing a microwave-assisted technique for the production of SLNs. Following preliminary studies, an optimized formulation containing stearic acid and Tween® 20 was used for all the studies carried out in subsequent analyses. However, it was observed that the lipid and surfactants have a major role in determining the physical characteristics of the SLNs and other systems were not found to be as successful. Future work should, therefore, be undertaken on a variety of other lipids and surfactants. The selection of lipid-surfactant(s) combination should be made using methods such as HLB matching or contact angle measurements in addition to statistical methods such as the mathematical experimental design used in this study. More systematic trials of surfactant mixtures may prove efficacious for the less successful lipids and may be required before the microwave technique proves of general use.
Nanostructured lipid carriers (NLCs) are second generation SLNs that have a lipid matrix composed of binary mixtures of lipids (two solid lipids or one solid and one liquid lipid). The application of this novel technique in their production would be beneficial given the added advantage of microwave heating. Surface modification with receptor-specific ligands is another area that could be explored in SLN research.
A thorough understanding of the interaction of microwave energy with individual ingredients and the effect of dielectric constants should be established to achieve a better selection of ingredients in SLN production by the microwave-assisted microemulsion technique.
11.2.2 Structure of the SLNs
Understanding the internal structure, or ultrastructure, of the SLNs is one of the most critical factors that need special attention. Although several studies have shown an association of drug molecules with SLNs, it remains to be proven whether the drug is really encapsulated or whether it co-exists as a drug nano-suspension. The structure of SLNs not only influences the drug release properties and stability but also influences some of the important biological processes including biodistribution and cellular uptake.
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Assuming that the drug is encapsulated, further understanding of its location (core, shell or molecularly dispersed) is particularly important in understanding the release properties of the carrier system. For better understanding of SLNs and their better development as drug vehicles, it is necessary to study the ultrastructure of this lipid matrix. Future work, such as small angle X-ray scattering and small angle neutron scattering, should be undertaken to provide insights into the SLN structure. A parallel DSC study with the SAXS would provide a thorough understanding of the changes in the lipid phases that play a critical role in drug release and stability of SLNs.
The particle morphology was studied by scanning electron microscopy (SEM) where sample preparation such as air-drying and gold coating may have altered the particle morphology. Future studies should include more sophisticated techniques such as cryo- field emission scanning electron microscopy (cryo-FESEM).
11.2.3 Stability of the SLNs
The SLNs produced in this study were found to be stable for at least 28 days at refrigerated conditions. The particle size was used as an indicator of physical stability. Future research should be undertaken to investigate the chemical stability of the carriers and the drug molecules. An attempt should be made to achieve physical stability at ambient temperatures. In addition, long-term storage, and storage in different packaging materials and conditions should also be undertaken.
The physical stability of drug-free and drug-loaded SLNs (indomethacin-loaded and miconazole nitrate-loaded SLNs) was assessed at different pH and simulated gastric conditions. Though the particle characteristics showed similar trends for both the drugs, the encapsulation efficiency of indomethacin-loaded SLNs decreased significantly at pH 10. In contrast, the encapsulation efficiency of miconazole nitrate-loaded SLNs was not affected at pH 10. An attempt should, therefore, be made to undertake such encapsulation studies at different pH conditions and with different drug-loaded SLNs. In addition to pH-dependence, the physical stability of SLNs was electrolyte-dependent. An extensive study should be undertaken at different ionic strengths and/or in presence of different pH conditions.
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11.2.4 Drug release studies
The drug release studies suggested that the release profiles differed for different drug chemistries. An attempt should be made to develop the product by incorporating the drug-loaded SLNs with a burst release into hydrogels to slow the release the drug molecules. According to FDA guidelines, the release data must be obtained at different pH conditions such as pH 1.2, pH 6.8 and pH 4.5. Studies investigating release of drugs from SLNs at different pH and simulated body conditions should be undertaken to develop these drug carriers further.
11.2.5 In vivo studies
Despite excellent in vitro success, many potential drug delivery vehicles fail because of the disappointing in vivo results. The ultimate aim for future SLN research should be to investigate the in vivo effects of the SLNs loaded with drugs in animal models. An extensive pharmacokinetic study should be undertaken to establish the in vitro in vivo correlation (IVIVC).
The pH-dependent study was carried out in vitro. The in vivo situation is much more complex such that the SLNs that were stable in vitro may not be equally stable in vivo and, vice versa, those of which were unstable in vitro may be stable in vivo. The different gastrointestinal proteins (charged and uncharged) may have a stabilizing and/or destabilizing effect on the SLNs. Enzymatic degradation can lead to disaggregation of SLNs (Olbrich et al 1999). Hence, a thorough study should be undertaken to study such influences in environments which mimic these conditions. In other words, the focus of this thesis has been on the synthesis, stability, storage and drug loading capacity of the novel SLNs. Focus can now shift to their efficacy as drug delivery systems.
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References
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311 References
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358 Appendices
Appendices
359 Appendices
Figure A.5.1
7
6
5
4
3
2
1 Area 100000) under (xcurve Area 0 0 20 40 60 80 100 Concentration of tetracycline (µg/ml)
A.5.1 Calibration curve of standard solutions of tetracycline (R2 = 0.999).
360 Appendices
Figure A.5.2
A.5.2 A typical report generated after microwave reaction. The set temperature in this case was 85C for 10 min at the set point. The microwave power was set to reach maximum of 18 W.
361 Appendices
Figure A.6.1 uV (x100,000) 1.0
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
0.00.51.01.52.02.53.03.54.0 (a) 4.5 5.0 5.5 6.06.57.07.58.08.59.09.5min
I.6.1 (a) Determination of indomethacin by HPLC. The chromatogram shows that indomethacin was eluted at 5.2 min. The concentration of indomethacin was 100 µg/mL. Injection volume was 5 µL. The wavelength of tetracycline detection was set at 318.
7
6
5
4
3
2
1 Area under Area curve 100000)(x 0 0 20 40 60 80 100 Concentration of indomethacin (µg/mL) (b)
A.6.1 (b) Calibration curve of standard solutions of indomethacin (R² = 0.995).
362 Appendices
Figure A.6.2 uV (x100,000)
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0.00.51.01.52.02.53.0 (a) 3.5 4.0 4.5 5.05.56.06.57.07.58.08.59.09.5min
A.6.2 (a) Determination of ketoprofen by HPLC. The chromatogram shows that ketoprofen was eluted at 4.2 min. The concentration of ketoprofen was 100 µg/mL. Injection volume was 5 µL. The wavelength of ketoprofen detection was set at 254.
30
25
20
15
10
5 Area 100000) under (xcurve Area 0 0 20 40 60 80 100 Concentration of ketoprofen (µg/mL) (b)
I.6.2 (b) Calibration curve of standard solutions of ketoprofen (R² = 0.999).
363 Appendices
Figure A.6.3 uV (x100,000) 1.75
1.50
1.25
1.00
0.75
0.50
0.25
0.00
0.00.51.01.52.02.53.0 (a) 3.5 4.0 4.5 5.05.56.06.57.07.58.08.59.09.5min
A.6.3 (a) Determination of nimesulide by HPLC. The chromatogram shows that nimesulide was eluted at 4.2 min. The concentration of nimesulide was 100 µg/mL. Injection volume was 5 µL. The wavelength of nimesulide detection was set at 295.
100 90 80 70 60 50 40 30 20
Area 100000) under (xcurve Area 10 0 0 20 40 60 80 100 Concentration of nimesulide (µg/mL) (b)
I.6.3 (b) Calibration curve of standard solutions of nimesulide (R² = 0.997).
364 Appendices
Figure A.6.4
400
300
200
100 Derived rate (kcps) count Derived
0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Concentration of indomethacin-loaded SLNs (%v/v) (a)
A.6.4 (a) Light scattering of indomethacin-loaded SLNs in water (R² = 0.995).
400
300
200
100 Derived rate (kcps) count Derived
0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Concentration of ketoprofen-loaded SLNs (%v/v) (b)
A.6.4 (b) Light scattering of ketoprofen-loaded SLNs in water (R² = 1.000).
365 Appendices
Figure A.7.1 uV (x100,000)
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0.00.51.01.52.02.53.03.54.04.55.0 (a) 5.5 6.0 6.57.07.58.08.59.09.5min
A.7.1 (a) Determination of clotrimazole by HPLC. The chromatogram shows that clotrimazole was eluted at 5.8 min. The concentration of clotrimazole was 100 µg/mL. Injection volume was 5 µL. The wavelength of clotrimazole detection was set at 210 nm.
45 40 35 30 25 20 15 10 5 Area 100000) under (xcurve Area 0 0 20 40 60 80 100 Concentration of clotrimazole (µg/mL) (b)
A.7.1 (b) Calibration curve of standard solutions of clotrimazole (R² = 0.993).
366 Appendices
Figure A.7.2 uV (x10,000)
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
0.00.51.01.52.02.53.03.54.04.55.05.56.06.5 (a) 7.0 7.5 8.08.59.09.5min
A.7.2 (a) Determination of miconazole nitrate by HPLC. The chromatogram shows that miconazole nitrate was eluted at 7.5 min. The concentration of miconazole nitrate was 100 µg/mL. Injection volume was 5 µL. The wavelength of miconazole nitrate detection was set at 230 nm.
12
10
8
6
4
2 Area 100000) under (xcurve Area 0 0 20 40 60 80 100 Concentration of miconazole nitrate (µg/mL) (b)
A.7.2 (b) Calibration curve of standard solutions of miconazole nitrate (R² = 1.000).
367 Appendices
Figure A.7.3 uV (x100,000)
3.75
3.50
3.25
3.00
2.75
2.50
2.25
2.00
1.75
1.50
1.25
1.00
0.75
0.50
0.25
0.00
0.00.51.01.52.02.53.03.54.04.55.0 (a) 5.5 6.0 6.57.07.58.08.59.09.5min
A.7.3 (a) Determination of econazole nitrate by HPLC. The chromatogram shows that econazole nitrate was eluted at 5.9 min. The concentration of econazole nitrate was 100 µg/mL. Injection volume was 5 µL. The wavelength of econazole nitrate detection was set at 200 nm.
45 40 35 30 25 20 15 10 5 Area 100000) under (xcurve Area 0 0 20 40 60 80 100 Concentration of econazole nitrate (µg/mL) (b)
A.7.3 (b) Calibration curve of standard solutions of econazole nitrate (R² = 0.999).
368 Appendices
Figure A.7.4
500
400
300
200
100 Derived rate (kcps) count Derived
0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Concentration of miconazole nitrate-loaded SLNs (%v/v)
A.7.4 (a) Light scattering of miconazole nitrate-loaded SLNs in water (R² = 1.000).
400
300
200
100 Derived rate (kcps) count Derived
0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Concentration of econazole nitrate-loaded SLNs (%v/v)
A.7.4 (b) Light scattering of econazole nitrate-loaded SLNs in water (R² = 0.997).
369