Food Protein-Based Core-Shell Nanocarriers for Oral Drug Delivery Applications

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Theses and Dissertations

2017 Food Protein-based Core-shell Nanocarriers for Oral Drug Delivery Applications: (Influence of Shell Composition on In vitro and In vivo Functional Performance of Zein Nanocarriers MD Saiful Islam South Dakota State University

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FOOD PROTEIN-BASED CORE−SHELL NANOCARRIERS FOR ORAL DRUG

DELIVERY APPLICATIONS: INFLUENCE OF SHELL COMPOSITION ON IN

VITRO AND IN VIVO FUNCTIONAL PERFORMANCE OF ZEIN NANOCARRIERS

MD SAIFUL ISLAM

A dissertation submitted in partial fulfillment of the requirements for the

Doctor of Philosophy

Major in Pharmaceutical Sciences

South Dakota State University

2017

iii

THIS DISSERTATION IS DEDICATED TO MY PARENTS

ACKNOWLEDGMENTS

So many peoples have a positive influence throughout my graduate study at South Dakota

State University (SDSU).

First, I would like to express my heartfelt gratitude to Dr. Omathanu Perumal for his continuous support, motivation, guidance, and supervision during my Ph.D. research work. I also want to express my sincere gratitude and appreciation to advisory committee members including Dr. Xiangming Guan, Dr. Xiuqing Wang and Dr. Alan Davis for their continuous encouragement, direction throughout my Ph.D. degree. I also want to express my gratitude to my previous advisor Dr. Hongwei Zhang for his guidance, support, and supervision for first two years. I would like to thank all my previous and current lab members including Dr. Mohammed Alqahtani, Dr. Kaushalkumar Dave, Dr. Ranjith

Averineni, Dr. Manju Saraswathy, Mibin Kuruvilla Joseph and Abdulsalm Alqahtani for their kind help for my rapid progress with the assigned project in the lab.

It was my great pleasure to be a member of Pharmacy family at SDSU which reminds me the humble behavior of Dr. Chandradhar Dwivedi. I greatly appreciate Dr.

Shafiqur Rahman for his continuous help and motivation during my Ph.D. degree. I would like to thank Dr. Jayarama Gunaje for his motivation and encouragement during my Ph.D. research work. I appreciate the help of Dr. Joshua Reineke by providing enormous useful information and assisting me with bioadhesive experiments. I want to express my gratitude to Dr. Hemchand Tummala for helping me in learning in vivo imaging instrument and supervising fludrocortisone project. I would like to thank Dr. Monzurul Amin Roni, Dr.

Muzaffar Abbas and Dr. Sayef Abdullah for their support and helping me with ELISA experiment v

I want to thank Dr. James Hoefelmeyer and Dr. Aravind Baride from Department of

Chemistry, University of South Dakota, Vermillion for his help with the transmission electron microscopy (TEM) studies. I also want to thank Dr. Jayarama Gunaje for his continuous encouragement and help in Caco-2 cell culture study.

I owe my gratitude and utmost respect to my wonderful parents for their unconditional and sincere love, support, and encouragement. I am forever indebted to my dear wife, for her love, patience and exceptional forgiveness that provided me the strength and confidence to complete my dissertation.

Lastly, but not least of all, I will always remain grateful to the department of

Pharmaceutical Sciences, College of Pharmacy and Allied Health Professions at South

Dakota State University, for Ph.D. fellowship and financial support.

CONTENTS

Page no.

LIST OF FIGURES------xi

LIST OF TABLES------xv

SYMBOLS/ABBREVIATIONS------xviii

ABSTRACT------xx

CHAPTER ONE: Introduction------1

1.1.Oral drug delivery------1

1.2. Oral drug absorption------1

1.2.1. Gastrointestinal anatomy and physiology------1

1.2.2. Mechanism of oral drug absorption------4

1.3. Oral drug delivery challenges------12

1.3.1. Physiological barriers to oral drug delivery------12

1.3.2. Influence of physicochemical and biopharmaceutical factors on 19 oral drug delivery------

1.4. Different approaches for oral drug delivery------23

1.4.1. Physical or chemical modification of drug molecules------23

1.4.2. Drug carriers------27

1.4.2.1. Lipid-based delivery systems------29

1.4.2.2. Polymeric nanocarriers------39

1.5. Natural polymers------46

1.5.1. Polysaccharide-based nanocarriers------46 vii

1.5.2. Protein polymers ------48

1.5.2.1. Animal proteins------50

1.5.2.2. Plant proteins------52

1.6. Scope and objectives------57

CHAPTER TWO: Preparation and Study of Structure-Function 59 Relationship of Core-Shell Nanocarriers------

2.1. Introduction------60

2.2. Materials and methods------65

2.2.1. Materials------65

2.2.2. Preparation of zein-based core-shell nanocarriers------65

2.2.3. In vitro characterization and optimization------67

2.2.4. Determination of encapsulation and loading efficiency------67

2.2.5. In vitro release of Nile red (NR)------68

2.2.6. Enzymatic degradation of core-shell nanocarriers------68

2.2.7. Influence of pH and ionic strength on nanocarriers stability------69

2.2.8. Cell culture------69

2.2.9. Mechanism of cellular uptake of NR loaded nanocarriers------69

2.2.10. Calcein uptake assay------70

2.2.11. In vitro transepithelial transport of core-shell nanocarriers------71

2.2.12. Cell uptake studies using confocal laser scanning microscopy------71

2.2.13. Ex vivo bioadhesion assay------72

2.2.14. Ex vivo tissue uptake studies using pig jejunum------76 viii

2.2.15. Animal studies------75

2.3. Statistical analysis------79

2.4. Results and discussion------80

2.4.1. Characteristics and stability of core-shell nanocarriers------80

2.4.2. In vitro release of NR from core-shell nanocarriers------96

2.4.3. In vitro transepithelial transport and cell uptake of nanocarriers------101

2.4.4. Oral biodistribution of nanocarriers------111

2.4.5. Ex vivo bioadhesion assay------117

2.4.6. Immunogenicity of core-shell nanocarriers------120

2.5. Conclusion------122

CHAPTER THREE: Oral Delivery of a Model Anti-Retroviral Drug 125 Using Core-Shell Nanocarriers------

3.1. Introduction------126

3.2. Materials and methods------129

3.2.1. Materials------129

3.2.2. Methods------129

3.2.2.1. Preparation of nanocarriers------129

3.2.2.2. Characterization of LPV loaded nanocarriers------130

3.2.2.3. Differential Scanning Calorimetry (DSC)------130

3.2.2.4. HPLC analysis of LPV------130

3.2.2.5. Determination of encapsulation and loading efficiency of LPV---- 131

3.2.2.6. In vitro release of LPV from nanocarriers------131 ix

3.2.2.7. Solid state stability of free LPV and LPV in nanocarriers------132

3.2.2.8. Transepithelial permeability of LPV loaded nanocarriers------133

3.2.2.9. Enzymatic metabolism studies------134

3.2.2.10. Pharmacokinetic studies in rat------134

3.3. Statistical analysis------136

3.4. Results------137

3.4.1. Development and characterization of LPV loaded nanocarriers------137

3.4.2. In vitro release of LPV from nanocarriers------141

3.4.3. Stability of LPV loaded nanocarriers------147

3.4.4. Transepithelial permeability of LPV loaded nanocarriers ------148

3.4.5. Metabolic stability studies------150

3.4.6. In vivo pharmacokinetics in rats------152

3.5. Discussion------157

3.6. Conclusions------162

CHAPTER FOUR: Oral Delivery of an Investigational Anti-Cancer

Compound Using Core-Shell Nanocarriers------163

4.1. Introduction------164

4.2. Materials and methods------167

4.2.1. Materials------167

4.2.2. Methods------167

4.2.2.1. Preparation of Fenretinide loaded nanocarriers------167

4.2.2.2. Characterization of Fenretinide loaded nanocarriers------168

4.2.2.3. HPLC analysis of Fenretinide------168 x

4.2.2.4. Determination of encapsulation and loading efficiency of

Fenretinide------168

4.2.2.5. In vitro release of Fenretinide from nanocarriers------169

4.2.2.6. Transepithelial permeability of fenretinide through Caco-2 cell 170 monolayers------

4.2.2.7. Stability of Fenretinide in nanocarriers------170

4.2.2.8. Pharmacokinetic studies of fenretinide nanocarriers in rat------171

4.3. Statistical analysis------172

4.4. Results------173

4.4.1. Development and characterization of Fenretinide loaded core-shell 173 nanocarriers------

4.4.2. In vitro release of Fenretinide from nanocarriers------178

4.4.3. Transepithelial permeability of Fenretinide loaded nanocarriers across Caco-2 cell monolayers------184

4.4.4. Stability of Fenretinide in nanocarriers------186

4.4.5. In vivo pharmacokinetics------188

4.5. Discussion------195

4.6. Conclusions------196

5. Summary------198

6. Future studies------201

7. Bibliography------202

LIST OF FIGURES

Page no.

Figure 1: Gastrointestinal anatomy showing major regions and 3 microanatomy of digestive tract------

Figure 2: Various pathways of drug absorption from gastrointestinal 6 lumen to blood stream------

Figure 3: Schematic diagram of the steps and factors associated with oral 8 drug absorption------

Figure 4: Illustration of Cell internalization pathways ------11

Figure 5: Structure of P-gp efflux pump and mechanism of inhibition of 18 drug absorption------

Figure 6: Biopharmaceutics Classification System (BCS)------21

Figure 7: Biopharmaceutic Drug Disposition Classification System 22 (BDDCS)------

Figure 8: Schematic structure of beta-cyclodextrin-enalapril maleate 27 complex------

Figure 9: Application of nanocarriers in oral drug delivery applications--- 28

Figure 10: Different nanocarrier systems for oral drug delivery------29

Figure 11: Schematic diagram of mechanisms of intestinal drug transport 38 from SEDDS formulations------

Figure 12: Different techniques for preparation of polymeric nanocarriers 42

Figure 13: Schematic presentation of everted sac method to test 72 bioadhesion of nanocarriers------xii

Figure 14: Schematic presentation of texture analyzer set up for 74 determination of bioadhesive properties using ------

Figure 15: Transmission Electron Microscopy images of nanocarriers----- 82

Figure 16: MALDI-TOF analysis of free zein and PEGylated zein ------83

Figure 17: Enzymatic stability of nanocarriers in SGF with pepsin------93

Figure 18: Enzymatic stability of nanocarriers in SIF with pancreatin------94

Figure 19: Cumulative percent of NR released from different nanocarriers in the presence of SGF and SIF------96

Figure 20: Transepithelial permeability of NR loaded nanocarriers across 101 Caco-2 cell monolayers------

Figure 21: Flow cytometry analysis for the quantification of cell uptake 103 of nanocarriers------

Figure 22: Cell uptake of NR loaded nanocarriers at 4°C and 37°C after 104 incubation for 2 hours------

Figure 23: Mechanism of in vitro cell uptake of NR loaded nanocarriers 106 by Caco-2 cells------

Figure 24: Confocal microscopy images of polarized Caco-2 cells after 107 treatment with NR loaded nanocarriers------

Figure 25: P-gp inhibition activity of nanocarriers using Calcein AM 110 assay------

Figure 26: In vivo biodistribution of Cy5.5 loaded nanocarriers after oral 112 delivery in rat------

Figure 27: Fluorescence from GI tract after 24 hrs------113 xiii

Figure 28: Fluorescence from GI tract after 6 hrs------114

Figure 29: Tissue section of rat jejunum after oral delivery of Cy5.5 115 loaded nanocarriers ------

Figure 30: Tissue section of pig jejunum after ex vivo incubation of NR 116 loaded nanocarriers------

Figure 31: Ex vivo mucoadhesion of NR loaded nanocarriers in pig 119 jejunum------

Figure 32: Ex vivo mucoadhesion of blank nanocarriers to pig jejunum 121 using texture analyzer------

Figure 33: Oral immunogenicity of nanoparticles in mice------122

Figure 34: Chemical structure of lopinavir------128

Figure 35: TEM images of LPV loaded nanocarriers------139

Figure 36: DSC analysis of free LPV and LPV in nanocarriers------140

Figure 37: Cumulative percent of LPV released from different zein-based 143 nanocarriers in the presence of SGF and SIF------

Figure 38: Sequential release of lopinavir from different zein nanocarrier- 145

Figure 39: Solid state stability of LPV and LPV loaded ZC and ZLG 147 nanocarriers------

Figure 40: Transepithelial permeability of free LPV, LPV in Kaletra® and LPV in nanocarriers across Caco-2 cell monolayers------148

Figure 41: Metabolic stability of LPV in Kaletra® and LPV in nanocarriers------151

xiv

Figure 42: Plasma profile of LPV after oral administration of free LPV,

Kaletra® and LPV loaded nanocarriers------153

Figure 43: Plasma profile of LPV after multiple dose administration------155

Figure 44: Chemical structure of fenretinide------165

Figure 45: TEM images of fenretinide loaded nanocarriers------175

Figure 46: DSC analysis of fenretinide loaded nanocarriers------177

Figure 47: Cumulative percent of fenretinide released from different zein- 180 based core-shell nanocarriers in presence of SGF and SIF------

Figure 48: Sequential release of fenretinide from different zein 182 nanocarriers ------

Figure 49: Transepithelial permeability of fenretinide loaded nanocarriers 185 across Caco-2 cell monolayers------

Figure 50: Solid state stability of free fenretinide and fenretinide in 187 nanocarriers------

Figure 51: Plasma profile of fenretinide after oral delivery of different 189 fenretinide loaded zein-based nanocarriers in rat------

Figure 52: Plasma profile of free fenretinide and ZPL-fenretinide 192 nanocarriers after oral administration for 4 days------

Figure 53: Organ distribution of free fenretinide and fenretinide loaded 194 ZPL nanocarriers after oral delivery in rat------

LIST OF TABLES

Page no.

Table 1: Anatomical and physiological features of human GIT------14

Table 2: Common pharmaceutical salts------25

Table 3: Lipid nanocarriers for oral delivery applications------35

Table 4: Representative synthetic and natural polymers in oral drug 41 formulations------

Table 5: Different polymeric nanocarriers used in oral drug delivery 43 applications ------

Table 6: Physicochemical properties of protein polymers------49

Table 7: Natural protein polymers for oral drug delivery applications------55

Table 8: Characteristics of NR loaded nanocarriers------80

Table 9. Influence of pH on mean particle size and polydispersity index 86 of zein-β-casein (ZC) nanoparticles------

Table 10. Influence of pH on mean particle size and polydispersity index of zein-lactoferrin (ZLF) nanoparticles------86

Table 11. Influence of pH on particle characteristics of zein-β- lactoglobulin (ZLG) nanoparticles------87

Table 12. Influence of pH on particle characteristics of zein- whey protein 87 isolate (ZWP) nanoparticles------

Table 13. Influence of pH on mean size and polydispersity index of zein- 88 pluronic-lecithin (ZPL) nanoparticles------

xvi

Table 14. Influence of pH on mean size and polydispersity index of

PEGylated zein (ZPEG) micelles------88

Table 15. Influence of ionic strength on particle characteristics of zein- 90 casein (ZC) nanoparticles------

Table 16. Influence of ionic strength on particle characteristics of zein- lactoferrin (ZLF) nanoparticles------90

Table 17. Influence of ionic strength on mean particle size and polydispersity index of zein-β-lactoglobulin (ZLG) nanoparticles------91

Table 18. Influence of ionic strength on particle characteristics of zein- whey protein isolate (ZWP) nanoparticles------91

Table 19: Influence of ionic strength on particle characteristics of Zein- pluronic-lecithin (ZPL) nanocarriers------92

Table 20: Influence of ionic strength on particle characteristics of 92 PEGylated zein (ZPEG) micelles------

Table 21: Non-linear fit of NR release kinetics using different models----- 99

Table 22: Characteristics of Lopinavir loaded nanocarriers------137

Table 23: Release kinetics of LPV nanocarriers in presence of SGF and 143 SIF ------

Table 24: Release kinetics of LPV nanocarriers after sequential release in 145 food matrices followed by SGF and SIF ------

Table 25: PK parameters of free LPV, Kaletra®, and LPV loaded nanocarriers after oral delivery in rats------153

xvii

Table 26: Steady state PK parameters of Kaletra® and LPV loaded ZPEG 155 micelles after oral delivery in rats------

Table 27: Characteristics of fenretinide loaded zein-based nanocarriers-- 174

Table 28: Fenretinide release kinetics using different models------179

Table 29: Fenretinide sequential release kinetics using different models--- 181

Table 30: PK parameters of free fenretinide and fenretinide loaded nanocarriers after oral delivery in rats------188

Table 31: Steady state PK parameters of free fenretinide and fenretinide 191 loaded ZPL nanocarriers for oral delivery in rats------

Table 31: Comparison of zein-based nanocarriers for drug delivery------198

xviii

SYMBOLS AND ABBREVIATIONS

Cy5.5 Cyanine 5.5

HBSS Hank’s balanced salt solution

NR Nile Red

4-HPR 4-hydroxyphenyl retinamide

LPV Lopinavir

ATCC American Type Culture Collection

AUC Area Under the Curve

Caco-2 Human colon carcinoma cells

BCS Biopharmaceutics Classification System

EMEM Eagle’s Minimum Essential medium

DMSO Dimethyl sulfoxide

DSC Differential Scanning Calorimetry

EE% Percent Encapsulation Efficiency

LE% Percent Loading Efficiency

FBS Fetal bovine serum

GRAS Generally regarded as safe

GIT Gastrointestinal tract

Papp Apparent permeability coefficient

HPLC High-performance liquid chromatography

LOQ Limit of quantification

LOD Limit of detection

M-cells Microfold cells

MWCO Molecular weight cut off xix

PEG Polyethylene glycol

P-gp P-glycoprotein

PDI Polydispersity index

R2 Correlation coefficient rpm Rotation per minute

SD Standard deviation

SEM Standard Error of Mean

Zein-β-lactoglobulin ZLG

Zein-β-casein ZC

Zein-lactoferrin ZLF

PEGylated zein ZPEG

Zein-whey protein isolate ZWP

Pharmacokinetic PK

Half-life t 1/2 Maximum plasma concentration of drug C max Time to reach maximum plasma concentration of drug T max Area-under plasma drug concentration AUC

Mean residence time MRT

Css-max Maximum steady state plasma concentration

Css-min Minimum steady state plasma concentration

Css-avg Average steady state plasma concentration

RTV Ritonavir

ABSTRACT FOOD PROTEIN-BASED CORE−SHELL NANOCARRIERS FOR ORAL DRUG

DELIVERY APPLICATIONS: INFLUENCE OF SHELL COMPOSITION ON IN

VITRO AND IN VIVO FUNCTIONAL PERFORMANCE OF ZEIN NANOCARRIERS

MD SAIFUL ISLAM

2017

Oral delivery is the most preferred route for drug administration. Oral drug delivery is limited by poor physicochemical properties of drugs and physiological barriers in the gastrointestinal tract. To this end, there is a need for developing new carrier systems to enhance the oral bioavailability of poorly absorbed molecules. Food-grade biopolymers are attractive materials for developing drug delivery carriers’ due to their unique properties and proven safety. Six different core-shell nanocarriers were prepared using food-grade biopolymers including zein-casein (ZC) nanoparticles, zein-lactoferrin (ZLF) nanoparticles, zein-β-lactoglobulin (ZLG) nanoparticles, zein-whey protein isolate (ZWP) nanoparticles, zein-pluronic-lecithin (ZPL) nanoparticles and zein-PEG (ZPEG) micelles.

The study was aimed at systematically investigating the influence of shell composition on the functional performance of core-shell nanocarriers for oral drug delivery applications.

The first goal was to develop and study the structure-function relationship of core- shell nanocarriers for oral drug delivery applications. Nile red (NR) and Cy 5.5 were used as model dyes for this study. The particle size of the nanocarriers ranged from 100 to 250 nm, and the nanocarrier had a uniform size distribution as evidenced from the low PDI

(0.08 to 0.3). The zeta potential values varied from -10 to 30 mV depending on the shell composition. The core-shell structure of the nanocarrier was confirmed by Transmission xxi

Electron Microscopy (TEM). The nanocarriers sustained the release of NR in simulated gastric and intestinal fluids. NR release from the nanocarriers predominantly followed

Peppas model which indicates the diffusion of NR from nanocarriers by polymer erosion by hydrolytic or enzymatic cleavage. NR release from ZPEG micelles followed first order release kinetics. The nanocarriers were taken up by endocytosis in Caco-2 cells, which is an established model for intestinal permeability studies. ZLG nanocarriers showed the highest permeability across Caco-2 cell monolayers, while ZC nanoparticles showed the lowest permeability among the six formulations. ZPEG micelles also showed P-gp inhibitory activity. All the nanocarriers were found to have bioadhesive properties. Among the six different nanocarriers, ZLG and ZWP nanocarriers showed significantly higher bioadhesive property. In-vivo biodistribution of the nanocarriers was studied using Cy 5.5, a near-IR dye and all the formulations showed longer retention in the rat gastrointestinal tract compared to the free dye. Among the formulations, ZLG and ZWP nanoparticles were retained longest in the rat gastrointestinal tract (≥24 hours). All the nanocarriers were found to be non-immunogenic on oral administration to mice.

The second goal was to investigate the use of core-shell nanocarriers for oral delivery of a model antiretroviral drug, lopinavir (LPV). LPV is a first-line protease inhibitor used for the treatment of HIV infections, especially in children. The drug has poor oral bioavailability due to its poor water solubility, poor membrane permeability and first- pass metabolism in the intestine. LPV is a substrate for the CYP3A4 enzyme and hence is used in combination with ritonavir (a CYP3A4 inhibitor) to boost the oral bioavailability of LPV. The current pediatric oral liquid formulation contains LPV and ritonavir (RTV) in xxii a mixture of high proportion of propylene glycol and alcohol. The main goal was to test the feasibility of developing a water dispersible RTV free pediatric formulation of LPV using zein-based core-shell nanocarriers. The impact of shell composition on the functional properties of LPV loaded nanocarriers was evaluated in vitro and in vivo. The encapsulation efficiency for LPV was above 70% in all the nanocarriers, and ZPL nanoparticles showed the highest encapsulation efficiency (87.92±7.19%). The loading efficiency ranged from 2 to 5% based on the shell composition. The release of LPV was sustained both in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) for 24 hours. To test the feasibility of developing a food sprinkle formulation, the compatibility of the nanoformulations with model food matrices were studied. The nanocarriers were stable when incubated in food matrices (milk and applesauce) and <30% of LPV was released within first 1 hour followed by sustained release in SGF and SIF for 24 hours. The nanocarriers increased the permeability coefficient (Papp) of LPV across the Caco-2 cell monolayers by two to four-fold. The Papp values of LPV loaded nanocarriers decreased in the following order ZPEG>ZC>ZLF>ZWP>ZLG>ZPL. In vivo pharmacokinetic study in rats showed that the oral bioavailability of LPV increased by 2-fold compared to marketed

LPV/RTV liquid formulation (Kaletra®). The highest oral bioavailability was obtained with LPV loaded ZPEG micelles followed by ZWP and ZLG nanoparticles. Highest plasma concentration (Cmax) of LPV was achieved with ZPEG micelles which was comparable to Kaletra® formulation. The extent of absorption (AUC) of LPV was in the following decreasing order of ZPEG>ZWP>ZLG>Kaletra®>free LPV. Multiple dose PK study further demonstrated that similar or higher steady-state plasma concentration can be obtained using ZPEG micelles compared to Kaletra®. Findings from this chapter xxiii concludes that zein-based nanocarriers can be used to develop ritonavir free LPV formulation which will ultimately reduce the total drug load and drug-drug interaction in the treatment of HIV infection.

The last objective was to demonstrate the feasibility of using zein-based core-shell nanocarriers for oral delivery of fenretinide, an investigational anti-cancer molecule.

Fenretinide has been found to be effective against several cancers including pediatric neuroblastoma, However, the clinical development of fenretinide is limited by its poor physicochemical properties. Fenretinide is a poorly soluble and poor permeable anti-cancer agent. Further, the compound has poor chemical stability. The encapsulation efficiency for fenretinide was above 70% in all the nanocarriers and zein-β-casein (ZC) nanoparticles showed the highest encapsulation efficiency (90±0.091%). The release of fenretinide was sustained both in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) for 24 hours. The nanocarriers were stable when incubated in food matrices (milk and applesauce), and less than 30% of fenretinide was released after incubation for 1 hour in food matrices. About 60% of fenretinide was released over 24 hours when the nanocarriers was transferred from food matrices to SGF and SIF. The nanocarriers enhanced the permeability of fenretinide across the Caco-2 cell monolayers from 1x10-6 to 72.42x10-6 cm/s. The order of permeability of fenretinide loaded nanocarriers was found to be in the following decreasing order ZPL>ZLG>ZC>ZWP>ZLF>ZPEG. Among others tested for single dose PK study of fenretinide, ZLG nanocarriers showed the highest oral bioavailability of fenretinide (6-fold) compared to free fenretinide suspension.

Nanocarriers increased the elimination half-life (t1/2) by 2- to 4-fold. ZPL nanocarriers showed the highest Cmax (0.61 μg/mL) of fenretinide, while fenretinide loaded ZC xxiv

nanocarriers showed the lowest Cmax (0.23 μg/mL). Nanocarriers showed the following decreasing rank order for relative oral bioavailability, ZWP>ZLG>ZPL>ZC, indicating that shell composition has a significant influence on the oral bioavailability. Further, multiple dose pharmacokinetic (PK) studies of fenretinide and fenretinide loaded zein- pluronic-lecithin (ZPL) nanocarriers was performed. The pharmacokinetics of twice a day free fenretinide suspension was compared with once a fenretinide loaded ZPL nanocarriers.

The steady state concentration of fenretinide and fenretinide loaded ZPL nanocarriers was achieved at around 50-hours. However, the steady-state plasma concentration of fenretinide from the ZPL nanocarriers was 5-fold higher compared to free fenretinide suspension.

Overall, the outcomes from this study demonstrate the structure-function relationship of core-shell protein nanocarriers for oral drug delivery applications. The findings from this study can be used to develop food protein based oral drug delivery systems with specific functional attributes for various oral drug delivery applications.

CHAPTER ONE: Introduction

1.1. Oral drug delivery

Oral drug delivery is the preferred route of drug administration due to the ease of drug administration, cost-effective, and ease of manufacturing. Additionally, oral drug administration has high patient compliance (Fix 1999). Therefore, 60% of the marketed formulations are for oral administration (Renukuntla et al. 2013).

Despite the advantages for oral drug administration, the drug delivery by this route is associated with multiple challenges including varying pH, poor water solubility, poor membrane permeability, poor stability, and first-pass metabolism.

1.2. Oral drug absorption

1.2.1. Gastrointestinal anatomy and physiology

Human GIT is about 8.35 m long starting from the esophagus followed by the stomach, small intestine (duodenum, jejunum, and ileum) and large intestine (cecum, colon, and rectum) (Fig. 1A). Small intestine covers about 81% of the total length of the

GIT and is the major site of drug absorption due to the large surface area (~100 m2)

(DeSesso and Jacobson 2001). The presence of villi and microvilli contributes to the large surface area of small intestine (Fig. 1B) (Kararli 1995). There are numerous epithelial projections with lamina propria (villi) in the apical surface (Fig. 1B). Each villus is subdivided into microvilli and estimated to have 3000-7000 microvilli on each epithelial cell (Ritschel 1991). This anatomical feasure significantly increase the absorptive surface area of duodenum and jejunum than ileum in small intestine. Absorbing surface area 2 dramaticaly reduced in cecum (0.05 m2), colon (~0.25 m2) and rectum (0.015 m2) due reduced length and absence microvilli (Kararli 1995).

The epithelial cells are connected to each other by zonula occludens or tight junctions in the mucosa side. Tight junctions allow only small hydrophilic molecules to through the aqueous channel (paracellular transport). In addition, the surface of the small intestine is covered with a thin aqueous mucus layer (around 25 μm thickness) which serves as a protective barrier against toxins and xenobiotics (Winne 1976; Strocchi et al. 1996).

Various physiological factors including gastrointestinal transit time, variable pH, enzymatic activity, and metabolism can influence drug absorption from the GI tract.

Figure 1: Gastrointestinal anatomy showing major regions (A) and microanatomy of digestive tract (B). Reproduced from Remesz et al. (2004) and http://www.vivo.colostate.edu/hbooks/pathphys/digestion/basics/gi_microanatomy.html.

1.2.2. Mechanism of oral drug absorption

After oral administration, drug molecules can be transported from the absorption site to the blood by passive diffusion, facilitated transport, active transport, and endocytosis. Drug molecules can passively diffuse through the absorption membrane using transcellular and paracellular route. Facilitated transport is a carrier mediated transport which is mainly influenced by the concentration gradient. Transmembrane protein (e.g. vitamin B12 transporter, hexose transporter etc.) facilitates the entry and exit of molecules

(Fig. 2). The active transport is an energy-dependent process and occur through transporters expressed on the epithelial cells, while vesicular transport (endocytosis) is dependent on the size (mainly particulates and macromolecules) (Thomas et al. 2006; Hurst et al. 2007; Varma et al. 2010). The absorption mechanisms are further described in more detail in subsequent sections.

1.2.2.1. Passive diffusion

Passive diffusion of drug molecules is determined by the physicochemical properties of compounds such as molecular weight, lipophilicity, and capacity to form hydrogen bonds (Lipinski 2000; Avdeef 2001). Passive diffusion by transcellular pathway is limited to small molecules (<500 Da), and rate of absorption or flux (J) is described by the Fick’s law of diffusion,

DS(Ko/w)(Cg.i.) J = h

Where, D is the diffusion coefficient which is influenced by the molecular weight of drug and the membrane characteristics.

‘S’ is the surface area of the membrane which is influenced by the location in the GI tract. 5

‘K’ is the octanol/water (o/w) partition coefficient which is influenced by the lipophilicity and ionization of drug molecules.

‘C’ is the concentration of drug in the GI lumen which is dependent on the solubility and dosage form of drugs.

‘h’ is the thickness of the diffusion membrane which varies in different section of GI tract.

The intestinal epithelial layer serve as a protective barrier for the entry of pathogens, toxins, antigens, and foreign particles from the GI lumen to the systemic circulation (Lee 2015).

The surface of the mucosal layer of the intestine is lined with epithelial cells connected to each other by the tight junction (Fig. 2). Tight junction is a multiprotein complex and pore diameter between cells is reported to be <10Å and is hence limited to small molecules

(Takeuchi and Gonda 2004). Hydrophilic drugs and nutrients can be absorbed via an aqueous channel between the intercellular space of enterocytes (Lennernas 1995). Drug molecules with molecular weight <500 Da, have been found to be utilized this absorption pathway (Karlsson et al. 1999; Lee 2015; Turner 2006; Nusrat, Turner, and Madara 2000).

The paracellular transport is also important for the absorption of drugs from GI tract.

Hydrophilic molecules that are restricted to cross the lipid membrane of the epithelial cells usually absorb via paracellular pathway.

Figure 2: Various pathways of drug absorption from gastrointestinal lumen to blood

stream. Reproduced from Agrawal et al. (2014).

1.2.2.2. Transporter-mediated uptake and efflux

Intestinal epithelial cells express multiple families of uptake and efflux transporters which is mainly divided into solute carrier (SLC) transporters and ATP-binding cassette

(ABC) transporters (Fig. 3) (Leibach and Ganapathy 1996; Tamai 2012; Englund et al.

2006; Roth, Obaidat, and Hagenbuch 2012). In general, ABC transporters use ATP as an energy source and play a major role in intestinal absorption, while SLC utilize H+, Na+, 7

Ca++ ion gradient created by Na+/K+-ATPase, or Na+/H+-ATPase (Tsuji and Tamai 1996;

Ogihara, Tamai, and Tsuji 1998).

ABC transporter includes P-glycoprotein (P-gp), breast cancer resistance protein

(BCRP), and multidrug resistance proteins (MRP1-6) (Roth, Obaidat, and Hagenbuch

2012). ABC transporters can be subdivided into uptake and efflux transporters. The uptake transporters play an important role in the absorption of nutrients such as glucose, amino acids, and small peptides, while the efflux transporters involve in the removal of absorbed foreign or toxic substances and return them to GI lumen. The apical membrane also expresses brush border enzymes for metabolizing macromolecules to small molecules to facilitate uptake by nutrient transporters (Hamman, Demana, and Olivier 2007). Drugs that have structural similarity with nutrients can bind with transporters and can be taken up by epithelial cells. In this regard, peptide transporters, amino acid transporters, and nucleoside transporters play a major role in the uptake of orally administered drugs (Hamman,

Demana, and Olivier 2007). Peptide transporter 1 (PepT1) can bind and transport diverse compounds including antibiotics, antivirals, and peptidyl prodrugs (Smith, Clemencon, and

Hediger 2013), while organic anion transporters can interact with statins, angiotensin- converting enzyme inhibitors and other group of drugs (e.g., fexofenadine) (Kalliokoski and Niemi 2009). Taken together, all these transporters play a significant role in uptake or efflux, distribution, metabolism, and excretion of administered drugs.

Drugs to overcome numerous barriers after oral administration to achieve therapeutic concentration in the blood. Figure 3 summarizes different factors that can influence drug absorption and bioavailability. 8

Figure 3: Schematic diagram of the steps and factors associated with oral drug absorption. Molecular weight (MW), Unstirred water layer (UWL), Cytochrome P450 (CYP), UDP- glucuronosyltransferase (UGT), Glutathione S-transferase (GST), Sulfotransferase (SULT), apical sodium-dependent bile acid transporter (ASBT), Organic cation transporter (OCT), Concentrative nucleotide transporter (CNT), Electroneutral organic cation transporter (OCTN), Organic anion transporting polypeptide (OATP), Peptide transport protein (PEPT), P-glycoprotein (P-gp), Multidrug resistance protein (MDR), Multidrug resistance-associated protein (MRP), Breast cancer resistance protein (BCRP), Monocarboxylate transporter protein (MCT), equilibrative nucleoside transporter (ENT), (+) and (-) indicates an increase or a decrease in the rate and/or extent of drug absorption, respectively. Adapted from Huang, Lee, and Yu (2009). 9

1.2.2.3. Endocytosis

The uptake of macromolecules and particulate systems occurs by endocytosis. This is an energy-dependent process which can be divided into receptor-mediated or non-receptor mediated endocytosis. Vesicular transport mechanisms include clathrin-mediated endocytosis, caveolae-mediated endocytosis, and macropinocytosis (Fig. 4) (Lundquist and Artursson 2016). Clathrin-mediated endocytosis involves internalization by ligand- bound receptors followed by transport to endosomes and fuse with lysosome for degradation or recycle back to the cell membrane (Yameen et al. 2014). Clathrin-coated pit

(CCP) is a well-studied mechanism for receptor-mediated endocytosis. The process includes invagination of the cell membrane and formation of clathrin-coated vesicle

(Somsel Rodman and Wandinger-Ness 2000; Roger et al. 2010; Ford et al. 2002). Clathrin- independent process as shown in figure 4 does not require coat proteins for the formation vesicles. Instead of coat protein, actin and actin associated proteins is involved in clathrin- independent endocytosis process (Robertson, Smythe, and Ayscough 2009). Clathrin- independent pathway mediate uptake using glycolipids and glycoproteins and are insensitive to endocytosis inhibitors (Kirkham and Parton 2005). Uptake by clathrin mediated endocytosis mainly dependent on the size, shape and surface charge (Yameen et al. 2014). For example, particulate systems prepared using cationic polymers are predominantly taken up by clathrin-mediated endocytosis by electrostatic interaction with the negatively charged cell surface (Yameen et al. 2014).

Caveolae-mediated endocytosis process involves the formation of cavities which are transported to the nucleus by dynamin- and actin-mediated uptake (Lundquist and

Artursson 2016). Caveolae-mediated endocytosis utilizes lipid-raft which is mainly 10 composed of cholesterol and sphingolipid for the formation of membrane microdomain

(Conner and Schmid 2003). Caveolae-mediated endocytosis is characterized by the presence of caveolin protein which leads to the formation of caveosomes (Pelkmans,

Kartenbeck, and Helenius 2001). Negatively charged polymers are generally found to be internalized via caveolae-mediated endocytosis (Sahay, Alakhova, and Kabanov 2010).

Macropinocytosis also called as fluid-phase endocytosis is mainly dependent on the concentration of solute around the cells (Adler and Leong 2010). Macropinocytosis is an actin-driven endocytic process which usually takes up considerable volume of extracellular fluid into large vesicle known as macropinosomes (Falcone et al. 2006). Unlike the receptor-mediated endocytosis, the formation of macropinosomes is not activated by direct interaction of particulate systems (Fig. 4). Tyrosine kinase pathway is involved in the activation and polymerization of actin (Kerr and Teasdale 2009). Although micron size particles can be internalized via macropinocytosis, majority of macromolecules and particulate systems taken up by more than one endocytic process (Gratton et al. 2008;

Zhang et al. 2014).

The particle size of the drug carrier for oral delivery plays a significant role in the uptake by epithelial cells (Kulkarni and Feng 2013). Particle size of <50 nm diameter is shown to be transported via the paracellular pathway, while particles in the range of 100-

500 nm diameter are taken up by endocytosis (Desai et al. 1996). Particle size >1 µm to <5

µm are usually taken up by M-cells in the Peyer’s patches (Desai et al. 1996). In general, particles around 100 nm diameter were observed to be taken up better by at intestinal mucosa (Desai et al. 1996; Agrawal et al. 2014). Further, Reineke et al. reported that wide 11 range of particles (500 nm to 5 µm) could be absorbed in small intestine via clathrin- dependent endocytosis (Reineke, Cho, Dingle, Morello, et al. 2013).

Figure 4: Illustration of internalization pathways (phagocytosis, macropinocytosis, clathrin-dependent endocytosis, clathrin-independent endocytosis, and caveolin-dependent endocytosis). The fate of internalized cargo and localization to subcellular compartments are also depicted. ER: endoplasmic reticulum, NLS: nuclear localization signal, NPC: nuclear pore complex, TPP: triphenylphosphonium cation. Reproduced from Yameen et al. (2014).

1.3. Oral drug delivery challenges

Despite many advantages of oral drug delivery, there are several barriers for drugs absorption. Factors that influence the oral bioavailability of drugs include physiological, physicochemical, and biopharmaceutical factors (Sabnis 1999; Horter and Dressman 2001;

Kramer and Wunderli-Allenspach 2001; Zhou 2003).

1.3.1. Physiological barriers to oral drug delivery

Multiple physiological factors including variable pH, digestive enzymes, efflux transporters, GI transit time, mucus layer, and first-pass metabolism influence oral drug absorption.

1.3.1.1. Variable pH and digestive enzymes

One of the major barriers for oral drug delivery is the variable pH in the GI tract.

The stomach pH ranges from 1.0 to 2.5 (Evans et al. 1988; O'Neill et al. 2011) and gradually increases to pH 6.6 and pH 7.5 in the proximal portion of intestine, then the pH decreases to 6.4 close to caecum, and again rises to pH 7.0 in the colon (Table 1). Majority of the drugs are either weak acid or weak base and the degree of ionization is dependent on the pKa of the drug molecule and pH of the biological fluid. For example, an acidic drug is predominantly ionized at a pH two units higher than pKa of the drug while the drug predominantly remains as unionized, if the pH is two units lower than the pKa (Roche

2007). This is reverse for basic drugs. The unionized and soluble form of the drug is mainly absorbed by passive diffusion and drugs should remain as ionized to be soluble in GI fluid.

Therefore, a drug which is not completely ionized or unionized at intestinal pH show good 13 absorption. (Chawla 2003). In addition to pH, the presence of numerous enzymes (pepsin, amylase, trypsin, lipases, pancreatin, peptidases, maltase etc.) can also pose an obstacle for oral delivery of drugs (Table 1).

Table 1: Anatomical and physiological features of human GI tract. Reproduced from Chawla et al. (2003).

1.3.1.2. GI transit time and mucus layer

GI transit time is another important factor that influence the drug absorption. GI transit time is influenced by the individual differences, meals, fluid intake, and disease state

(Davis, Hardy, and Fara 1986; Dressman et al. 1992; Coupe, Davis, and Wilding 1991).

Gastric emptying time for healthy individual varies from 25 minutes to 3 hours, while the intestinal residence time varies from ~3 to 4 hours. The residence time of drugs in upper intestine is lower than distal portion, and the movement of drugs gradually slow down when it reaches to the large intestine. The transit time for large intestine varies from 4 to

20 hours (Table 1) (DeSesso and Jacobson 2001).

Mucus layer in GI tract prevents damage to epithelial surfaces and can limit the oral drug absorption as the drug has to diffuse through the viscous mucus layer before reaching the epithelial cells (Ensign, Cone, and Hanes 2012). Mucus is a complex mixture of proteins (glycosaminoglycans), lipids, carbohydrates, salts, and unidentified materials

(Larhed, Artursson, and Bjork 1998). GI mucus efficiently trap pathogens and foreign particles and continuous mucus turn-over clears the trapped bacteria and solid particles

(Corfield et al. 2001). The mucus turn-over limits the residence time and prevents the penetration of particulate systems through the loosely adherent mucus layer (Ensign, Cone, and Hanes 2012). Drug delivery systems have been designed to enhance the penetration through loose mucus layer delay the GI transit time to enhance the absorption and oral bioavailability (Ch'ng et al. 1985; Longer, Ch'ng, and Robinson 1985; Lehr 1994, 2000;

Vasir, Tambwekar, and Garg 2003). One of the commonly used approaches is to incorporate mucoadhesive materials to enhance residence time in GI tract (Ch'ng et al.

1985; Shaikh et al. 2011). Polymers with high capacity of forming hydrogen, hydrophobic 16 or electrostatic interaction with mucus layer showed increased retention after oral delivery

(Lai, Wang, and Hanes 2009; Date, Hanes, and Ensign 2016). Polymers can interact with the mucus layer by the following mechanisms: i) hydrogen bonding, ii) hydrophobic interaction, iii) anionic surface charge, and iv) polymer entanglement (Jimenez-Castellanos

1993; Deraguin 1969; Gu, Robinson, and Leung 1988). Particles prepared from polymers such as poly(lactic acid) (PLA), poly(sebacic acid) (PSA), poly(lactic-co-glycolic acid)

(PLGA) and poly(acrylic acid) (PAA) has been reported to interact with mucus through one or more of the above mentioned mechanisms (Lai, Wang, and Hanes 2009).

1.3.1.3. GI metabolism and efflux pump Intestinal metabolic enzymes especially phase-I metabolic enzymes such as cytochrome P450 (CYP 450) are abundantly expressed in intestinal enterocytes (Chawla

2003). Many orally administered drugs interact with cytochrome P450 (CYP450) enzymes in the intestine (Watkins 1997). CYP3A is one of the main metabolic enzymes expressed in human intestine (Bezirtzoglou 2012; Thelen and Dressman 2009). CYP3A activity is higher in the small intestine and gradually decline in the ilium and colon (Chawla 2003).

In addition to enzymes, efflux pumps can limit drug absorption. P-glycoprotein (P- gp) is an ATP-dependent transmembrane protein expressed in columnar epithelial cells in the intestine (Loo and Clarke 2005). P-gp composed of 1280 amino acids (170 kDa) and contains a single chain of two homologous regions. Each region comprises six transmembrane domains connected by a flexible polypeptide linker (Fig. 5A). The ATP- binding domains are positioned in cytosolic regions which are also known as nucleotide- binding folds (NBFs). The NBFs are responsible for supplying energy for transporting substrate through the membrane. The Magnesium (Mg2+) ion is reported to play a role in 17 stabilizing the ATP-binding site (Tombline et al. 2004). P-gp translocate its substrate from cytosol of epithelial cells to intestinal lumen and thereby reduces the bioavailability

(Chawla 2003). A wide range of drug molecules (mainly hydrophobic) can interact with P- gp. These drugs include anticancer agents, immunosuppressants, steroid hormones, calcium channel blockers, beta-adrenoreceptor blockers, cardiac glycosides etc. (Sharom

2011; Varma et al. 2003; Sharom et al. 2001). Most of these drugs are also substrate for

CYP3A4 in the intestinal epithelial cells (Sharom 2011). The P-gp efflux pump along with

CYP3A4 and can limit the oral absorption of these drugs. (Fig. 5B) (Li et al. 2016).

Different classes of P-gp inhibitors have been investigated to overcome the P-gp efflux.

These include small molecule P-gp inhibitors (e.g., Verapamil, Cyclosporin A), polymeric

P-gp inhibitors (e.g. TPGS, pluronics), and natural P-gp inhibitors (e.g. Curcumin,

Grapefruit) (Varma et al. 2003; Liscovitch and Lavie 2002; Kabanov, Batrakova, and

Alakhov 2002; Zhou, Lim, and Chowbay 2004; Deferme, Van Gelder, and Augustijns

2002; Cornaire et al. 2004). 18

Figure 5: Structure of P-gp efflux pump and mechanism of inhibition of drug

absorption (A). Functional relationship between P-gp and CYP3A4 (B). Reproduced

from Bansal et al. (2009) and Watkins (1997). 19

1.3.2. Influence of physicochemical and biopharmaceutical factors on oral drug delivery

Oral bioavailability of drugs limited by the physicochemical properties of drugs.

These includes poor solubility and permeability, poor chemical stability, and enzymatic metabolism in the GI tract (Prabhu, Ortega, and Ma 2005). The poor physicochemical properties of drug molecules lead to ~40% failure in drug development (Siew et al. 2012).

Lipinski et al. developed ‘Rule of 5’ to guide oral drug development. According to this rule drugs with molecular weight >500 Da, log P >5, >5 H-bond donors, >10 H-bond acceptors are less likely to show good absorption after oral administration (Lipinski 2000;

Wenlock et al. 2003). The rate of solubility in the intestinal fluid is one of the important factors that influence the drug absorption. Noyes-Whitney equation is used to describe the factors that influences the rate of drug dissolution (Healy 1984; Frenning and Stromme

2003),

퐴. 퐷 푅푎푡푒 표푓 푑𝑖푠푠표푙푢푡𝑖표푛 = (퐶푠 − 퐶) ℎ

Where A is the surface area, D is the diffusion coefficient, h is the thickness of the diffusion layer adjacent to the drug surface, Cs is the saturation solubility of the drug in the diffusion layer, and C is the concentration of drug in the bulk solution at any time. The above equation indicates that rate of drug dissolution increases with increase in drug surface area, which can be achieved by decreasing the particle size. Diffusion coefficient is dependent on the viscosity of the fluid (solvent) and rate of drug dissolution is inversely proportional to the viscosity of solvent. Saturation solubility (Cs) is dependent on the physicochemical characteristics of drug and nature of the fluid (solvent). Therefore, the 20 alteration of pH of the solvent can alter the degree of ionization of drug (discussed in section 1.3.1.1.) and thus can change the drug solubility.

Among all the factors, solubility and permeability are the primary determinants of oral bioavailability. This lead to the development of Biopharmaceutic Classification

System (BCS) which classifies drugs based on its solubility and permeability (Fig. 6)

(Amidon et al. 1995; Dahan, Miller, and Amidon 2009). According to BCS, a drug is considered as highly soluble if its highest dose is soluble in 250 mL water over the entire pH range of 1 to 7.5 (Yu et al. 2002). Similarly, a drug is regarded as highly permeable, if

>90% of its administered dose is biologically available (Lennernas 2007). As shown in

Figure 6, BCS class I drugs are highly soluble and highly permeable. BCS class I drugs are readily absorbed and are good candidates for oral delivery. BCS Class II drugs are poorly soluble and highly permeable, while BCS Class III drugs are highly soluble and poorly permeable. BCS Class IV drugs are poorly soluble and poorly permeable and require carriers or chemical modification to improve solubility and or permeability (Fig.

6).

Figure 6: Biopharmaceutics Classification System (BCS). Reproduced from Dahan,

Miller, and Amidon (2009).

Benet et al. further modified BCS by including drug metabolism. This lead to the development of Biopharmaceutics Drug Disposition Classification System (BDDCS) (Fig.

7) (Wu and Benet 2005). According to BDDCS, highly permeable drugs (class I and class

II) are extensively metabolized, while the poorly permeable drugs (class III and class IV) are poorly metabolized. For class I and class II drugs, the prmary route of elimination is metabolism, while for class III and class IV drugs, the primary route of elimination is renal and biliary excretion (Fig. 7) (Benet et al. 2008; Wu and Benet 2005). In general, BDDCS 22 serve as basis for predicting the role of transporters in drug disposition and drug-drug interactions.

Figure 7: Biopharmaceutic Drug Disposition Classification System (BDDCS).

Reproduced from Wu and Benet (2005).

1.4. Different approaches for oral drug delivery

Numerous approaches have been used to overcome oral drug delivery challenges.

These can be divided mainly into two categories: i) physical or chemical modification of drug molecules, and ii) use of drug carriers (Bernkop-Schnurch 2013). The first strategy involves altering the physical or chemical form to improve the physicochemical characteristics of the drug. These include micronization, polymorphism, salt formation, pro-drug, and complexation. The second approach is to using drug carriers with different types of materials.

1.4.1. Physical or chemical modification of drug molecules

Various physical and chemical modification have been used to enhance aqueous solubility, intestinal permeability, and bioavailability of drug molecules (Savjani, Gajjar, and Savjani 2012).

Micronization is one of the well-studied techniques to overcome the limitations associated with drug dissolution (Blagden et al. 2007). Reducing the particle size of drug crystals significantly increases the surface area, and rate of dissolution. For example, micronized formulation of poorly water-soluble glimepiride has been used to enhance the dissolution rate and to increase the oral bioavailability (Ning et al. 2011). Similarly, micronized megestrol acetate formulation show enhanced oral bioavailability (Farinha,

Bica, and Tavares 2000).

Drug crystallinity and polymorphisms can influence drug solubility and bioavailability (Singhal and Curatolo 2004). A drug that can crystallize in more than one crystal form and is known as polymorphism. Majority of drugs (50-70%) exhibit 24 polymorphism, which differ in the internal arrangement and conformations of the molecules in the crystal lattice (Higuchi et al. 1963; Podaralla 2008). The polymorphs have distinct chemical and physical properties such as difference in melting point, chemical reactivity, apparent solubility, dissolution rate, vapor pressure, density, optical and electrical properties. For example, HIV protease inhibitor ritonavir (Norvir®, Abbott

Laboratories) exist as two polymorphs. Form I of ritonavir is more soluble than form II

(Gardner, Walsh, and Almarsson 2004). An amorphous form of the drug does not have regular crystal lattice and has a higher solubility in comparison to crystalline form of the drug (Hancock 2000). Several reports have shown the improved solubility of amorphous form of the drug compared to the crystalline form (Imaizumi, Nambu, and Nagai 1980; al.

1975). For example, aqueous solubility of amorphous celecoxib was found to be higher than its crystalline counterpart (Gupta, Chawla, and Bansal 2004).

Salt formation is one of the most commonly used strategies to increase the solubility of ionic drugs (Berge, Bighley, and Monkhouse 1977; Chowhan 1978). The impact of salt formation on the rate of drug dissolution was first introduced by Nelson (1957) by comparing choline and isopropanolamine salts of theophylline with ethylenediamine salts.

Approximately 70% drugs are ionizable and are weakly basic or weakly acidic (Kalepu and Nekkanti 2015). Therefore, the formation of an appropriate salt of drug molecules using oppositely charged counter-ions can alter the pH of the diffusion layer resulting improved solubility. Weakly acidic drugs form salt with strong base (e.g. Phenytoin sodium) while weakly basic drugs form salt with strong acids (e.g. Atropine sulfate). The salt formation is dependent on the relative pKa values of the drug and the salt forming 25 species (counter-ion). Table 2 lists commonly used counterions to form pharmaceutical salts.

Table 2: Common pharmaceutical salts.

Salts class Examples Anions Inorganic acids Hydrochloride, hydrobromide, sulfate, nitrate, phosphate, Sulfonic acids mesylate, esylate, isethionate, tosylate, napsylate, besylate, Carboxylic acids acetate, propionate, maleate, benzoate, salicylate, fumarate, Anionic amino acids glutamate, aspartate, citrate, lactate, succinate, tartrate, glycolate, Hydroxyacids hexanoate, octanoate, decanoate, oleate, stearate, pamoate, Fatty acids polystyrene sulfonate (resinate) Insoluble salts Cations Organic amines Triethylamine, ethanolamine, triethanolamine, meglumine, Insoluble salts ethylenediamine, choline procaine, benzathine, sodium, Metallic potassium, calcium, magnesium, zinc, arginine, lysine, histidine Cationic amino acids

Prodrug approaches has been used to enhance aqueous solubility or permeability of drugs (Van Gelder et al. 2000). Chemical modification to create prodrug should be reversible and prodrug should be converted back into parent drug by an in vivo chemical and/or enzymatic reaction (van De Waterbeemd et al. 2001; Beaumont et al. 2003). For example, inactive sulindac prodrug derived from sulfinylindene which is 100-times more water soluble than sulindac drug. The prodrug is converted in vivo to an active sulfide compound by liver enzyme (Davies and Rampton 1991). 26

Complexation of drug molecules with hydrophilic polymers is another approach to enhance water solubility of lipophilic drugs (Loftsson 1998). Drug complexation with polymers like cyclodextrin (CD) improve both the pharmaceutical and biological properties of drug-CD complexes. Cyclodextrins are divided into α-, β-, and γ- cyclodextrin-based into some D-glucopyranose units. Βeta-cyclodextrin is most commonly used to entrap and improve the solubility of lipophilic drugs (Fig. 8) (Shimpi, Chauhan, and Shimpi 2005). Complexation can also be used to increase the stability of compounds, mask the bitter taste of the drug, and control the drug release (Ranade 1991). Complexation of drug molecules with cyclodextrin has been used to enhance solubility and oral bioavailability of several drugs (Loftsson and Brewster 1996; Loftsson and Duchene 2007;

Loftsson and Brewster 2010; Irie and Uekama 1997). For example, complexation of enalapril (antihypertensive) with beta-cyclodextrin enhanced the solubility, stability, and bioavailability of enalapril after oral administration (Fig. 8) (al. 2006). Other complexing agents such as sodium benzoate, caffeine, nicotinamide, and sodium salicylate have also been used to increase drug solubility.

Figure 8: Structure of beta-cyclodextrin-enalapril maleate complex. Reproduced from Ali et al. (2006).

1.4.2. Drug carriers

Several types of drug carriers have been used to improve the oral drug absorption.

Drug carriers allow the delivery of poorly water-soluble drugs, target the drug release to specific site in the GI tract, sustain drug release, reduce drug efflux, and transport drugs through the GI membrane (Fig 9). Various types of drug carriers have been tested for oral drug delivery applications including micelles, nanospheres, liposomes, nanoemulsions, solid lipid nanoparticles, polymeric particles (nano and microparticles), and self- emulsifying drug delivery systems (SEDDS) etc. (Fig. 10). Nanoparticles are defined by the diameter on the order of 100 nm which is comparable to many viral particles

(Pridgen, Langer, and Farokhzad 2007). 28

Figure 9: Application of nanocarriers in oral drug delivery applications. Reproduced from Agrawal et al. (2014).

Figure 10. Different nanocarrier systems investigated for oral drug delivery. Reproduced from Zhang, Wang, Zhang, et al. (2013).

1.4.2.1. Lipid-based delivery systems

1.4.2.1.1. Liposomes

Liposomes are lipid vesicles with a hydrophilic core and a lipophilic bilayer.

Liposomes can be used to entrap hydrophilic and/or hydrophobic molecules. Traditional liposomes are composed of phospholipid and cholesterol. Liposomes are promising drug carrier. The composition of lipids in the liposomes can be varied to alter the surface charge and particle size (Wu, Lu, and Qi 2015). The size of liposomes can vary from very small

(25 nm) to large (2.5 µm) vesicles and can be classified as unilamellar and multilamellar vesicles. In general, liposomes is prepared by dry-film-rehydration method where a thin lipid film is formed by evaporation of organic solvent followed by hydration of lipid film 30 using aqueous drug solution and sonication to encapsulate drug in the core of the liposome

(Akbarzadeh et al. 2013). In this method, primarily form large multilamellar vesicles which require to either sonicate or extruded to produce small unilamellar vesicles. Alternatively, ethanol injection method is used prepare liposome. In this method, water injected into a concentrated lipid-ethanol solution followed by evaporation of ethanol (Maitani et al. 2007;

Maitani et al. 2001; Pons 1993).

Liposome based drug delivery is limited by i) low loading efficiency, ii) poor stability in GI media, and iii) leakage of entrapped drugs. Lipases can hydrolyze the liposomes within 2 hours of oral ingestion leading to disruption of bilayer (Liu et al. 2015).

The integrity of liposomes can also be altered in the low gastric pH leading to burst release of drug in stomach. In this regard, polysaccharides and protein polymers have been used to improve the stability of liposomes (Manconi et al. 2013; Smistad et al. 2012).

Polymerized liposomes showed enhanced stability in the GI tract and improved oral absorption. For example, incorporation of sodium glycocholate in liposomal composition resulted in increased resistance to peptic and tryptic digestion of encapsulated insulin (Niu et al. 2011). Thiolated chitosan-coated liposomes were found to be stable at low pH with mucoadhesive properties (Gradauer et al. 2013). Liposomes with multiple layers of polyelectrolyte have been prepared to achieve higher stability in GI fluid. The multilayer liposomes were reported to enhance the blood concentration of doxorubicin and paclitaxel

(Thanki et al. 2013; Jain, Patil, et al. 2012; Jain, Kumar, et al. 2012). Lecithin vesicles achieved >98% encapsulation and enhanced the bioavailability of cyclosporine A compared to marketed Sandimmune® formulation (Guo, Ping, and Chen 2001; Chen et al.

2003). Further, folic acid coupled phosphatidylcholine-based liposomes was used to 31 encapsulate cefotaxime to achieve receptor-mediated endocytosis and achieve higher oral bioavailability in rats (Ling et al. 2009).

1.4.2.1.2. Solid lipid-based drug carriers

Several solid lipid-based carriers have been investigated to overcome the limitations such as stability in low pH associated with liposome-based formulations. These includes solid lipid nanoparticles (SLNs), lipid-drug conjugate nanoparticles (LDC-NPs) and nanostructured lipid carriers (NLCs). SLNs are promising carriers for compounds with low water solubility and intestinal permeability (Attama 2011). SLNs are prepared from lipids with high melting points (Severino et al. 2012; Agrawal et al. 2014). The ease of scaling up using high-pressure homogenizer and the absence of organic solvents makes it an attractive drug delivery carrier. Small molecules and peptides have been encapsulated in SLNs and evaluated for oral delivery (Muller, Mader, and Gohla 2000). Insulin-loaded

SLNs were found to increase their tolerance against peptic enzymes and enhanced the bioavailability in vivo compared to subcutaneous injection (Zhang et al. 2006).

Incorporation of simvastatin (HMG-CoA reductase and BCS II drug) in SLNs, consisting of glyceryl behenate, glyceryl palmitostearate, glyceryl monostearate and PEG glyceride, and enhanced the oral bioavailability (Padhye and Nagarsenker 2013). NLCs are advantageous over other lipid-based systems in terms of high drug loading, longer shelf- life, and feasibility of incorporating both hydrophilic and lipophilic drugs (Poonia et al.

2016). However, SLNs suffer from low drug loading efficiency due to dense pack lipid molecules and can expel the loaded drug on storage (Muchow, Maincent, and Muller 2008;

Poonia et al. 2016). To address this issue, lipid-drug conjugate (LDCs) nanoparticles have 32 been developed. Lipid-drug conjugates are prepared by covalently conjugating drug molecules with lipids (Irby, Du, and Li 2017). For example, lipid-drug conjugate nanoparticles (LDC-NPs) of methotrexate (MTX) have been prepared to overcome low and variable oral bioavailability of this drug (Paliwal, Rai, and Vyas 2011). Nanostructured lipid carriers (NLCs) have also been tested for oral drug delivery (Poonia et al. 2016). For example, atorvastatin loaded NLCs demonstrated higher solubility and oral bioavailability compared to Lipitor® formulation (Elmowafy et al. 2017). NLCs are advantageous over other lipid-based systems in terms of high drug loading, longer shelf-life, and feasibility of incorporating both hydrophilic and lipophilic drugs (Poonia et al. 2016). Table 3 lists some representative examples of lipid nanoparticles used for oral drug delivery.

1.4.2.1.3. Self-emulsifying drug delivery systems

Self-emulsifying drug delivery systems (SEDDS) or self-micro emulsifying drug delivery systems (SMEDDS) is an isotropic mixture of solvents/co-solvents, lipids/oils, and surfactants designed to deliver compounds with poor solubility (Gursoy and Benita

2004). Micro or nanoemulsions are thermodynamically stable, an isotropic mixture of oil, surfactant, water, and co-solvents. Micro or nanoemulsion technology is used to address the challenges associated with the delivery of water-insoluble compounds.

Micro/nanoemulsions are usually prepared using high-pressure homogenizer to reduce the droplet size in the range of 50-500 nm diameter (Table 3). The microemulsion have been reported to be effective in protecting the drug from enzymatic attack after oral delivery in the rabbits (Nicolaos et al. 2003). 33

SEDDS/SMEDDS can be placed in soft or hard gelatin capsules for oral administration and form stable oil-in-water emulsions in the presence of GI fluids (Shao et al. 2015; Pouton 2000). The lipid content in the formulation can also stimulate the biliary secretion from the gallbladder (Kalepu, Manthina, and Padavala 2013). In the presence of bile salts, lipid formulations (e.g., SEDDS or SMEDDS) can be digested leading to the formation of vesicles, micelles or mixed micelles (Fig. 9). Drug absorption efficiency is dictated by the physicochemical characteristics of SEDDS/SMEDDS formulations such as the ratio of oil and surfactant, the concentration of surfactant, polarity, droplet size and surface charge (Hauss 2007). Taken together, SEDDS/SMEDDS can improve the solubilization of drugs in the small intestine and enhance bioavailability after oral administration (McClements and Xiao 2014; Gursoy and Benita 2004). SEDDS have been efficiently used to enhance the oral bioavailability of BCS class III and class IV drugs.

Currently, there are several SEDDS formulations are available in the market including

Sandimmune®, Sandimmun Neoral® (Cyclosporin A), Norvir® (Ritonavir), and

Fortovase® (Saquinavir).

Lipid-based drug carriers have additional benefit that they mimic chylomicron pathway and target intestinal lymphatic system after oral delivery (Ahn and Park 2016).

The lymphatic system plays an important role in the uptake and removal of toxins and foreign materials from the body (Longmire, Choyke, and Kobayashi 2008). Lymphatic systems are also responsible for maintaining the fluid balance in the body by removing interstitial fluid and return to blood after filtering damaged cells, cancer cells, bacteria, and viruses (Dixon 2010). Furthermore, lymphatic system plays an important role in the absorption and distribution of fat and fat-soluble vitamins from the GI tract (Dixon 2010). 34

Targeting lymphatic systems using lipid-based formulations (liposomes, SLNs, NLCs,

SEDDS) is especially useful for treatment of diseases like lymphoma and HIV (Kalepu,

Manthina, and Padavala 2013). Figure 11 shows the mechanism of drug absorption of drug from SEDDS formulation. The lipid-based drug delivery system can mimic the chylomicron pathway to improve the bioavailability and by-pass the first-pass metabolism

(Chaudhary et al. 2014). Further, the lipid based delivery system can facilitate transcellular absorption due to increased membrane fluidity, allow paracellular transport by opening tight junctions, and increase epithelial cell uptake by inhibiting P-gp/CYP450 (Zeng et al.

2012; O'Driscoll 2002; Frazer 1955).

However, SEDDS formulations suffer from limitation such as i) migration of volatile co-solvents to capsule shell, ii) lack of good predictive in vitro models for assessment of formulations, and iii) high concentration of surfactants in SEDDS can be toxic to the epithelial membrane. 35

Table 3: Lipid nanoparticles used for oral drug delivery applications.

Drug Excipients Type Outcome References

Cefotaxime Unsaturated soybean Liposomes At 90% confidence interval, the value for Ling et al. (2009)

phosphatidylcholine AUC0–∞ was 1.4–2-times higher and the value

for Cmax was 1.2–1.8-times higher for the folic acid coupled liposomes compared with folic acid-free liposomes. Testosterone Dynasan 118, stearic acid, NLC Facilitated administration of a single dose of Muchow et al. undecanoate Tween 80, carnauba wax testosterone undecanoate in a unit oral dosage (2011) form and reduced variation in bioavailability in the fed and fasted states Pentoxifylline Lecithin, cetyl alcohol, SLN SLN prepared by homogenization followed by Varshosaz, Tween 20 sonication. The system enhanced the Minayian, and bioavailability of the drug (5.23-fold higher in Moazen (2010) comparison with the suspension) by avoidance of the first-pass metabolism Crypto Glyceryl monostearate, SLN Incorporation of the drug into a solid lipid Hu et al. (2010) tanshinone Compritol ATO, matrix altered the in vivo metabolic behavior of Tween 80, soy lecithin, the drug, thereby increasing the bioavailability. sodium Incorporation of sodium dihydrofolate into 36

dihydrofolate SLNs significantly enhanced the oral bioavailability Buspirone Poloxamer, soy lecithin, SLN SLNs enhanced the bioavailability of the drug Varshosaz, spermaceti, Polysorbate 80, 2.53-fold by avoiding the pre-systemic hepatic Tabbakhian, and cetyl alcohol metabolism. Mohammadi (2010)

Vinpocetine Compritol ATO, Solutol NLC Nanostructured lipid carriers showed sustained Zhuang et al. (2010) HS 15, Poloxamer, Miglyol release of the drug, with a remarkable increment 812N, monostearate in bioavailability (322 %) in comparison to a drug suspension. Application of Solutol HS 15 as a surfactant in the NLC altered the integrity of intestinal epithelial cells and increased the permeability. Lopinavir Stearic acid SLN The SLN showed a biphasic sustained drug Ravi et al. (2014) release, which led to enhanced oral bioavailability (5- fold) and improved the distribution of the drug to HIV reservoirs. The report suggested this is a better an alternative to the marketed lopinavir/ritonavir coformulation. 37

Saquinavir Dextran protamine, Precirol NLC The permeability of saquinavir loaded into Beloqui et al. (2014) ATO15, Miglyol 812, dextran protamine-coated nanostructured lipid Polysorbate 80, Poloxamer, carriers was increased ninefold in comparison protamine sulfate, dextran with uncoated NLC. Cyclosporin A Olive oil, polyglycolyzed SEDDS Increased solubility and oral bioavailability of Gursoy and Benita glycerides, ethanol Cyclosporin A. (2004)

Ritonavir Oleic acid, Polyoxyl 35 SEDDS Improved oral bioavailability of ritonavir. FDA (2006) castor oil, ethanol Paclitaxel dl-α-tocopherol, TPGS, SMEDDS Enhanced solubility and oral bioavailability of Gursoy and Benita paclitaxel. Tyloxapol (2004)

Cefpodoxime Medium-chain Microemulsion Enhancement of the absolute bioavailability of Nicolaos et al. proxetil triglycerides, Soybean cefpodoxime proxetil. (2003) Lecithin, Polysorbate 80, HIV: human immunodeficiency virus, NLC: nanostructured lipidic carrier, SLN: solid lipid nanoparticle, AUC: Area under the plasma concentration-time curve, NLCs: Nanostructured lipid carriers, SLN: Solid lipid nanoparticles, SEDDS: Self-emulsifying drug delivery system, SMEDDS: Self-microemulsifying drug delivery system, Cmax: Maximum plasma drug concentration.

Reproduced from Pathak and Raghuvanshi (2015) and Gursoy and Benita (2004). 38

Figure 11: Schematic representation of mechanisms of intestinal drug transport from

SEDDS formulations. Reproduced from Kalepu, Manthina, and Padavala (2013).

1.4.2.2. Polymeric nanocarriers

Polymeric materials have been extensively investigated for the development of drug carriers (Galindo-Rodriguez et al. 2005; Pridgen, Alexis, and Farokhzad 2014, 2015).

A variety of synthetic and natural polymers have been tested for their potential to overcome barriers associated with oral drug delivery (Table 4) (Agrawal et al. 2014). Drug molecules are encapsulated inside the polymeric matrix or dispersed, adsorbed, complexed within the polymeric matrix (Huang and Dai 2014).

Various techniques have been used to prepare polymeric nanocarriers, which mainly fall into top-down and bottom-up processes (Fig. 10). The top-down method is based the reduction of particle size using various techniques such as ultrasonication, cavitation, homogenization, microfluidization, milling and spray drying (Reis et al. 2006).

On the otherhand, the bottom-up technique is based on particle growth from individual particles such as phase separation method including controlled crystallization during freeze-drying or technologies that use supercritical fluid (de Waard, Frijlink, and Hinrichs

2011).

Polymeric microparticles exhibit higher stability in GI tract, encapsulate both hydrophilic and hydrophobic molecules (Vilos and Velasquez 2012). Different types of polymers have been used to prepare nanoparticles or microparticles (Table 5) (Chawla,

Sharma, and Pawar 2012; Rahman et al. 2006; Hsu, Yu, and Huang 2013; Patel et al. 2016;

Simonoska Crcarevska, Glavas Dodov, and Goracinova 2008). For example, alginate and chitosan are widely used natural polymers to develop nanoparticles and microparticles.

These polymers found to reduce drug release in stomach, increase stability, and sustain drug release at higher pH in intestine (Calija et al. 2013). 40

Nanoparticles are defined by the diameter on the order of 100 nm which is comparable to many viral particles (Pridgen, Langer, and Farokhzad 2007). Polymeric nanoparticles have also been studied for oral drug delivery applications and drug molecules can be entrapped in the core of the nanoparticles during the preparation (Mo et al. 2014;

Galindo-Rodriguez et al. 2005). The surface of polymeric nanoparticles can be modulated by utilizing the polymeric end groups or by conjugating another polymer to the surface of nanoparticles (Valencia et al. 2013).

Polymeric micelles are relatively small, spherical structure composed of amphiphilic polymers (Croy and Kwon 2006). The polymers used in the micelle helps to orient lipophilic hydrocarbon chain towards center leaving aqueous groups in contact to aqueous medium. The concentration of polymers at which micelles are formed is known as critical micelle concentration (CMC). Polymeric micelles have been investigated for improving oral bioavailability of hydrophobic drugs molecules (Francis, Piredda, and

Winnik 2003; Dabholkar et al. 2006; Pierri and Avgoustakis 2005). Polymeric micelles have been tested to increase aqueous solubility of cyclosporin A (Francis, Cristea, and

Winnik 2005; Francis et al. 2005; Francis et al. 2003). Further, pH-sensitive polymeric micelles have also been tested to enhance intestinal absorption of hydrophobic compounds

(Pierri and Avgoustakis 2005; Ould-Ouali et al. 2005). Polyethylene glycol (PEG)-b-

P(alkyl(meth)acrylate-co-methacrylic acid)s (PEG-b-P(Al(M)Aco-MAA)s) is a diblock copolymer and shows pH-dependent micellization in aqueous media. Polymeric micelles formed from this diblock copolymers have been studied for the delivery of several hydrophobic drugs. Several studies shown that fluid phase endocytosis pathway is the 41 major cell uptake mechanism for polymeric micelles (Allen et al. 1999; Luo et al. 2002).

Table 5 lists some representative examples polymeric micelles used for oral drug delivery.

Table 4: Representative synthetic and natural polymers for oral drug delivery.

Class of polymers Examples

Polyesters Poly(lactic-co-glycolic acid) (PLGA), polylactic acid (PLA),

polyglycolic acid (PGA), and poly(ɛ-caprolactone).

Polyanhydrides Poly(sebacic acid), poly(adipic acid), poly(terephthalic acid), and

their copolymers)

Polyamides Poly(imino carbonates) and polyamino acids)

Polyethers Polyethylene glycol (PEG) and polypropylene glycol

Cellulose Carboxymethyl cellulose, hydroxypropyl methyl cellulose derivatives (HPMC), ethyl cellulose, hydroxypropyl methyl cellulose acetate

succinate (HPMC-AS), and cellulose acetate succinate (CAS)

Protein Collagen, gelatin, and albumin

Polysaccharides Chitosan, alginate, carrageenan, cyclodextrin, and hyaluronic acid

Reproduced from Kapoor et al. (2015) and De Jong and Borm (2008). 42

Figure 12: Different techniques used for the preparation of polymeric nanocarriers. Adapted from Bennet and Kim (2014). 43

Table 5: Representative list of polymeric nanocarriers used for oral drug delivery.

Polymers Drug Key findings Reference

PEG-b-PCL NHS-PEGb- PCL solution of Coumarin 6 The functional nanocarriers specifically interact Du et al. (2013)

7pep (Transferrin receptor (TfR) specific with gastrointestinal epithelial cells and increased

7peptide nanocarrier) drug transport.

Tocopherol succinate glycol chitosan (GC- Ketoconazole GC-TOS increased the solubility of ketoconazole Duhem et al.

TOS) conjugates (Micelles) (BCS class II drug) and enhanced the intestinal (2012)

permeation.

Pluronic copolymers and LHR conjugate Paclitaxel Pluronic/ LHR micelles enhanced the oral Dahmani et al.

(Mixed polymeric micelles) bioavailability of paclitaxel. (2012)

Alginate-oligochitosan-Eudragit(®) L100- NSAIDs Improved the stability and reduced drug release in Calija et al. 55 (ALG-OCH-EL) (Microparticles) acidic pH (stomach). (2013) Alginate coated chitosan core-shell Naringenin Effective in the treatment of dyslipidemia, Maity et al. (Nanoparticles) hyperglycemia compared to free Naringenin (2017) Vitamin B12-Chitosan (Nanoparticles) Scutellarin 2-3 fold greater oral bioavailability than free Wang et al. scutellarin (2017) 44

N-trimethyl chitosan-palmitic acid Resveratrol 3.8-fold increase in oral bioavailability Ramalingam (Micelles) and Ko (2016) PLGA (Nanoparticles) Lopinavir 13.9-fold increase in oral bioavailability Joshi, Kumar, and Sawant (2016) PEG-PLGA (Nanoparticles) Ginsenoside 3 to 9-fold increase in oral bioavailability Voruganti et al. (2015) Methacrylate copolymer (Eudragit 100) Efavirenz Higher serum drug concentration than free drug Hari et al. (Nanoparticles) (2016) sericin/poly(ethylcyanoacrylate) Fenofibrate 70% increase in oral absorption Parisi et al. (Nanospheres) (2015) Gelatin-pluronic F68 (Nanoparticles) Acyclovir 2-fold increase in drug exposure Kharia and Singhai (2015)

PEG-PAMAM dendrimer (Nanoparticles) Probucol Increased plasma concentration and lipid- Qi et al. (2015) lowering effect when delivered using nanoparticles Basic methacrylate copolymer Atazanavir 2.91-fold increase in drug exposure Singh and Pai RL100 (Nanoparticles) (2016) 45

Increased the mice survival rate against advanced Poly(butyl cyanoacrylate) and Poly(ε- Ortiz et al. 5-Fluorouracil or recurrent colon cancer compared to free 5- Caprolactone) (Nanoparticles) (2015) Fluorouracil.

Mucoadhesive dendrimer (Nanoparticles) Albendazole 2.4-fold increase in Cmax. Mansuri et al. (2016) Poly(amido amine) dendrimers Camptothecin Cationic and anionic PAMAM dendrimers were Sadekar et al. (Nanoparticles) effective in enhancing the oral absorption of (2013) camptothecin. pH-dependent micellization and high drug Satturwar et al. Poly(ethylene glycol)-b- Candesartan loading. poly(alkyl(meth)acrylate-co- cilexetil (2007) methacrylic acid) micelles

High drug loading, stable micelle in simulated Pierri and Poly(lactide)-poly(ethylene glycol) micelles Griseofulvin gastrointestinal fluid. Avgoustakis

(2005)

PMMMA-PLGA:poly[(methyl methacrylate)-co-(methyl acrylate)-co-(methacrylic acid)]-poly(D,L-lactide-co-glycolide), PAMAM: Poly(amidoamine), PCL: Poly(caprolactone). 46

1.5. Natural polymers

Natural polymers are attractive materials for developing nanoparticulate based oral drug delivery systems due to their biocompatibility. Natural polymers are derived from plant sources like corn, cellulose, potato, soybean, or animal sources or synthesized by bacteria (Nair and Laurencin 2007). The characteristics of natural polymers can be improved by changing the surface chemistry such as dextran, cyclodextrins, and derivatives of starch, cellulose, chitosan (Cumpstey 2013). These polymers have been widely investigated for their application in drug delivery (Mogosanu and Grumezescu 2014). For example, characteristics of cyclodextrins have been further improved by the substitution of some of the hydrogen bonds with methyl groups result in increased solubility, stability, and bioavailability, while decreasing the toxicity of polymer or drug (Figueiras et al. 2007).

Several research groups have studied natural polymers to develop nanocarriers for oral delivery of drugs (Alqahtani et al. 2017; Hu et al. 2015; Bagre, Jain, and Jain 2013;

Huang et al. 2015; Santipanichwong et al. 2008).

Both polysaccharide and protein-based natural polymers have been investigated for oral drug delivery applications.

1.5.1. Polysaccharide-based polymers

Polysaccharide-based polymers are ubiquitous and mainly obtained from algae, plants, microbes, and animals. These polymers have been studied for drug delivery applications (Cumpstey 2013). The diversity of structure and availability of derivable functional groups provide enormous potential for the development of non-toxic, safe, and cost-effective nanocarriers (Zhang, 2013). Polysaccharides are mainly divided into 47 polyelectrolyte and non-polyelectrolyte polymers (dextran, dextrin, pullulan, etc.).

Polyelectrolyte polysaccharides can also be divided into positively charged (chitosan) and negatively charged (heparin, hyaluronic acid) polymers (Sinha and Kumria 2001).

Electrostatic interaction of oppositely charged polymers have been used for the formation of polysaccharide-based nanocarriers (Boddohi et al. 2009; Boddohi et al. 2010). Some polysaccharide polymers such as chitosan exhibit efficient mucoadhesion due to the formation of non-covalent bonds with intestinal mucosa and modifies the GI transit time

(Guggi, Krauland, and Bernkop-Schnurch 2003). Alginate, chitosan, guar gum, pectin, xanthan gum, gellan gum and carrageenan based nanocarriers have been investigated for oral drug delivery applications (Bhatia 2016; Jana 2011). Alginate has been used in combination with other synthetic or natural polymer to modulate the functional performance (Bacon 2002). Chitosan is a cationic, biodegradable, and non-toxic polymer and has been extensively investigated alone or in combination with other polymers for oral drug delivery applications (George and Abraham 2006). Alginate can be modified by cross- linking to control the release of encapsulated drugs (Pillay et al. 1998). Alginate has also been grafted with albumin, PLGA, PEG, heparin, and guar gum to control the drug release from polymer matrix (Hauptstein et al. 2015; Moebus, Siepmann, and Bodmeier 2009;

Davidovich-Pinhas, Harari, and Bianco-Peled 2009; El-Sherbiny et al. 2011; Mennini et al. 2012; Pongjanyakul and Puttipipatkhachorn 2007; Wells and Sheardown 2011). For example, rifampicin loaded PLGA-alginate core-sehll microsphere was shown to modify drug release kinetics and achieved near zero-order release pattern (Wu et al. 2013).

1.5.2. Protein polymers

Protein polymers are versatile class of biopolymers with a wide-range of amino acid composition and varying physicochemical properties, which in-turn can influence its functional performance (Podaralla 2009). The protein polymers have gained increased attention due to the following advantages such as i) availability of various modifiable functional groups (-NH2, -COOH and -SH), ii) renewable source and low cost, iii) protein polymers are obtained from natural source and do not require initiators for synthesis, and iv) proven biocompatibility compared to some of the synthetic polymers (Mukherjee et al.

2014). The formation of nanocarriers using protein polymers is mainly dictated by the protein structure and subsequent intra- or inter-molecular interaction. (Ko and

Gunasekaran 2006).

However, the purity of protein polymers is difficult to control compared to synthetic polymers. In addition, immunogenicity is one of the major concerns with protein polymers

(Podaralla 2009). The major limitation of natural protein polymers is batch-to-batch variation (Podaralla 2009). Table 6 lists the physicochemical properties of some of the protein polymers used for drug delivery.

Table 6: Physicochemical properties of protein polymers.

Protein Source Composition Molecular Isoelectric

weight point

Gelatin Collagen 4-hydroxylysine, 15-250 KDa 7-9 (Type

hydroxyproline, glycine, A), 4-5

alanine, and proline (Type B)

Albumin Plasma Single polypeptide with 585 66 KDa 4.7

protein amino acids

Whey Milk protein α-lactoglobulin (LG), β-LG, β-LG-18 KDa 3.5-5.2

protein lactalbumin, α-LG-14 KDa

immunoglobulin, lactoferrin.

Casein Milk protein Proline- α s1, α s2, β and k α s1-23 KDa 4.6

subunits α s2- 25 KDa

β – 24 KDa

k – 19 KDa

Zein Zea mays L. High proportion of glutamine α-zein-22-24 5.0-9.0

and proline KDa, β-zein-

44 KDa, γ-

zein-14 KDa

Gliadin Wheat flour Glutamine, Proline 28-55 KDa 6.8

Reproduced from Podaralla (2009).

1.5.2.1. Animal proteins

1.5.2.1.1. Gelatin

Gelatin is the hydrolytic product of collagen and has a long history of use in pharmaceutical industry as gelatin capsules (Marty, Oppenheim, and Speiser 1978; Ziv,

Avtalion, and Margel 2008). Gelatin is non-toxic, non-immunogenic, cost-effective and can be easily modified to develop nanocarriers (Jahanshahi, Sanati, and Babaei 2008;

Boulle et al. 2008). The presence of multiple ionizable functional groups in gelatin (-

COOH, -NH2, phenol, guanidine, imidazole) favors conjugation of a variety of molecules

(Saxena et al. 2005; Shutava et al. 2009). However, unmodified gelatin is less stable and is water insoluble (Lohcharoenkal et al. 2014). Addition of cross-linking agent such as glutaraldehyde can overcome the limitations associated with gelatin’s stability and can be used to control the release of encapsulated drugs (Jameela and Jayakrishnan 1995). For example, glutaraldehyde cross-linked gelatin microsphere coated with alginate or chitosan improved the stability of gelatin microsphere and controlled the release of methotrexate after oral administration in rats (Narayani 1995).

1.5.2.1.2. Albumin

Albumin (66 kDa) can be obtained from different sources such as egg white, bovine serum albumin (BSA), and human serum albumin (HSA). Albumin maintains the osmotic pressure in human blood and is responsible for binding of nutrients. Albumin is highly soluble at physiological pH and is an attractive carrier due to its ability to bind to various molecules (Peters 1985). The reactive functional groups in albumin can be manipulated to conjugate drug molecules depending on the application (Casi and Neri 2012). For example, 51 emulsion solidification method has been used to prepare fluorouracil loaded BSA-alginate.

The nanoparticles were found to be distributed in liver, kidneys, lungs and brain after oral delivery in rat (Yi, Yang, and Pan 1999). The major limitation of natural protein polymers is batch-to-batch variation and may hinder the scaling-up for industrial application

(Elzoghby, Samy, and Elgindy 2012). HSA is obtained by fractionation of human plasma and can carry bloodborne pathogens. However, recombinant HSA can overcome these limitations (Chuang, Kragh-Hansen, and Otagiri 2002). It is important to note that human serum albumin-bound paclitaxel (Abraxane®) is currently in clinical use for the treatment of breast cancer, lung cancer and pancreatic cancer.

1.5.2.1.3. Milk proteins

Milk proteins include casein (80%) and whey proteins (20%). (Livney 2010) Casein is a mixture of α-, β-, γ-, and κ-casein. Sodium caseinate is widely used as a stabilizer and emulsifier in dairy and food products (Kimpel and Schmitt 2015). Beta-casein is a globular protein and has been explored for oral delivery of hydrophobic molecules (Kytariolos et al. 2013; Bachar et al. 2012; Shapira et al. 2010).

Whey protein is isolated from bovine milk has several proteins including β- lactoglobulin, α-lactalbumin, lactoferrin, bovine serum albumin, immunoglobulins, glycomacropeptide, and enzymes. It is widely used for its nutritional value in infants and children due to the presence of essential amino acids (Baer et al. 2011; Coker et al. 2012;

Miller, Alexander, and Perez 2014). β-lactoglobulin (LG) is a major protein in the whey protein and has been investigated as a carrier for drug and nutraceuticals, because of its ability to bind with lipophilic molecules (Dufour, Genot, and Haertle 1994) such as 52 retinoids (Collini, D'Alfonso, and Baldini 2000), hemin (Frapin, Dufour, and Haertle

1993), aromatic and carcinogenic hydrocarbons (Farrell, Behe, and Enyeart 1987; Tavel et al. 2010), palmitic acids (Ragona et al. 2000; Wu et al. 1999), cholesterol and tocopherol

(Wang, Allen, and Swaisgood 1997), omega-3-fatty acids (Zimet and Livney 2009), and anti-neoplastic agents (Eberini et al. 2008). β-lactoglobulin is relatively less affected by peptic enzymes and is a promising vehicle for oral delivery of therapeutics (Miranda and

Pelissier 1983; Yvon et al. 1985).

Lactoferrin is an iron-binding glycoprotein which possesses multiple biological activities including antibacterial, antiviral, antioxidant and anticancer activity (Baker and

Baker 2009). Lactoferrin acts as a natural iron transporter and has been investigated as a ligand for targeting blood-brain barrier and intestinal epithelium through the transferrin receptors (Zhang, Wang, Ayman, et al. 2013; Singh et al. 2016).

1.5.2.2. Plant proteins

1.5.2.2.1. Gliadin

Gliadin is a gluten protein found in wheat and is water-insoluble due to the presence of high proportions of glutamine and proline residues (Thewissen et al. 2011; Delcour et al. 2012). Gliadin proteins are divided into two groups based on solubility. These includes monomeric gliadin (soluble in 70% alcohol) and polymeric glutenin (insoluble precipitate).

The presence of neutral and hydrophobic amino acids in gliadin favors interaction with the epithelium by forming hydrogen and hydrophobic bonds (Ramteke and Jain 2008). Gliadin can also interact with mucin due to the presence of disulfide groups (Arangoa et al. 2001;

Gulfam et al. 2012). Gliadin based nanoparticles have been tested for oral delivery of 53 retinoic acid and vitamin E (Duclairoir et al. 2003). However, some individuals with gluten intolerance can be sensitive to gliadin, thus limiting its application as a drug carrier

(Ciclitira et al. 2005; Dewar, Pereira, and Ciclitira 2004; Friis 1996; Joye, Nelis, and

McClements 2015).

1.5.2.2.2. Zein

Zein is one of the few water-insoluble natural proteins with a high proportion

(>50%) of hydrophobic amino acids (proline, alanine, and leucine). It is the major storage protein in corn and is composed of α, β, γ, and δ zein, classified based on the solubility in hydroalcoholic solvents (Joshi et al. 2015). Commercial zein is mainly composed of α-zein

(22−27 kDa). Zein is a US-FDA approved Generally recognized as safe (GRAS) material and is widely used in the food and packaging industries to provide an impervious moisture barrier (Corradini et al. 2014). Zein has also been used to encapsulate hydrophobic compounds and sustain the release from microspheres, nanoparticles, and nanofibers

(Table 7) (Zhang, Cui, Che, et al. 2015; Gong et al. 2011; Hashem et al. 2015; Zhang, Cui,

Chen, et al. 2015; Zhang et al. 2016). However, Zein nanoparticles exhibit poor colloidal stability leading to particle aggregation and thus require additional polymer or other materials to form stable nanoparticles (Joye, Davidov-Pardo, and McClements 2015; Chen and Zhong 2014).

1.5.2.2.3. Soy proteins

Soy protein isolate (SPI) contains a high concentration of protein rich in essential amino acids. Glycinin and β-conglycinin constitutes the major portion of SPI (Yaklich 54

2001). The presence of polar, non-polar and charged amino groups facilitates the incorporation of a variety of drug molecules (Teng, Luo, and Wang 2012). The globular protein forms a hydrophobic core in the presence of water and the addition of crosslinking agent leads to aggregation and formation of microspheres (Lazko, Popineau, and Legrand

2004). Curcumin nanocomplexation with SPI significantly enhanced the solubility of curcumin and stability in GI tract (Table 7) (Chen, Li, and Tang 2015). The physicochemical properties of SPI are variable and dependent on nature and composition of starting materials (defatted soy flour or flakes), processing and preparation procedure used, and environmental conditions (Liu and Tang 2013; Keerati and Corredig 2009). In addition, some portion of SPI remains as aggregated particles during the process of isolation of SPI from its starting materials, and the surface hydrophobicity significantly increases with heat treatment (Keerati and Corredig 2009; Liu and Tang 2013).

Table 7: Natural protein polymers for oral drug delivery applications.

Protein polymers Drugs Findings Reference

Zein nanoparticles Folic acid Two-times higher oral Peñalva (2015) bioavailability of folic acid compared to free folic acid. Zein-alginate nanoparticles Superoxide Reduced intracellular reactive Lee, Kim, and Park (2016) Dismutase oxygen species. Zein nanoparticles Quercetin Sustained plasma level of Penalva et al. (2017) quercetin and anti-inflammatory activity. Compressed zein microsphere Ivermectin Increased oral bioavailability of Gong et al. (2011) ivermectin in dogs.

Zein microsphere Aceclofenac Sustained release oral drug Karthikeyan et al. (2012) sodium delivery system. Casein nanoparticles Cisplatin Increased oral absorption of Zhen et al. (2013) cisplatin. Casein nanoparticles Flutamide Enhanced oral bioavailability of (Elzoghby, Helmy, et al. 2013b, flutamide for the treatment of 2013a; Elzoghby, Saad, et al. prostate cancer. 2013) Bovine Lactoferrin Doxorubicin Increased doxorubicin Golla et al. (2012) bioavailability in hepatic tumor model. 56

β-Casein Nanomicelles Paclitaxel Increased stability and availability Bar-Zeev, Assaraf, and Livney of paclitaxel in gastric carcinoma (2016) animal model.

β-Casein micelle Curcumin Increased solubility and cell Esmaili et al. (2011) uptake of curcumin in human leukemia cells. β-Lactoglobulin nanoparticles Epigallocatechin Prevent oxidation and degradation (Li et al. 2012; Shpigelman, gallate (EGCG) of EGCG Cohen, and Livney 2012)

β-Lactoglobulin nanoparticles Curcumin Enhanced Solubility of curcumin Teng, Li, and Wang (2014)

Nanocomplexation of curcumin with Curcumin Enhanced antioxidant properties of Tapal (2012) soy protein isolate nanoparticles curcumin

Nanocomplexation of curcumin with Curcumin Significantly enhanced solubility Chen, Li, and Tang (2015) Soy Protein Isolate nanoparticles and permeability of of curcumin 57

1.6. Scope and objectives

Food-grade polymers are promising materials for developing oral drug delivery systems due to their biocompatibility and proven safety. This study focuses on the use of food protein-based nanoparticles/micelles for oral drug delivery applications.

Zein has been used to form nanoparticles for various drug delivery applications

(Penalva et al. 2017; Irache and Gonzalez-Navarro 2017; Penalva et al. 2015; Luo et al.

2013; Podaralla and Perumal 2012). However, in the absence of a stabilizer, zein nanoparticles tend to aggregate (Davidov-Pardo et al. 2015; Chen and Zhong 2014). To this end, the goal of this study is to develop stable core-shell nanocarriers using other proteins or polymers as shell. The overall goal of this study was to systematically study the influence of shell composition on the physicochemical and functional performances of zein nanocarriers for oral drug delivery applications. The study was based on the hypothesis that the hydrophobic core can be used to encapsulate water-insoluble compounds and achieve sustained release, while the shell biopolymer can be used to provide unique functional characteristics and good sensory properties for oral drug delivery applications.

Six different core−shell nanocarriers were prepared including zein-β-casein (ZC) nanoparticles, zein-lactoferrin (ZLF) nanoparticles, zein-polyethylene glycol (ZPEG) micelles, zein-β-lactoglobulin (ZLG) nanoparticles, zein-whey protein isolate (ZWP) nanoparticles and zein-pluronic-lecithin (ZPL) nanoparticles. The core-shell nanocarriers in addition to stabilizing the zein core, offers the following advantages i) enhanced dispersibility and enzymatic stability, ii) sustained drug release, and iii) enhanced permeability and bioavailability of encapsulated drugs. 58

The overall goal is to demonstrate the feasibility and application of core-shell nanocarriers for oral drug delivery.

To achieve this goal, following were the specific aims of this study:

Objective 1: Preparation and study of the structure-function relationship of core-shell zein nanocarriers for oral drug delivery applications.

Objective 2: Use of core-shell nanocarriers for oral delivery of a model antiretroviral drug.

Objective 3: Use of core-shell nanocarriers for oral delivery of an investigational anticancer drug molecule.

CHAPTER TWO

PREPARATION AND STUDY OF THE STRUCTURE-FUNCTION

RELATIONSHIP OF CORE-SHELL NANOCARRIERS

2.1. Introduction

Given that oral delivery is the most common and convenient route of drug administration with high patient compliance, several strategies (nanoparticles, micelles, emulsions, and lipid-based carriers) have been explored to address the oral delivery challenges (Agrawal et al. 2014; Zhang, Wang, Zhang, et al. 2013; Kohli et al. 2010;

Simoes et al. 2015). Considering the versatility of nanocarriers for oral drug delivery applications, a wide range of materials (natural and synthetic polymers) have been tested for developing nanoformulations (Agrawal et al. 2014; Zhang, Wang, Zhang, et al. 2013).

However, very limited studies have focused on the development of nanocarriers for pediatric oral drug delivery. The major concern in developing nanocarriers in general and pediatric in particular to ensure that excipients are safe.

Given the dynamic change in physiology from birth through adolescence, development of medicines for pediatrics remains a challenge in formulation development

(Ivanovska et al. 2014; Nahata 1999). The Pediatric Research Equity Act (PREA) was introduced in 2012 (Christensen 2012; Ren and Zajicek 2015). The Best Pharmaceuticals for Children Act (BPCA) and Pediatric Research Equity Act (PREA) together was introduced to develop safe and effective medicines for pediatric patients (Ren and Zajicek

2015; Christensen 2012). Formulations developed for adult per say may not suitable for pediatric patients. The excipients that are suitable for adults may not necessarily be safe for pediatrics. Therefore, a comprehensive assessment of the excipients is essential before in pediatric drug formulations (Schmitt 2015; Salunke et al. 2013; Salunke, Giacoia, and

Tuleu 2012). There have been some efforts to develop easy, reliable, and flexible pediatric formulations such as minitablets, pellets, orally dispersible tablets, chewable tablets, 61 powders for reconstitutions, liquid syrup, and suspension (Ivanovska et al. 2014).

However, there is an unmet need especially to improve the oral bioavailability of drugs with poor physicochemical properties.

In this regard, food-grade biopolymers especially protein polymers are promising for developing oral drug delivery vehicles since they are edible, safe and biocompatible.

Protein polymers that have been explored for oral drug delivery applications include gelatin, casein, whey proteins, soy proteins, zein, and wheat proteins (Arangoa et al. 2001;

Liu et al. 2005). Zein is a water-insoluble protein GRAS protein polymer that is widely used in food and packaging industry (Corradini et al. 2014). Zein has been used to encapsulate hydrophobic compounds and sustain the release from microspheres, nanoparticles, and nanofibers (Zhang, Cui, Che, et al. 2015; Gong et al. 2011; Hashem et al. 2015; Zhang, Cui, Chen, et al. 2015; Zhang et al. 2016). However, zein nanoparticles exhibit poor colloidal stability leading to particle aggregation (Joye, Davidov-Pardo, and

McClements 2015; Chen and Zhong 2014). To this end, the main goal of this study is to develop zein-based nanocarriers using different food-grade biocompatible polymers as stabilizers on the outer shell of the nanocarrier. The focus of this study is to systematically investigate the influence of shell composition on the physicochemical and functional performance of core-shell zein nanocarriers for oral delivery applications.

In this study, milk proteins including casein whey protein as a whole or individual proteins ( (lactoglobulin and lactoferrin which differ in their physicochemical properties were used (Livney 2010). Beta-casein can form microsphere and micelles, and it has been explored as an oral drug delivery vehicle for hydrophobic compounds (Willmott et al.

1992). Beta-casein is comparatively more hydrophobic among the milk proteins and 62 therefore can stabilize zein nanoparticles by utilizing hydrophobic interaction between zein and casein. Whey protein which is isolated from bovine milk has several proteins (β- lactoglobulin, α-lactalbumin, lactoferrin, bovine serum albumin, immunoglobulins, glycomacropeptide, and enzymes) and is widely used for its nutritional value in infants and children due to the presence of essential amino acids (Coker et al. 2012; Miller, Alexander, and Perez 2014). β-lactoglobulin (LG) is the major portion of Whey protein and has been investigated as drug or nutraceutical carrier for its binding capacity with lipophilic molecules (Dufour, Genot, and Haertle 1994; Collini, D'Alfonso, and Baldini 2000; Frapin,

Dufour, and Haertle 1993; Farrell, Behe, and Enyeart 1987; Tavel et al. 2010; Ragona et al. 2000; Wu et al. 1999; Wang, Allen, and Swaisgood 1997; Zimet and Livney 2009;

Eberini et al. 2008). β-lactoglobulin was less affected by peptic enzymes and is a promising vehicle for oral delivery of therapeutics. (Miranda and Pelissier 1983; Yvon et al. 1985).

Lactoferrin (LF) is an iron-binding glycoprotein that belongs to the transferrin family

(Baker and Baker 2009). Lactoferrin has a high nutritional value for infants and children as an iron transporter. (Manzoni 2016). It also has been used as targeting ligand for improving the delivery across the blood−brain barrier and intestinal epithelial barrier through lactoferrin receptors. (Singh et al. 2016; Zhang, Wang, Ayman, et al. 2013).

Nanoparticles prepared using zein per se results in larger particles with wide size distribution, particle aggregation, and low drug encapsulation. Our lab previously has reported the use of pluronic F68 and lecithin to stabilize zein nanoparticles and achieve higher drug encapsulation (Podaralla and Perumal 2010). A combination of pluronic F68 and lecithin in 2:1 ratio stabilized the zein nanoparticles (Podaralla and Perumal 2010, 63

2012). In this study, we will explore the use of zein-pluronic-lecithin (ZPL) nanoparticles for oral drug delivery.

Polyethylene glycol (PEG) is an FDA approved biocompatible polymer that has been used to modify the surface of nanoparticles and proteins (D'Souza A and Shegokar

2016). Further, PEG is a widely used water-soluble excipient in oral and other formulations

(D'Souza A and Shegokar 2016). Earlier research from our group has demonstrated the ability of PEGylated zein to form self-assembled micelles with hydrophobic zein as the core and hydrophilic PEG chain as the shell (Podaralla et al. 2012). The PEG-zein (ZPEG) micelles enhanced the aqueous solubility and chemical stability of curcumin, a water- insoluble anticancer agent. Further, the curcumin-loaded PEG-zein micelles showed higher cell uptake than free curcumin in drug-resistant cancer cells and reduced the IC50 value of curcumin by 3-fold (Podaralla et al. 2012). However, the ZPEG micelles is yet to be investigated for oral drug delivery.

In this study, six different core−shell nanocarriers were prepared including zein-β- casein (ZC) nanoparticles, zein-lactoferrin (ZLF) nanoparticles, zein-polyethylene glycol

(ZPEG) micelles, zein-β-lactoglobulin (ZLG) nanoparticles, zein-whey protein isolate

(ZWP) nanoparticles and zein-pluronic-lecithin (ZPL) nanoparticles. The six nanocarriers differ in their surface charge and hydrophilicity. The influence of shell composition on the physical stability, enzymatic stability, release kinetics, cell/tissue uptake, intestinal permeability, and in vivo biodistribution of zein nanocarriers was evaluated. Nile red (NR) was used as a model hydrophobic compound for in vitro studies, while Cy 5.5, a near- infrared dye, was used for the in vivo imaging studies.

Specific aims of this study were:

i) To develop and characterize zein-based core-shell nanocarriers.

ii) To test the release of encapsulated Nile Red (NR) from the nanocarriers in

simulated gastrointestinal fluids.

iii) In vitro cell uptake studies in Caco-2 cells to determine the kinetics and the

mechanism of cell uptake of the nanocarriers.

iv) Test the bioadhesive properties of the core-shell nanocarriers.

v) Oral immunogenic studies of core-shell nanocarriers in mice.

vi) Oral biodistribution of core-shell nanocarriers in rats.

2.2. MATERIALS AND METHODS 2.2.1. Materials White zein (Zein F-4000) was purchased from Freeman Industries Inc, (Tuckahole,

NY, USA). Nile red, β-casein, β-lactoglobulin, and D-α-Tocopherol polyethylene glycol

1000 succinate (TPGS 1000) were purchased from Sigma-Aldrich Company (St. Louis,

MO, USA). Bovine lactoferrin and whey protein isolate were provided by Dr. Hasmukh

Patel from the Department of Dairy Science, South Dakota State University. Trehalose was obtained from Acros Organics (Bridgewater, NJ, USA). Precast-Gels and reagents for sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) were purchased from Bio-Rad (Hercules, CA). Pepsin, trypsin, sodium azide and Dulbecco’s Modified

Eagle Medium were purchased from Fisher Scientific (Bridgewater, NJ, USA). Dialysis membrane (MWCO 10 kDa) was purchased from Spectrapor (Houston, TX, USA).

ProLong Gold Antifade mounting medium with DAPI was purchased from Invitrogen-

Molecular Probes (Eugene, OR, USA). Polyethylene glycol (PEG, 5kDa) was purchased from Jenkem Technology (Plano, TX, USA). Cyanine 5.5 NHS ester dye was purchased from Lumiprobe (Hallandale Beach, FL, USA).

2.2.2. Preparation of zein-based core-shell nanocarriers The core-shell nanoparticles were prepared using the phase separation method based on differential solubility of zein and milk proteins (Alqahtani et al. 2017; Podaralla et al. 2012). Briefly, 15 mg of zein was dissolved in 2 mL of 90% ethanol containing 1 mg of Nile red (NR) or Cy5.5 dye. The alcoholic phase was added dropwise under probe sonication (Sonics & Materials, Inc., Danbury, CT, USA) to the aqueous phase consisting 66 of 15 mL 0.1 M citrate buffer (pH 7.4) and 0.2% w/v of milk protein (β-casein or lactoferrin) or pluronic (0.9%, w/v)-lecithin (0.45%, w/v) (PL).

Zein-β-lactoglobulin (ZLG) and zein-whey protein isolate (ZWP) nanoparticles were prepared by preheating 15 mg of β-lactoglobulin (LG) or whey protein isolate (WP) in 15 mL of 0.1 M citrate buffer (pH 6.8) for 30 minutes at 60°C before adding in zein hydroalcoholic solution. The resulting colloidal dispersion was placed on a magnetic stirrer

(200 rpm) for 3 hours to evaporate the ethanol. The nanoparticles were separated using centrifugal filter (10 kDa MWCO) (EMD Millipore, Billerica, MA, USA) at 4000 rpm and washed with deionized water to remove the free NR or Cy 5.5. Trehalose (30 mg) was added as a cryoprotectant before lyophilization. The lyophilized formulations were stored in a desiccator at 4°C until further use.

Polyethylene glycol (PEG5000) was conjugated to zein to prepare PEGylated zein micelles as reported earlier (Podaralla et al. 2012). Briefly, zein and methoxy PEG- succinimidyl succinate (5KDa) in the weight ratio of 1:2 (zein: mPEG ester) were dissolved in 90% ethanol and incubated overnight. The reaction was stopped by adding 1 M of glycine followed by dialysis (10 kDa MWCO) for 24 h against water to remove the free

PEG. To prepare the micelles, NR or Cy 5.5 was dissolved in 20 mL of 90% alcohol along with zein-PEG (5.5 × 10−2 g/L), and the mixture was stirred overnight in a magnetic stirrer to allow for partitioning of the dye into the hydrophobic zein core. Ethanol was removed using a rotary evaporator, and the resultant film was hydrated with citrate buffer (pH 7.4) to form ZPEG micelles. The mixture was dialyzed (10 kDa MWCO) against deionized 67 water (100 mL) to remove the free dye. The dye-loaded ZPEG micelles was lyophilized and stored in a desiccator at 4°C until further use.

2.2.3. In vitro characterization and optimization

The particle size, size distribution, and zeta potential were determined using the

Malvern Zetasizer Nano-ZS (Malvern Instruments Inc., Southborough, MA) by dispersing lyophilized nanoparticles in deionized water (0.1 mg/mL). For morphological analysis, the nanocarriers were visualized by transmission electron microscopy (TEM). The specimen was prepared by placing a dilute dispersion of the nanoparticles on carbon-coated 200 mesh copper grid and the sample was evaporated overnight. TEM images were acquired using a

Tecnai Spirit G2 TEM (FEI, Hillsboro, OR, USA), operated at an accelerating voltage of

120 kV. The electron micrographs were recorded using Orius SC200 CCD camera coupled to TEM. Image analysis was performed using Digital Micrograph software.

2.2.4. Determination of Nile Red (NR) encapsulation efficiency

Briefly, 5 mg of NR loaded lyophilized particles was dispersed in deionized water and centrifuged at 14000 rpm for 10 minutes. After decanting the supernatant, the nanoparticles were digested in 90% alcohol to extract the encapsulated NR. The concentration of NR was determined using a calibration curve (0.2 to 5µg/ml) of NR in

90% alcohol. The samples were analyzed by spectrofluorimetry (SpectromaxM2,

Molecular Devices, Sunnyvale, CA) using the excitation and emission wavelength of 559 and 629 nm respectively. The encapsulation efficiency (EE%) was calculated using the following equation

푊푒𝑖푔ℎ푡 표푓 푁푅 𝑖푛 푁푎푛표푝푎푟푡𝑖푐푙푒푠 NR Encapsulation Efficiency (%) = x 100 푊푒𝑖푔ℎ푡 표푓 푎푑푑푒푑 푁푅 68

2.2.5. In vitro Release of NR The in vitro release of NR from the nanocarriers was determined in simulated gastric (SGF) and intestinal fluid (SIF). SGF was prepared using 0.1 M HCl and 0.32% w/v pepsin (pH 1.2), while SIF was prepared using 0.05M KH2PO4 with 0.1 M NaOH (pH

7.5) and 1% w/v pancreatin. For release studies, 20 mg of NR loaded nanocarriers (ZC,

ZLF, ZLG, ZWP, ZPL, and ZPEG) was suspended in 5 ml release medium and placed in a dialysis cassette (EMD Millipore, 10KDa MWCO). The cassette was placed in 200 ml release medium containing Tween 80 (0.1% v/v) to maintain sink conditions. At predetermined intervals, 1 ml of the release medium was removed and replaced with an equal volume of release medium. The sample was mixed with 1ml of ethanol, and the concentration of NR was determined by spectrofluorimetry as described earlier.

2.2.6. Enzymatic degradation of core-shell nanocarriers The degradation profile of nanoparticles was determined by incubating the nanoparticles in simulated gastric fluid (SGF) and intestinal fluid (SIF) for up to 4 hours.

The samples were analyzed by SDS-PAGE gel electrophoresis (12%). ZC and ZLF was stained with Coomassie blue, while for ZPEG, ZLG, and ZWP the gels were stained with

Gel Code Blue Staining Reagent (Life Technologies).

2.2.7. Influence of pH and ionic strength on nanoparticle stability To determine the effect of pH on particle size and zeta potential, lyophilized blank nanocarriers were dispersed in solution varying in pH from 2 to 10. The pH was adjusted using 0.1 M HCl or 0.1 M NaOH. Similarly, the effect of salt concentrations (0-200 mM of NaCl) on particle size and zeta potential of the nanocarriers were also determined. 69

2.2.8. Cell culture Caco-2 cells (ATCC, Rockville, MD, USA) cells were maintained in Dulbecco’s

Modified Eagle Medium (DMEM) (4.5 g/L glucose) supplemented with 20% FBS

(HyClone; Thermo Scientiﬁc, Waltham, MA, USA), 1% non-essential amino acids, 1% L- glutamine, 1% streptomycin (100 μg/ml) and penicillin (100 IU/ml). The growth medium was changed every day in the first two weeks followed by replacement of the medium three times a week.

2.2.9. Mechanism of cellular uptake of NR loaded nanocarriers Caco-2 cells were seeded in a 12-well plate at a concentration of 1 x 105 cells/well

(passage number 10-15). Next day, the culture medium was removed, and the cells were treated with one µg of NR loaded different nanocarriers in Hank’s Balanced Salt Solution

(HBSS) for 30 minutes to 2 hours at 37°C. At the end of the treatment period, the cells were washed with HBSS three times followed by trypsinization. The cells were washed with ice-cold HBSS and fixed using 2% paraformaldehyde. The mean fluorescence intensity was analyzed by flow cytometry (FACS, BD Biosciences, San Jose, CA). To understand the mechanism of cell uptake of the nanoparticles, the experiments were performed at 4°C and compared with the cell uptake at 37°C.

In a separate set of experiments, Caco-2 cells were pre-incubated with endocytosis inhibitors including 1µM phenyl arsine oxide (PAO), 4µM Filipin and 10 µM Cytochalasin

D for 30 minutes, followed by cell uptake experiment using 1 µg NR loaded nanocarriers for 2 hours.

2.2.10. Calcein uptake assay

For P-gp- inihibition assay, Caco-2 cells were seeded in a 96-well plate (1x104 cells/mL) 24 hours before treatment with nanocarriers. Blank nanocarriers were dispersed in HBSS buffer (1 mg/mL) and cells were incubated with 50 μL of blank nanocarriers for

30 minutes. Cells were washed three times with HBSS buffer followed by addition of 200

μL of 0.5 μM calcein AM, a P-gp substrate (Molecular Probes, Eugene, OR, USA) and incubated for 2 hours. Cells were washed three times with ice-cold HBSS and lysed using

0.5% Triton X-100. A control experiment was performed following the same procedure, but without the addition of nanocarriers. Calcein uptake was measured by spectrofluorimetric analysis using 485 and 530 nm as excitation and emission wavelengths respectively. To determine P-gp inhibition, the relative calcein fluorescence (FL) was calculated for the nanocarrier treated and non-treated groups using the following equation,

퐹퐿 (푡푟푒푎푡푚푒푛푡) − 퐹퐿(푛표푛 − 푡푟푒푎푡푒푑) % 푅푒푙푎푡𝑖푣푒 푓푙푢표푟푒푠푐푒푛푐푒 = [ ]푥100 퐹퐿 (푛표푛 − 푡푟푒푎푡푒푑)

2.2.11. In vitro transepithelial transport of core-shell nanocarriers Caco-2 cells (1×105 cells/well) were seeded onto Transwell polyester insert (pore size 3.0 µm, surface area 1.12 cm2) in a 12-well plate (Transwell®, Corning Costar Corp.,

Cambridge, MA, USA). The cells were grown in an atmosphere of 5% CO2 and 95% air with 95% relative humidity at 37°C. The cells were allowed to grow for three weeks, and the formation of a monolayer was confirmed by measuring the transepithelial electrical resistance (TEER) using EVOM meter (Sarasota, FL). Before starting the experiment, the medium in the apical side was replaced with 2mg/ml of nanoparticle dispersion in Hank’s balanced salt solution (HBSS), and the permeability of NR loaded nanoparticles was 71 determined for 4 hours. Samples (200µl) were withdrawn from the basolateral compartment at pre-determined time points and replaced with an equal volume of fresh and pre-warmed HBSS buffer solution. The apparent permeability coefficient (Papp) was calculated using the following equation

(dQ/dt) Papp (cm/s) = [ ] x 100 퐴퐶표

Where dQ/dt is the flux of NR across Caco-2 monolayer, C0 is the initial concentration of

NR in the apical chamber, and A is the surface area of the 12-well plate Transwell insert

(1.12 cm2).

2.2.12. Cell uptake studies using confocal laser scanning microscopy To visualize the cell uptake of core-shell nanocarriers, Caco-2 cells (5x104 cells/well) were seeded in a chamber slide (Nunc Lab-TEK®II Chamber SlideTM system,

Thermo Scientific, Waltham, MA) and was incubated overnight. Next day, the growth medium was replaced with HBSS buffer (pH 7.4) and equilibrated for 30 min at 37°C.

Then, the nanoparticle dispersion (500µg/mL) was added to the wells and incubated for

30-60 min. At the end of treatment period, cells were washed three times with cold HBSS to remove the surface adsorbed nanoparticles. Cells were then fixed using 4% paraformaldehyde for 20 min at room temperature followed by staining F-actin with Alexa

Fluor 488-Phalloidin (Life Technologies, Carlsbad, CA). DAPI containing mounting medium (Vector Labs) was used to stain the nucleus. Images were taken using Olympus

FluoView 1200 (FV 1200) confocal laser scanning microscope (CLSM) at a 60x magnification.

2.2.13. Ex vivo adhesion assay

2.2.13.1. Everted sac method

To determine the mucoadhesive properties of core-shell nanoparticles, everted sac method was used (Reineke, Cho, Dingle, Cheifetz, et al. 2013). Pig jejunum was procured from the Department of Animal Science at South Dakota State University. Briefly, a section of freshly collected pig jejunum (6 cm length) was everted using a glass rod to expose the mucosal side, and the open ends were tied to form a sac (Fig. 11). The loose mucus was removed from the intestine. The sac was filled with phosphate buffered saline glucose (PBSG). The everted sac was placed in NR loaded nanoparticle suspension (100 mg/ml) in PBSG and incubated at 37˚C in a shaker water bath for 1 hour to allow time for the nanoparticles to adhere to the tissue. Fluorescent-labeled polystyrene nanoparticles

(200nm, Phosphorex, Hopkinton, MA, USA) were used as a positive control. Following incubation, the everted sac was removed and processed (adherent mucus and remaining suspension collected as bound and unbound fractions, respectively) for determining the NR concentration by spectrofluorimetry. The ratio of NR concentration in the bound and unbound nanoparticles was used to calculate the percent adhesion.

Figure 13: Schematic presentation of everted sac method to test the bioadhesion of nanocarriers on the mucosal surface. Reproduced from Alam, Al-Jenoobi, and Al-Mohizea

(2012).

2.2.13.2. Determination of bioadhesive property of nanocarriers using Texture

Analyzer

The bioadhesive property of the nanocarriers was further determined using a texture

(Reineke, Cho, Dingle, Cheifetz, et al. 2013). Bioadhesive property of the nanocarriers was determined by measuring the maximum force required to separate the nanocarriers from mucosal surface of the intestinal tissue (Thirawong et al. 2007). Polystyrene nanoparticles

(PS) (Phosphorex Inc., Hopkinton, MA, USA) of 200 nm size was used as a positive 74 control. Briefly, ‘T’ shapped metal-head probe was coated by dip and dry method using

5% (w/v) aqueous nanoparticle dispersion. A thin uniform layer of the coat was obtained by repeated cycles of dipping and drying the metal head for eight times. The coated probe was then fitted in the loading arm of the texture analyzer. Freshly collected piglet jejunum was washed with pre-warmed oxygenated PBS (pH 7.4) and placed below the probe. The coated metal probe was programmed to descend at 0.5 mm/s until a final force of 5 g was achieved between the coated probe and the intestinal tissue. The probe was incubated for

7 minutes to allow for interaction (Mathiowitz et al. 1997; Santos et al. 1999; Reineke,

Cho, Dingle, Cheifetz, et al. 2013; Thanos et al. 2003) between the coated probe and intestinal tissue. Then the probe was ascended with the same speed, and the peak loads were recorded during start of the fracture between tissue and probe. The fracture strength was calculated and normalized using projected surface area (PSA). The following equation was used for calculation of PSA (Reineke, Cho, Dingle, Cheifetz, et al. 2013):

1 PSA = × 6 × 푎 × ℎ 2

Where, a is the length of each side of the hexagon and h is the radius of the probe surface.

Figure 14: Texture analyzer set up to determine the force required to remove nanoparticle coated probe from the excised intestinal tissue. Modified from Shaikh et al. (2011).

2.2.14. Ex vivo tissue uptake studies in pig jejunum To determine the tissue uptake of NR loaded nanocarriers, pig jejunum was used.

The jejunum was collected from 11-day old pig and maintained in Krebs buffer at 37°C. A

6 cm jejunum was flushed with buffer, tied open ends, and filled with NR loaded nanocarriers (10µg/ml) followed by incubation in HBSS (pH 7.4) for 2 hours at 100rpm

(37°C). At the end of the treatment, the jejunum was washed and fixed with 4% paraformaldehyde overnight at 4°C. The fixed tissue was embedded using optimal cutting 76 temperature medium (OCT), and 10µm sections were prepared using a cryo microtome

(Leica, Buffalo Grove, IL). F-actin was stained with Alexa Fluor 488-Phalloidin and the nucleus was stained with DAPI. The images were taken at 20x magnification.

2.2.15. Animal studies

2.2.15.1. Immunogenicity studies

Female Balb/c mice (4 weeks old) were used for the immunogenicity study. The experiments were conducted according to the approved protocol by the Institutional

Animal Care and Use Committee (IACUC) at SDSU. Mice were randomly divided into five groups with four animals in each group. Nanocarriers (100µg of total protein) was administered by oral gavage at 0 and 3rd week (booster dose). Blood samples were collected from the retro-orbital plexus at 0, 3rd and 5th week. The samples were then processed to separate the serum and analyzed for IgG antibody titers. Intestinal contents were also collected and processed (Kim et al. 2002; Pecquet et al. 2000). to determine the mucosal

IgA levels. Briefly, freshly collected intestinal contents were diluted in 1:32 (w/v) ratio of intestinal content and chilled PBS containing 50mM EDTA and 0.1mg/mL trypsin inhibitor. The samples vortex vigorously to disperse the tissue contents. Then the sample was centrifuged at 650g for 10 minutes. The supernatant was separated and mixed with

0.03 mL of 100 mM phenyl methyl sulfonyl fluoride (PMSF). Then the sample was centrifuged at 27000xg for 20 minutes at 4°C to further clarify the secretions. Another 0.02 mL of PMSF and 0.02 mL of sodium azide was added to each of the 2 mL clarified solutions. The solution was incubated for 15 minutes and 0.2 mL of fetal bovine serum

(FBS) as added as substrate. The final samples were stored in -80°C until further analysis. 77

All the samples were analyzed for anti-zein, anti-ZC, anti-ZLF, anti-ZLG, anti-

ZWP and anti-ZPEG IgG and IgA antibodies by Enzyme-linked Immunosorbent Assay

(ELISA). Briefly, 96-well plates were coated with 200ul of 0.1% (w/v) total protein

(nanocarriers). After overnight incubation at 4°C, the plates were washed with buffer (PBS in 1% Tween 20) and blocked with 3% normal goat serum for 1 hour at 37°C. A second washing step was done with PBS buffer (pH 7.4), followed by incubation with 1/16 diluted mouse serum for 2 hours at room temperature. The intestinal samples were also analyzed to determine the level of IgA antibody. The plate was washed with PBS buffer (4 times) and incubated with Horse Reddish Peroxidase (HRP) conjugated goat anti-mouse IgG or anti-mouse IgA for 1 hour. Then the plate was washed for four times using PBS buffer and incubated with 100µL TMB (3, 3’, 5, 5’-tetramethylbenzidine) substrate. The reaction was stopped after 10 minutes using 50µL 1M H2SO4. The optical density was recorded at 450 nm in a plate reader (SpectraMax2, microplate reader, Molecular Devices, Sunnyvale, CA).

2.2.15.2. In vivo biodistribution

To determine the in vivo oral biodistribution of core-shell nanocarriers, Cy 5.5, a near infra-red dye was used. Male Sprague-Dawley rats (6–8 weeks of age, 200-250 g) were used for the study. The animal studies were conducted after approval from IACUC at

SDSU. The animals were acclimatized one week before the start of the study and had free access to water and food. Cy 5.5 loaded nanoparticles (50µg) were dispersed in water (2ml) and administered using a flexible oral gavage tube under mild isoflurane anesthesia. The time-dependent biodistribution (2, 6, 12, and 24 hrs) of nanocarriers was determined using the in-vivo imaging system (Xtreme, Bruker, Billerica, MA, USA). The free dye was used as a control. The animal was placed in the imaging chamber, and a short exposure of x-ray 78 was used to record the anatomy followed by determination of fluorescence. After 6 and 24 hours, the animals were sacrificed, and the gastrointestinal tract (GIT) was separated, and the fluorescence was recorded using the in-vivo imaging system. All images were captured at 0.1-second exposure using the excitation and emission wavelengths as 690 and 750 nm respectively. Bruker MI software was used to process the images.

2.2.15.3. In vivo tissue uptake studies through rat jejunum To determine the tissue uptake of Cy 5.5 loaded nanocarriers, the jejunum was collected at 6 hours after oral administration of nanocarriers and the tissue was fixed with

4% paraformaldehyde overnight at 4°C. The fixed tissue was embedded using optimal cutting temperature medium (OCT), and 10µm sections were prepared using a cryo- microtome (Leica, Buffalo Grove, IL). F-actin was stained with Alexa Fluor 488-

Phalloidin and the nucleus was stained with DAPI. The images were taken at 20x magnification.

2.3. Statistical analysis

All the experiments were conducted in triplicate. Data is represented as the mean ± standard deviation. Statistical evaluation was performed by one-way analysis of variance

(ANOVA) followed by Tukey’s post-hoc test using Minitab® statistical software (Minitab

Inc., State College, PA) at a significance level of p < 0.05.

2.4. RESULTS AND DISCUSSION

Core-shell nanocarriers were developed using zein, a hydrophobic plant protein as the core and milk proteins (β-casein or lactoferrin or β-lactoglobulin or whey protein isolate), polyethylene glycol or pluronic-lecithin as the shell. The physicochemical characteristics of the six nanocarrier formulations is shown in Table 8. Part of the work related to zein-β-casein (ZC) nanoparticles, zein-lactoferrin (ZLF) nanoparticles and

PEGylated zein (ZPEG) micelles was previously reported by us and reproduced here for comparison.

2.4.1. Characteristics and Stability of core-shell nanocarriers

All the three nanocarriers had a particle size in the range of 100-200 nm with a uniform size distribution, as seen from the low polydispersity index (Table 8). The nanoparticles in this size range have been reported to increase drug solubility and permeability through the membrane (Desai et al. 1996; Win and Feng 2005).

The shell composition influenced the NR encapsulation efficiency in the nanocarriers (Table 8). Encapsulation efficiency was relatively high with ZLF followed by

ZLG, ZPL, ZWP, ZC nanoparticles and ZPEG micelles (Table 8). The properties of the shell polymer and the kinetics of nanoparticle formation can influence the encapsulation efficiency of nanoparticles (Joye, Davidov-Pardo, and McClements 2015). On the other hand, similar loading efficiency with all the six formulations indicate that the loading efficiency is mainly influenced by the affinity of NR with hydrophobic zein core.

Table 8: Characteristics of NR loaded nanocarriers. Zeta NR Encapsulation Formulation Size (d.nm) PDI potential (mV) Efficiency (%)

ZC nanoparticles 118.6 ±6.3 0.180 ±0.05 -36.3 ±4.5 71.6 ±9

ZLF nanoparticles 175.2 ±6.8 0.251 ±0.02 28.6 ± 3.12 82.5 ±7

ZPEG micelle 102.3 ±8.2 0.233 ±0.014 -1.63 ±4.3 56.1 ±4

ZLG nanoparticles 222.7±14.0 0.09±0.019 -35.5±1.83 78.51±3.68

ZWP nanoparticles 248.9±0.14 0.29±0.01 -29.7±1.55 74.68±1.04

ZPL nanoparticles 291.86±2.89 0.34±0.065 -49.68±3.13 76.3±3.4

PDI: Polydispersity Index; NR: Nile Red; ZC: Zein-β-casein nanoparticles; ZLF: Zein-

Lactoferrin nanoparticles; ZPEG: PEGylated zein micelles; ZLG: Zein-β-Lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles; ZPL: Zein-Pluronic-Lecithin nanoparticles; Each value represents mean±SD (n= three different batches). Data for ZC,

ZLF, and ZPEG is reproduced from our earlier study (Alqahtani et al. 2017) and included here for comparison.

The spherical morphology and the core-shell structure of the nanocarriers was confirmed from the TEM images (Fig. 15). The formation of core-shell architecture was further confirmed by the zeta potential values (Table 8). The negative zeta potential of ZC,

ZLG, ZWP, and ZPL nanoparticles is attributed to β-casein, β-lactoglobulin, whey protein isolate, and lecithin respectively, while lactoferrin imparted a positive charge to the ZLF nanoparticles. The ZPEG micelles had a very weak negative charge and was close to zero.

ZPEG micelles was characterized by MALDI-TOF analysis to determine the degree of

PEGylation. The PEG is covalently conjugated to zein. MALDI-TOF analysis (Fig. 16) indicated that one PEG molecule covalently conjugated with zein where PEG provides a steric barrier against particle aggregation.

Figure 15: TEM images of blank nanocarriers. ZC: Zein-β-casein nanoparticles; ZLF: As can be seen from the TEM images, the nanocarriers were spherical with a Zein-Lactoferrin nanoparticles; ZPEG: PEGylated zein micelles; ZLG: Zein-β-

Lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles; ZPL: Zein-

Pluronic-Lecithin nanoparticles; Representative images are presented here. TEM images for ZC and ZLF nanoparticles are reproduced from our earlier study (Alqahtani et al.

2017) and is included here for comparison. Scale bar for ZC, ZLF is 100 nm, for ZPEG,

ZLG, ZWP scale bar is 200 nm and for ZPL scale bar showing 500 nm. 83

Figure 16: MALDI-TOF analysis of free zein and ZPEG.

The nanocarriers were found to be stable at different pH encountered in the gastrointestinal tract and there was no significant particle aggregation (Table 9, 10 11, 12,

13, and 14). Casein (pI= 4.6) is positively charged at acidic pH in the stomach and is negatively charged in the alkaline pH of the intestine (Tavares et al. 2014). Earlier studies have used sodium casein to stabilize zein nanoparticles, but significant aggregation was observed at pH close to the isoelectric point of casein (pH 3-5) (Joye, Davidov-Pardo, and

McClements 2015; Patel, Bouwens, and Velikov 2010). Sodium casein contains a mixture of caseins (α, β and κ caseins) with different physicochemical characteristics (Cross et al.

2005). The caseins differ in the number of hydrophilic and hydrophobic domains which in turn influences the interaction with zein (Cross et al. 2005). Patel et al. formed zein-sodium casein nanoparticles through electrostatic interaction between the zein and sodium casein by controlling the pH of the solution (Patel, Bouwens, and Velikov 2010). Unlike sodium casein, β-casein used in the present study stabilized the zein nanoparticles mainly through hydrophobic interactions.

Lactoferrin (pI=8.7) is positively charged throughout the entire pH range of the gastrointestinal tract (Tavares et al. 2014). Zein, which is negatively charged at pH 7.4

(pI=6.8), is stabilized through electrostatic interaction with the positively charged lactoferrin (Podaralla and Perumal 2012). However, there was a slight increase in the particle size of ZC and ZLF nanoparticles closer to the isoelectric pH of casein and lactoferrin respectively, as a result of a reduction in the electrostatic charge on the nanocarriers (Table 9 and 10).

ZLG and ZWP nanoparticles has negative surface charge and the electrostatic repulsive force can prevent particle aggregation (Xiong 1992; Zhang and Zhong 2009). 85

ZLG and ZWP nanoparticles nanoparticles were found to be stable with respect to size,

PDI and zeta potential when exposed to a wide range of pH (2-9) (Table 11 and Table

12). β-Lactoglobulin is the major protein in whey protein isolate, and its isoelectric point is 5.3. (Aich, Batabyal, and Joardar 2015) Below the isoelectric point (pH 2.0) the surface zeta potential of both of ZLG and ZWP nanoparticles shifted towards positive zeta potential with less impact on particle size (Table 11 and Table 12). At lower pH (pH <4), the proteins used in our study are expected to be positively charged. This can lead to electrostatic repulsion resulting in desorption of the shell protein and particle aggregation.

The fact that the nanocarriers did not aggregate signify that hydrophobic interactions and steric repulsion play a major role in preventing particle aggregation (Tokle, Mao, and

McClements 2013).

In case of ZPL nanoparticles, the particle size, PDI and zeta potential did not change at different pH (Table 13). The isoelectric point of lecithin is 4 and the presence of pluronic may reduce the influence of pH on size and surface charge of nanoparticles by providing a steric barrier (Chain and Kemp 1934).

In case of ZPEG micelles, the particle size remains unchanged, except at pH 2, where the particle size increased (Table 14). Zein is known to undergo structural changes in acidic pH to form aggregates (Cabra et al. 2006). However, the zeta potential of ZPEG micelles did not change much with an increase in pH and stayed close to zero (Table 14).

Table 9. Influence of pH on particle size and PDI of zein-casein (ZC) nanoparticles.

pH Particle size (nm) PDI 2 146.7 ±12.27 0.110 ±0.008 3 156.1 ±18.32 0.184 ±0.125 4 179.9 ±11.23 0.128 ±0.058 5 138.6 ±9.23 0.113 ±0.014 6 135.8 ±8.91 0.095 ±0.014 7 130.6 ±11.10 0.097 ±0.009 8 132.7 ±11.31 0.093 ±0.011 9 130.4 ±13.82 0.103 ±0.016 PDI: Polydispersity Index; Each value represents mean±SD (n= 3). This data is reproduced from our earlier study (Alqahtani et al. 2017) and is included here for comparison.

Table 10. Influence of pH on particle size and PDI of zein-lactoferrin (ZLF) nanoparticles.

pH Particle size (nm) PDI 2 157.21 ±12.24 0.194 ±0.012 3 179.55 ±7.93 0.189 ±0.035 4 165.32 ±9.43 0.188 ±0.018 5 181.63 ±8.71 0.167 ±0.018 6 165.91 ±5.65 0.188 ±0.005 7 175.21 ±6.8 0.251 ±0.02 8 201.35 ±19.11 0.247 ±0.021 9 202.15 ±17.29 0.289 ±0.013 PDI: Polydispersity Index Each value represents mean±SD (n= 3). This data is reproduced from our earlier study (Alqahtani et al. 2017) and is included here for comparison.

Table 11. Influence of pH on particle size and PDI of zein-β-lactoglobulin (ZLG) nanoparticles.

pH Particle Size PDI Zeta Potential (mV) 2 248.43±3.36(d.nm) 0.18±0.01 -25.7±1.47 3 248.66±2.80 0.12±0.03 -38.1±1.91 4 263.42±3.94 0.189±0.02 -40.7±1.25 5 268.17±8.78 0.20±0.025 -40.13±1.06 6 251.7±9.79 0.13±0.05 -40.73±1.45 7 242.5±5.28 0.064±0.04 -36.9±1.65 8 251.63±6.08 0.12±0.02 -37.4±0.95 9 270.1±17.74 0.26±0.02 -34.93±2.03 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Table 12. Influence of pH on the mean particle size and PDI of zein-whey protein isolate

(ZWP) nanoparticles.

pH Particle Size PDI Zeta Potential (mV) 2 219.33±2.11(d.nm) 0.10±0.05 -27.43±1.79 3 234.9±4.51 0.19±0.02 -36.53±1.95 4 239.63±4.95 0.19±0.05 -35.5±1.56 5 236.93±4.13 0.16±0.02 -36.9±1.44 6 235.03±4.38 0.17±0.01 -36.16±1.66 7 235.2±3.56 0.10±0.03 -33.8±3.17 8 244.01±4.16 0.20±0.01 -34.7±1.3 9 271.76±27.73 0.27±0.08 -32.43±2.87 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Table 13. Influence of pH on mean particle size and PDI of zein-pluronic-lecithin (ZPL) nanoparticles.

pH Particle size (nm) PDI Zeta potential (mV) 2 291.86±2.89 0.34±0.06 -49.68±3.13 3 286.12±3.43 0.20±0.07 -45.05±1.25 4 292.12±5.15 0.3±0.026 -50.58±3.24 5 299.05±9.07 0.2±0.01 -52.34±1.26 6 291.71±5.04 0.20±0.04 -42.89±5.32 7 296.61±10.23 0.25±0.02 -48.87±3.56 8 299.66±3.87 0.26±0.03 -46.57±6.89 9 287.75±3.90 0.25±0.01 -53.66±4.98 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Table 14. Influence of pH on the mean particle size and PDI of PEGylated zein (ZPEG) micelles.

pH Particle size (nm) PDI 2 161.76±6.98 0.25±0.012 3 86.12±3.43 0.23±0.073 4 92.12±9.15 0.25±0.026 5 99.05±7.87 0.23±0.015 6 91.71±8.14 0.23±0.043 7 96.61±13.23 0.23±0.024 8 99.66±3.87 0.21±0.031 9 87.75±5.76 0.24±0.011 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Nanocarriers were also stable at different ionic strength (Table 15, 16, 17, 18, 19, and 20). There was no significant change in the particle size of ZC and ZLF nanoparticles when exposed to ionic strength (10-200 mM), typically encountered in the gastrointestinal tract. However, the magnitude of the zeta potential decreased with increase in ionic strength for ZC and ZLF nanoparticles can be attributed to the electrostatic screening effect from the adsorption of counterions (sodium or chloride ions) around the charged nanoparticles

(Table 15 and 16) (Tokle, Mao, and McClements 2013).

ZLG and ZWP nanoparticles have negative surface charge and which prevented aggregation by electro repulsion. ZLG and ZWP nanoparticles were found to be stable at different ionic strength (10-500 mM). There was a change in surface charge with the increase in ionic strength (Table 17 and 18). The magnitude of change of zeta potential was higher for ZLG nanoparticles (-32.06 mV to -5.8 mV) compared to ZWP nanoparticles

(-30.55 mV to -15.2 mV). This variation may arise from the presence of other proteins in whey protein isolate. A higher change in surface charge with higher ionic strength may be attributed to the adsorption of counterions on the nanoparticles (Tokle, Mao, and

McClements 2013). Similar to the impact of pH, particle size and surface charge of ZPL nanoparticles remained unchanged at different ionic strength of the dispersing medium

(Table 19).

For ZPEG micelles, the particle size was relatively small at higher ionic strength

(≥100 mM) (Table 20). Given that PEG-zein micelles has a weak charge, the adsorption of ions at higher ionic strength provided a charge barrier to prevent aggregation. However, no specific trend was observed in the zeta potential of ZPEG micelles with change in the ionic strength. 90

Table 15. Influence of ionic strength on particle characteristics of zein-casein (ZC) nanoparticles.

Ionic strength Particle size (nm) PDI Zeta potential (mV) (mM) 0 118.6 ± 6.3 0.18 ± 0.05 -36.3 ± 4.5 10 131.7 ±13.29 0.085 ±0.025 -35.25 ±2.495 20 134.2 ±12.02 0.115 ±0.015 -30.8 ±3.414 50 128.9 ±13.15 0.105 ±0.016 -22.15 ±3.909 100 130.7 ±14.35 0.106 ±0.018 -20.05 ±2.281 150 128.8 ±12.73 0.108 ±0.021 -17.6 ±1.849 200 133.4 ±12.15 0.092 ±0.018 -14.15 ±2.201 PDI: Polydispersity Index; Each value represents mean±SD (n= 3). This data is reproduced from our earlier study (Alqahtani et al. 2017) and is included here for comparison.

Table 16. Influence of ionic strength on particle characteristics of zein-lactoferrin (ZLF) nanoparticles.

Ionic strength (mM) Particle size PDI Zeta potential (mV) (nm) 0 175.2 ±6.8 0.251 ±0.02 28.6 ± 3.12 10 187.95 ±24.4 0.188 ±0.018 32.21 ±2.838 20 174.35 ±27.08 0.197 ±016 26.85 ±4.849 50 183.9 ±29.6 0.184 ±045 20.32 ±3.788 100 175.35 ±24.11 0.187 ±0.021 14.85 ±2.758 150 169.25 ±14.21 0.183 ±0.017 9.55 ±3.869 200 175.1 ±32.9 0.191 ±0.030 6.19 ±2.687 PDI: Polydispersity Index; Each value represents mean±SD (n= 3). This data is reproduced from our earlier study (Alqahtani et al. 2017) and is included here for comparison.

Table 17. Influence of ionic strength on particle characteristics of zein-β-lactoglobulin

(ZLG) nanoparticles.

Ionic Strength (mM) Particle Size PDI Zeta Potential 10 256.7(d.nm)±7.85 0.07±0.03 -32.06±4.81(mV) 20 260.26±7.23 0.14±0.005 -19.9±0.65 50 257.66±3.84 0.12±0.02 -17.06±0.37 100 270.56±2.11 0.15±0.02 -14.8±0.85 250 249.43±2.65 0.09±0.07 -11.93±1.30 500 258.43±2.63 0.16±0.04 -5.8±2.98 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Table 18. Influence of ionic strength on particle characteristics of zein-whey protein isolate

(ZWP) nanoparticles.

Ionic Strength (mM) Particle Size PDI Zeta Potential 10 280.9±3.93(d.nm) 0.23±0.047 -30.55±3.04(mV) 20 264.63±2.3 0.15±0.057 -28.2±1.55 50 260.1±6.18 0.19±0.078 -18.45±1.76 100 253.66±6.68 0.08±0.039 -17.35±0.91 250 257.1±3.11 0.17±0.036 -12.15±0.77 500 267.7±4.10 0.11±0.066 -15.2±2.82 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Table 19. Influence of ionic strength on mean particle size and PDI of zein-pluronic- lecithin (ZPL) nanoparticles.

Ionic strength (mM) Particle size PDI Zeta potential (nm) (mV) 0 289.81±2.12 0.31±0.06 -58.60±3.02 10 280.02±5.65 0.25±0.17 -55.01±3.65 20 288.12±6.54 0.3±0.06 -55.12±2.35 50 290.5±8.70 0.3±0.01 -50.02±5.45 100 292.70±6.14 0.30±0.05 -45.09±1.32 150 300.61±8.93 0.26±0.01 -45.80±2.50 200 296.06±5.80 0.27±0.02 -56.51±6.50 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

Table 20. Influence of ionic strength on particle characteristics of PEGylated zein (ZPEG) micelles.

Ionic strength (mM) Particle size PDI Zeta potential (nm) (mV) 0 102.3 ±8.2 0.233 ±0.014 -1.63 ±4.3 10 125.16±29.17 0.26±0.053 -4.21±1.67 20 130.34±30.55 0.29±0.050 -0.85±0.37 50 131.33±24.30 0.25±0.024 -2.30±2.33 100 91.30±2.54 0.26±0.012 -1.26±0.233 150 92.86±9.56 0.25±0.042 -1.07±1.43 200 91.10±6.36 0.25±0.039 -0.96±0.83 PDI: Polydispersity Index; Each value represents mean±SD (n= 3).

The enzymatic stability of the core-shell nanocarriers was tested in SGF and SIF in presence of pepsin and pancreatin respectively. In general, all the six formulations were enzymatically more stable in SGF compared to SIF (Fig. 17 and 18). SDS-PAGE analysis indicating that nanocarriers are relatively stable in SGF in presence of pepsin (Fig. 17) while slow degradation was observed in SIF in presence of pancreatin (except ZPEG) (Fig.

18). 93

This is in agreement with the reported enzymatic stability of the proteins used in

our study (Hurtado-Lopez and Murdan 2006; Luo, Pan, and Zhong 2015; Lonnerdal, Jiang,

and Du 2011). SDS-PAGE analysis indicating that nanocarriers are relatively stable in SGF

in presence of pepsin (Fig. 17) while slow degradation observed in SIF in presence of

pancreatin (Fig. 18).

Figure 17: Enzymatic Stability of nanocarriers in Simulated Gastric Fluid (SGF) with pepsin after incubation for different time points and analyzed by SDS-PAGE. ZC and

ZLF data is reproduced from our earlier study (Alqahtani et al. 2017) and included for comparison.

Figure 18: Enzymatic Stability of nanocarriers in Simulated Intestinal Fluid (SIF) with pancreatin after incubation for different time points and analyzed by SDS-PAGE. ZC and

ZLF data is reproduced from our earlier study (Alqahtani et al. 2017) and included here for comparison.

2.4.2. In vitro release of NR from core-shell nanocarriers

The in-vitro release of NR from the nanocarriers was tested in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF). As can be seen from Fig. 19, the NR release was sustained from all the six nanocarriers, but the release kinetics was strongly influenced by the shell composition. PEG, which is the most hydrophilic polymer among the six formulations showed faster release (Fig. 19) and significantly higher burst release

(20% within the first few hours). ZPL nanoparticles showed the slowest release of NR in both SGF and SIF. The release was relatively high in SIF compared to SGF for ZC nanoparticles, while the release was high in SGF for ZLF, ZPEG and ZLG formulations

(Fig. 19). The low solubility of casein in acidic pH resulted in slow release in SGF compared to the release in SIF. Unlike ZLG, ZWP nanoparticles released less NR in SGF than in SIF. 96

Figure 19: Cumulative percent of NR release from different nanocarriers in presence of

Simulated gastric fluid (SGF) and simulated intestinal fluid (SIF). ZC: Zein-β-casein, ZLF:

Zein-lactoferrin, ZPEG: PEGylated zein, ZLG: Zein-β-lactoglobulin, ZWP: Zein-whey protein isolate. Each value represents mean±SD (n=3). Data for ZC, ZLF and ZPEG is reproduced from our earlier study (Alqahtani et al. 2017) and included for comparison.

To understand the release kinetics and to guide future formulation optimization, the data was fitted to different release kinetic models. The release of NR from the nanocarriers followed mixed order kinetics that was a combination of diffusion and erosion (Table 21).

The release of the entrapped hydrophobic compounds from the zein matrix has been reported to occur through the diffusion-degradation mediated process (Liu et al. 2010;

Parris, Cooke, and Hicks 2005). During the early phases, the drug release occurs mainly by diffusion through the protein matrix, while in the later phases; release is mediated by both diffusions of the entrapped molecule and enzymatic degradation of the protein itself

(Parris, Cooke, and Hicks 2005). The release kinetics was influenced by the shell composition including the molecular weight, enzymatic stability, and hydrophobicity of the polymer. The initial release is controlled by the polymer swelling and diffusion through the swollen matrix, while erosion of the polymer controls the release at later time points

(Hu et al. 2012). The release of NR from ZC nanoparticles showed a good fit to the Peppas model, indicating initial zero-order kinetics (by diffusion) followed by first-order kinetics

(polymer erosion by hydrolytic and enzymatic degradation) in both SGF and SIF (Table

21). ZLF nanoparticles showed a biphasic release with an initial burst release (~10%) from the NR trapped in the shell, followed by sustained drug release at later time points (Table

21). In case of ZPEG micelles, the release followed first-order kinetics (Table 21) by hydrolytic and enzymatic degradation of zein. The release of NR from ZLG, ZWP and ZPL nanoparticles showed mixed order kinetics. However, ZLG, ZWP and ZPL nanoparticles showed a better fit to Peppas model indicating that NR release was diffusion controlled at the early phases followed by polymer erosion at later time points. The mixed order kinetics observed in this study agrees with reported studies for zein particulate systems in the 98 literature (Hu et al. 2012; Mehta, Kaur, and Verma 2011). The release did not directly correlate with the enzymatic stability of the core-shell matrix in SGF and SIF (Fig. 17 and

18) This is because other factors (pH, ionic strength, etc.) may influence the release of NR from nanoparticles.

The chemical properties of both the core and the shell dictate the extent of water diffusion and polymer erosion. For casein, which is relatively more hydrophobic of the among the milk protein-based shell composition, in the early stage of drug release the diffusion of water through the nanoparticle matrix appears to be the rate-limiting step, while for PEG-zein micelles, the polymer erosion appears to influence the release. On the other hand, ZLF nanoparticles appeared to show varying extent of diffusion-erosion to sustain the release of NR. For ZLG and ZWP nanocarriers, the relatively higher enzymatic stability causes slower surface erosion and controlled the release of encapsulated NR. In

ZPL nanocarriers, the hydrophobic lecithin has a role in controlling the release of NR in

SGF and SIF. In addition to polymer characteristics, the relative binding affinity of the encapsulant and the encapsulation/loading efficiency also can influence the release.

Overall, results from this study demonstrate that the shell matrix has a strong influence on the drug release kinetics from the core-shell zein nanocarriers. 99

Table 21: Summary of nonlinear fit of NR release kinetics using different models.

Formulation R2 (Medium) Peppas Hixson-Crowell Zero Order First Order Higuchi 푛 퐹 = 퐾 ∗ 푡 퐹 = 100 ∗ (1 − (1 − 푘 ∗ 푡)^3) C=C0-K0t F=100*(1-exp(-k*t)) F = k ∗ sqrt(t) ZC (SGF) 0.9758 0.8992 0.9233 0.8780 0.7007 ZC (SIF) 0.9903 0.9902 0.9884 0.9903 0.8929 ZLF (SGF) 0.9573 0.5202 0.7661 0.5976 0.9114 ZLF (SIF) 0.9682 -0.4053 0.6926 -0.3524 0.6320 ZPEG (SGF) 0.8146 0.4173 0.4368 0.9718 0.4450 ZPEG (SIF) 0.8940 0.7376 0.6169 0.9501 0.7049 ZLG (SGF) 0.9906 0.9838 0.9923 0.9771 0.8252 ZLG (SIF) 0.9986 0.9238 0.9604 0.9212 0.6669 ZWP (SGF) 0.9845 0.7870 0.9095 0.8157 0.9845 ZWP (SIF) 0.9728 0.9729 0.9717 0.9655 0.8435 ZPL (SGF) 0.976 0.972 0.970 0.974 0.852 ZPL (SIF) 0.980 0.980 0.984 0.980 0.800 SGF-Simulated gastric fluid; SIF-Simulated intestinal fluid; R2 calculated from SigmaPlot 13.0. ZC: Zein-β-casein nanoparticles, ZLF:

Zein-lactoferrin nanoparticles, ZPEG: PEGylated zein micelles, ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles; ZPL: Zein-pluronic-lecithin nanoparticles. Highlighted values indicate the best fit model. 100

2.4.3. In vitro transepithelial transport and cell uptake of nanocarriers

Caco-2 cells, a well-established model for oral drug transport was used to study the influence of shell composition on the in-vitro transepithelial transport and cell uptake of nanocarriers. The permeability of NR loaded nanoparticles was determined using polarized

Caco-2 monolayers, and the formation of a polarized monolayer was confirmed from

TEER measurements (>400 ohms/cm2). There was a time-dependent increase in the apical to basolateral transport of NR loaded nanoparticles (Fig. 20). ZPL nanoparticles showed the highest permeability, while ZC nanoparticles showed the lowest permeability among the six formulations. ZWP showed faster cell uptake than other nanocarriers. (Fig. 20) In general, the apparent permeability (Papp) increased over time for all the six nanocarriers.

All the six nanocarriers increased the permeability of NR, and there was no detectable permeation of free NR under the experimental conditions. Apparent permeability of nanocarriers was in the following decreasing ranks order:

ZPL>ZLG>ZPEG>ZWP≥ZLF>ZC (Fig 20). The nanocarriers did not affect the cell viability of Caco-2 cells (data not shown).

101

Figure 20: Transepithelial permeability of NR loaded nanocarriers across Caco-2 cell monolayers. Apparent Permeability coefficient (Papp) from apical to basolateral chamber

(A→B) was determined at different time points. Each value represents mean±SD (n=4),

*P<0.05 compared to free NR permeability. ZC, ZLF and ZPEG data is reproduced from our earlier study (Alqahtani et al. 2017) and included for comparison.

102

To confirm the transcellular uptake of the nanoparticles, the cell uptake studies were conducted using sub-confluent culture of Caco-2 cells. As shown in Figure 21, there was a time-dependent increase in the uptake of NR loaded nanoparticles. Unlike the transepithelial transport studies shown in Figure 21, ZWP nanoparticles showed the highest cell uptake, while ZC nanoparticles showed the lowest cell uptake among the six formulations (Fig. 21). This is contrary to the Papp values which may be attributed by the presence of minor proteins in whey protein isolate. For example, the presence of positively charged lactoferrin in whey protein isolate may favor the interaction with negatively charge cell membrane. In addition, lactoferrin receptor may also be involved in higher cell uptake. minor proteins in whey protein isolate may synergistically work with lactoglobulin for enhancing cell uptake, while delayed exocytosis due to minor proteins may explain the lower permeability in first two hours (Fig. 25). Further studies are required to understand the differences in cell uptake between the nanocarriers. 103

Figure 21. Flow cytometry analysis of time dependent cell uptake of free NR or NR loaded nanocarriers in Caco-2 cells. Each value represents mean±SD (n=3), *P<0.05.

ZC, zein-casein nanoparticles; ZLF, zein-lactoferrin nanoparticles; ZPEG, zein-PEG micelles; ZLG, zein-lactoglobulin nanoparticles; ZWP, zein-whey protein nanoparticles;

ZPL, Zein-pluronic-lecithin nanoparticles. NR, ZC, ZLF and ZPEG data is from our earlier study (Alqahtani et al. 2017) and included for comparison.

104

There was less than 10% release of NR from the nanocarriers under the experimental conditions (data not shown here), signifying that most of the cell uptake is attributed to the encapsulated NR. The cell uptake decreased by 50% when the temperature was reduced to 4oC indicating that nanocarriers were taken up by energy-dependent process

(Fig. 22).

Figure 22: Cell uptake of NR loaded nanocarriers at 4°C and 37°C after incubation for

2 hours. Each value represents mean±SD (n=4). ZC and ZLF data is reproduced from

our earlier study (Alqahtani et al. 2017) and included for comparison.

105

To determine the mechanism of cell uptake, different endocytosis inhibitors were used. When phenyl arsine oxide (PAO) was used as an inhibitor for clathrin-dependent endocytosis, the cell uptake of ZLF, ZPEG, ZLG, ZWP, and ZPL nanocarriers decreased by 50%, 36%, 39%, 52% and 65% respectively (Fig 23). On the other hand, there was only a slight decrease in the uptake of ZC nanoparticles. In presence of filipin, an inhibitor for lipid raft-mediated endocytosis, there was minimal decrease in the cell uptake of ZC, ZLF and ZPEG nanocarriers (12-25%), while cell uptake of ZLG, ZWP and ZPL nanocarriers significantly decreased (45-55%). Cytochalasin-D, an inhibitor for macropinocytosis, reduced the uptake of ZPEG, ZC, ZLG, ZWP and ZPL nanocarriers by 64%, 42%, 43%,

32% and 31% respectively, while the uptake of ZLF nanoparticles was reduced by 20%

(Fig 23).

106

Figure 23: Mechanism of in vitro cell uptake of NR loaded nanocarriers by Caco-2

cells. Cells were treated with different endocytosis inhibitors for 30 minutes followed

by cell uptake studies using different NR loaded nanocarriers. Each value represents

mean ± SD (n=4). ZC, ZLF and ZPEG data is reproduced from our earlier study

(Alqahtani et al. 2017) and included for comparison.

The fluorescence microscopy studies showed that the nanoparticles were taken up by endocytosis, as evidenced from the punctuated fluorescence of NR loaded nanoparticles

(Fig. 24). Images from confocal microscopy showed that all nanocarriers enhanced cell uptake compared to free NR control. The images are consistent with flow cytometry data indicating that ZWP and ZLG nanocarriers showed higher cell uptake among the six nanocarriers. ZC, ZLF, ZPEG and ZPL nanocarriers showed comparable cell uptake after incubation for 30 minutes (Fig. 24). 107

Figure 24. Confocal microscopy images of polarized Caco-2 cells showing the internalization of Nile red (NR) loaded nanocarriers after 30 min incubation. Blue is nucleus stained with DAPI, green is Alexa Fluor 488 labeled with Phalloidin for F-actin, and red is NR loaded nanoparticles (magnification 60x). ZC, zein-casein nanoparticles;

ZLF, zein-lactoferrin nanoparticles; ZPEG, zein-PEG micelles; ZLG, zein-lactoglobulin nanoparticles; ZWP, zein-whey protein nanoparticles; ZPL, Zein-pluronic-lecithin nanoparticles. Free NR, ZC, ZLF and ZPEG images are reproduced from our earlier study (Alqahtani et al. 2017) and included for comparison.

108

The cell uptake is strongly influenced by the particle size, surface charge and surface hydrophobicity of the nanoparticles (Bannunah et al. 2014). Nanoparticles can be taken up by non-specific and specific endocytosis pathways (Bannunah et al. 2014; He et al. 2013). Lactoferrin receptor is expressed in the intestinal epithelial cells, and they are mainly found in the clathrin vesicles (Jiang et al. 2011). The results from the competitive uptake studies and endocytosis inhibitor studies suggest that ZLF nanoparticles are taken up predominantly through lactoferrin receptor (Alqahtani et al. 2017). Nevertheless, the

ZLF nanoparticles can also be taken up by non-specific endocytosis pathways. The positively charged ZLF nanoparticles can be taken up through adsorptive endocytosis by binding to the negative charge glycocalyx in the cell membrane (Bannunah et al. 2014). In contrast, the cell uptake of negatively charged ZC nanoparticles can be limited by the charge repulsion from the cell membrane. Macropinocytosis is a nonspecific process for the uptake of fluid and particles into the cells (He et al. 2013). The results from the endocytosis inhibitor studies suggest that both ZC nanoparticles and ZPEG micelles are predominantly taken up by macropinocytosis. Similarly, ZLG and ZWP nanoparticles are also predominantly taken up by macropinocytosis pathway. Our results are in agreement with the non-specific uptake of nanoparticles reported in the literature (Luo et al. 2013;

Song et al. 2013). The formulations used in the present study showed 3 to 8-fold higher permeability compared to the permeability reported for zein-sodium casein nanoparticles

(Luo et al. 2013). The β-casein unlike the sodium casein does not cause charge-induced the aggregation of zein particles, which may be attributed to the enhanced cell uptake of ZC nanoparticles (Alqahtani et al. 2017). 109

In case of beta-lactoglobulin, the amino acid sequence has similarity with lipocalin-

1 (Lcn-1), a ligand of lipocalin-interacting membrane receptor (LIMR) which is highly expressed in intestine (Fluckinger et al. 2008; Sawyer and Kontopidis 2000; Kontopidis,

Holt, and Sawyer 2002). The presence of only beta-lactoglobulin on the surface of ZLG nanoparticles may favor the uptake by its receptor, although this was not investigated in this study. Unlike, ZLG, ZWP nanoparticles may be taken taken up by additional non- specific endocytosis pathway, thus contributing to the higher uptake of ZWP nanoparticles

(Fig 22 and Fig.23). ZPL nanoparticles was found to be taken up by both clathrin and caveolae-mediated endocytosis indicating that the shell components (pluronic and lecithin) in ZPL favored the interaction with clathrin-coated pit as well as lipid-rafts (Gu et al. 2016;

Batzri and Korn 1975; Pagano, Huang, and Wey 1974). The difference in the transepithelial transport of the nanoparticles is influenced by the kinetics of the different endocytosis processes and the intracellular release of cargo from the nanocarriers.

The efflux proteins expressed in the intestinal epithelial cells can prevent uptake of drug or nanocarriers. Previous results support our findings that PEG can inhibit P-gp activity although the mechanism remains to be elucidated (Shen et al. 2008). Pluronic F127 was reported to inhibit P-gp (Wei et al. 2013) and used as positive control (Fig. 25).

However, in spite of having pluronic F127 in ZPL nanoparticles, the presence of lecithin might be a contributing factor in the lower P-gp inhibitory activity of ZPL nanoparticles.

(Fig. 25). Further studies are required to clarify the mechanism. ZLG and ZWP nanoparticles did not show P-gp inhibitory activity (Fig. 25). ZC and ZLF nanoparticles showed small increase in calcein uptake with the increase in concentration of nanoparticles used for the treatment of cells. 110

Overall, the difference in the transepithelial transport of the nanoparticles is influenced by the kinetics of the different endocytosis processes and the intracellular release of cargo from the nanocarriers.

111

Figure 25. P-gp inhibition activity of nanocarriers by calcein AM uptake assay. Each value represents mean±SD (n=3). ZC, zein-casein nanoparticles; ZLF, zein-lactoferrin nanoparticles; ZPEG, zein-PEG micelles; ZLG, zein-lactoglobulin nanoparticles; ZWP, zein-whey protein nanoparticles; ZPL, Zein-pluronic-lecithin nanoparticles. Pluronic

F127 used as positive control. Data for ZC, ZLF and ZPEG P-gp iniibition assay is reproduced from our earlier study (Alqahtani et al. 2017) and included for comparison.

X-axis represents nanocarrier concentration, Y-axis represents fluorescence intensity from calcein.

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2.4.4. Oral biodistribution of nanocarriers

The in-vivo oral biodistribution of core-shell nanoparticles was studied in rats using

Cy 5.5, a near-IR dye. The nanocarriers prolonged the retention of the Cy 5.5 dye up to 12-

24 hrs, while the free dye was cleared within 6 hrs. ZC, ZLG, ZWP and ZPL nanoparticles were found to be retained in the gastrointestinal tract for 24 hours, while the other two formulations (ZPEG and ZLF) were retained only up to 12 hours (Fig. 26 and 27). To confirm these results, the animals were sacrificed at 6 and 24 hours after oral administration to image the gastrointestinal tract. At 6 hours, all the six formulations were retained in the small intestine, with ZC, ZLG and ZWP nanoparticles compared to the other three formulations (Fig. 28). At 24 hours, there was still a strong signal from ZC, ZLG, ZWP and ZPL nanoparticles in the caecum and colon, while there was only a faint signal from the other two formulations (Fig 26). The tissue sections taken from the rat jejunum at 6 hours showed that the nanocarriers were taken up by the epithelial cells in the villi through endocytosis, as evidenced from the punctuated fluorescence (Fig. 29). These results were consistent with ex-vivo tissue uptake studies in pig jejunum (Fig. 30). Among the six nanocarriers, ZPL and ZPEG nanocarriers showed higher uptake in intestinal epithelial tissue (Fig. 30). 113

Figure 26. Biodistribution of Cy 5.5 loaded nanocarriers after oral administration.

Whole body image of rats at different time points and rat gastrointestinal tract 24 h after oral administration of nanocarriers. This is a representative image of four animals in each treatment group. ZC, zein-casein nanoparticles; ZLF, zein-lactoferrin nanoparticles; ZPEG, zein-PEG micelles; ZLG, zein-lactoglobulin nanoparticles; ZWP, zein-whey protein nanoparticles. 114

Figure 27. Biodistribution of Cy 5.5 loaded nanoparticles after oral administration in rats.

Images shows the fluorescence in rat gastro-intestinal tract 24 hrs after oral administration of nanoparticles. This is a representative image of four animals in each treatment group.

ZC, zein-casein nanoparticles; ZLF, zein-lactoferrin nanoparticles; ZPEG, zein-PEG micelles; ZLG, zein-lactoglobulin nanoparticles; ZWP, zein-whey protein nanoparticles;

ZPL, Zein-pluronic-lecithin nanoparticles.

115

ZC ZLF ZPEG

ZPL ZLG ZWP

Figure 28. Biodistribution of Cy 5.5 loaded nanoparticles after oral administration in rats. Images shows the fluorescence in rat gastro-intestinal tract 6 hrs after oral administration of nanoparticles. This is a representative image of four animals in each treatment group. ZC, zein-casein nanoparticles; ZLF, zein-lactoferrin nanoparticles;

ZPEG, zein-PEG micelles; ZLG, zein-lactoglobulin nanoparticles; ZWP, zein-whey protein nanoparticles.

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Figure 29: In vivo distribution of Cy 5.5 loaded nanocarriers in rat jejunum. Rats were sacrificed at 6 hours after oral delivery of nanocarriers. The jejunum was separated, washed, fixed with 4% paraformaldehyde and sectioned for imaging by confocal microscopy. Magnification is 20X.

117

Figure 30: Ex vivo uptake of NR loaded nanocarriers in pig jejunum. Magnification is 20X.

118

2.4.5. Ex vivo bioadhesion assay

Since the nanocarriers were retained for a prolonged period in the gastrointestinal tract, the mucoadhesive properties were evaluated using everted pig jejunum and texture analyzer. All the six formulations were found to be mucoadhesive (Fig. 31 and 32) and were comparable to polystyrene nanoparticles, a known mucoadhesive polymer (Reineke,

Cho, Dingle, Cheifetz, et al. 2013). ZLG and ZWP nanoparticles showed significant bioadhesive/mucoadhesive property among the six formulations (Fig. 31 and 32).

Bioadhesion can occur through intermolecular interaction such as electrostatic attraction, hydrophobic interactions, hydrogen or disulfide bonding (Andrews, Laverty, and Jones

2009; Sosnik A. 2014). Increased interaction of cationic polymers such as chitosan, lactoferrin and polylysine with anionic glycoproteins or glycolipids (abundant in small intestinal membrane) resulted in enhanced mucoadhesion and cell uptake (Liu 2012;

Thongborisute and Takeuchi 2008; Bengoechea 2011; Tang et al. 2012). Cationization of beta-lactoglobulin was also reported to enhance interaction with negatively charged mucus

(Teng et al. 2016; Teng et al. 2014; Teng et al. 2013). In addition, thermal denaturation of whey protein has previously been reported to show increased interaction with mucin by hydrogen and disulfide bonding (Hsein et al. 2015). ZLG and ZWP nanocarriers were prepared by pre-heating β-LG and WP which results in unfolding the protein and exposure of hydrophobic regions or thiol groups resulting in hydrophobic interaction with mucus layer. Further, zein nanoparticles have been reported to show increased interaction with mucus layer by hydrophobic interaction (González-Navarro 2017; Penalva et al. 2015).

Taken together, enhanced bioadhesive/mucoadhesive of ZLG and ZWP nanocarriers may be attributed to prolonged in vivo retention after oral delivery in rats. 119

Figure 31. Ex vivo mucoadhesion of Nile red (NR) loaded nanocarriers to pig jejunum after 1 h treatment. Y-axis represents the percentage of nanocarriers bound to the tissue. Each value represents mean ± SD of four independent experiments, *P<0.05 compared to PS nanoparticles. PS, polystyrene nanoparticles used as positive control;

ZC. zein-β-casein nanoparticles; ZLF, zein-lactoferrin nanoparticles; ZPEG, zein-

PEG micelles; ZLG. Zein-β-lactoglobulin nanoparticles; ZWP. Zein-whey protein nanoparticles; ZPL, Zein-pluronic-lecithin nanoparticles.

120

Figure 32. Ex vivo mucoadhesion of Nile red (NR) loaded nanocarriers using Texture

Analyzer to determine fracture strength (mN) between Piglet jejunum and nanoparticle coated probes. Each value represents mean ± SD of four independent experiments,

*P<0.05 compared to PS nanoparticles. PS, polystyrene nanoparticles used as positive control; ZC. zein-β-casein nanoparticles; ZLF. zein-lactoferrin nanoparticles; ZPEG, zein-PEG micelles; ZLG. Zein-β-lactoglobulin nanoparticles; ZWP. Zein-whey protein nanoparticles; ZPL. Zein-pluronic-lecithin nanoparticles.

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2.4.6. Immunogenicity of core-shell nanocarriers

The nanocarriers were found to be non-immunogenic when orally administered to mice. The nanoparticles were administered during the first week followed by a second dose on the third week. There was no significant change in the serum IgG levels compared to the saline-treated group (Fig. 33).

Figure 33: Oral immunogenicity of nanoparticles in mice. Serum IgG level determined

after oral delivery of blank nanoparticles to Balb/c mice at 0 and 3rd week. Serum IgG

was measured at 0, 3rd and 5 weeks. Each value represents mean±SD (n=4), *P<0.05.

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The nanoparticles can be taken up by multiple pathways from the GIT. The intestinal epithelium consists of different cell types including enterocytes, mucin-secreting goblet cells, and M-cells. (Pridgen, Alexis, and Farokhzad 2015) The M-cells are associated with Peyer’s patches, which is part of the gut-associated lymphoid tissue

(GALT). The M-cells in the intestine can take up the nanoparticles based on their charge, surface hydrophobicity and the presence of specific ligands (Beloqui, des Rieux, and Preat

2016). The protein biopolymers used in this study are GRAS food proteins that are used for daily consumption. In general, there is oral immune tolerance to commonly used food proteins (Pabst and Mowat 2012; Paula-Silva et al. 2015). Furthermore, the denaturation of the protein during the preparation of the nanoparticles can also reduce the allergenicity/immunogenicity of protein biopolymers (Livney 2010). Given that the M- cells make up only 5-10% of the epithelium, the enterocytes serve as the major absorptive cell population in the intestine for endocytosis of nanoparticles (Pridgen, Alexis, and

Farokhzad 2015; Beloqui, des Rieux, and Preat 2016; Sass, Dreyer, and Seifert 1990).

However, the mucus covering the surface of the nanoparticles can limit drug absorption through the enterocytes (Lai, Wang, and Hanes 2009; Ensign, Cone, and Hanes 2012). To this end, the mucoadhesive polymers can interact with the intestinal mucus layer to increase the retention and absorption of encapsulated drug at the site of absorption (Smart 2005).

As discussed in section 2.4.5., different shell structure can interact differently with the mucus in GI tract. Although, zein protein has mucoadhesive property (Irache and

Gonzalez-Navarro 2017), the presence of LG and WP in the shell enhanced the mucoadhesiveness. The differences in the mechanism of mucoadhesion of the core-shell nanoparticles can be attributed to the observed differences in the in-vivo retention of 123 nanoparticles. Further studies are required to understand the mechanism of mucoadhesion of the core-shell nanoparticles in different regions of the GIT.

The shell composition can be varied to develop nanocarriers with specific functional attributes. ZC nanoparticles in addition to provid a sustained drug release for systemic drug absorption. The ZPEG micelles can be especially useful for improving the oral bioavailability of drugs that are susceptible to P-gp efflux (Alqahtani et al. 2017). ZLF nanoparticles can be used to increase the drug absorption through receptor-mediated endocytosis. The ZLG and ZWPO nanocarriers can be a potential delivery vehicle for colon diseases. Taken together, the findings from this study demonstrate that the functional properties of the protein biopolymers can be used for rational development of core-shell nanocarriers for various oral drug delivery applications.

2.5. Conclusions The findings from this study demonstrate the influence of shell composition on the physicochemical, biological, and functional characteristics of zein nanocarriers for oral drug delivery applications. The shell composition influenced the drug release kinetics, cell uptake, permeability, retention, and absorption through the oral route. ZC nanoparticles showed the slowest release of NR, while ZWP nanoparticles showed the highest cell uptake. Among six nanocarriers, ZPL nanoparticles showed the highest apparent permeability across Caco-2 cell monolayer. ZPEG micelles inhibited P-gp efflux. ZLF nanoparticles were taken up by lactoferrin receptors in the intestinal cells. All the six formulations were mucoadhesive and increased the retention of the dye in the gastrointestinal tract of rats. ZWP and ZPL nanocarriers showed the longest retention (>24 hours) in GI tract. Although, all six nanocarriers have higher bioadhesive/mucoadhesive 124 property compared to polystyrene nanoparticles, ZLG and ZWP nanocarriers showed the highest bioadhesive property. Overall, the results demonstrate the potential of using food protein based core-shell nanocarriers to develop a safe and effective oral drug delivery vehicle in general and pediatric formulations in particular.

125

CHAPTER THREE

USE OF CORE-SHELL NANOCARRIERS FOR ORAL DELIVERY OF A

MODEL ANTIRETROVIRAL DRUG

126

3.1. Introduction

Acquired immune deficiency syndrome (AIDS) is a disease of human immune system caused by human immunodeficiency virus (HIV) (Tuset 1935). HIV infection gradually reduce the effectiveness of human immune system leading the individuals susceptible to opportunistic infections (Freed 2001). As per the latest estimates, about 36.7 million people are living with HIV infection including 1.8 million children (WHO 2016).

Despite significant progress in the diagnosis and treatment, the number of newly infected people (especially children) remains unacceptably high. The rate of progression of the disease is higher in infants than adults at the developmental stages of the immune system.

(Newell et al. 2004). Further, treatment of HIV infection in young patients hindered by the delayed diagnosis, lack of a reliable marker to predict rapid disease progression, lack of evidence-based treatment guidance, and more importantly lack of child friendly drug formulations (Coovadia et al. 2010; Kuhn et al. 2012; Palumbo et al. 2010; Violari et al.

2008; Prendergast et al. 2012). The standard treatment for HIV infection consists of a combination of at least three different class of anti-retroviral drugs known as highly active anti-retroviral therapy (HART) (Althoff et al. 2012). These anti-retroviral drug classes include protease inhibitors (PIs), nucleoside reverse transcriptase inhibitors (NRTIs), non- nucleoside reverse transcriptase inhibitors (NNRTIs), nucleotide reverse transcriptase inhibitors (NTRTIs), and integrase strand transfer inhibitors (INSTIs) (Viswanathan et al.

2015). A typical HAART combination includes two NRTIs and one PI, NNRTI, INSTI, or

NNRTI. HAART combination is effective in lowering viral load by interfering at the different stages of viral life-cycle, and significantly improves patients’ quality of life

(Thompson et al. 2012; Gunthard et al. 2014; Piacenti 2006; Vadlapatla et al. 2014). 127

Among the anti-retroviral drugs, majority of the regimen include PI as one of the main class of drugs.

PIs suppress HIV protease enzymes, responsible for the progression and maturation of viral gag and gag-pol polyproteins. (Vadlapatla et al. 2014) Inhibition of these protein results in immature and non-infectious viral particles. First generation PIs include saquinavir, ritonavir, nelfinavir, indinavir, and fosamprenavir, while the second-generation

PIs are lopinavir, darunavir, atazanavir, and tipranavir. All PIs administered suffer from porr oral bioavailability with values ranging from 4% (saquinavir) to 70% (nelfinavir)

(Vadlapatla et al. 2014). The poor oral bioavailability of PIs attributed to the poor water solubility, poor membrane permeability and first-pass metabolism in the intestine

(Williams and Sinko 1999). Ritonavir is a potent inhibitor for CYP3A4 and serve as pharmacokinetic enhancer for other PIs. As a result, all PIs (except nelfinavir), is used in combination with low dose ritonavir to improve the oral bioavailability of PIs. (Vadlapatla et al. 2014)

Lopinavir (LPV) is a first-line PI used for the treatment of HIV infections, especially in children. LPV is coformulated withritonavir (LPV/r). The current pediatric oral liquid formulation contains LPV and ritonavir in a mixture of propylene glycol and alcohol (42.4%, v/v). Both lopinavir and ritonavir are very bitter, which results in poor patient compliance of this formulation (Pham et al. 2016). Further, high alcohol concentration has the potential for toxicity in younger children (Marek and Kraft 2014).

Addition of ritonavir in the formulation causes the multiple drug interactions leading to adverse effects (Pandie et al. 2016).

128

Figure 34: Chemical structure of lopinavir Stoll et al. (2002).

To this end, the goal of this chapter is to use zein based nanocarriers for improving the oral bioavailability of LPV and test the feasibility of developing a ritonavoir free LPV pediatric formulation. The impact of shell composition on the functional properties of LPV loaded nanocarriers was evaluated in vitro and in vivo.

The specific aims of the study are as follows:

i) Preparation and characterization of LPV loaded nanocarriers.

ii) Determination of in vitro release of LPV from the nanocarriers in simulated GI

fluids and food matrices (milk and applesauce).

iii) Determination of in vitro enzymatic stability of LPV loaded nanoparticles.

iv) Determination of apparent permeability (Papp) of LPV loaded nanocarriers in

Caco-2 cell monolayers.

v) Determine the pharmacokinetics LPV loaded nanocarriers in rats.

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3.2. MATERIALS AND METHODS

3.2.1. MATERIALS

Lopinavir was purchased from AvaChem Scientific (San Antonio, TX, USA).

Ritonavir was obtained from Selleckchem (Houston, TX, USA). 2% milk and applesauce were purchased from Hyvee Supermarket (Brookings, South Dakota, USA). Sterile saline and heparin lock flush syringes, and 23G syringe with blunt needles were purchased from

SAI Technologies (Lake Villa, Illinois, USA). Acetonitrile and glacial acetic acid were obtained from Fisher Scientific (Hampton, NH, USA). All other chemicals and reagents were similar to the ones used in chapter two.

3.2.2. METHODS

3.2.2.1. Preparation of nanocarriers

Nanocarriers were prepared by phase separation method as described in the earlier chapter (Section 2.2.2.). Briefly, 1 mg of LPV was dissolved in 1 mL of 90% ethanol and mixed with 15 mL hydroalcoholic solution of zein. LPV containing zein solution was added dropwise to the aqueous phase to form core-shell nanocarriers. LPV (1mg) loaded

ZPEG micelles was prepared using the method reported in the earlier chapter (section

2.2.2) All the other steps were similar to the ones mentioned in chapter two. Loading efficiency of LPV further optimized based the ratio of drug to polymer, ratio of core to shell and alcohol concentration. Drug to core polymer (zein) ratio was found to be an important parameter for drug loading and therefore different drug/polymer ratio was varied from 1 mg to 5 mg to achieve higher LPV loading.

130

3.2.2.2. Characterization of LPV loaded nanocarriers

LPV loaded nanocarriers were characterized for particle size and zeta potential using Malvern Zeta Sizer Nano ZS (Malvern Instrument Inc., Southborough, MA). The morphology of LPV loaded nanocarriers was visualized by TEM as described in chapter two (Section 2.2.3.).

3.2.2.3. Differential Scanning Calorimetry (DSC)

Thermal analysis of free LPV and LPV loaded nanocarriers was performed by

Differential Scanning Calorimetry (DSC Q200, TA Instruments Inc., USA). Three to five mg of LPV loaded nanocarriers was placed in an aluminum pan in DSC (T zero Lid #

T100819), and the heat flow was maintained at 10°C/minutes from 25 to 300°C under nitrogen gas ( 20 mL/minute). The Thermograms were processed using TA Universal software (TA Instruments Inc., USA).

3.2.2.4. HPLC analysis of LPV

HPLC analysis of LPV was performed on a Waters system (Milford, MA) equipped with an isocratic pump, a degasser, an autosampler and data processing software

(Breeze version 3.30 SPA). LPV was separated on a symmetry® C18 Column (Waters

Corporation, Milford, USA) (5 µm, 4.6 mm X 150 mm). The mobile phase was a mixture of 10 mM ammonium acetate (pH 6.5) and acetonitrile (35:65 v/v).(Vats, Murthy, and Ravi

2011) The mobile phase was pumped at a flow-rate of 1.0 mL/min. LPV was monitored at a wavelength of 210 nm. The calibration curve (peak area versus drug concentration) was linear (R2=0.999) in the LPV concentration range of 0.39–2.5 μg/mL. 131

3.2.2.5. Determination of encapsulation and loading efficiency of LPV

To determine the encapsulation/loading efficiency, around 2 mg LPV loaded lyophilized nanocarriers was dispersed in 1 mL of water and centrifuged at 1000 rpm for

10 minutes. The supernatant was discarded, and the nanocarriers was dispersed in 1 mL of

90% ethanol to digest the nanocarrier. The LPV extracted from the nanocarrier was filtered through 0.2 µm syringe filter, and 50 µL was injected into HPLC column. Encapsulation efficiency (EE%) and loading efficiency (LE%) was calculated using the following equations:

푊푒𝑖푔ℎ푡 표푓 퐿푃푉 𝑖푛 푛푎푛표푐푎푟푟𝑖푒푟푠 EE% = x 100 푊푒𝑖푔ℎ푡 표푓 퐿푃푉 𝑖푛𝑖푡𝑖푎푙푙푦 푎푑푑푒푑

푊푒𝑖푔ℎ푡 표푓 퐿푃푉 𝑖푛 푛푎푛표푐푎푟푟𝑖푒푟푠 LE% = x 100 푊푒𝑖푔ℎ푡 표푓 푛푎푛표푐푎푟푟𝑖푒푟푠

3.2.2.6. In vitro release of LPV from nanocarriers

The release of LPV from nanocarriers was performed using dialysis method in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) in the presence of pepsin and pancreatin enzymes respectively (as described in section 2.2.5.). Briefly, 50 mg of LPV loaded nanocarrier was dispersed in 5mL of SGF or SIF and placed inside the dialysis tube

(Snakeskin dialysis membrane, 10 kDa molecular weight cutoff). The dialysis sac was placed in a beaker containing 25 mL SGF or SIF. 0.1% (w/v) Tween 80 mixed with release medium to maintain sink condition. The beaker was placed in a temperature controlled shaker at 37°C and agitated at 100 rpm. Around 400 µL of sample was withdrawn at predetermined time points up to 24 hours, and an equal volume of pre-warmed SGF or SIF 132 was replaced in the beaker. The sample was diluted with equal volume of ethanol and analyzed by HPLC.

Sequential release of LPV was determined by incubating LPV loaded nanocarriers in food matrices (2% milk or applesauce) and transferred to SGF followed by SIF. Briefly,

50 mg LPV nanocarriers was dispersed in 5 mL of 2% milk or 5 mL apple sauce (diluted

2 times using water) and transferred into a dialysis sac (10 kDa molecular weight cutoff).

Nanocarrier containing dialysis sac placed in a beaker containing 25 mL of 2% milk or apple sauce and was incubated for 1 hour. After 1 hour, the dialysis sac was placed in equal volume of SGF containing 0.32% pepsin and in a separate beaker containing 25 mL SGF with 0.1% Tween 80 and 0.32% pepsin. At the end of 2 hours, in the dialysis sac was placed in 10 mL SIF containing 1% pancreatin in a separate beaker containing 30 mL SIF with

0.1% Tween 80 and 1% pancreatin. About 400 µL of the sample was withdrawn at predetermined time points (1, 2, 4, 8, 12, and 24 h) and was mixed with equal volume of ethanol followed by analysis in HPLC.

3.2.2.7. Solid state stability of free LPV and LPV in nanocarriers

The solid-state stability of free and encapsulated LPV in nanocarriers was evaluated for three months according to the ICH guidelines. Briefly, 5 mg of LPV loaded nanocarriers was placed in a constant climate chamber (Binder, Tuttlingen, Germany) at

30°C±2°C/65% RH±5% RH for three months. At predetermined time points, particle size,

PDI and zeta potential of LPV nanocarriers were measured and the LPV content in the nanocarriers was determined using HPLC.

133

3.2.2.8. Transepithelial permeability of LPV nanocarriers

The transepithelial permeability of 10 µg/mL free LPV, 10 µg/mL LPV with low dose of ritonavir (2.5 mg/mL) and 10 µg/ml of LPV loaded nanocarriers was studied using

Caco-2 cell monolayer. Caco-2 cells (Passage number # 20-25) was maintained in Eagle’s

Minimum Essential Medium (EMEM from ATCC: American Type Cell Culture

Collection, Manassas, VA, USA) with 10% FBS, 1% streptomycin/penicillin antibiotic and

4 placed in incubator with 5% CO2. Briefly, 5x10 cells were seeded in collagen-coated 12- well plate transwell inserts (3 µm pore size) with an area of 1.12 cm2 (Transwell®, Corning

Costar Corp. Cambridge, MA, USA). The growth medium was changed every two days for 15 days. The integrity of the Caco-2 cell monolayers was determined by measuring the transepithelial electrical resistance (TEER) using EVOM instrument (World Precision

Instrument, Sarasota, FL, USA). Cell monolayers with TEER value >400 Ω.cm2 was used for the permeability study. Cell monolayers were incubated with 0.5 mL of Hank’s

Balanced Salt Solution (HBSS) in the apical chamber and 1 mL of HBSS in the basolateral compartment for 30 minutes at 37°C. For permeability studies, the donor solution was replaced with 500 μL of free LPV suspension (10 μg/mL) or equivalent LPV in LPV/r combination (2.5 μg/mL ritonavir) or equivalent LPV loaded nanocarriers dispersed in

HBSS buffer. Around 100 μL of the sample was collected at each time point (0h, 1h, 2h and four h) from the basolateral chamber. An equal volume of pre-warmed HBSS buffer was added to the basolateral chamber to maintain the volume. The samples were mixed with equal volume of ethanol for analysis by HPLC. The apparent permeability coefficient

(Papp) of free LPV, LPV/r, and LPV loaded nanocarriers across Caco-2 cell monolayers was calculated using the following equation 134

(dQ/dt) Papp (cm/s) = [ ] x 100 퐴퐶표

Where dQ/dt is the flux of LPV across Caco-2 monolayer, C0 is the initial concentration of

LPV in the apical chamber, and A is the surface area of the 12-well plate Transwell insert

(1.12 cm2).

3.2.2.9. Enzymatic metabolism studies

To determine the metabolic stability of LPV, human intestinal microsomes was purchased from Sekisui Xenotech, LLC (Kansas City, KS, USA) and incubated with LPV nanoformulations. The microsomal protein was diluted with rapid start solution (5mM magnesium chloride, 5mM glucose-6-phosphate, 1mM b-NADPI, and 1U/mL glucose-6- phosphate dehydrogenase) supplied by Sekisui Xenotech, LLC (Kansas City, KS, USA).

Briefly, 0.3 mg/mL of microsomal protein was incubated with 10 μg/mL of LPV, LPV/r, and LPV loaded nanocarriers. The study was performed for 30 minutes at 37°C under 100 rpm. Around 50 μL of the reaction mixture was collected at 15 and 30 minutes followed by mixing with equal volume of cold acetonitrile to stop the reaction. The LPV content was determined by HPLC.

3.2.2.10. Pharmacokinetic studies in Rats

Based on the results from in vitro permeability study, LPV loaded ZPEG, ZLG and

ZWP nanocarriers were selected for pharmacokinetic studies in the rat. Free LPV and marketed liquid LPV formulation (Kaletra®) were used as controls. All animal experiments were carried out after approval from the IACUC at SDSU. Male Sprague 135

Dawley rats (3–4 weeks of age) weighing 115-150g were used for the study. Rats with surgically placed jugular vein catheter were purchased from Charles River (Wilmington,

MA) and acclimatized for one week. After fasting for 12 hours, free LPV or LPV/r in water with 2% Tween 20, LPV loaded ZPEG and ZPL nanoparticles in water (LPV: 52 mg/kg body weight) were administered by oral gavage to rats. Blood samples (200 µL) were collected at 0, 15 min, 30 min, 1 h, 3 h, 6 h, 12 h, 15 h, 18 h and 24 h in heparinized tubes.

After centrifugation (15 minutes, 4000 rpm), the plasma was collected and stored at -80 °C until further analysis by HPLC. LPV concentration in the plasma samples was determined by HPLC using a calibration plot prepared by spiking known amount of LPV in rat plasma.

The LPV was extracted from the plasma by liquid-liquid extraction method using a mixture of ethyl acetate and n-hexane (50:50, v/v). An equal volume of the organic solvent mixture was added to plasma and centrifuged to separate the organic LPV layer. The extraction was repeated for three times to ensure complete LPV extraction from the plasma. The organic solvent was evaporated under dry nitrogen atmosphere. The residue was reconstituted in

90% ethanol and used for HPLC analysis. The lower limit for the detection of LPV was found to be 50 ng/mL, and the extraction efficiency was 90.96±4.36%. The pharmacokinetic parameters such as peak concentration (Cmax), time to reach peak concentration (Tmax), area under the plasma concentration-time (AUC), and half-life (t1/2) were calculated by non-compartmental analysis using PK-solution software. Percent relative bioavailability (Frel%) of LPV was calculated using the following formula,

퐴푈퐶 (푛푎푛표푐푎푟푟𝑖푒푟푠) Frel (%) = 푋100 퐴푈퐶 (푠푢푠푝푒푛푠𝑖표푛)

136

Based on the AUC values obtained after single dose PK study, the multiple dose pharmacokinetics of ZPEG micelle was studied. In the multiple dose study, 52 mg/kg

(similar to the single dose study) LPV containing Kaletra® liquid formulation and ZPEG micelle were orally administered twice a day for 2 days. Blood samples were collected from the jugular vein catheter at 0, 0.5, 1, 3, and every 3 hours up to 48 hours. All the blood samples were processed as described above and the plasma concentration of LPV was determined by HPLC. Steady state PK parameters such as Css max, Css min, AUCss 0-t were calculated using PK-solution software. Average steady state plasma concentration (Cavg ss) was calculated using the following equation,

퐴푈퐶0−휏 Cavg ss = 휏

Where, τ is the dose interval (12 hours).

3.3. Statistical analysis

All the experiments were conducted in triplicate using three independent batches of nanoparticles. The data is represented as a mean ± standard deviation. Student t-test and analysis of variance (ANOVA) was performed to determine statistical significance at p <

0.05.

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3.4. Results 3.4.1. Development and characterization of LPV loaded nanocarriers

The particle size of the nanocarriers was in the range of 100 to 250 nm with a uniform size distribution (PDI 0.1 to 0.36) (Table 22). ZPEG micelles showed the smallest in size (97 nm), while ZLG nanoparticles was was relatively the largest nanoparticles (251 nm) among the six formulations. The zeta potential of the nanocarriers varied from 30 to -

58 mV based on the shell composition. The LPV loaded nanocarriers had a spherical morphology as was visualized by TEM (Fig. 35). The encapsulation efficiency of LPV was above 65% for all nanocarriers and zein-pluronic-lecithin (ZPL) nanoparticles showed the highest encapsulation efficiency (Table 22). The loading efficiency was optimized and increasing drug to core polymer (zein) ratio was found to increase the loading efficiency.

The loading efficiency of LPV varied from 2.14% to 5.3% depending on the shell composition (Table 22). ZPL and ZC nanocarriers showed the highest loading efficiency, while ZLF nanoparticles showed the lowest loading efficiency. LPV was entrapped in the nanocarriers and was confirmed by thermal analysis (DSC) (Fig. 36). DSC thermogram showed the presence of melting peak for free LPV at around 100°C and absence of LPV peak in LPV loaded nanocarriers confirmed the encapsulation of LPV in the nanocarriers

(Fig. 36).

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Table 22: Characteristics of LPV loaded nanocarriers.

Nanoparticle Particle size PDI Zeta EE (%) LE (%) (d.nm) Potential (mV)

ZC 130.25±0.070 0.18±0.06 -29.3±1.93 70.47±2.15 5.12±0.20

ZLF 185.12±4.32 0.27±0.25 30.24±4.58 64.86±1.84 2.14±0.19

ZPEG 97.56±7.26 0.15±0.012 -3.12±2.23 71.56±4.21 4.58±0.15

ZLG 251.36±3.52 0.093±0.07 -29.6±3.34 84.46±1.62 3.08±0.25

ZWP 215.03±10.94 0.24±0.06 -21.3±1.28 81.36±0.57 3.32±0.22

ZPL 247.5±1.13 0.36±0.02 -58.45±0.49 87.92±7.19 5.31±0.38

EE%: Encapsulation efficiency in percent; LE%: Loading efficiency in percent; ZC: Zein-

β-casein nanoparticles; ZLF: Zein-lactoferrin nanoparticles; ZPEG: PEGylated zein micelles; ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein nanoparticles; ZPL: Zein-pluronic-lecithin nanoparticles. Each value represents mean±SD

(n=3).

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Figure 35: TEM images of lopinavir loaded nanocarriers. ZC: Zein-β-casein nanoparticles; ZLF: Zein-lactoferrin nanoparticles; ZPEG: PEGylated zein micelles;

ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein nanoparticles; ZPL:

Zein-pluronic-lecithin nanoparticles.

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Figure 36: DSC thermograms of free lopinavir and lopinavir loaded nanocarriers. ZC.

Zein-β-casein nanoparticles, ZLF. Zein-lactoferrin nanoparticles, ZPEG. PEGylated zein micelles, ZLG. Zein-β-lactoglobulin nanoparticles, ZWP. Zein-whey protein nanoparticles, ZPL. Zein-pluronic-lecithin nanoparticles. X-axis shows the Temperature

(°C) and Y-axis shows the Heat Flow (W/g). Red line: Free LPV; blue line: LPV loaded nanocarriers; black line: blank nanocarriers.

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3.4.2. In vitro release of LPV from nanocarriers

All six nanocarriers showed sustained release of LPV in simulated gastric fluid

(SGF) and simulated intestinal fluid (SIF) for 24 hours. ZPEG micelles showed the slowest release (<30%), while relatively faster (~80%) release was seen with ZPL nanoparticles

(Fig. 37). ZC, ZLF, ZLG and ZWP nanocarriers released 40% to 65% of LPV in both SGF and SIF within 24 hours. ZLG nanocarriers showed relatively faster release of LPV in SGF than SIF, due to the higher solubility of β-lactoglobulin in acidic pH (Taulier and Chalikian

2001). There was no significant difference in LPV release between SGF and SIF for other nanocarriers (Fig. 37).

To understand the mechanism of LPV release, the data was fitted to different empirical release kinetic models (Table 23). The release of LPV from the nanocarriers followed Peppas model in both SGF and SIF, except for ZLG nanocarriers. This is indicative of polymer swelling and diffusion from polymer matrix followed by surface erosion of polymer due to hydrolytic cleavage (Sivakumar and Rao 2003). In case of ZLG nanocarriers, the release of LPV in SGF followed first-order kinetics which was consistent with NR release shown in second chapter (Section 2.4.2.). LPV release from ZLG nanocarriers in SIF followed Hixon-Crowell model indicating that the release is dissolution limited. In case of ZWP and ZPL nanocarriers, LPV release in SGF followed Peppas model, while in the presence of SIF followed mixed order kinetics (Table 24).

The nanocarriers was stable when incubated with food matrices (milk and applesauce). In general, less than 40% of LPV was released within two hours when incubated with food matrices and less than 80% of LPV was released from the nanocarriers in 24 hours after transferring to SGF followed by SIF (Fig. 38). ZPEG micelles showed 142 slowest release of LPV in both milk and applesauce, while ZLG and ZWP nanocarriers released LPV faster in milk and applesauce. However, the release of LPV in SGF and SIF

(Fig. 37) did not change much after treating the nanoparticles with milk or applesauce, which indicates that there was no influence of the presence of food matrices on the release of LPV from the nanocarriers. This property concludes that nanocarriers have the potential to use as food sprinkle.

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Figure 37: Cumulative percent of lopinavir released from different zein-based nanocarriers in Simulated Gastric Fluid (SGF) and Simulated Intestinal Fluid (SIF).

ZC: Zein-β-casein nanoparticles, ZLF: Zein-lactoferrin nanoparticles, ZPEG:

PEGylated zein micelles, ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles; ZPL: Zein-pluronic-lecithin nanoparticles. Each value represents mean±SD (n=3).

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Table 23: Summary of nonlinear fit of LPV release kinetics using different models.

Formulation R2 (Medium) Peppas Hixson-Crowell Zero Order First Order Higuchi 푛 퐹 = 퐾 ∗ 푡 퐹 = 100 ∗ (1 − (1 − 푘 ∗ 푡)^3) C=C0-K0t F=100*(1-exp(-k*t)) F = k ∗ sqrt(t) ZC (SGF) 0.909 0.853 0.820 0.890 0.900 ZC (SIF) 0.957 0.907 0.904 0.932 0.939 ZLF (SGF) 0.983 0.790 0.859 0.839 0.982 ZLF (SIF) 0.994 0.920 0.945 0.941 0.976 ZPEG (SGF) 0.924 0.307 0.665 0.354 0.862 ZPEG (SIF) 0.994 0.896 0.946 0.910 0.975 ZLG (SGF) 0.891 0.906 0.853 0.919 0.860 ZLG (SIF) -0.717 0.843 0.890 0.822 0.629 ZWP (SGF) 0.981 0.873 0.905 0.905 0.979 ZWP (SIF) 0.970 0.969 0.972 0.966 0.820 ZPL (SGF) 0.982 0.824 0.925 0.877 0.979 ZPL (SIF) 0.981 0.951 0.984 0.957 0.960 SGF-Simulated gastric fluid; SIF-Simulated intestinal fluid; R2 calculated from SigmaPlot 13.0. ZC: Zein-β-casein nanoparticles,

ZLF: Zein-lactoferrin nanoparticles, ZPEG: PEGylated zein micelles, ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein- whey protein isolate nanoparticles; ZPL: Zein-pluronic-lecithin nanoparticles. The highlighted value indicates the best fit model.

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Figure 38: Sequential release of LPV from different zein nanocarriers in food matrices

(milk or apple sauce) for 1 h followed by 1 h in SGF and up to 24 h in SIF. Zein-β-casein nanoparticles, ZLF: Zein-lactoferrin nanoparticles, ZPEG: PEGylated zein micelles, ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles; ZPL: Zein-pluronic-lecithin nanoparticles. Each value represents mean±SD (n=3).

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Table 24: Summary of non-linear fit of lopinavir sequential release kinetics using different models.

Formulation (Medium) R2

Peppas Hixson-Crowell Zero First Order Higuchi 퐹 = 퐾 ∗ 푡푛 퐹 = Order F= F = k ∗ sqrt(t) 100 ∗ (1 − (1 − 푘 ∗ 푡)^3) C=C0-K0t 100*(1-exp(-k*t)) ZC (milk to SGF to SIF) 0.969 0.910 0.888 0.942 0.969 ZC (apple sauce to SGF to SIF) 0.981 0.915 0.933 0.943 0.980 ZLF (milk to SGF to SIF) 0.987 0.961 0.962 0.977 0.964 ZLF (applesauce to SGF to SIF) 0.977 0.931 0.937 0.949 0.975 ZPEG (milk to SGF to SIF) 0.995 0.989 0.977 0.992 0.949 ZPEG (applesauce to SGF to SIF) 0.989 0.826 0.913 0.856 0.989 ZLG (milk to SGF to SIF) 0.942 -6.67 0.500 0.130 0.643 ZLG (applesauce to SGF to SIF) 0.969 -0.230 0.571 -0.161 0.579 ZWP (milk to SGF to SIF) 0.941 0.0065 0.490 0.157 0.636 ZWP (applesauce to SGF to SIF) 0.973 -0.235 0.549 -0.136 0.547 ZPL (milk to SGF to SIF) 0.975 0.464 0.671 0.591 0.842 ZPL (applesauce to SGF to SIF) 0.958 0.138 0.688 0.201 0.746 SGF-Simulated gastric fluid; SIF-Simulated intestinal fluid; R2 calculated from SigmaPlot 13.0. ZC: Zein-β-casein nanoparticles, ZLF:

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3.4.3. Stability of LPV loaded nanocarriers

Solid state stability of LPV in ZC and ZLG nanoformulations was determined by storing the formulation at 30°C±2°C/65% RH±5% RH for three months (according to ICH guidelines) (ICH 2013). More than 90% of LPV remained at the end of 3 months and there was no significant difference in the stability of free LPV and LPV loaded nanoformulations

(Fig. 39a). However, the particle size of ZLG nanoparticles increased after two months indicating, aggregation of particles (Fig. 39b). On the other hand, the physicochemical characteristics of ZC nanocarriers did not change over time (Fig. 39c and Fig. 39d).

Figure 39: Solid state stability of free LPV and LPV loaded ZC and ZLG nanoparticles.

Nanoparticles were kept in constant climate chamber for 3 months at 30°±2°C and

65±5% relative humidity. Each value represents mean±SD (n=3).

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3.4.4. Transepithelial permeability of LPV loaded nanocarriers across Caco-2 cell monolayers

All the nanocarriers significantly enhanced apparent permeability (Papp) of

LPV across the Caco-2 cell monolayers (Fig. 40a). LPV loaded ZPEG micelles showed the highest permeability of LPV (6-fold) compared to free LPV. The apparent permeability of LPV loaded nanocarriers was found to be in the following decreasing rank order

ZPEG>ZC>ZLF>ZWP>ZLG>ZPL>LPV/r>LPV (Fig. 40a). Results from percent permeability indicates that percent of LPV permeated after 1 to 2 hours was comparable between free LPV and nanoformulations (Fig. 40b). However, after 4 hours the nanocarriers showed significantly higher permeability than the free LPV (Fig 40b)

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Figure 40: Apparent permeability coefficient (P ) (a) and percent of dose of LPV 3.4.5. Metabolic stability studies app permeated (b) across Caco-2 monolayer from LPV loaded nanocarriers. Each value

represents mean±SD (n=3), *P<0.05.

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3.4.5. Metabolic stability studies

To understand the metabolic stability of LPV in vitro, human intestinal microsomes was used. Two different concentrations (10 and 20 μM) of free LPV, Kaletra®, and LPV loaded nanocarriers were incubated with human microsomal enzymes for 15 and 30 minutes. After 15 minutes, 58% of LPV was metabolized when the initial LPV concentration was 10 μM, while only 20% metabolized when 20 μM LPV was used, indicating that higher concentration leads to saturation of CYP3A4 enzymes (Fig. 41a).

However, there was no statistically significant effect of incubation time on the metabolic stability of LPV in the nanocarriers. More than 85% of LPV remained stable in nanocarriers after 15 minute incubation and was comparable to Kaletra®. After 30 minute incubation, around 30% LPV was metabolized in Kaletra® with 10 µM LPV, while there was no change in LPV concentration with 20 µM (Fig. 41b).

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Figure 41: In vitro metabolic stability of LPV in presence of human intestinal microsomes. Free LPV, Kaletra®, and LPV loaded nanocarriers were incubated for 15 minutes (a) and 30 minutes (b). Each value represents mean±SD (n=3), P<0.05.

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3.4.6. In vivo pharmacokinetics in rats Based on the results from in vitro permeability study, ZLG, ZWP and ZPEG nanocarriers were selected for in vivo pharmacokinetic studies in rats. A dose of 52 mg/kg body weight of free LPV (1 mL water with 2% Tween 20), Kaletra®, ZLG, ZWP and

ZPEG nanocarriers (dispersed in water) was administered by oral gavage to rats. Kaletra® increased the oral bioavailability of LPV by 3-fold compared to free LPV suspension. The nanocarriers increased the oral bioavailability of LPV by 5- to 6.5-fold compared to free

LPV suspension. The highest oral bioavailability was obtained with LPV loaded ZPEG micelles followed by ZWP and ZLG nanocarriers (Fig. 42). Further, the highest plasma concentration (Cmax) of LPV was achieved with ZPEG micelles, which was 4-fold higher compared to free LPV. Kaletra® liquid formulation enhanced the oral bioavailability by 3- fold compared to free LPV. On the other hand, ZPEG micelles showed 2-fold higher oral bioavailability compared to Kaletra® liquid formulation (Table 25). The AUC of LPV was in the following decreasing rank order ZPEG>ZWP>ZLG>Kaletra®>free LPV.

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Figure 42: Plasma concentration of free LPV suspension, Kaletra® and LPV loaded

ZLG, ZWP and ZPEG nanocarriers delivered orally in rats. ZPEG: PEGylated zein micelles, ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles. Each value represents mean±SD (n=3).

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Table 25: PK parameters of free LPV, Kaletra®, and LPV loaded nanocarriers after oral delivery in rats.

LPV Kaletra ® ZWP-LPV ZLG-LPV ZPEG-LPV suspension C max 0.52±0.05 1.77±0.20 1.29±0.05 * 1.39±0.13 * 1.98±0.04* (μg/mL)

T (hr) max 6.00±0.00 3.00±0.00 6.00±0.00 6.00±0.00 9.00±0.00

t (hr) 1/2 5.81±1.28 6.53±1.45 11.72±3.30 11.81±2.07 8.63±3.60

AUC 0-t 5.04±0.18 15.86±0.68 18.12±0.28 16.99±0.59 28.11±0.30 (μg-hr/mL) AUC 0-∞ 5.04±0.18 15.86±0.68 23.63±2.21* 20.75±1.27 * 32.48±1.57 * (μg-hr/mL)

MRT (hr) 6.30±0.10 6.70±0.31 16.97±3.51 15.04±1.20 14.26±1.96

F (% rel) -- 323.71±14.06 149.00±13.95* 130.86±8.01* 204.81±9.91 *

Each value represents mean±SD (n=3) *P<0.05. Cmax: Maximum plasma concentration;

Tmax:- Time to reach maximum plasma concentration; AUC:- Area under plasma concentration-time curve; MRT:- Mean residence time; t1/2:- Elimination half-life;

Kaletra®:-Lopinavir with a low dose of ritonavir; F (% rel):- Percent relative bioavailability. F(%rel) for Kaletra® is in comparison to LPV suspension, F(%rel) for nanocarriers is in comparison to Kaletra®.

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Since ZPEG micelles showed the highest oral bioavailability, this formulation was used for steady-state pharmacokinetic studies by multiple dosing. The formulations were administered orally twice a day for two days. The LPV absorption increased after the second dose of Kaletra® and gradual accumulation of LPV was observed after subsequent doses of Kaletra® and ZPEG micelles (Fig. 43). Steady state plasma concentration of LPV was achieved after second dose (24-48 hours) and the PK parameters were comparable between Kaletra® and ZPEG micelles (Table 26). Steady state Cmax for both Kaletra® and

ZPEG formulations was significantly increased (around 2.5-fold) compared to Cmax obtained with single dose (Table 25 and Table 26). 156

Figure 43: Plasma profile of LPV after multiple dose administration (52 mg/Kg twice a day for 2 days) of Kaletra® and LPV loaded ZPEG nanocarriers. Each value represents mean±SD. (n=3).

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Table 26: Steady state PK parameters of Kaletra® and LPV loaded ZPEG micelles after oral delivery in rats.

Kaletra® ZPEG-LPV

Css max (µg/mL) 5.50±0.65 4.24±0.49*

Css avg (µg/mL) 4.43±0.73 4.0±0.27*

Css min (µg/mL) 1.06±0.12 1.49±0.32*

Tss max (hrs) 27.00±0.00 30.00±0.00*

AUCo-12 ss (μg-hr/mL) 53.20±8.84 53.16±3.35*

Css max. Maximum concentration during dosing interval at steady state; Css min. Minimum concentration during dosing interval at steady state; Css avg. Average plasma drug concentration at steady state; ZPEG: PEGylated zein micelles; Each value represents mean±SD (n=3); *P<0.05 compared to Kaletra®. 158

3.5. Discussion

The main goal of this study was to test the feasibility of developing a water dispersible ritonavir free formulation of LPV using food-grade biopolymers. LPV was encapsulated in the hydrophobic zein core, while the external hydrophilic shell was used to increase the water solubility and permeability through the gastrointestinal membrane.

The size and surface charge of LPV loaded nanocarriers were similar to NR loaded nanocarriers as described in chapter two (Section 2.4.1). The encapsulation and loading efficiency varied with different shell composition (Table 22). The highest encapsulation and loading efficiency of LPV obtained with ZPL nanocarriers can be attributed to the presence of both lecithin and pluronic in the shell. The lecithin in the shell favors the entrapment of LPV in the ZPL nanocarriers (Chen, Chen, Su, Hong, et al. 2016; Chen,

Chen, Su, Wong, et al. 2016), while addition of pluronic F127 can sterically stabilize zein nanoparticles (Podaralla and Perumal 2012). Lecithin alone was not able to prevent aggregation of zein nanoparticles (Podaralla and Perumal 2012). Pluornic stabilizes the lecithin layer by hydrophobic interaction of polypropylene oxide unit of pluronic with hydrophobic tail of lecithin and hydrophilic interaction of polyethylene oxide chain of pluronic with polar head of lecithin (Schubert and Muller-Goymann 2005; Mosqueira et al. 2000; Zhang et al. 2008). The loading efficiency of LPV in ZC nanocarriers were comparable to ZPL due to the relatively higher hydrophobicity of β-casein among the milk proteins used in this study (Patel, Bouwens, and Velikov 2010). Lactoferrin has high aqueous solubility and thereby contributed to the lowest encapsulation and loading of LPV in ZLF nanocarrier (Table 22). In general, the results obtained with loading of NR (Section

2.4.1) and LPV in nanocarriers suggest that the encapsulation and loading efficiency 159 dictated by both shell composition and the physicochemical properties of the encapsulated molecule.

The long-term stability study indicated that LPV remained stable both in free form and in nanocarriers with a gradual increase in ZLG particle size which may be attributed by the alteration in β-lactoglobulin (LG) conformation over time (Majhi et al. 2006).

In vitro food compatibility study indicated that LPV loaded nanocarriers can be mixed with food matrices (milk and applesauce) and also suggest that the formulations have the potential to be used as food sprinkle. Water, milk and applesauce are commonly used vehicles to disperse drug formulations. (WHO 2010) Administration of multi- particulate drug formulation by mixing with food or drinks (sprinkles) can improve organoleptic properties and thereby can increase the acceptability of the formulation especially for pediatric patients. However, compatibility of the formulation with food matrix, drug release in food matrix and bioavailability should be taken into account

(MacDonald et al. 2006; den Uyl et al. 2010). Albertini et al. (2014) reported the compatibility of solid lipid microparticles with milk and yogurt and can be used as sprinkle for drug administration. The practice of crushing lopinavir/ritonavir (LPV/r) tablet and mixing with food leads to reduce the total lopinavir and ritonavir exposure by 45% and

47% respectively (Best et al. 2011). In this regard, zein-based nanoformulations are advantageous to ensure flexibility in dosing. In addition, LPV loaded zein-based nanocarriers showed compatibility with food matrices due to less drug release and have potential to mask the bitter taste of drugs and can be used as food sprinkle. However, further studies needed to confirm the palatability and taste masking using these core-shell nanoformulations. 160

In vitro metabolic stability study demonstrated the protection of lopinavir from

CYP3A4 metabolic degradation. Apparent permeability (Papp) of LPV across Caco-2 cell monolayers was also significantly increased using nanocarriers compared to free LPV

LPV/r combination. This result signifies that zein-based nanoformulations can be used to develop ritonavir free lopinavir formulation. The shell composition of nanocarriers play an important role in the interaction, uptake, and distribution of the nanoparticles. ZC and

ZPEG nanocarriers are taken up by non-specific endocytosis in Caco-2 cells (Alqahtani et al. 2017). On the other hand, ZLF can be taken up through lactoferrin receptors in the intestinal epithelial cells by receptor mediated endocytosis (Alqahtani et al. 2017). The efflux pumps expressed in the intestinal cells limits the drug absorption. The P-gp inhibitory activity of PEG in ZPEG micelles resulted in higher permeability of LPV across

Caco-2 monolayers (Alqahtani et al. 2017). ZLG and ZWP nanocarriers mainly taken up by non-specific endocytosis. Taken together, findings from the in vitro studies suggest that the shell composition influences the cell uptake kinetics and the mechanisms of transepithelial transport of zein based core-shell nanocarriers.

Results from single-dose Pharmacokinetic study in rat demonstrated that the trough plasma concentration was 1 μg/mL, which is consistent with the concentration required to reduce the HIV viral load (Lopez-Cortes et al. 2013). Further, the half-life of LPV using nanocarriers significantly increased and was found to be useful to improve plasma level of

LPV by gradual accumulation after administration of multiple dose (Fig. 43). The P-gp inhibitory activity of ZPEG contributed to suppress the interplay between CYP3A4 and P- gp efflux pump to reduce the absorption of LPV. The steady-state plasma concentration of

LPV using ZPEG micelle was obtained after administration of second dose and steady- 161 state PK parameters were comparable to Kaletra® indicated the potential of developing ritonavir free LPV formulation using zein nanocarriers.

The HIV treatment regimen includes 3 different groups of drugs and concomitant administration increases the chance of drug-drug interaction (Barry et al. 1999). For example, ritonavir in lopinavir/ritonavir combination can interact with non-nucleoside reverse transcriptase inhibitors by inducing drug metabolizing enzymes and thereby reduce the plasma concentration of protease inhibitors (Barry et al. 1999; Piscitelli and Allicano

2001). The potential of developing ritonavir free lopinavir formulation can reduce the overall drug load and drug-drug interactions.

Overall, the findings from this study demonstrated that food-grade biopolymers can be used to develop a safe and effective carrier for LPV.

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3.6. Conclusions

The present study demonstrates that zein based core-shell nanocarriers are promising for enhancing the oral bioavailability of LPV. In vitro studies showed that zein based core-shell nanocarriers significantly improved the water solubility of LPV, sustained the LPV release, and increased membrane permeability. Low LPV release in food matrices

(milk and applesauce) indicated that LPV loaded nanocarriers are compatible with food matrices and have the potential to be used as a food sprinkle. In vitro metabolic stability study demonstrated that zein based core-shell nanocarriers protected LPV from CYP3A4- mediated enzymatic degradation. Results from the pharmacokinetic study showed that the bioavailability obtained with ZPEG micelles was similar or higher compared to Kaletra® liquid formulation. Overall the results suggest the feasibility of developing a ritonavir pediatric formulation of LPV using zein based nanocarriers.

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CHAPTER FOUR

USE OF CORE-SHELL NANOCARRIERS FOR ORAL DELIVERY OF AN

INVESTIGATIONAL ANTI-CANCER DRUG MOLECULE

164

4.1. Introduction

Given the promising outcomes from chapter two and chapter three, the goal of this chapter is to use zein-based nanocarriers for encapsulation and oral delivery of fenretinide, an investigational anti-cancer compound. Fenretinide [N-(4-hydroxyphenyl) retinamide (4-

HPR)] is a poorly soluble and poorly permeable anti-cancer agent (Torrisi et al. 2001;

Wischke et al. 2010; Orienti et al. 2007; Ledet et al. 2015). Further, the compound has poor chemical stability. Fenretinide has been investigated for its effectiveness against various cancers in clinical trials including breast (Kazmi et al. 1996), ovarian (Supino et al. 1996;

Sabichi et al. 1998; Formelli and Cleris 1993), lung (Kalemkerian et al. 1995), pediatric neuroblastoma (Ponzoni et al. 1995; Di Vinci et al. 1994; Maurer et al. 2000), prostate

(Hsieh, Ng, and Wu 1995; Igawa et al. 1994) and colorectal (Ziv et al. 1994) cancer. There are several mechanisms reported for fenretinide’s anticancer activity including i) formation of reactive oxygen species (ROS), ii) increasing the level of ceramides, iii) anti-angiogenic activity, and iv) enhanced NK cell activity (O'Donnell et al. 2002; Maurer et al. 1999;

Oridate et al. 1997; Delia et al. 1997; DiPietrantonio et al. 1998; Batra, Reynolds, and

Maurer 2004; Rehman, Shanmugasundaram, and Schrey 2004; Ribatti et al. 2001; Zhao et al. 1994).

However, a major challenge in realizing its therapeutic potential is the compound’s poor oral bioavailability. Fenretinide at a dose of 100 to 400 mg/day has been investigated as a chemoprevention agent in phase I, phase II and phase III trial using oral gelatin capsule

(Villablanca et al. 2011). In the capsule formulation of fenretinide was dissolved in corn oil and a surfactant (polysorbate 80) and achieves very low blood concentration.

Fenertinide has been observed to have dose-limited toxicity (Torrisi et al. 1994). A high- 165 dose fenretinide (1800 mg/m2/day) when administered in pediatric patients with neuroblastoma was found to be associated withs hepatic toxicities and pseudotumor cerebri

(Children's Oncology et al. 2006). Further, fenretinide using capsule formulation showed the high patient variability in plasma concentration (2-5 μg/mL) with rebound neuroblastoma (Garaventa et al. 2003; Villablanca et al. 2011; Children's Oncology et al.

2006; Schneider et al. 2009). As a result of the poor compliance with fenertinide capsule formulation, clinical trials have been discontinued (Caruso et al. 1998).

An oral lipid formulation, Lym-X-Sorb® (LXS), has been investigated to enhance bioavailability of fenretinide with improved patient compliance (Kummar et al. 2011;

Maurer et al. 2013). LXS® oral powder achieved 4-fold plasma and 7-fold tissue fenretinide concentration in mice compared to fenretinide capsule formulation (Maurer et al. 2007).

LXS®-fenretinide powder formulation was successful in overcoming some of the difficulties with corn oil capsule (Kummar et al. 2011). However, there is a strong unmet need for an effective and safe oral formulation of fenertinide, especially for pediatric patients.

Figure 44: Chemical structure of fenretinide. 166

To this end, the goal of this study is to develop and test the feasibility of using zein based core-shell nanocarriers for enhancing the oral bioavailability of fenretinide. Six different core-shell nanocarriers that were evaluated in previous two chapters, was used for this study with the goal of studying the influence of the shell composition on the in vitro and in vivo functional performance of fenretinide loaded nanocarriers and identifying a suitable formulation for further development

The specific aims of this study are:

i) To prepare and characterize fenretinide loaded core-shell nanocarriers.

ii) Determine the in vitro release of fenretinide in simulated GI fluids and food

matrices (milk and applesauce).

iii) Determine the apparent permeability (Papp) of fenretinide and fenretinide loaded

nanocarriers across Caco-2 cell monolayers.

iv) Determine the oral Pharmacokinetics of fenretinide loaded nanocarriers in rats.

167

4.2. Materials and methods

4.2.1. Materials

Fenretinide was purchased from LC Laboratories (Woburn, MA, USA). All other materials and chemicals used in this study were similar to those mentioned in chapters two and three.

4.2.2. Methods

4.2.2.1. Preparation of fenretinide loaded nanocarriers

Phase separation method used to prepare fenretinide loaded nanocarriers as described in the second chapter (section 2.2.2.). Briefly, 15 mg of zein was dissolved in 2 mL of 90% ethanol and 1 mg of fenretinide was mixed with zein solution. The hydroalcoholic phase was added dropwise to aqueous phase containing milk protein (β- casein-C or lactoferrin-LF or β-lactoglobulin-LG or whey protein isolate-WP) or pluronic- lecithin under probe sonication. Beta-lactoglobulin (LG) and whey protein isolate (WP) was preheated at 60°C for 30 minutes followed by slow addition of zein solution as described in the second chapter (section 2.2.2.). The dispersion was stirred for 3 to 4 hours at 100 rpm (room temperature) to evaporate the remaining ethanol. Free fenretinide was removed by centrifugation using centrifugal filters (EMD Millipore). The purification step was repeated for 3 to 5 times. The resultant formulation was lyophilized for 48 hours, and the dried powder was stored at 4°C in a desiccator until further analysis.

Around 1 mg of fenretinide was loaded in ZPEG micelles using the same method as described in the second chapter (section 2.2.2.)

168

4.2.2.2. Characterization of fenretinide loaded nanocarriers

Fenretinide loaded nanocarriers were characterized for particle size, PDI and zeta potential using Malvern Zeta Sizer Nano ZS (Malvern Instrument Inc., Southborough,

MA). The morphology of fenretinide loaded nanocarriers was visualized using TEM using the procedure described in chapter two (section 2.2.3.). Differential Scanning Calorimetry

(DSC) analysis was performed to determine the thermal properties of free fenretinide and fenretinide loaded nanocarriers using the same procedure as described in chapter 3 (section

3.2.2.3.).

4.2.2.3. HPLC analysis of fenretinide

HPLC analysis of fenretinide was performed on a Waters system (Milford, MA) equipped with an isocratic pump, a degasser, an autosampler and data processing software

(Breeze version 3.30 SPA). The separation of fenretinide was performed on a symmetry®

C18 Column (Waters Corporation, Milford, USA) (5 µm, 4.6 mm X 150 mm). The mobile phase was a mixture of acetonitrile: water: glacial acetic acid (80:18:2, v/v). The mobile phase was pumped at a flow-rate of 0.8 mL/min. Fenretinide was monitored at a wavelength of 340 nm. The calibration curve (peak area versus drug concentration) was linear (R2=0.999) in the fenretinide concentration range of 0.39–2.5 μg/mL.

4.2.2.4. Determination of encapsulation and loading efficiency of fenretinide

Lyophilized fenretinide formulations were used to determine the encapsulation and loading efficiency. Briefly, 2 mg of fenretinide loaded nanocarriers was dispersed in 1 mL of water and centrifuged at 1000 rpm for 10 minutes, the supernatant was discarded, and 169 the nanoparticles was reconstituted in 1 mL 90% ethanol. The extracted fenretinide was filtered through 0.2 µm syringe filter, and 50 µL was injected into the HPLC column. The concentration of fenretinide in nanocarriers was calculated from the calibration curve of fenretinide in 90% ethanol. The encapsulation efficiency (EE%) and loading efficiency

(LE%) were calculated using the following equations:

푊푒𝑖푔ℎ푡 표푓 푓푒푛푟푒푡𝑖푛𝑖푑푒 𝑖푛 푛푎푛표푐푎푟푟𝑖푒푟푠 EE% = x 100 푊푒𝑖푔ℎ푡 표푓 푓푒푛푟푒푡𝑖푛𝑖푑푒 𝑖푛𝑖푡𝑖푎푙푙푦 푎푑푑푒푑

푊푒𝑖푔ℎ푡 표푓 푓푒푛푟푒푡𝑖푛𝑖푑푒 𝑖푛 푛푎푛표푐푎푟푟𝑖푒푟푠 LE% = x 100 푊푒𝑖푔ℎ푡 표푓 푓푒푛푟푒푡𝑖푛𝑖푑푒 푛푎푛표푐푎푟푟𝑖푒푟푠

4.2.2.5. In vitro release of fenretinide from nanocarriers

The release of fenretinide from nanocarriers was performed by dialysis method in

SGF and SIF using the proedure as described in chapter two (section 2.2.5.). Briefly, 50 mg of fenretinide loaded nanocarriers was dispersed in 5mL of SGF or SIF and placed inside the dialysis tube (Snakeskin dialysis membrane, 10 kDa molecular weight cutoff).

The dialysis sac was placed in a beaker and placed in a temperature controlled shaker at

37°C and agitated at 100 rpm. Around 400 µL of the sample was withdrawn at predetermined time points, diluted with equal volume of ethanol and 50 µL of the sample was injected into the HPLC column.

Sequential release of fenretinide was determined by incubating fenretinide loaded nanocarriers in 2% milk or applesauce and then transferred to SGF followed by SIF.

Briefly, 50 mg fenretinide nanocarriers was dispersed in 5 mL 2% milk or 50% apple sauce and transferred into a dialysis sac (10 kDa molecular weight cutoff). All other procedure was similar to sequential release of LPV described in section 3.2.2.6.

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4.2.2.6. Transepithelial permeability through Caco-2 cell monolayers

The transepithelial permeability of free fenretinide and fenretinide loaded nanocarriers was studied using Caco-2 cell monolayers as described in the earlier chapter

(section 3.2.2.8). Briefly, 5x104 cells were incubated in 12-well plate transwell inserts with an area of 1.12 cm2 (Transwell®, Corning Costar Corp. Cambridge, MA, USA). The growth medium was changed every two other days for 15 days. The tight junction integrity of the Caco-2 cell monolayers was determined using TEER measurements. Prior to applying the fenretinide formulations, caco-2 cell monolayers were incubated with Hank’s

Balanced Salt Solution (HBSS) for 30 minutes at 37°C to polarize cell monolayers. About

500 μL of free fenretinide suspension (10 μg/mL) or equivalent of fenretinide loaded nanocarriers dispersed in HBSS buffer was added to the apical chamber and 100 μL of the sample was collected at predetermined time points (0h, 1h, 2h and 4 h) from the basolateral chamber. An equal volume of HBSS buffer was added to maintain the volume in the basolateral compartment. The samples were mixed with an equal volume of ethanol and 50

μL of the sample was injected into HPLC for determination of fenretinide concentration.

The apparent permeability coefficient (Papp) of fenretinide loaded nanoparticle across

Caco-2 cell monolayers was calculated using the equation described in second chapter

(section 2.2.11.).

4.2.2.7. Stability of fenretinide in nanocarriers

The stability of fenretinide loaded ZC, ZLG and ZPL nanocarriers were evaluated.

Briefly, 5 mg of fenretinide loaded nanocarriers was incubated in a constant climate chamber (Binder, Germany) at 30°C±2°C/65% RH±5% RH for three months (according 171 to ICH guidelines) (ICH 2013). Around 1 mg of free fenretinide was used as a control. At predetermined time points, the particle size, PDI and zeta potential were measured using the particle sizer (Malvern instrument). Fenretinide content in the nanocarriers was determined using HPLC.

4.2.2.8. Pharmacokinetic studies in Rats All the animal experiments were carried out after approval from the IACUC at

SDSU. Male Sprague-Dawley rats (3–4 weeks of age) weighing 115-150g were used for the study. Rats with surgically implanted jugular vein catheter were purchased from

Charles River (Wilmington, MA) and acclimatized for one week. After fasting for overnight, 20 mg/kg of free fenretinide (in water with 2% Tween 20) or fenretinide loaded

ZC, ZLG, ZWP, and ZPL nanocarriers were administered by oral gavage. Blood samples

(200 µL) were collected at 0, 15 min, 30 min, 1 h, 3 h, 6 h, 12 h, 15 h, 18 h and 24 h from the jugular vein. The plasma was separated by centrifuging at 4000 rpm for 10 minutes.

Fenretinide was extracted from the plasma by adding an equal volume of ethyl acetate and n-hexane mixture (50:50, v/v) followed by centrifugation at 10000 rpm for 10 minutes. The supernatant was collected, and the extraction process was repeated three times to ensure complete extraction. The fenretinide concentration in the plasma was determined by HPLC method using a calibration plot prepared by spiking known amount of fenretinide (0.1-2.0

µg/mL) in the plasma. The pharmacokinetic parameters including peak concentration

(Cmax), time to reach peak concentration (Tmax), area under the plasma concentration-time

(AUC), and half-life (t1/2) were calculated by non-compartmental analysis using PK- solution software. The percent relative bioavailability (Frel%) of fenretinide was calculated by using the following formula, 172

퐴푈퐶 (푓푒푛푟푒푡𝑖푛𝑖푑푒 푛푎푛표푐푎푟푟𝑖푒푟푠) Frel (%) = 푋100 퐴푈퐶 (푓푟푒푒 푓푒푛푟푒푡𝑖푛𝑖푑푒 푠푢푠푝푒푛푠𝑖표푛)

Based on the results from single dose PK study, fenrettinide loaded ZPL nanocarrier was further used for steady-state pharmacokinetic studies. Based on the half-life of fenretinide obtained after single dose PK study, the dose interval for multiple dose study was designed. Fenretinide loaded ZPL nanocarrier (20 mg/kg fenretinide equivalent) was orally administered once a day for 4 days. Free fenretinde suspension (20 mg/kg) was administered orally twice a day. Blood samples were collected from the jugular vein at 0,

0.5, 1, 3, and every 3 hours up to 96 hours. All the blood samples were processed as described above and the plasma concentration of fenretinide was determined by HPLC.

Steady state PK parameters such as Css max, Css min, AUCss 0-t were calculated using PK- solution software. Average steady state plasma concentration (Cavg ss) was calculated using the following equation,

퐴푈퐶0−휏 Cavg ss = 휏

Where, τ is the dose interval (12 hours for free fenretinide suspension and 24 hours for fenretinide loaded ZPL nanocarrier).

4.3. Statistical analysis

All the experiments were conducted in triplicate using three independent batches of nanocarriers unless noted otherwise. The data is represented as a mean ± standard deviation. Student t-test and One-way ANOVA was performed to determine statistical significance at p < 0.05. 173

4.4. Results

4.4.1. Development and characterization of fenretinide loaded core-shell nanocarriers

The particle size of the nanocarriers ranged from 100 to 250 nm diameter and had a uniform size distribution as evidenced from the low polydispersity index (0.08 to 0.3)

(Table 27). The core-shell structure of nanocarriers was confirmed from TEM (Fig. 45) and the morphology of fenretinide loaded nanocarriers was similar to NR and LPV loaded nanocarriers (Fig. 15 and Fig. 35). The zeta potential varied from -45.75±0.91 to

32.95±1.48 mV depending on the shell composition and the values are consistent with LPV and NR loaded nanocarriers (Table 8 and Table 22). The encapsulation efficiency (EE) for fenretinide was above 70% in all the nanocarriers with zein-β-casein (ZC) nanoparticles showing the highest encapsulation efficiency (89%) (Table 27). The EE of NR in ZPEG micelles was about 56%, while EE of fenretinide was 77% indicating that the interaction between fenretinide and zein core favors the higher entrapment of fenretinide in ZPEG micelles. The EE of LPV in ZPEG micelles was similar to EE of fenretinide. The EE of fenretinide in all other nanocarriers was similar to EE of NR and LPV (Table 8 and Table

22). The loading efficiency was further optimized based on the ratio of drug to polymer, core to shell, and alcohol concentration. Drug to core polymer ratio was found to be important parameter and by increasing fenretinide from 1 mg to 5 mg resulted in increase in loading efficiency. The loading efficiency (LE) varied from 3 to 8% based on the shell composition (Table 27). The highest loading of fenretinide was obtained with ZPEG micelles, while ZPL nanocarriers showed the lowest loading efficiency. The LE for ZC nanocarriers (7.5%) was similar to ZPEG micelles. Further, LE of fenretinide was about 2- fold higher than LE of LPV in ZPEG micelles (Table 22). 174

The encapsulation of fenretinide in the nanocarriers was confirmed by differential scanning calorimetry (DSC) (Fig. 46). DSC thermogram for free fenretinide showed two sharp endothermic peaks at around 175°C and 180°C, which indicates the presence of two polymorphic forms of fenretinide. (Walkling 1986) The absence of melting peak indicates loss of crystallinity due to entrapment in the nanocarriers.

175

Figure 45: Transmission electron microscopy images of fenretinide loaded nanocarriers. ZC: Zein-β-casein nanoparticles; ZLF: Zein-lactoferrin nanoparticles;

ZPEG: PEGylated zein micelles; ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein- whey protein nanoparticles; ZPL: Zein-pluronic-lecithin nanoparticles. Scale bar is 200 nm.

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Table 27: Characteristics of fenretinide loaded nanocarriers.

Zeta Particle size Characteristics PDI potential EE (%) LE (%) (nm) (mV)

ZC 148.25±0.77 0.099±0.055 -40.95±1.06 89.32±0.091 7.5±0.09

ZLF 240.1±3.53 0.15±0.02 32.95±1.48 70.11±0.49 3.75±0.035

ZLG 272.2±7.63 0.30±0.01 -23.25±1.0 78.51±3.68 3.5±0.037 ZWP 256.7±0.98 0.08±0.03 -36±3.25 74.68±1.04 3.09±0.012 ZPL 219.3±22.88 0.33±0.065 -45.75±0.91 76.05±0.918 3.01±0.23 ZPEG 114.43±2.90 0.34±0.018 -11.35±0.07 77.43±0.47 8.33±0.03 Values represent mean±SD (n=3). EE (%): Encapsulation efficiency in percent; LE (%):

Loading efficiency in percent; ZC: Zein-β-Casein nanoparticles; ZLF: Zein-Lactoferrin nanoparticles; ZPEG: Zein-Polyethylene Glycol micelles; ZPL: Zein-Pluronic-Lecithin nanoparticles; ZLG: Zein-β-Lactoglobulin nanoparticles; ZWP: Zein-Whey Protein isolate nanoparticles.

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Figure 46: DSC analysis of free fenretinide and fenretinide loaded nanocarriers. ZC. Zein-

β-casein nanoparticle, ZLF. Zein-lactoferrin nanoparticle, ZPEG. PEGylated zein micelle,

ZLG. Zein-β-lactoglobulin nanoparticle, ZWP. Zein-whey protein nanoparticle, ZPL.

Zein-pluronic-lecithin nanoparticles. X-axis showing Temperature (°C) and Y-axis showing Heat Flow (W/g). Red line: Free fenretinide; Blue line: Fenretinide loaded nanocarriers; Black line: Blank nanocarriers.

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4.4.2. In vitro release of fenretinide from nanocarriers

The release of fenretinide was sustained both in SGF and SIF for 24 hours (Fig.

47). The release of fenretinide was faster than the release of NR (Fig. 19), while it was similar to the release of LPV (Fig. 37) from ZC nanocarriers in both SGF and SIF. The

ZLG and ZPEG nanocarriers showed the slowest release of fenretinide (<40% released) in both SGF and SIF over 24 hours, which was similar to NR and LPV release from these two nanocarriers. The release profile of fenretinide from ZWP nanocarriers (Fig. 47) was similar to the release of NR and LPV (Fig. 19 and Fig. 37) in both SGF and SIF. About 40 to 50% burst release was observed with ZLF nanocarriers within first one hour in SGF and

SIF (Fig. 47), while less than 10% burst release was observed in case of NR and LPV. The release profile of fenretinide from ZPL nanocarriers was similar NR, while the LPV release was slower both in both SGF and SIF (Fig. 47).

The nanocarriers were stable when incubated with food matrices (milk or applesauce), and less than 30% of fenretinide was released within two hours when transferred to SGF. About 60% of fenretinide was released in 24 hours after transferring from SGF to SIF (Fig. 48). The compatibility with food matrices indicate that the fenretinide loaded nanocarriers can be used as a food sprinkle.

The release kinetics was consistent with release of LPV from nanocarriers (Table

23 and Table 24). The release of fenretinide from the nanocarriers predominantly followed

Peppas model, except for ZLG nanoparticles (Table 28). This indicates that the release of fenretinide from nanocarriers depends on polymer swelling, diffusion of fenretinide and surface erosion of polymer (Sivakumar and Rao 2003). There was slow release of fenretinide in the presence of food matrices and release kinetics (R2-values) indicates that 179 food matrices have less impact on drug release from nanocarriers (Table 29). The release of fenretinide from all the six nanocarriers followed Peppas model indicating that the release is mediated by the diffusion due to surface erosion followed by hydrolytic cleavage or enzymatic degradation of the polymer (Table 28). In SIF, the release of fenretinide from

ZLG nanocarriers was followed by Hixon-Crowell and first order model indicating that the release is dissolution limited. Similar release pattern (Fig. 48) and kinetics (Table 29) was obtained in the sequential release study in food matrices (milk and apple sauce) followed by SGF and SIF indicating that the food matrices had little influence on the release of fenretinide from the nanocarriers. 180

Figure 47: Cumulative percent of fenretinide released from different core-shell nanocarriers in simulated gastric fluid (SGF) and simulated intestinal fluid (SIF). ZC. Zein-β-casein nanoparticle, ZLF. Zein-lactoferrin nanoparticle, ZPEG. PEGylated zein micelle, ZLG.

Zein-β-lactoglobulin nanoparticle, ZWP. Zein-whey protein nanoparticle, ZPL. Zein- pluronic-lecithin nanoparticles. Each value represents mean±SD (n=3).

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Table 28: Fenretinide release kinetics using different models. Formulation (Medium) R2

Peppas Hixson-Crowell Zero Order First Order Higuchi 퐹 퐹 = 100 ∗ (1 − (1 − 푘 C=C0-K0t F=100*(1-exp(- F = k ∗ sqrt(t) = 퐾 ∗ 푡푛 ∗ 푡)^3) k*t)) ZC (SGF) 0.993 0.857 0.878 0.904 0.973 ZC (SIF) 0.991 0.884 0.895 0.922 0.977 ZLF (SGF) 0.993 -0.352 0.376 -0.239 0.313 ZLF (SIF) 0.993 -0.417 0.312 -0.263 0.183 ZPEG (SGF) 0.978 0.607 0.858 0.643 0.941 ZPEG (SIF) 0.972 0.541 0.851 0.588 0.914 ZLG (SGF) 0.987 0.844 0.944 0.856 0.982 ZLG (SIF) 0.981 0.981 0.981 0.981 0.859 ZWP (SGF) 0.981 0.875 0.932 0.883 0.969 ZWP (SIF) 0.988 0.845 0.931 0.868 0.987 ZPL (SGF) 0.986 0.684 0.869 0.741 0.940 ZPL (SIF) 0.974 0.727 0.874 0.798 0.925

SGF-Simulated gastric fluid; SIF-Simulated intestinal fluid; R2 calculated from SigmaPlot 13.0. ZC: Zein-β-casein nanoparticles, ZLF:

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Figure 48: Cumulative percent of fenretinide released from different core-shell nanoparticles in milk (A), apple sauce (B) for 1 hour followed by release in simulated gastric fluid (SGF) for

1 hour and followed by release in simulated intestinal fluid (SIF) up to 24 hours. Values represents mean±SD (n=3).

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Table 29: Fenretinide sequential release kinetics using different models.

Formulation (Medium) R2

Peppas Hixson-Crowell Zero First Order Higuchi 퐹 퐹 Order F F = k ∗ sqrt(t) 푛 = 퐾 ∗ 푡 = 100 ∗ (1 − (1 − 푘 ∗ 푡)^3) C=C0-K0t =100*(1-exp(-k*t)) ZC (milk to SGF to SIF) 0.947 0.745 0.656 0.850 0.790 ZC (apple sauce to SGF to SIF) 0.912 0.707 0.750 0.789 0.897 ZLF (milk to SGF to SIF) 0.793 0.567 0.583 0.665 0.773 ZLF (apple sauce to SGF to SIF) 0.855 0.631 0.695 0.671 0.854 ZPEG (milk to SGF to SIF) 0.998 0.928 0.957 0.946 0.974 ZPEG (apple sauce to SGF to SIF) 0.994 0.995 0.993 0.995 0.850 ZLG (milk to SGF to SIF) 0.976 0.421 0.791 0.465 0.924 ZLG (apple sauce to SGF to SIF) 0.971 0.913 0.941 0.920 0.932 ZWP (milk to SGF to SIF) 0.970 0.884 0.896 0.917 0.962 ZWP (apple sauce to SGF to SIF) 0.954 0.934 0.915 0.948 0.906 ZPL (milk to SGF to SIF) 0.952 0.906 0.851 0.948 0.946 ZPL (apple sauce to SGF to SIF) 0.948 0.941 0.895 0.961 0.904

SGF-Simulated gastric fluid; SIF-Simulated intestinal fluid; R2 calculated from SigmaPlot 13.0. ZC: Zein-β-casein nanoparticles, ZLF:

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4.4.3. Transepithelial permeability of fenretinide loaded nanocarriers across Caco-2 cell monolayers

The nanocarriers enhanced the apparent permeability (Papp) of fenretinide across the Caco-2 cell monolayers (Fig. 49). The Papp was increased from 1 to 36-fold compared

-6 -6 to free fenretinide. The Papp ranged from 2.09x10 to 72.42x10 cm/s depending on the shell composition of the nanocarriers (Fig. 49). ZPL nanocarriers showed the highest permeability, while lowest permeability was observed with ZPEG micelles. The apparent permeability of fenretinide loaded nanocarriers was found to be in the following decreasing rank order ZPL>ZLG>ZC>ZWP>ZLF>ZPEG. The highest Papp values for NR was obtained with ZLG nanocarriers followed by ZPEG, while NR loaded ZC nanocarriers showed the lowest Papp value (section 2.2.2.). However, the rank order was different compared to LPV loaded nanocarriers (section 3.4.3). Unlike fenretinide formulations,

LPV loaded ZPEG micelles showed the highest Papp, while the lowest value was obtained with ZPL nanocarrier (Fig. 49). Overall, from the results showed that the zein nanocarriers significantly enhanced the permeability of fenertinide.

185

Figure 49: Apparent permeability (Papp) of free fenretinide and fenretinide loaded nanocarriers across caco-2 cell monolayers. ZC: Zein-β-casein nanoparticles; ZLF:

Zein-lactoferrin nanoparticles; ZPEG: PEGylated zein micelles; ZLG: Zein-β- lactoglobulin nanoparticles; ZWP: Zein-whey protein nanoparticles; ZPL: Zein- pluronic-lecithin nanoparticles. Each value represents mean±SD (n=3), *P<0.05.

186

4.4.4. Stability of fenretinide in nanocarriers

Fenretinide in ZC and ZLG nanoformulations was chemically stable compared to free fenretinide in the solid state when tested for three months. Around 45% of fenretinide degraded in free-form, while more than 90% fenretinide remained stable after encapsulation in nanocarriers (Fig. 50a). The particle size of fenretinide loaded ZC nanocarriers increased slightly after two months, while the particle size of fenretinide loaded ZLG nanocarriers increased by 2-fold (Fig. 50b). The PDI for both ZC and ZLG nanocarriers increased after two months (Fig. 50c). The zeta potential for ZC nanocarrier changed gradually from -55 mV to -35 mV, while the charge of ZLG nanocarrier changed from -40 mV to slightly positive (+4.0 mV) (Fig. 50d). Particles with zeta potential values around ±30 mV is reported to be stable for overcoming particle aggregation (Bhattacharjee

2016). The change of zeta potential is consistent with the aggregation of ZLG nanocarriers.

Similar results were observed with LPV loaded ZLG nanocarrier (Fig. 39). Overall, the stability studied indicate that the zein based nanocarriers can enhance the chemical stability of fenertinide.

187

Figure 50: Solid state stability of free fenretinide, fenretinide loaded Zein-β-casein and zein-β-lactoglobulin nanocarriers.

Nanocarriers and free drug were kept in constant climate chamber at 30°C and 65% RH for 3 months. Each value represents mean±SD

(n=3).

188

4.4.5. In vivo pharmacokinetics

Based on the results from in vitro permeability studies, ZC, ZLG, ZWP, and ZPL nanocarriers were selected for in vivo pharmacokinetic studies in rat. Free fenretinide suspension showed aCmax of 0.21 μg/mL at 3 hours (Tmax). ZPL nanocarrier showed the highest Cmax (0.61 μg/mL) of fenretinide at 6 hours (Tmax), while fenretinide loaded ZC nanocarrier showed the lowest Cmax (0.23 μg/mL) at the same Tmax (Fig. 51). ZLG and

ZWP nanocarriers showed a Cmax of fenretinide of 0.49 and 0.58 μg/mL respectively. Free fenretinide showed a Cmax of 0.21 μg/mL at 3 hours (Tmax). The AUC of fenretinide was significantly increased with ZWP nanocarriers (~ 8-fold), whereas the AUC for ZLG, ZPL and ZC nanocarriers were about 6-, 5- and 3-fold higher compared to free fenretinide suspension (Table 30). All the nanocarriers under investigation increased the elimination half-life (t1/2) of fenretinide. The t1/2 was increased by 8-, 6-, 5- and 4-fold with ZC, ZLG,

ZWP and ZPL nanocarriers respectively (Table 30). Overall, the relative oral bioavailability (Frel%) of fenretinide in nanocarriers was increased significantly with all the nanocarriers. ZWP nanocarriers enhanced the oral bioavailability of fenretinide by 7-fold followed by ZLG (6-fold), ZPL (5-fold) and ZC (3-fold) nanocarriers.

189

Figure 51: Plasma concentration of free fenretinide and fenretinide loaded ZC, ZLG,

ZWP, and ZPL nanocarriers after oral administration to rats. Each value represents mean±SD, (n=3).

190

Table 30: PK parameters of free fenretinide and fenretinide loaded nanocarriers after oral delivery in rats.

Fenretinide suspension ZC-Fenretinide ZLG-Fenretinide ZWP-Fenretinide ZPL-Fenretinide

C (μg/mL) max 0.22±0.0087 0.23±0.005* 0.54±0.001* 0.58±0.01* 0.60±0.02* T (h) 6.00±0.00 max 3.00±0.00 6.00±0.00 6.00±0.00 6.0±0.00

MRT (h) 4.37±0.08 16.61±7.09 11.28±0.53 9.07±0.04 8.49±0.21

-1 Ke (h ) 0.71±0.60 0.08±0.04 0.09±0.04 0.09±0.02 0.12±0.04 t (h) 1/2 1.50±0.06 12.90±6.49* 9.82±3.38* 7.84±2.11* 6.17±1.93*

AUC (μg-h/mL) (0-inf) 1.11±0.11 3.26±0.74* 7.03±0.47* 8.82±3.23* 5.57±0.07*

F (% rel) -- 294.53±66.75* 633.51±42.68* 673.37±12.08* 502.19±6.58*

Each value represents mean±SD (n=3), *P<0.05 compared to fenretinide suspension. Cmax: Maximum plasma concentration; Tmax: Time to reach maximum plasma concentration; AUC: Area under plasma concentration-time curve; MRT: Mean residence time; t1/2:

Elimination half-life; F (% rel): Percent relative bioavailability. 191

Based on results from single dose PK study (Fig. 52), free fenretinide was administered twice a day, while fenretinide loaded ZPL nanocarriers was given once a day.

Results from multiple-dose PK study show that ZPL nanocarriers increased the steady state plasma concentration of fenertinide by 5-fold (Fig. 52). It is important to note that the higher levels achieved with ZPL nanocarriers was achieved with a once-a-day dosing as opposed twice-a-day dosing with free fenertinide. Around 1.5-fold higher Cmax of fenretinide was achieved at steady state with ZPL nanocarriers. However, there was no significant change in Cmax for free fenretinide suspension after multiple dose. (Table 31).

192

Figure 52: Plasma profile of free fenretinide and ZPL-fenretinide nanocarriers after oral administration of 20 mg/Kg fenretinide for 4 days. Free fenretinide administered twice a day, while fenretinide loaded ZPL nanoparticles administered once a day. Each value represents mean±SD. (n=3).

193

Table 31: Steady state PK parameters of free fenretinide and fenretinide loaded ZPL- nanocarriers after oral delivery in rats.

Fenretinide suspension ZPL-fenretinide

Cmax-ss (µg/mL) 0.33±0.01 0.95±0.13*

Cavg-ss (µg/mL) 0.20±0.06 0.66±0.05*

Cmin-ss (µg/mL) 0.11±0.04 0.13±0.03*

Tmax-ss (hrs) 51.00±0.00 54.00±0.00*

Each value represents mean±SD (n=3), *P<0.05 compared to fenretinide suspension. ZPL.

Zein-pluronic-lecithin nanoparticles; Cmax-ss. Maximum concentration during dosing interval at steady state; Cmin-ss. Minimum concentration during dosing interval at steady state; Cavg-ss. Average plasma drug concentration at steady state t. Each value represents mean±SD (n=3).

194

At the end of multiple dose PK study, rats were sacrificed and different organs were collected to deterrmine the distribution of fenretinide in the body. Results show that significantly higher fenretinide was distributed in liver and kidney compared to other organs such as brain, lung and spleen (Fig. 53). In general, concentration of fenretinide in different organs were significantly higher than free fenretinide suspension which is consistent with plasma concentration of fenretinide.

Figure 53: Organ distribution of free fenretinide and ZPL-fenretinide nanocarriers after

oral administration of 20 mg/Kg fenretinide in rats for 4 days. Free fenretinide

administered twice a day, while fenretinide loaded ZPL nanoparticles administered

once a day. Each value represents mean±SD. (n=3), P<0.05.

195

4.5. Discussion

The clinical investigation of fenretinide isfocused on its anticancer activity especially against pediatric neuroblastoma (Children's Oncology et al. 2006), oral leukoplakia (Lippman et al. 2006), and ovarian cancer (Garcia. A. A. 2004). However, fenretinide is reported to have low and variable bioavailability and dose escalation is required to achieve reasonable therapeutic concentration. One important impediment in the clinical application of fenretinide is the lack of a suitable delivery system to achieve high and sustained therapeutic concentration. A corn-oil capsule has been used and achieved around 5 µg/mL blood concentration of fenretinide with a daily dose of 4000 mg/m2 of fenretinide (Garaventa et al. 2003). Although a lipid formulation of fenretinide (LYM-X-

SORB) was reported to achieve 3- to 7-fold higher plasma level of fenretinide compared to corn-oil capsules, the safety of the lipid matrix in pediatrics especially infant patients is yet to be clarified (Maurer et al. 2007).

Fenretinide has poor oral bioavailability due to its poor water solubility and membrane permeability and poor chemical stability. The hydrophobic fenretinide was encapsulated in the zein core, while the external hydrophilic shell was used to increase the water solubility and permeability through the gastrointestinal membrane. In addition, the core-shell nanocarriers sustained the drug release, thus reducing the dose and dosing frequency in pediatric patients. The long-term stability study demonstrated the enhanced chemical stability of the zein nanoformulation.

Apparent permeability coefficient (Papp) of fenretinide across Caco-2 cell monolayers was also significantly increased using nanocarriers compared with free fenretinide. The uptake of nanocarriers in Caco-2 cells was predominantly by non-specific 196 endocytosis. Lecithin favors the interaction with lipophilic cell membrane and results in higher cell uptake (Zhirnov et al. 2005). In addition, pluronic can inhibit P-gp and evade the P-gp mediated efflux (Wei et al. 2013). Both lecithin and pluronic in ZPL nanoparticles contributed to significantly higher permeability across cell monolayers. However, apparent permeability for all other nanocarriers (except ZPL) was comparable to free fenretinide in the first two hours, while a significant difference was observed at four hours indicating that of the cellular uptake and subsequent transport and release play an important role in the higher permeability observed with ZPL nanocarriers.

Lower plasma concentration of fenretinide with ZC nanocarrier was obtained can be attributed to thefaster release of fenretinide in SGF and SIF. All other tested nanocarriers

(ZLG, ZWP, and ZPL) significantly enhanced Cmax, AUC, t1/2 and oral bioavailability of fenretinide compared to fenretinide oral suspension. The enhanced membrane permeability and intestinal epithelial cell uptake contributed to the increased absorption and bioavailability of fenretinide using ZLG, ZWP, and ZPL nanocarriers. About 3-fold higher steady-state plasma concentration of fenreitnide was obtained using ZPL nanocarrier compared to free fenretinide suggests that lecithin composition in shell may favor the uptake by lymphatic systems in intestine (Randolph and Miller 2014). However, further studies are required to confirm the absorption mechanism of ZPL nanocarriers. We used fenretinide at a dose of 20 mg/kg body weight of rat, which is 18-times lower dose than reported for the lipid formulation of fenretinide (Maurer et al. 2007). Reported dose of fenretinide with lipid formulation used as divided dose (twice a day) and ZPL nanocarriers can be administered once day which is also advantageous in reducing dosing frequency

(Maurer et al. 2007).. Our results demonstrated that fenretinide loaded nanocarriers can 197

achieve up to 0.6 μg/mL plasma concentration of fenretinide (Cmax), which is 13-fold less than maximum plasma concentration reported for the lipid formulation with same dosing frequency in mice (Maurer et al. 2007). Since the ZPL nanoformulation was able to significantly increase the fenretinide concentration in the various organs, this can be used for different types of cancers. A higher dose of ZPL nanoformulation is expected to achieve equivalent or higher plasma levels compared to the lipid formulation. In addition, the use of food-grade biopolymers offers significant advantages for developing a pediatric formulation as a food-sprinkle. Further, the sustained release of fenertinide from ZPL nanocarriers can reduce the dose and dosing frequency, thus improving the safety and compliance in pediatric patients.

4.6. Conclusion

The present study demonstrated that zein based core-shell nanocarriers can be used to enhance the oral bioavailability of fenretinide. In vitro studies showed that core-shell nanocarriers significantly improved the stability and aqueous solubility/dispersibility of fenretinide, sustained the release of fenretinide, and increased membrane permeability. The compatibility with food matrices (milk and applesauce) indicate that fenretinide loaded nanocarriers can be used as a food sprinkle, especially for pediatric patients. In vivo pharmacokinetic study demonstrated that the oral bioavailability of fenretinide increased from 3- to 7-fold using zein nanocarriers. Results from this multiple dose pharmacokinetic study demonstrated that ZPL nanocarrier can be used to develop a once-a day orally bioavailable formulation of fenretinide. Overall, the findings from this study can be used to develop a safe, effective, and food compatible oral pediatric formulaton of fenretinide. 198

5. Summary

Six different core-shell nanocarriers were developed using zein (corn protein) as the core and milk protein (casein, lactoferrin, lactoglobulin, whey protein isolate) or PEG or pluronic-lecithin as the shell. The shell structure-function relationship of zein-based nanocarriers were evaluated in-vitro and in-vivo. The results were used to develop orally bioavailable formulation for two challenging drug molecules. Zein nanocarriers were used to encapsulate lopinavir, an antiretroviral drug, and fenretinide, an investigational new chemical entity. Table 32 is a summary of the results from this dissertation and compares the functional performance of the different zein-based nanocarriers. The particle size of drug-loaded nanocarriers was 100 to 250 nm diameter with uniform size distribution. The zeta potential varied based on shell composition. All the carriers were non-immunogenic and safe for oral administration. Nanocarriers showed above 70% encapsulation efficiency with 3 to 8% drug loading efficiency. Nanocarriers sustained the release of drug in simulated gastric fluid, simulated intestinal fluid and in food matrices signifies the potential of using as food sprinkle and mask the taste of bitter drugs. The release was mainly dependent on shell the composition, physicochemical properties of encapsulated molecule, and nature of the release of the medium. As shown in Table 32, ZC and ZPL ranked high in terms of sustaining drug release. However, in presence of food matrices, these two systems ranked lower than the other nanoformulations. Among the six formulations,

ZPEG, ZPL and ZLG showed relatively higher permeability than the other three formulations. Further, the ZPEG also has P-gp inhibitory activity, suggesting the potential use of this nanocarriers for enhancing the oral bioavailability of drugs that are substrates for P-gp efflux pump. This was evident from the enhanced oral bioavailability of LPV, 199 which was comparable to the oral bioavailability commercial LPV/r liquid formulation. On the other hand, ZLG and ZWP have high bioadhesive property and may be suitable to enhance the oral absorption of drugs by increasing the drug retention in the GI tract. These carriers may also be used for developing colon targeted delivery systems. Although the dissertation provides a general structure-function relationship for developing zein based nanocarriers, the findings from this dissertation suggest that the zein nanocarriers have to be customized based on the drug’s physicochemical properties, the functional properties of the shell and the disease type. To this end, depending on the physicochemical properties of the drug, one or more of the functional characteristics of the zein-based nanocarriers contributes to the enhanced oral bioavailability. In case of LPV, the inhibition of P-gp and

CYP3A4 metabolism are the primary determinants of oral bioavailability. On the other hand, in case of fenertinide, the enhanced memberane permeability and sustained release characteristics are important determinants for enhanced oral bioavailbility. Overall, the results from this dissertation provides a roadmap for rational development of zein-based nanocarriers in particular and protein based nanocarrier in general for oral drug delivery applications.

200

Table 32: Comparison of zein-based nanocarriers for the feasibility of using for oral drug delivery applications.

Characteristics ZC ZLF ZPEG ZPL ZLG ZWP

Sustained release +++ + ++ +++ ++ ++

Inhibition of P-gp efflux + ++ +++ +++ + + Sequential release (Food matrix, SGF ++ +++ +++ ++ +++ +++ and SIF) Transepithelial permeability (Caco-2 ++ ++ +++ +++ +++ ++ monolayer)

Gastrointestinal Retention ++ + + ++ +++ +++

Bioadhesive/mucoadhesive property ++ ++ ++ ++ +++ +++

Oral Immunogenicity +++ +++ +++ +++ +++ +++

Oral bioavailability of lopinavir ND ND +++ ND ++ ++

Oral bioavailability of fenretinide + ND ND +++ +++ +++ (+++) Excellent; (++) good; (+) fair. ZC: Zein-β-casein nanoparticles; ZLF: Zein- lactoferrin nanoparticles; ZPEG: PEGylated zein micelle; ZPL: Zein-pluronic-lecithin nanoparticles; ZLG: Zein-β-lactoglobulin nanoparticles; ZWP: Zein-whey protein isolate nanoparticles. ND: Not done.

201

6. FUTURE STUDIES Findings from this dissertation open several new opportunities to expand the application of these nanocarriers for the delivery of other drugs. Future studies should include the following:

• The findings from this study should be extended to BCS class II drugs (low

solubility and high permeability) and BCS class III drugs (highly soluble and low

permeability).

• To understand the role of zein in core-shell nanocarriers, future studies should

include zein nanoparticles as a control.

• Studies should evaluate the taste masking ability of these nanocarriers by

encapsulating drugs with a bitter taste. Future studies should also focus testing the

compatibility with additional food matrices based on preferences for different age

group of pediatric patients.

• Mechanistic studies should be performed to understand the segmental absorption

in the gastrointestinal tract. Further studies should be performed to understand the

mechanism involved and identifying the major site of absorption.

• The ability of the nanocarriers to target M-cells or mesenteric lymph nodes should

be explored to understand the potential of these nanocarriers for the treatment of

metastatic cancer and HIV infection.

• Future studies should confirm the findings from this dissertation by testing the

formulations in appropriate pediatric animal models such as a juvenile pig model.

• Future studies should also focus on testing the efficacy of these formulations in

suitable animal models.

202

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