Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in the Lung

TARGETING DELIVERY OF MAGNETIC AEROSOL PARTICLES TO SPECIFIC REGIONS IN THE LUNG

Anusmriti Ghosh B.Sc. (Mathematics), M.Sc. (Applied Mathematics)

Submitted in fulfilment of the requirements for the degree of Master of Philosophy (Research)

IF80

School of Chemistry, Physics and Mechanical Engineering Science and Engineering Faculty Queensland University of Technology 2018

KEYWORDS

Airflow; Deposition; Deposition Concentration; Deposition Efficiency; Drug Delivery; Discrete Phase Model (DPM); Euler-Lagrange Method; Flow Rate Distribution; 2-generation Lung Model; Lung Airway; Magnetic Number; Magnetic Field; Magneto Hydro Dynamics Model (MHD); Micro Particle; Monodisperse Particle; Nano Particle; Numerical Modelling; Particle Transport; Pharmaceutical Aerosol particle; Targeted Drug Delivery; Velocity Contour.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung i ABSTRACT

The inhalation of aerosol is a substantiated technique for drug delivery in the lung.

Aerosolised drug inhalation plays an important role in oral and arterial routes of delivery for the treatment of respiratory diseases. A precise understanding of the aerosolised drug transport and deposition in the specific site of the lung is important as the standard dose deposit is 88% of the drug in the unwanted location of the lung.

All of the published in silico, in vivo and in vitro studies have increased the knowledge of the aerosol particle transport and deposition in the human respiratory system.

However, the understanding of the pharmaceutical particle deposition in the targeted region of the lung airways is still not clear. Detailed knowledge of targeting magnetic particle transport and deposition in the specific region is important, to improve the efficiency of the delivered drug and to minimise the unwanted side effects. The present study is the first-ever approach to simulate magnetic particle transport and deposition in the specific region of a 2-generation lung model by considering two different magnetic field positions. The symmetrically explicit, 2-generation lung model is generated from the geometry and mesh generation software of ANSYS 18.0. A comprehensive size- and shape-specific uniform aerosolised micro and nano-particle transport and deposition study is performed for different magnetic field positions, physical conditions and magnetic numbers for this present model. Uniform aerosolised micro and nano particle transport and deposition in the specific region of the lung airways will be reported by conducting turbulence k–ω low Reynolds number simulation. Moreover, the Magneto hydrodynamics (MHD) model is implemented and

ANSYS Fluent 18.0 solver is used for targeting drug particle delivery. The aerosolised magnetic micro-particles are navigated to the targeted cell under the influence of an

ii Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung external magnetic force, which is applied in two different positions of the lung airways.

The numerical results reveal that most particles are deposited at the targeted positions and show a new deposition technique for the lung model, which could help the targeted drug delivery in the specific region of respiratory airways. The magnetic nanoparticle transport and deposition in the specific region of the lung are investigated for a wide range of diameters (1≤nm≤500) and different flow rates. A comprehensive magnetic targeting delivery is calculated throughout the 2-generation model for two different magnetic field positions, which might be helpful for the therapeutic purpose of the lung disease patient. The numerical study performed comprehensive deposition in the targeted position. The deposition efficiency in the specific region of the lung is different for different magnetic numbers, magnetic field positions and breathing conditions, which could help the health risk assessment of respiratory diseases and eventually could help the targeted drug delivery system. The findings of the present study will help in developing better efficient drug delivery systems in affected regions of the lung airways. This process will also be cost-effective, due to systemic drug distribution in the specific region of the lung.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung iii LIST OF PUBLICATIONS

Journal Paper:

1. Pharmaceutical Aerosol Transport in the Targeted Region of Human Lung Airways due to External Magnetic Field Effect. (To be submitted to Journal of Aerosol

Science).

2. Targeted Drug Delivery of Magnetic Nano Particle in the Specific Region of Lung.

(To be submitted to Aerosol Science and Technology).

Peer Review Conference Paper:

1. Saha, S.C., Ghosh, Anusmriti, Islam, M.S., 2018. Pharmaceutical aerosol transport in the targeted position of human lung by external magnetic field. The 3rd Australian

Conference on Computational Mechanics (ACCM-3), Deakin University, Waurn Ponds

Campus, Melbourne, Australia, 12-14 February. (Abstract Only)

iv Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung

TABLE OF CONTENTS

KEYWORDS ...... i ABSTRACT ...... ii LIST OF PUBLICATIONS ...... iv TABLE OF CONTENTS ...... v LIST OF FIGURES ...... vii LIST OF TABLES ...... xi LIST OF ABBREVIATIONS ...... xii STATEMENT OF ORIGINAL AUTHORSHIP ...... xiii Chapter 1 : INTRODUCTION ...... 1 1.1 BACKGROUND ...... 2 1.2 AIMS ...... 2 1.3 OBJECTIVES ...... 3 1.4 SIGNIFICANCE, SCOPE AND INNOVATION...... 3 1.5 THESIS OUTLINE ...... 4 Chapter 2 : LITERATURE REVIEW ...... 6 2.1 BIOLOGICAL ASPECTS OF THE LUNG ...... 6 2.2 DEPOSITION MECHANISM ...... 11 2.3 TARGETED DRUG DELIVERY ...... 12 2.3.1 PASSIVE TARGETING ...... 13 2.3.2 ACTIVE TARGETING ...... 14 2.4 MAGNETIC MICRO PARTICLE TRANSPORT AND DEPOSITION ...... 17 2.5 MAGNETIC NANOPARTICLE TRANSPORT AND DEPOSITION...... 19 2.6 SUMMARY AND IMPLICATIONS ...... 22 Chapter 3 : METHODOLOGY ...... 24 3.1 ASSUMPTIONS FOR NUMERICAL SIMULATIONS ...... 26 3.2 NUMERICAL METHODOLOGY FOR CASE STUDY 1 ...... 27 3.2.1 DRAG FORCE ...... 28 3.2.2 MAGNETIC FORCE ...... 29 3.2.2.1 EXTERNALLY IMPOSED MAGNETIC FIELD GENERATED IN NON- CONDUCTING MEDIA ...... 30 3.3 NUMERICAL METHODOLOGY FOR CASE STUDY 2 ...... 31 Chapter 4 : RESULTS AND DISCUSSION ...... 36 4.1 CASE STUDY 1: MAGNETIC MICROPARTICLE ...... 36 4.1.1 COMPUTATIONAL DOMAIN AND MESH GENERATION ...... 36 4.1.2 GRID INDEPENDENCE TEST ...... 38

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung v 4.1.3 MODEL VALIDATION ...... 39 4.1.4 POST PROCESSING RESULTS FOR MAGNETIC MICRO-PARTICLE ...... 43 4.2 CASE STUDY 2: MAGNETIC NANOPARTICLE ...... 56 4.2.1 COMPUTATIONAL DOMAIN AND MESH GENERATION: ...... 56 4.2.2 GRID INDEPENDENCE TEST: ...... 57 4.2.3 MODEL VALIDATION:...... 57 4.2.4 POST PROCESSING RESULTS FOR MAGNETIC NANOPARTICLE ...... 59 Chapter 5 : CONCLUSIONS ...... 74 5.1 CONCLUSIONS ...... 74 5.2 LIMITATIONS AND FUTURE STUDY ...... 76 BIBLIOGRAPHY ...... 77 APPENDICES ...... 83 A: CASE STUDY 1 (MAGNETIC MICRO PARTICLE) ...... 83 A1: MESH GENERATION ...... 83 A2: FLOW RATES EFFECT ...... 84 A3: PARTICLE DIAMETER EFFECT ...... 85 A4: MAGNETIC FIELD (POSITION) EFFECT ...... 86 B: CASE STUDY 2 (MAGNETIC NANO PARTICLE) ...... 87 B1: EFFECT OF FLOW RATES ON PARTICLE TD FOR MAGNETIC FIELD POSITION1, MN=2.5 AND DIFFERENT PARTICLE DIAMETER ...... 87 B2: EFFECT OF FLOW RATES ON PARTICLE TD FOR MAGNETIC FIELD POSITION 2, MN=2.5 AND DIFFERENT PARTICLE DIAMETE ...... 88 B3: PARTICLE DIAMETER AND MAGNETIC POSITION EFFECT FOR MN=0.18 AND 15 LPM FLOW RATES ...... 89 B4: DEPOSITION EFFICIENCY HISTOGRAM FOR MAGNETIC FIELD POSITION 1 ...... 90 B5: DEPOSITION EFFICIENCY HISTOGRAM FOR MAGNETIC FIELD POSITION 2 ...... 90 B6: REGIONAL DEPOSITION EFFICIENCY FOR 15 LPM AND MN 0.181 ...... 91 B7: REGIONAL DEPOSITION EFFICIENCY FOR 15 LPM AND MN 1.5 ...... 92 B8: STATIC PRESSURE FOR POSITION 2 ...... 92

vi Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung LIST OF FIGURES

Figure 1.1 Flowchart of the present thesis...... 5 Figure 2.1 Human respiratory system ("Human body. Reaspiratory system diagram. Retrieved April 6, 2017, from http://www.buzzle.com/images/diagrams/human-body/respiratorysystem-diagram.jpg," 2017)...... 7 Figure 2.2 (a) Structural design of lung components (b) The segmented view of the computational domain (Rahimi-Gorji et al., 2016)...... 8 Figure 2.3 Picture of human lung with alveoli. (Matthew Hoffman, 2014)...... 9 Figure 2.4 Particle size that enters into the respiratory system ("Respiratory system. Retrieved April 6, 2017, from http://www.livescience.com/22616-respiratorysystem.html,") (This figure has been modified.) ...... 10 Figure 2.5 Action of nanomagnetosols Mechanism (Plank, 2008)...... 14 Figure 2.6 Schematic representation of magnetic nanoparticle microcomposites (MnMs) by pulmonary delivery (Stocke et al., 2015)...... 16 Figure 2.7 Advantages and challenges of pulmonary drug delivery (Kuzmov & Minko, 2015)...... 17 Figure 3.1: Framework of the present thesis...... 25 Figure 4.1 (a) Anterior view of the 2-generation mesh with 179,660 unstructured cells, (b) first bifurcation, (c) inlet mesh, (d) inflation layer mesh near to the wall, (e) terminal bronchioles mesh, (f) outlet mesh of 2 generation lung model...... 37 Figure 4.2 Maximum velocity grid convergence ...... 39 Figure 4.3 Present simulated particle deposition efficiency comparison with the experimental data of (Cheng et al., 2010) and (Kleinstreuer et al., 2008)...... 40 Figure 4.4 Particle deposition fraction comparison between the present simulation data with the experimental different data sets of (Kleinstreuer et al., 2008), Chen et al.,(1999), (Lippmann & Albert, 1969), (Chan & Lippmann, 1980), Foord et al., (1978), (Stahlhofen et al., 1980) , Stahlhofen et al., (1983), (Emmett et al., 1982) and (Bowes & Swift, 1989)...... 40 Figure 4.5 Geometry specification. (Magnet position 2 has been set on the left lung) ...... 41 Figure 4.6 Particle deposition efficiency using magnetic position comparison between the present simulation and experimental data sets of (Cohen, 2009), (Haverkort, 2008), and (Oveis Pourmehran et al., 2016) ...... 42 Figure 4.7 Velocity profiles in the symmetric bifurcation airway model for steady inhalation with Q= 60 lpm. (a) Contour of velocity magnitude

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung vii for (a) 2- generation lung model; (b ) Left outlet 1and (c) Left outlet 2; (d) Right outlet 1and (e) Right outlet 2...... 43 Figure 4.8: Contour of Magnetic source for Mn=2.5T (a) position 1; (b) position 2. Particle traces coloured by particle residence time for (c) Position 1; (d) Position 2...... 44 Figure 4.9 Turbulent kinetic energy of magnitude contour for (a) position 2; (b) position 1; Particle traces coloured by (c) velocity magnitude for position 1; (d) velocity magnitude for position 2...... 46 Figure 4.10 Effect of flow rates on particle transport outline and DE (%) for Position 2, 푑푝 = 4 휇푚, 푀푛 = 2.5 푇, (a) 15 lpm; (b) 30 lpm; (c) 60 lpm; (d) Total deposition efficiency in terms of flow rates...... 47 Figure 4.11 Particle diameter effect on particle transport outline and DE (%) for position 2, 푀푛 = 2.5 푇, Q=60 lpm (a) 푑푝 = 2 휇푚; (b) 푑푝 = 4 휇푚; (c) 푑푝 = 6 휇푚; (d) overall deposition efficiency...... 49 Figure 4.12: Magnetic number effect (Flux value) on particle transport outline and DE (%) for Position 2, 푑푝 = 4 휇푚, Q=60lpm,(a) 푀푛 = 0.181T;(b)푀푛 = 2.5 T; (c)푀푛 = 3 T; (d) deposition efficiency for magnetic number...... 51 Figure 4.13: Effect of source position of magnet on particle transport outline and DE (%) for 푑푝 = 4 휇푚, Q=30 lpm, 푀푛 = 2.5 푇, (a) Position 1; (b) Position 2;(c) deposition efficiency for magnetic source position...... 53 Figure 4.14: Local deposition efficiency for (a) flow rates; (b) Particle diameter; (c) Magnetic number effect; (d) Magnetic source position. Generation 1 (g1), Left Generation 2 (lg2); Right Generation 2 (rg2)...... 54 Figure 4.15: (a) Anterior view of the 2-generation mesh with 0.54 million unstructured cells, (b) interior view and inflation layer mesh near to the wall, (c) inlet mesh, (d) outlet mesh of 2-generation lung model...... 56 Figure 4.16: Maximum pressure grid convergence ...... 57 Figure 4.17. Nano-particle DE comparison with the experimental data of Kim (2002) and the CFD results of Zhang and Kleinstreuer (2004) and (Islam et al., 2017), in a double bifurcation model (G3-G5), (a) first bifurcation, and (b) second bifurcation...... 58 Figure 4.18 Deposition fraction (DF) of Nano-particle comparison with the CFD results of Zhang and Kleinstreuer (2004) across different bifurcation for 30 lpm flow rates in the bifurcation airway model...... 58 Figure 4.19: Geometry specification of 2-generation model (Magnet position 2 has been set on the right lung)...... 59 Figure 4.20: Effect of Flow Rates on particle transport outline for position 1 and position 2, Mn=2.5 T, dp=1-nm, (a) 7.5 lpm for position 1; (b) 7.5 lpm for position 2; (c) 9 lpm for position 1; (d) 9 lpm for position 2; (e) 15 lpm for position 1; (f) 15 lpm for position 2; (g) Overall deposition efficiency...... 60

viii Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung Figure 4.21: Effect of magnetic number on particle transport outline for Position 1 and position 2, 7.5 lpm, dp=1-nm, (a) Mn=0.181 T for position 1; (b) Mn=0.181T for position 2 ; (c) Mn=1.5 T for position 1; (d) Mn=1.5 T for position 2; (e) Mn=2.5 T for position 1; (f) Mn=2.5 T for position 2; (g) Overall deposition efficiency for magnetic position 1 and magnetic position 2...... 62 Figure 4.22: Particle Traces Coloured by Turbulent Kinetic Energy (k) (푚2/푆2) for 60 lpm, Mn=2.5 T and magnet position 2, (a) 1- nm; (b) 10- nm; (c) 50- nm; (d) 100- nm; (e) 500- nm...... 64 Figure 4.23: Particle Traces Coloured by particle residence time at magnetic position 2 for 60 lpm and Mn=2.5 T (a) 1- nm; (b) 10- nm; (c) 50- nm; (d) 100- nm; (e) 500- nm...... 66 Figure 4.24: Deposition Efficiency comparisons for nano particles of various diameter and flow rates at position 1 and position 2 for magnetic number 2.5 T...... 68 Figure 4.25: Deposition Efficiency comparisons for nano particles of various diameters and magnetic number at position 1 and position 2 for 15 lpm flow rates...... 70 Figure 4.26: Regional particle deposition efficiency in each zone at different particle sizes, magnet position, magnetic number 2.5 T and inhalation rates. Generation 1 (g1), Left Generation 2 (lg2), Right Generation 2 (rg2)...... 72 Figure A.1: (a) interior view of the 2-generation mesh...... 83 Figure A.2: Effect of flow rates on particle transport outline and DE (%) for Position 2, 푑푝 = 4 휇푚, 푀푛 = 0.25 푇 , (a) 15 lpm; (b) 30 lpm; (c) 60 lpm; (d) Total deposition efficiency in terms of flow rates...... 84 Figure A.3: Effect of particle diameter on particle transport outline and DE (%) for Position 2, 푀푛 = 0.25 푇, Q=60 lpm (a) 푑푝 = 2 휇푚; (b) 푑푝 = 4 휇푚; (c) 푑푝 = 6 휇푚; (d) deposition efficiency...... 85 Figure A.4: Effect of magnetic field on particle TD outline for (a) position 1; (b) particle traces by particle id for magnet position 2...... 86 Figure A.5: Magnitude of 퐵 (magnetic flux density) vector for position 2...... 86 Figure A.6: Effect of flow rates on particle transport outline for particle diameter 1-nm, 10- nm, 50-nm,100-nm,500-nm, position 1, Mn=2.5T, (a) 1-nm for 7.5 lpm; (b) 10-nm for 7.5 lpm; (c) 50-nm for 7.5 lpm; (d) 100-nm for 7.5 lpm; (e) 500-nm for 7.5 lpm; (f) 1-nm for 9 lpm; (g) 10-nm for 9 lpm; (h) 50-nm for 9 lpm; (i) 100-nm for 9 lpm; (j) 500-nm for 9 lpm; (k) 1-nm for 15 lpm; (l) 10-nm for 15 lpm; (m) 50- nm for 15 lpm; (n) 100-nm for 15 lpm; (o) 500-nm for 15 lpm; (p) 1- nm for 60 lpm; (q) 10-nm for 60 lpm; (r) 50-nm for 60 lpm; (s) 100- nm for 60 lpm; (t) 500-nm for 60 lpm...... 87 Figure A.7: Effect of flow rates on particle transport outline for particle diameter 1-nm, 10- nm, 50-nm,100-nm,500-nm, position 2, Mn=2.5T, (a) 1-nm for 7.5 lpm; (b) 10-nm for 7.5 lpm; (c) 50-nm for 7.5 lpm; (d) 100-nm for 7.5 lpm; (e) 500-nm for 7.5 lpm; (f) 1-nm for 9 lpm;

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung ix (g) 10-nm for 9 lpm; (h) 50-nm for 9 lpm; (i) 100-nm for 9 lpm; (j) 500-nm for 9 lpm; (k) 1-nm for 15 lpm; (l) 10-nm for 15 lpm; (m) 50- nm for 15 lpm; (n) 100-nm for 15 lpm; (o) 500-nm for 15 lpm; (p) 1- nm for 60 lpm; (q) 10-nm for 60 lpm; (r) 50-nm for 60 lpm; (s) 100- nm for 60 lpm; (t) 500-nm for 60 lpm...... 88 Figure A.8: Effect of particle diameter and magnet position on particle transport outline Mn= 0.18T, flow rates 15 lpm, (a) 1-nm for position 1; (b) 1-nm for position 2; (c) 10-nm for position 1; (d) 10-nm for position 2; (e) 50-nm for position 1; (f) 50-nm for position 2...... 89 Figure A.9: Deposition Efficiency comparisons for NPs of various diameter and flow rates at position 1 for magnetic number 2.5T...... 90 Figure A.10: Deposition Efficiency comparisons for NPs of various diameter and flow rates at position 2 for magnetic number 2.5T...... 90 Figure A.11: Regional particle deposition efficiency in each zone at different particle sizes, magnet position, magnetic number 0.181T and 15 lpm flow rates...... 91 Figure A.12: Regional particle deposition efficiency in each zone at different particle sizes, magnet position, magnetic number 1.5 T and 15 lpm flow rates...... 92 Figure A.13: Static pressure for position 2, Mn=2.5 T, 1-nm, 9 lpm...... 92

x Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung LIST OF TABLES

Table 4.1. Respiratory particle TD comparisons for 1-, 50-, 100- and 500-nm diameter particles as a function of different breathing airflow rates and magnetic number 2.5T.Posi 1(position 1), Posi 2 (position 2)...... 68 Table 4.2. Respiratory particle TD comparisons at two different targeted positions for 0.181 T, 1.5 T, and 2.5 T magnetic number as a function of 15lpm breathing airflow rates and 1-, 50-, 100- and 500-nm diameter particle...... 70

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung xi LIST OF ABBREVIATIONS

CFD Computational Fluid Dynamic

CF Cystic Fibrosis

COPD Chronic Obstructive Pulmonary Disease

CT Computerized Tomography

DDS Drug Delivery Systems

DE Deposition Efficiency

DF Deposition Fraction

DPM Discrete Phase Model

3DCRT 3-Dimension Conformal Radiation Therapy

E-L Euler-Lagrange

IMRT Intensity Modulated Radiation Therapy

LPM Litre Per Minute

MHD Magneto hydro-dynamics

MRI Magnetic Resonance Imaging

Mn Magnetic Number (Tesla)

MNPs Magnetic Nanoparticles

MnMs Magnetic Nanoparticle Microcomposites

MMAD Mass Median Aerosol Diameter

NPs Nano Particles

PMDIs Pressurized Meter Dose Inhalers

TD Transport and Deposition

VMAT Volumetric Modulated Arc Therapy

xii Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung STATEMENT OF ORIGINAL AUTHORSHIP

The work contained in this thesis has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

Signature: QUT Verified Signature

Date: 27/03/2018

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung xiii ACKNOWLEDGEMENTS

I would like to express my gratitude, appreciation, and deepest sense of indebtedness to my supervisor, Dr Suvash C. Saha, for his willingness to accept me as a MPhil student. He has helped me to carry out my thesis work on this challenging topic and also has aided me through his patience, motivation, enthusiasm, constructive criticism, and endless encouragement during the completion of the thesis.

I would like to convey my gratitude to my other supervisor, Professor Richard Brown, for his support throughout my candidature. I would like to acknowledge them both, for their valuable insight, continuous encouragement, motivation and belief in my ability.

I want to thank Mohammad Saidul Islam, for his help to me in conducting this research.

The high performance computing facility in QUT is also acknowledged.

Professional editor, Diane Kolomeitz, provided copyediting and proofreading services, according to the guidelines laid out in the university-endorsed national guidelines for editing research theses.

Thanks also to all my friends in QUT and here in Brisbane for their support.

Finally, last but not least, I would like to acknowledge family members, not only for this MPhil journey, but also for their contribution to my whole life.

xiv Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung

Chapter 1 : INTRODUCTION

The lung is one of the unique organs of the human body involved in oxidative stress, because it flexibly brings down higher oxygen pressures. Lung cells involve enriched oxidant pressure because of their direct exposure to ambient air by environmental irritants and pollutants (Kinnula & Crapo, 2003). The inhaled air is consumed to transfer aerosolized drug particles into the lungs, in the therapeutic supervision of lung diseases. A predicted number of lung disorder patients increasing over the next two decades means different types of therapeutic techniques are being established to maximise treatments. These are techniques such as Intensity Modulated

Radiation Therapy (IMRT), 3-Dimension Conformal Radiation Therapy (3DCRT),

Volumetric Modulated Arc Therapy (VMAT) and chemotherapy. All of these aim is to deliver drugs to the affected area. There are very limited studies that have been conducted on magnetic aerosol particles or drug aerosols for targeting magnetic drug delivery in the specific region of the lungs. In the present study, an advanced magnetic aerosol particle transport and deposition (TD) model has been developed for the first time, for better prediction of drug delivery in the affected area of lung airways for a 2- generation, symmetrical lung model.

This chapter outlines the background (section 1.1) and aims (section 1.2) of the research, and its objectives (section 1.3). Section 1.4 describes the significance and scope of this research and provides definitions of terms used. Finally, section 1.5 includes an outline of the remaining chapters of the thesis.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 1 1.1 BACKGROUND

Magnetic aerosol has gained much attention among researchers for targeting local drug delivery to minimise undesired side effects in the organism. The most common lung diseases today are asthma, cystic fibrosis, chronic obstructive pulmonary disease (COPD), respiratory infection and lung cancer. Magnetic targeting of drugs is especially attractive for chemotherapy. Chemotherapy is an ideal application of drug delivery for localised targeted sites via inhaled aerosol. Targeting delivery of magnetic aerosol by an external magnetic field is such a drug delivery system, by which the drug is usually concentrated in a specific, targeted site. This process also minimizes the total drug dosage required, and decreases systemic toxicity as well as treatment cost. Even though enormous progress has been made in improving aerosol supply to the lung, magnetisable, targeted aerosol supply to the specific regions in the lung other than the lung periphery or airways has not been sufficiently achieved up to date (Dames et al., 2007). A precise understanding of magnetic particle transport and deposition in a specific region of the lung is important for respiratory health risk assessment. Therefore, a magnetic aerosol particle TD study is necessary for better prediction of the pharmaceutical aerosol delivery to the targeted position of the lung airways. Hence, detailed analyses of magnetic aerosol particles or drug aerosol transport and deposition phenomena in the human respiratory tract are needed, for a better understanding of the fluid-particle dynamics and aerosol drug impact studies.

1.2 AIMS

The aim of this study is to develop an advanced numerical model to analyse the magnetic field intensity, numerical methods for determining the overall algorithm of

2 Chapter 1: Introduction magnetic therapeutic aerosol targeting in a specific region of the lung, effects of particle diameter and inhalation flow rate for targeting magnetic drug aerosol deposition in a specific region of the lung, to guide the improvement and testing of novel therapies for lung disease.

1.3 OBJECTIVES

To achieve the aims of this study, the following objectives need to be addressed:

• Generate a 2-generation human lung geometry for determining the

accurate flow of magnetic aerosol particles;

• Develop an advanced numerical method and algorithm to guide

magnetic therapeutic aerosol towards a specific targeted region of the

lung;

• Investigate the effect of particle shape and size, magnetic source

position, strength of magnetic field and inhalation flow rate on the

transport and deposition in the targeted lung region for micro and nano

particles;

• Study the magnetic intensity in the specific region of the lung and

investigate the magnetic micro and nano particle deposition pattern in

the targeted position of a 2-generation symmetric lung model.

1.4 SIGNIFICANCE, SCOPE AND INNOVATION

A precise understanding of the size and shape-specific magnetic aerosol particle transport and deposition is the principal step in the assessment of a respiratory health hazard and more efficient drug aerosol delivery in the pulmonary airways. This thesis presents a comprehensive and advanced computational analysis of magnetic targeting

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 3 drug delivery or drug aerosol transport and uptake in the specific airways of a 2- generation symmetrical model for the first time. The deposition efficiency (DE) of different diameter particles, as a function of various deposition parameters, are investigated for this 2- generation lung model. The specific findings of the present study advance the field and improve the understanding of therapeutic aerosol transport to the specific targeted region of the airways. The magnetic aerosol particle TD study will improve the efficiency of the delivered drug to the targeted position of the lung and could potentially guide the development of future targeted drug delivery systems.

The magnetic nano particles (MNPs)’ TD analysis improves the knowledge of the nanoparticle (NPs) deposition pattern at the specific region of lung and this could possibly help to design new drug delivery devices. The advanced computational study could be used for clinical assessment of respiratory diseases. The new framework can be used to minimise the efficiency of the dose deposition at the unwanted region and unwanted site effects of the lung airways. This study enhances the knowledge of magnetic particle flow in different biomechanical engineering applications.

The present study develops a 2-generation symmetric model for more accurate prediction of the particulate deposition in a specific region of the lung, by an external magnetic field. This study develops a new framework to predict and analyse the realistic deposition pattern, which would potentially help to understand the deposition mechanism. This first-ever study investigates monodisperse microparticle and nanoparticle TD in the specific region of the lung by external magnetic field.

1.5 THESIS OUTLINE

This thesis structure is as follows: Introduction (Chapter 1), Literature review

(Chapter 2), Methodology (Chapter 3) based on Case study 1(Magnetic Micro particle)

4 Chapter 1: Introduction and case study 2 (Magnetic Nano particle) and its Results and Discussion in Chapter

4, regarding this case study 1 and case study 2. Finally, Chapter 5 describes the conclusions of the thesis.

The overall outline of this thesis is shown in figure 1.1.

Figure 1.1 Flowchart of the present thesis.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 5 Chapter 2 : LITERATURE REVIEW

In this chapter, the overall biological aspects of the lung and the development of magnetic drug delivery are summarised. The different aspects of targeted drug delivery are also discussed. This chapter begins with the biological aspects of the lung and the content includes

 Biological aspects of the lung;

 Deposition mechanism;

 Targeted drug delivery;

 Magnetic Microparticle transport and deposition;

 Magnetic Nanoparticle transport and deposition.

2.1 BIOLOGICAL ASPECTS OF THE LUNG

Due to the biomechanical and real life application of human lung research, most of the researchers in the field have an ample keenness towards human lung modelling and simulation. The human lung is a respiratory organ consisting of two spongy parts (Gray & Goss, 1878). Respiration is essential for both plant and animal cells, including human, to survive. Respiration happens through a group of organs forming the respiratory system. The lung is the main organ of breathing. Gas exchange is the fundamental role of the respiratory system, which helps our body to keep a balance in supplying oxygen to red blood cells and expelling carbon dioxide into the environment (Ratnovsky et al., 2008).

6 Chapter 3: Methodology The organs of the respiratory system are divided into two parts (Fig.2.1); one is the upper respiratory tract and the other one is the lower respiratory tract. The upper respiratory tract consists of mainly the nose, nasal cavity and pharynx, where the lower consists of larynx, trachea, bronchial tree and lung (Ionescu, 2013).

Figure 2.1 Human respiratory system ("Human body. Reaspiratory system diagram. Retrieved April 6, 2017, from http://www.buzzle.com/images/diagrams/human- body/respiratory-system-diagram.jpg," 2017).

All the above components play an inevitable contribution to supply oxygen into blood cells and expel the carbon-dioxide from the lung. The total surface area of the lung is about half of a tennis court and considered to be between 80 m2 and 140 m2 (Scheuch et al., 2006).

The human cell needs a flow stream of oxygen for its existence and to release the carbon dioxide, which is a waste product of the human body mechanism. The respiratory system is responsible for oxygen supply to the body cells and the removal of carbon dioxide. The nose, mouth, pharynx, larynx, trachea, bronchi, and bronchioles are the components of the airway system (Fig.2.2 a). The segmented

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 7 meshing view of the computational domain is shown in fig 2.2(b). The human lung acts as a working unit of the respiratory system.

Figure 2.2 (a) Structural design of lung components (b) The segmented view of the computational domain (Rahimi-Gorji et al., 2016).

The human airway starts with the trachea, then bronchi and bronchioles, with a total of about 23 to 32 generations that finally end at the alveoli (Mortensen et al., 2014).

The lung consists of spongy-like textures. These textures are full of air organs that are located on both side of the chest (thorax). The trachea transports the inhaled air into the lung through the bronchi. Then the bronchi partition into smaller and smaller branches, called bronchioles and finally, they become microscopic (Fig.2.3). The alveoli, microscopic air sacs at the end of the bronchioles, absorb oxygen (Gray &

8 Chapter 3: Methodology Goss, 1878; Tomlinson et al., 1994) from the air (Denison et al., 1982) and transport into the blood.

Figure 2.3 Picture of human lung with alveoli. (Matthew Hoffman, 2014).

These bronchioles ultimately end in bunches of microscopic air bags called alveoli

(Fig.2.3). Alveoli mainly absorb oxygen from the air. Carbon dioxide is a waste product of metabolism, which travels from the blood to the alveoli and then it can be exhaled. Interstitium is a thin layer of cells between the alveoli, which covers blood vessels. The alveoli surface is covered by water-based alveolar fluid. During inhaling and exhaling, the alveoli expand and compress.

In the time of an inhalation process, an adult human inhales somewhere between 100 bi1lion and 10 trillion particles per day with oxygen (Tsuda et al., 2013).

Particles sized less than 100µm are only able to enter into the body by inhalation

(Fig.2.4). Particles between 10 µm to100µm in size are cleared out by nasal hairs, nasal

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 9 mucosa or mucus that always moves up by cilia in the bronchi and bronchioles. Less than 10 µm can pass through the above-mentioned barriers and travel into the pulmonary region of the lung (Fig.2.4). Among these particles, only ultrafine particles

(<100nm) are consider most harmful (Anseth et al., 2005; N. Li et al., 2003; Sioutas et al., 2005) and can create many health hazards, particularly in the lung. The health hazards include Asbestosis (Shipyard, Mine and Mill workers), Benign pneumoconiosis (Iron miners, Tin workers and Welders), Beryllium disease

(Aerospace and Metallurgical workers), Occupational asthma (Grains and Tea farm workers), Silicosis (Foundry, Tunnel workers, Potters and Farmers)

(" Lung diseases. Environmental lung diseases. Retrieved April 6, 2017, from http://www.merckmanuals.com/home/lungand-airway-disorders/environmental-lungdiseases/overview-of-environmental-lungdiseases,").

Particle size <100µm

Particle size < 10µm

Figure 2.4 Particle size that enters into the respiratory system ("Respiratory system. Retrieved April 6, 2017, from http://www.livescience.com/22616- respiratorysystem.html,") (This figure has been modified.)

10 Chapter 3: Methodology Some of these particles are soluble and may be dissolved into the bloodstream.

Therefore, these types of particles have the ability to penetrate all the defense mechanisms of the lung, whereas, the other type of particles that are insoluble are mostly cleared by mucus, cilia or macrophages. Only a few of the insoluble particles can reach deep into the lung by penetrating the defense mechanisms of the respiratory system, which has a negative effect on human health.

2.2 DEPOSITION MECHANISM

The human lung is instinctively an integral part of the chest. The human lung cell is very important for particle transport and deposition. The particulate deposition in the human lung has become one of the interesting topics for researchers, for its practical application in medical science. Investigating the deposition pattern of inhaled particles in the human lung is very challenging due to the complex geometrical structure of the human lung (H. Kumar et al., 2009; Soni & Aliabadi, 2013; Weibel,

1963). Computational fluid dynamics (CFD) models are able to determine the high deposition efficiency.

In recent years, several geometric models of the human lung have been developed. In the case of modelling and simulation of particle deposition in human lung cells, Weibel’s (Weibel, 1963) lung model is still being used, due to its geometric simplicity. Because of the limitations of the idealised lung models, most of the experimentalists and CFD analysts now focus on realistic airway models to determine the particle deposition in the human lung (H. Kumar et al., 2009; Ma & Lutchen, 2006,

2009). Anatomically based human airway models, like the Computerized Tomography

(CT) scan or Magnetic Resonance Imaging (MRI) geometrical model, attract current

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 11 researchers. In order to investigate accurate particle deposition patterns in the human lung, realistic deposition models are very effective (B Asgharian et al., 2001).

Inhaled particle deposition in the human lung is mainly caused by Brownian diffusion, gravitational sedimentation and inertial impaction (Choi & Kim, 2007).

Inhaled particle deposition in the human respiratory tract is mainly governed by its shape (W Hofmann et al., 2009; Kasper, 1982) and size (Werner Hofmann, 2011).

The particulates >5 µm are deposited in the oropharynx and the particles 1-5 µm are deposited in the conducting airways (Everard, 2001; Newman, 1985).The particulates of size <1 µm are deposited in the alveoli region and peripheral airways (Everard,

2001). Micro-particles less than 0.5 µm are initially deposited in the human lung by

Brownian diffusion (Werner Hofmann, 2011), while larger particles are deposited by sedimentation and inertial impaction. Breathing patterns are also responsible for particle deposition in human airways. Due to the long residence time, slow breathing patterns are more effective for sedimentation and Brownian diffusion, whereas a fast breathing pattern is good for impaction (Werner Hofmann, 2011).

2.3 TARGETED DRUG DELIVERY

The lung represents an attractive alternative way of targeting drug delivery

(Kuzmov & Minko, 2015). The technology of targeted drug delivery is a significant area of biomedicine (O. Pourmehran et al., 2015). Today, scientists and researchers are mainly interested in recognising the role of drug particle deposition on lung systems and their reverse impacts. This process of drug delivery can provide an important role for researchers to assess how the particle transportation, diffusion and deposition are completed in the specific region of the human lung. It can also provide an advanced way of treatment for a drug particle delivery system to targeted areas

(Taherian et al., 2011). From the 1970s, when the magnetic micro-particles of

12 Chapter 3: Methodology polymer-coating were first developed, targeted drug delivery has been an interest area for drug delivery in the lung (Pankhurst et al.). The drug particles are concentrated and navigate towards the affected sites in the lung by using external magnetic fields.

Targeting magnetic delivery is especially attractive for chemotherapy. Drug direction for chemotherapy through aerosol inhalation is a perfect application for targeting magnetic drug delivery (Dikanskii, 1998).

A range of aerosolised medicines are now recommended for the use of nebulizer systems and devices. Drug delivery through an inhalation system needs an effective aerosolised formulation. These aerosol drug delivery devices must be used and need to be maintained correctly by patients and caregivers. In recent years, several types of technical developments have to led the drug delivery through the aerosol drug delivery devices for efficient drug delivery. For example, dose tracking, materials of manufacture, portability, breathe actuation, the patient interface, combination therapies, and drug delivery system. These modifications have developed presentation in all four types of devices: metered dose inhalers, spacers and holding chambers, dry powder inhalers, and nebulisers. Furthermore, some therapies generally given by injection are now recommended, for instance, aerosols for use in a variety of drug delivery devices (Dolovich & Dhand, 2011).

The ability of targeted drugs to the predetermined sites is a major challenging need for aerosol therapy (Dolovich & Dhand, 2011). There are two types of targeting

(passive and active targeting).

2.3.1 PASSIVE TARGETING

The passive targeting methodology directs deposition primarily to the respiration, especially to the more peripheral airways and alveolar section. These

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 13 depositions are due to variations of droplet size of drug carrier, inhalation patterns, breath holding for depth and duration, aerosol bolus timing to inspiratory air flow, dosage of drug aerosol, and inhaled gas density (Dolovich et al., 2005; Heyder, 2004).

Congruently, a considerable breathe fraction in aerosol can be dropped for narrowing at areas of respiration during exhalation, particularly when flow-restricted sections are present (Smaldone, 2006). Oropharyngeal drug deposition can be reduced by airway targeting, which also reduces the risk of local and systemic resulting side effects from the absorbed dose (Brown et al., 1993; Salzman & Pyszczynski, 1988).

Figure 2.5 Action of nanomagnetosols Mechanism (Plank, 2008).

2.3.2 ACTIVE TARGETING

In the active targeting method, the drug deposition is completed by directing to the infected area of the lung through the aerosol and providing a more appropriate drug delivery to the targeted site. That means it is more active for targeted delivery than passive targeting: for example, genes or drugs delivery directly to a lung lobe, the

14 Chapter 3: Methodology Aero Probe nebulising catheter of intracorporeal (TMI, London, ON, Canada) could be inserted through a fibre optic bronchoscope into the working channel (Köping‐

Höggård et al., 2005; Selting et al., 2008). Recently, in a nebuliser solution, NPs of super paramagnetic iron oxide are added for guiding aerosol to the affected lung region by the influence of an external strong magnetic field (See Fig 2.5)(Dames et al., 2007).

The direct chemotherapeutic agents’ delivery to the lungs could symbolise a unique therapeutic approach with pulmonary metastases for patients (Goel et al., 2013).

Targeted pulmonary delivery simplifies bioactive materials directly to the lung through a controlled manner and targeted MNPs provide to the lung through an exciting platform (Stocke et al., 2015). This is a first-line treatment for asthma, COPD, and pulmonary infections because of its inherent advantages (Dolovich et al., 2005).

Due to pharmaceutical action, drugs will achieve more concentration and minimise unwanted systematic side effects (Patton & Byron, 2007). Again, this inhalation method also avoids pharmaceutical agents, which is the first pass of metabolism

(Mansour et al., 2009). For this reason, less aerosol dosage is required in this delivery system.

Inhalation aerosol by dry powder offers many advantages, such as controllable particle size and increased stability of formulations for targeting regions of the lung

(Carpenter et al., 1997; Dolovich et al., 2005). Also, dry powder formulations can be used for nebulizers and pressurised meter dose inhalers (PMDIs). For all powders, magnetic nanoparticle microcomposites (MnMs) could deposit throughout the lung if the mass median aerosol diameter (MMAD) is < 5 μm. This inhalable treatment presents many potential applications and targeted thermal treatment of the lung by MNPs (Stocke et al., 2015).

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 15 Figure 2.6 Schematic representation of magnetic nanoparticle microcomposites (MnMs) by pulmonary delivery (Stocke et al., 2015).

The systematic inhalable dry powders are taken via inhaled dry powder by pulmonary delivery to the lung (see, Fig 2.6). Again, these materials can be taken into a capsule and placed into a dry powder inhaler for observing predictive deposition patterns in the lung through vitro aerosol dispersion performance and also alternating magnetic field (Stocke et al., 2015).

Recently, the advantages of pulmonary drug delivery have been growing for treating lung diseases, especially in cystic fibrosis (CF) and lung cancer. Because of the expanding successful aerosol formulations by the potential applications of targeted pulmonary delivery (Stocke et al., 2015), aerosols consist of small molecule drugs and excipients for inhalation therapies (Azarmi et al., 2008; Mansour et al., 2009).

16 Chapter 3: Methodology

Figure 2.7 Advantages and challenges of pulmonary drug delivery (Kuzmov & Minko, 2015).

The main advantages of an inhalation route are direct delivery of the drug by active components in the diseased cells and organs. Also, this process can protect possible adverse effects and potentially toxic therapeutics from other healthy organs in the body (Fig.2.7). Though drug delivery in this way has lots of advantages, it has also some challenges. Native nucleic acids and peptides cannot be delivered into the lung by this drug delivery system (Kuzmov & Minko, 2015).

2.4 MAGNETIC MICRO PARTICLE TRANSPORT AND DEPOSITION

Drug delivery in the lung by aerosol inhalation is an authenticated procedure. It has potential advantage in the treatment of respiratory disorders for drug delivery in oral and arterial routes. The usage of inhalation aerosols allows direct achievement of high drug concentrations for the selective treatment of the lungs (Darquenne, 2012).

The particle of one or several micrometers in size usually refers to the term

“microparticle” in drug delivery applications (Kuzmov & Minko, 2015). Many materials composed of microparticles, including glass, ceramics, metals, and polymers, are currently available commercially. For the drug delivery purposes, metal

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 17 and polymer microparticles are being primarily used. The critical understanding of the local and regional deposition of micro-sized aerosol is important for assessing pulmonary health risk. It is essentially important to understand the deposition characterisation in the targeted position of the pulmonary airways for effective delivery of the inhaled pharmaceutical aerosol.

There are very limited studies that have been conducted for targeting magnetic drug delivery in the specific region of the lungs. The external magnetic field as a passive technique, which is a potential application tool of drug delivery, was adopted by several researchers (Dahmani et al., 2009; Dolovich & Dhand, 2011; Goetz et al.,

2010; Plank, 2008). Dahmani et al., (2009) developed an aerosol cloud at the beginning of the inspired phase for delivering aerosols to the deepest areas of the lungs by synchronising the activation of the magnetic field with the breathing process. The authors, however, did not show a deposition pattern for any specific lung model.

Dolovich & Dhand, (2011) have shown therapeutic applications and again, did not consider any specific zone deposition pattern for the entire geometry. Goetz et al.,

(2010) have studied the particle size for reducing unwanted distribution outside the target due to the impact of the magnetic force and did not consider specific areas of the lung model for particle deposition. Plank, (2008) has developed a nano magnetic aerosol drug targeting method for reducing undesired side effects. This study has shown therapeutic applications and did not consider any specific zone deposition pattern for the lung geometry. Ally et al. (2005) and Dames et al. (2007) have developed an in vitro model to investigate the possibility of targeted magnetic aerosol deposition for lung cancer. Dames et al., (2007) have developed nanomagnetosols for targeting aerosol delivery to the lungs of mice. O. Pourmehran et al. (2015) have used

Lagrangian magnetic particle tracking, using a discrete phase model to investigate the

18 Chapter 3: Methodology effect of a magnetic field on behaviour of the magnetic drug career. Recently, Oveis

Pourmehran et al. (2016) have used a realistic model to investigate the human tracheobronchial airways using computational fluid and particle dynamics. They have developed an optimal magnetic drug characteristics coordination and magnetic impact for drug delivery to the human lung. Based on several attempts of studying particle deposition due to the external magnetic field effect by several authors, it is important to investigate the particle deposition in the specific position by an external magnetic field, by designing a more realistic drug delivery device. There are no suitable numerical and experimental studies that have been conducted to fully understand magnetic field effect for particle deposition in a specific targeted position.

Case study 1 (Chapter 3 and Chapter 4) of this thesis will discuss the drug aerosols delivery on magnetic microparticle transport and deposition in the targeted position of the human lung airways.

2.5 MAGNETIC NANOPARTICLE TRANSPORT AND DEPOSITION

Nano-particles or airborne particles are produced from nature (volcanic ash, smoke, ocean spray, fine sand and dust etc.), the workplace (running diesel engines, large-scale mining, and industry) and man-made processes (fires, traffic and drug aerosols are generated by inhalers for therapeutic purposes) (Lintermann & Schröder,

2017). Moreover, the increased popularity of nanomaterial products may expose a significant amount of NP emission into the atmosphere (Islam et al., 2017). These NPs or drug aerosols are inhaled through the extrathoracic and tracheobronchial airways down into the alveolar region (Zhang & Kleinstreuer, 2004). As the result of strong diffusion and thermophoretic effects, inhaled NPs deposit into extrathoracic airways

(Bahman Asgharian & Price, 2008). A certain percentage may deposit in various lung

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 19 regions by touching the moist airway surfaces and hence, are accessible for interactions with respiratory tissue (Zhang & Kleinstreuer, 2004). As a result, toxic particles may instigate pulmonary and other diseases, while drug aerosol may be harnessed to struggle with diseases (Zhang & Kleinstreuer, 2004). The inhalation of drug aerosols is broadly used for the treatment of lung disorders such as COPD, asthma, respiratory infection, CF and more recently, lung cancer. NPs significantly influence their retention for shape and size in the lungs and targeting properties. At present, for drug delivery purposes, NPs are widely used through various delivery routes, including inhalation. Targeted NP delivery to the affected lung tissue may improve therapeutic efficiency and minimise unwanted side effects (Dames et al.,

2007). Despite these attractive advantages, systemic inhalation of therapeutic drug aerosol delivery in the specific region of the lung is still not clear (Kuzmov & Minko,

2015). A comprehensive investigation of MNPs TD in a lung model is essential for the understanding of pharmaceutical aerosol transport into the targeted position of the lung.

A wide range of studies has been conducted on MNPs TD for targeted drug delivery to diminish the diseased cells (Ally et al., 2005; Arruebo et al., 2007;

Chomoucka et al., 2010; Cregg et al., 2008; Fernández-Pacheco et al., 2007; A. Kumar et al., 2010; Lin et al., 2009; Mishra et al., 2010; Shubayev et al., 2009; Stepp &

Thomas, 2009; Sun et al., 2008).

There are limited studies that have been conducted on MNPs for targeting magnetic drug delivery in the specific region of lungs. Dames et al. (2007) developed superparamagnetic iron oxide nanoparticles (nanomagnetosols) in a combination of target-directed magnetic gradient fields for targeting aerosol delivery to the lungs of mice. The theoretical and experimental study concluded that the nanomagnetosols may

20 Chapter 3: Methodology be useful for treating localised lung disease. D. Bennett William et al. (2004) discussed the potential application of aerosol drug delivery and deposition techniques for both serial and parallel pathways in the lung. They concluded that aerosol bolus delivery and extremely slow inhalation of aerosols in diagnostic lung tests may be useful for targeting drug delivery to the conducting airways. Ally et al. (2005) developed an in vitro model to investigate the possibility of targeted magnetic aerosol deposition for lung cancer and to predict the trajectories of the aerosol particles. They concluded that aerosol particle concentration and magnetic field gradient are important considerations for targeting magnetic delivery of aerosols. Mishra et al. (2010) focused on the potential application of nanotechnology in medicine and discussed drug- delivery systems as well as their applications in therapeutics, imaging and diagnostics.

They concluded that the surface characteristics of NPs and a better understanding NPs in vivo behaviour can achieve successful development on targeted NPs for use in therapy and imaging. Wilczewska et al. (2012) investigated the nano carrier connections with drugs and magnetic nanoparticles as carriers in drug delivery systems

(DDS). They concluded that for the drug delivery systems, nanocarriers can improve the therapeutic and pharmacological properties of conventional drugs. Lübbe et al.

(2001) reported that magnetic drug targeting is one of the various possibilities of drug targeting, and site-directed drug targeting is one way of local or regional antitumor treatment. Sharma et al. (2015) studied magnetic nanoparticle transport in a channel for targeted drug delivery. They concluded that the fluid velocity and MNPs is decreasing with the increasing of a magnetic field. Roa et al. (2011) showed that inhalable doxorubicin NPs are an effective way to treat lung cancer. They concluded that a non-invasive route of administration might change the way lung cancer is treated in the future. O. Pourmehran et al. (2015) have used Lagrangian magnetic particle

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 21 tracking using a discrete phase model to investigate the effect of a magnetic field on the behaviour of the magnetic drug carrier. Recently, Oveis Pourmehran et al. (2016) have used a realistic model to investigate the human tracheobronchial airways using computational fluid and particle dynamics. They have developed an optimal magnetic drug characteristics coordination and magnetic impact for drug delivery to the human lung.

Until now there have been no numerical or analytical studies that consider the human respiratory tract, available in the literature on magnetic nanoparticles TD for targeting drug delivery in the specific region of the human lung. Hence, detailed analysis of the MNPs transport and deposition in the human respiratory tract are needed for a better understanding of the fluid-particle dynamics.

Case study 2 (Chapter 3 and Chapter 4) of this thesis will discuss the magnetic nano-particle deposition in the targeted lung region.

2.6 SUMMARY AND IMPLICATIONS

Respiratory health risk is essentially increasing, as particulate emission is increasing day by day. Inhaled detrimental particulate matter deposited in the airways has been implicated in a causal connection with a large spectrum of respiratory diseases. The aerosol particulates occur different respiratory diseases by producing inflammation in the lung epithelium cells. Based on the estimation presented in

(Saillaja AK, 2014), asthma affects 300 million people in the world, and more than 22 million in the United States alone. In 2017, lung cancer was the most common cause of cancer death for men and women in Australia (12,434 deaths overall: 7,094 in men;

5,340 in women), accounting for 18.9 per cent of all cancer deaths ("Australian

Government. Lung cancer statistices. Retrieved August 8, 2017, from https://lung-

22 Chapter 3: Methodology cancer.canceraustralia.gov.au/statistics.,"). In the case of traditional drug delivery devices, a significant amount of therapeutic particles are deposited at an unwanted position of the lung and generate different types of side effects. That is why it is essential to develop a more accurate and efficient drug delivery device for the targeted drug delivery system. The proper understanding of the respiratory air flow field characterisation, targeted magnetic particle transport and deposition, is important for better delivery of drug aerosols in the specific pulmonary health burden assessment. It is clear from the literature review that the study of particle deposition in the human respiratory tract is vitally important for developing effective drug treatment methods for respiratory diseases. Particle deposition in the human lung is an important field for researchers. The numerical modelling of nano and micro particle deposition in a patient-specific way in the human lung is very important for the improvement of drug treatment methods. The investigation of magnetic aerosol drug deposition under the influence of an external magnetic field will be an excellent effort for the future advance of research on drug delivery in the human lung. Because of the complex geometrical structure of the human bronchial tree, the deposition pattern depends considerably on magnetic source position, magnetic number, particles diameter, inhalation condition and magnetic field strength. The MNPS and micro-particle deposition in the specific region of human lung under an external magnetic field is an area with limited investigation area. A comprehensive magnetic particle TD analysis in the specific region of lung airways is important in order to increase the efficiency of the targeted drug delivery and minimise unwanted side effects.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 23 Chapter 3 : METHODOLOGY

In order to achieve the ultimate aims and objectives of this research, a theoretical frame-work, as well as software simulation work, has been performed. The main challenge in conducting the proposed work is geometry generation. Firstly, the 3-D lung geometry is generated by geometry generation software. Then the computational mesh of the human bronchial tree is generated by using commercial software ANSYS

18. ANSYS FLUENT 18 is used to solve the Navier-Stokes equations for incompressible airflow with appropriate boundary conditions. For this present study, the particles are considered smooth surface micro-particles and NPs, which have magnetic susceptibility. After solving the governing equation by a simple algorithm, these magnetic particles have been injected in a steady state manner. The desired external magnetic force has been applied by a Magneto hydro-dynamics (MHD) model and programmed based depending on particle position. The complete step-by-step methodology of the present work is given below:

24 Chapter 3: Methodology

Figure 3.1: Framework of the present thesis.

Figure 3.1 presents the detailed framework of the present study. The present thesis lung model is developed from solid works. An ANSYS 18.0 meshing module is used for advanced and high quality mesh generation. K- 휔 low Reynolds number model, Euler-Lagrange (E-L) based discrete phase model (DPM) and MHD are used for the shape- and size- specific magnetic particle transport and deposition in the specific region of the lung. MATLAB and Tecplot 360 software are used for post- processing.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 25 3.1 ASSUMPTIONS FOR NUMERICAL SIMULATIONS

The present numerical study assumes the following assumptions for targeted magnetic particle transport and deposition in the specific region of the human lung:

i) Velocity inlet and pressure outlet boundary conditions are assumed for this

study. 7.5 litre per minute (lpm), 9 lpm, 15 lpm, 30 lpm and 60 lpm flow

rates are used to simulate different human physical activity conditions for

targeted drug delivery. Zero pressure is used at all outlets of the 2-

generation symmetric model. The present study used the first targeted

magnetic drug delivery in the specific region of the human lung for a 2-

generation symmetric model.

ii) Magnetic number or intensity is assumed for this study. External magnetic

fields of 0.181 tesla, 1.5 tesla, 2.5 tesla, and 3 tesla are used to simulate

different intensity of magnetic conditions for targeted drug aerosol delivery

in the specific position of the lung.

iii) The present study considers different shapes and sizes of particle diameter;

2 μm, 4 μm, 6 μm, 1-nm, 10-nm, 50-nm, 100-nm and 500-nm are used to

simulate different effects of magnetic particle transport and deposition in

the specific position of the lung by external magnetic field.

iv) The present study considers only one-way inhalation effects on magnetic

aerosols’ particle transport and deposition. The simulations run until every

particle has either escaped or is trapped through the outlets.

v) The present study used the boundary condition as a ‘trap’, which means the

particle will be deposited if the particles touches the wall. Once the particle

touches the airway wall, simulation will store the information (position,

26 Chapter 3: Methodology velocity, etc.) of those particles, and the trajectory calculations are

terminated.

vi) Two different magnetic field positions are used to show the deposition

enhancement in the specific position of the human lung.

vii) Stokes-Cunningham correction law is used for the targeted magnetic nano-

particle modelling. Specific correction factor values are used for the

different diameter particles.

3.2 NUMERICAL METHODOLOGY FOR CASE STUDY 1

ANSYS (Fluent) 18.0 was used to solve the following governing equations with proper initial and boundary conditions. The steady-state flow field is converged when the residuals decreased to less than10−6. Air was considered as the working fluid with constant density (ρ), viscosity (μ) and fluid static pressure (p). The governing equations for continuity and momentum equations are given as:

Continuity equation:

휕푢̅̅̅ 푖 = 0 (3.1) 휕푥푖

Momentum equations:

휕푢푖 휕푢푖 1 휕푝 휕 휕푢푖 휕푢푗 (3.2) + 푢푗 = − + [(푣푓 + 푣푇) ( + )] 휕푡 휕푥푗 𝜌푓 휕푥푖 휕푥푗 휕푥푗 휕푥푖

Where 푢푖 and 푢푗 (i, j = 1, 2, 3) are the velocity components along x-, y- and z- directions. Steady k–ω low Reynolds number turbulence model was adopted to calculate the air flow in the present study. The SIMPLE algorithm was used for the pressure-velocity coupling. The second-order upwind numerical scheme was chosen to discretise different terms in the transport equations. The k–ω turbulence model governing equations are written as follows:

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 27 휕푘 휕푘 ∗ 휕 ∗ 푘 휕푘 (3.3) + 푢푗 = 푃 − 훽 휔푘 + [(푣푓 + 훼푘훼 ) ] 휕푡 휕푥푗 휕푥푗 휔 휕푥푗 with Pseudo vorticity equation:

휕휔 휕휔 훾휔 2 휕 ∗ 푘 휕휔 훼푑 휕푘 휕휔 (3.4) + 푢푗 = 푃 − 훽휔 + [(푣푓 + 훼휔훼 ) ] + 휕푡 휕푥푗 푘 휕푥푗 휔 휕푥푗 휔 휕푥푗 휕푥푗

푘 where the turbulent viscosity, 푣 = 퐶 푓 , and the function, 푓 is defined as 푓 = 푇 휇 휇 휔 푢 푢

3.4 𝜌푘 exp [− ] with 푅 = . The other coefficients in the above equations are 푅 2 푇 (1+ 푇) (휇휔) 50 chosen from (Oveis Pourmehran et al., 2016) :

1 푅 = 8, 푅 = 2.61, 푅 = 6, 훼 = , 훽 = 0.0708 , 훽∗ = 0.09 , 훼∗ = 1, 훽 휔 푘 0 9 0 0 ∞

𝜎휔 = 훼푘 = 0.5

Wall condition is considered as trap (if the particle trajectory touch the wall then the trajectory calculations will be terminated and the fate of the particle is recorded as trapped), outlet condition is pressure outlet and inlet is uniform mass flow considered for the boundary conditions.

To simulate the particle trajectories, the Lagrangian particle tracking approach and discrete phase model (DPM) have been applied. In this approach, the force balance equation for individual particles is given as follows:

푑푈⃗⃗⃗⃗푝⃗⃗ (3.5) 퐹⃗ = 퐹⃗⃗⃗⃗⃗ + 퐹⃗⃗⃗⃗⃗⃗ = 푚 . 퐷 푀 푝 푑푡 where 푈⃗⃗⃗⃗푝⃗ is the particle velocity and 퐹⃗⃗⃗⃗ is the force term. 퐹⃗⃗⃗퐷⃗⃗ , 퐹⃗⃗⃗⃗푀⃗⃗ are drag and magnetic forces, respectively.

3.2.1 DRAG FORCE

For a spherical particulate, the Stokes drag force is expressed as:

28 Chapter 3: Methodology ⃗⃗⃗⃗⃗ 18휇 푚푝푓푅푒푃 (3.6) 퐹퐷 = 2 (푢푓 − 푢푝) 𝜌푝푑푝 24

The drag coefficient 퐶퐷 , for smooth particle using the spherical drag law can be taken from

푎2 푎3 (3.7) 푓 = 푎1 + + 2 푅푒푃 푅푒푃

𝜌푓푑푃|푢푃−푢푓| where 푅푒푃 is the particle Reynolds number, which is defined as 푅푒푃 ≡ . 휇푓

푢푃, 𝜌푓, 𝜌푃 휇푓, 푢푓 and 푑푃 are the air velocity, fluid density, particle density, particle velocity, fluid molecular viscosity and particle diameter. Also in (3.7) 푎1, 푎2 and 푎3 are constants.

3.2.2 MAGNETIC FORCE

For magnetic force, the Magneto Hydrodynamics Model (MHD) approach has been applied. The fluid flow field and the magnetic field connection can be implicit on the basis of induction of electric current due to the movement of conducting material in a magnetic field and the effect of Lorentz force as the result of electric current and magnetic field interaction. This equation provides the connection between the flow and the magnetic field.

Electromagnetic fields are determined by Maxwell’s equations:

∇ ∙ 퐵⃗⃗ = 0 (3.8)

휕퐵⃗⃗ (3.9) ∇ × 퐸⃗⃗ = − 휕푡

∇ ∙ 퐷⃗⃗⃗ = 푞 (3.10)

휕𝑗⃗ ∇ × 퐻⃗⃗⃗ = 퐽⃗ + (3.11) 휕푡

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 29 The magnetic simulation equation can be derived from Ohm’s law and Maxwell’s equation, which is:

휕퐵⃗⃗ 1 + (푈⃗⃗⃗⃗. ∇)퐵⃗⃗ = ∇2퐵⃗⃗ + (퐵⃗⃗. ∇)푈⃗⃗⃗⃗ (3.12) 휕푡 휇𝜎

From Ampere’s relation the current density, 퐽⃗ can be calculated as:

1 퐽⃗ = ∇ × 퐵⃗⃗ (3.13) 휇

Generally, the magnetic field, 퐵⃗⃗ ( 퐵⃗⃗ = 휇0퐻) in an MHD problem can be decomposed ⃗⃗ into the externally imposed field, 퐵⃗⃗⃗⃗0⃗ and the induced field, 푏 due to fluid motion. Only the induced field, 푏⃗⃗ must be solved.

From Maxwell’s equations, the imposed field, 퐵⃗⃗⃗⃗0⃗ satisfies the following equation:

휇𝜎(휕퐵⃗⃗⃗⃗0⃗) (3.14) ∇2퐵⃗⃗⃗⃗⃗ − = 0 0 휕푡

3.2.2.1 EXTERNALLY IMPOSED MAGNETIC FIELD GENERATED IN NON-

CONDUCTING MEDIA

In this case, the imposed field 퐵⃗⃗⃗⃗0⃗ satisfies the following conditions:

(3.15) ∇ × 퐵⃗⃗0 = 0

2 (3.16) ∇ 퐵⃗⃗0 = 0

⃗⃗ With 퐵⃗⃗ = 퐵⃗⃗⃗⃗0⃗ + 푏, the induction equation (3.14) can be written as:

휕푏⃗⃗ 1 휕퐵⃗⃗⃗⃗0⃗ (3.17) + (푈⃗⃗⃗⃗. ∇)푏⃗⃗ = ∇2푏⃗⃗ + ((퐵⃗⃗⃗⃗⃗ + 푏⃗⃗). ∇) 푈⃗⃗⃗⃗ − (푈⃗⃗⃗. ∇)퐵⃗⃗⃗⃗⃗ − 휕푡 휇𝜎 0 0 휕푡

The current density is:

30 Chapter 3: Methodology 1 푗⃗ = ∇ × 푏⃗⃗ = 0 (3.18) 휇

3.3 NUMERICAL METHODOLOGY FOR CASE STUDY 2

A Lagrangian particle-tracking scheme and an ANSYS 18.0 (FLUENT) solver based DPM and MHD model have been applied to investigate the nano-particle

Transport and Deposition in the 2-generation airways. Euler-Euler (E-E) and Euler-

Lagrange (E-L) approaches are usually used for nanoparticle simulation. An E-L approach solves the particle trajectory equation while an E-E approach is used to solve convection-diffusion equations (Islam et al., 2017). The E-L method tracks the individual particle trajectory by considering inertia, electrostatic effects, diffusivity, and near wall terms directly (Longest et al., 2004). The present study uses the E-L approach as it also considers dp ≥ 100 nm.

The present study considers the 2-generation lung model as derived from the trachea, which does not include the extrathoracic region. The k- low Reynolds number turbulence model is used for the current study and calculated maximum

Reynolds number is 5×103. Reynolds number describes the ratio of the magnitudes of the inertial and viscous forces on the particle.

The k–ω turbulence model governing equations are written as follows:

휕푘 휕푘 ∗ 휕 ∗ 푘 휕푘 (3.19) + 푢푗 = 푃 − 훽 휔푘 + [(푣푓 + 훼푘훼 ) ] 휕푡 휕푥푗 휕푥푗 휔 휕푥푗

Pseudo vorticity equation:

휕휔 휕휔 훾휔 2 휕 ∗ 푘 휕휔 훼푑 휕푘 휕휔 (3.20) + 푢푗 = 푃 − 훽휔 + [(푣푓 + 훼휔훼 ) ] + 휕푡 휕푥푗 푘 휕푥푗 휔 휕푥푗 휔 휕푥푗 휕푥푗

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 31 u 2 u 2 1  u u  Where P   i ;  T(2S  k  )   ; S   i  j  ; ij ij ij ij ij ij   x j 3 xk 3 2  x j xi 

푘    f ; the turbulent viscosity, 푣 = 퐶 푓 and the function, 푓 is defined as 푓 = 0 푇 휇 휇 휔 푢 푢

3.4 𝜌푘 exp [− ] with 푅 = . The other coefficients in the above equations are 푅 2 푇 (1+ 푇) (휇휔) 50 chosen from ANSYS fluent 18.0:

1 푅 = 8, 푅 = 2.95, 푅 = 6, 훼 = , 훽 = 0.0708 , 훽∗ = 0.09 , 훼∗ = 1, 𝜎 = 훼 훽 휔 푘 0 9 0 0 ∞ 휔 푘

= 0.5

Wall condition, pressure outlet and velocity condition were used for the boundary conditions.

In this approach, the force balance equation for individual particles is given as follows:

푑푈⃗⃗⃗⃗푝⃗⃗ (3.21) 퐹⃗ = 퐹⃗⃗⃗⃗⃗ + 퐹⃗⃗⃗⃗⃗⃗ = 푚 . 퐷 푀 푝 푑푡 where 푈⃗⃗⃗⃗푝⃗ is the particle velocity and 퐹⃗⃗⃗⃗ is the force term. 퐹⃗⃗⃗퐷⃗⃗ , 퐹⃗⃗⃗⃗푀⃗⃗ are drag and magnetic forces respectively.

The following mass and momentum equations respectively were solved to calculate air flow.

  (3.22)  v  Sm t where Sm is the mass source term.

       T  2    (3.23) v vv  p  v  v   vI  g  F t    3 

32 Chapter 3: Methodology  where, p is fluid static pressure, g is body force due to gravity, μ is the molecular  viscosity, I is the unit tensor, and F is body force due to external force (particle-fluid interaction). A pressure-velocity coupling scheme, SIMPLE, was used to solve the pressure-velocity coupling in the flow field. A parabolic inlet condition for laminar flow (White, 2003) was used

r 2 (3.24) u(r)  2u (1 ) av R2 where R is the airway inlet radius.

Brownian motion was considered for this nano-particle simulation. An appropriate particle motion equation was solved to calculate the individual particles.

p (3.25) gp pg dui FD() u i u i  F Brownian  F Lift  g i   p dt

For a spherical particulate, the Stokes -Cunningham drag force is expressed as:

 18g (3.26) FD  2  pd pCc

2 1.1d p / 2 (3.27) Cc 1 (1.257  0.4e ) d p

Where Cc is the Cunningham correction factor. The specific correction factor values were used for different diameter particles. 𝜌푃 , 푑푃, are particle density, particle diameter and λ is the mean free path of the gas molecules. The Brownian force amplitude is defined as

S (3.28) F   0 Brownian t

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 33 Where ζ is the unit variance independent Gaussian random number, ∆t is the particle time-step integration, and S0 is the spectral intensity. S0 is defined as

216k T (3.29) S  B o   2 d 5 ( p )2 C p p  c g

T is the fluid absolute temperature, kB is the Boltzmann constant, ρg is the gas density.

The Saffman’s lift force is used (A. Li & Ahmadi, 1992), which is a generalisation of the Saffman expression (Saffman, 1965).

1/ 2 (3.30) 2Kv dij   FLift  1/ 4 (u  u p )  pd p (dlk dkl)

where K=2.594 1and dij is the deformation tensor.

For magnetic force, the Magneto hydrodynamics model (MHD) approach has been applied. The magnetic simulation equation is derived from Ohm’s law and Maxwell’s equation. This equation provides the connection between the flow and the magnetic field.

The magnetic force, 퐹⃗⃗⃗⃗푀⃗⃗ on a small sphere in a nonmagnetic fluid, was calculated as

1 퐹⃗ = 휇 χ푉 ∇ (퐻⃗⃗⃗⃗⃗2⃗) (3.31) 푀 2 0 푃

Where 휇0 is the magnetic permeability of vacuum, χ is the magnetic susceptibility of the particle, Vp is the particle volume, and 퐻⃗⃗⃗⃗⃗ is the magnetic field intensity.

The magnetic susceptibility of the particle equation (Oveis Pourmehran et al., 2016) is defined as:

6 χ = −0.14푑푝. 10 + 0.98 (3.32)

Where, 푑푝 is the particle diameter.

34 Chapter 3: Methodology Magnetic number Mn (Tesla) is defined as follows (Oveis Pourmehran et al., 2016):

푀푛 = 휇0퐻0 (3.33)

퐻0 is the characteristic magnetic field strength. Magnetic number is dependent to the magnetic field intensity.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 35 Chapter 4 : RESULTS AND DISCUSSION

The purpose of this chapter is to interpret and describe the significance of case study findings for the present thesis. The present thesis case study includes the discussion of aerosolised magnetic microparticle (Case study 1) and magnetic nanoparticle (Case study 2) transport and deposition in the targeted position of the human lung.

4.1 CASE STUDY 1: MAGNETIC MICROPARTICLE

4.1.1 COMPUTATIONAL DOMAIN AND MESH GENERATION

The 2-generation lung symmetric model is constructed to calculate the complex flow field in the human lung for k- low Reynolds number turbulence model. This 2- generation lung geometry contains 450,429 elements and 179,660 nodes.

36 Chapter 4: Results and Discussion

(b) (a)

(e) (f)

Figure 4.1 (a) Anterior view of the 2-generation mesh with 179,660 unstructured

cells, (b) first bifurcation, (c) inlet mesh, (d) inflation layer mesh near to the wall, (e)

terminal bronchioles mesh, (f) outlet mesh of 2 generation lung model.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 37

An unstructured fine boundary layer mesh is constructed to calculate the complex flow field (Fig 4.1 (a)). Fig 4.1 (b) shows the mesh for the first bifurcation of a 2- generation lung model. An inflation of 10 boundary layer mesh was calculated near the solid wall (Fig 4.1(c)). Fig 4.1 (d) shows the inflation layer mesh of 2- generation lung model. Fig 4.1 (e) shows the outlet mesh of a 2- generation lung symmetric model.

4.1.2 GRID INDEPENDENCE TEST

After completing the meshing, a grid resolution test is performed for choosing the appropriate mesh for the present simulation. Since the fluid flow is complex and results are sensitive due to regional turbulence effects, it is required to consider a grid resolution to adequately refine the mesh. This model is tested for seven different grid numbers (see Fig. 4.2), comparing with the maximum velocity calculated on the outlet plane. The flow seems converged from the red point and it is conceivable to use any of the grid numbers from this point. However, 179,660 grid numbers are adopted for the present simulations. Note that the minimum and the maximum cell sizes are 1.e-

005 m and 1.9772e-003m respectively. Also, an inflation of 10 boundary layer is chosen in the boundary layer (near the solid wall).

38 Chapter 4: Results and Discussion 10

Maximum velocity (m/s) (m/s) velocity Maximum 2

0 0 50000 100000 150000 200000 250000 300000 Grid Number or nodes

Figure 4.2 Maximum velocity grid convergence 4.1.3 MODEL VALIDATION

A comprehensive validation has been performed for the present study. The present micro-particle simulation results have been compared with the experimental data sets of steady laminar flows available in the literature.

For the present airway model, results are compared with the observations by (Cheng et al., 2010) and (Kleinstreuer et al., 2008) for three inhalation flow rates (Fig.4.3).

The overall deposition fraction (DF) is compared against the Stokes number. The

2 Stokes number is defined by 푠푡 = 𝜌푝푑푝푈/(9휇퐷), where U is the mean velocity and

D is the minimum hydraulic diameter. All experimental results show that the DF is proportional to the Stokes number. The experimental data and the present numerical result show the similar trend against total deposition for the Stokes number. However, the DF of the present model is slightly lower than that of the experimental model, as the present model has considered only two generations instead of the four generations that were considered by the experimental study.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 39

Figure 4.3 Present simulated particle deposition efficiency comparison with the experimental data of (Cheng et al., 2010) and (Kleinstreuer et al., 2008).

Figure 4.4 Particle deposition fraction comparison between the present simulation data with the experimental different data sets of (Kleinstreuer et al., 2008), Chen et al.,(1999), (Lippmann & Albert, 1969), (Chan & Lippmann, 1980), Foord et al., (1978), (Stahlhofen et al., 1980) , Stahlhofen et al., (1983), (Emmett et al., 1982) and (Bowes & Swift, 1989).

40 Chapter 4: Results and Discussion Fig 4.4 shows the present airway model results compared with the observations of

(Kleinstreuer et al., 2008), Chen et al.,(1999), (Lippmann & Albert, 1969), (Chan &

Lippmann, 1980), Foord et al., (1978), (Stahlhofen et al., 1980) , Stahlhofen et al.,

(1983), (Emmett et al., 1982) and (Bowes & Swift, 1989) for impaction parameter.

This result shows the comparison of microparticle deposition fraction in the present airway model with in vivo deposition data as a function of the impaction parameter.

2 2 −1 The impaction parameter is defined by 푑푎푒푄(휇푚 퐿푚푖푛 ), where 푑푎푒 is the aerodynamic particle diameter and Q is the flow rate. All experimental results show that the DF is proportional to the impaction parameter. The experimental data and the present numerical result show the similar trend for the impaction parameter. The present micro particle DF for impaction parameter shows good agreement with the experimental data, but the trend is slightly lower than the experimental data as they have used a 4- generation lung model in their experiment and a 2-generation lung model has been chosen for the present simulation.

Figure 4.5 Geometry specification. (Magnet position 2 has been set on the left lung)

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 41

The 2- generation lung model specification and magnetic source position has been indicated in Fig 4.5. Position 1 and position 2 indicate the magnetic field position.

Position 2 has been set on the left lung (targeted region). Due to the symmetrical shape of the present model, inlet and outlet are same. Right and left generation of this model are indicated by rg2 and lg2.

Figure 4.6 Particle deposition efficiency using magnetic position comparison between the present simulation and experimental data sets of (Cohen, 2009), (Haverkort, 2008), and (Oveis Pourmehran et al., 2016)

Fig 4.6 shows particle deposition efficiency comparison based on magnet position between the present simulation and the experimental data of Cohen, (2009), Haverkort,

(2008), and Pourmehran et al., (2016). The total deposition efficiency under an externally applied magnetic force for the present model is in the range of the experimental data and sufficiently reaches an agreement with the published literature.

42 Chapter 4: Results and Discussion 4.1.4 POST PROCESSING RESULTS FOR MAGNETIC MICRO-PARTICLE

The present 2- generation lung airway model has been designed to determine the exact deposition in the targeted region. Fig 4.7 (a) shows the velocity magnitude for triple bifurcation lung airways.

(a)

(b) (c)

(d) (e)

Figure 4.7 Velocity profiles in the symmetric bifurcation airway model for steady

inhalation with Q= 60 lpm. (a) Contour of velocity magnitude for (a) 2- generation lung

model; (b ) Left outlet 1and (c) Left outlet 2; (d) Right outlet 1and (e) Right outlet 2.

The velocity magnitude at different outlets of the double bifurcation model is investigated and is shown in Fig. 4.7. Figs. 4.7(b, c) show the velocity contour at the

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 43 outlet planes of the left lung, whereas the velocity contour at the outlet planes of the right lung are presented in Figs. 4.7(d, e). The overall flow contour shows a vortex is generated due to the strong change of the airway cross-sectional area. However, the turbulence intensity at the left outlet 2 and right outlet 1 seems stronger than the other outlets. The highly complicated airway bifurcation, change of the angle and curvature, and centrifugally-induced pressure stimulates the velocity field at the selected outlet planes of the airway model.

Magnitude of B Magnitude of B

(b) (a)

Figure 4.8: Contour of Magnetic source for Mn=2.5T (a) position 1; (b) position 2. Particle traces coloured by particle residence time for (c) Position 1; (d) Position 2.

44 Chapter 4: Results and Discussion Figs.4.8 (a, b) clarify the effect of magnetic intensity at two targeted positions. To identify the magnetic source intensity, the magnitude of 퐵⃗⃗ (magnetic flux density) is shown for position 1 and position 2. It is found that the magnetic field intensity is higher in wall position 1 (targeted position) than other positions in the lung airways when the magnetic source is in position 1, as shown in Fig.4.8 (a). Correspondingly, in Fig.4.8 (b), magnetic field intensity is higher in the wall at position 2 (targeted position) when the magnetic source is in position 2. Due to the maximum intensity of magnetic flux on the two specific targeted positions, the present result shows the DE have been increased on those two positions. Magnetic flux density (퐵⃗⃗) diminishes with the increasing of distance from the magnetic source position. Figs.4.8 (a, b) have been shown to investigate where the magnetic field intensity is maximum after applying a magnetic field. To show how particles interact in the presence of this magnetic field, particle traces are shown in terms of particle residence time in Figs.4.8(c, d) after creating magnetic fields in two different position. Figs.4.8(c, d) show the maximum number of trajectories for a particle hitting a given targeted location and the deposition particle is higher on that position.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 45 (b)

Turbulent Kinetic Energy Turbulent Kinetic Energy

(a) (b)

Figure 4.9 Turbulent kinetic energy of magnitude contour for (a) position 2; (b) position 1; Particle traces coloured by (c) velocity magnitude for position 1; (d) velocity magnitude for position 2.

Fig.4.9 shows the contour of turbulence kinetic energy (TKE) magnitude for two different magnetic source positions in the present model. Fig.4.9 (a) shows the magnitude of TKE contour in the targeted magnetic field position 2. Similarly Fig.4.9

(b) shows the TKE contour magnitude for magnetic field position 1. In turbulent flow, the fluid speed at a point is continuously undergoing changes in both direction and magnitude. Turbulent intensity is measured by TKE. It is recognised that for

46 Chapter 4: Results and Discussion turbulence kinetic energy, airflow rapidly goes faster in the compression region and as a result, a maximum number of particles are deposited on that region. Fig.4.9(c) shows the velocity magnitude for magnetic particle for position 1. Fig .4.9(d) shows the velocity magnitude for magnetic particle for position 2. Velocity is a vector quantity.

The change of particle position over the injected time and particle direction movement is identified by velocity magnitude.

(a) (b)

(d)

(c)

Figure 4.10 Effect of flow rates on particle transport outline and DE (%) for Position

2, 푑푝 = 4 휇푚, 푀푛 = 2.5 푇, (a) 15 lpm; (b) 30 lpm; (c) 60 lpm; (d) Total deposition efficiency in terms of flow rates.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 47 Figs.4.10 (a, b, c) represent the deposition efficiency for three different breathing flow rates (slow, medium and fast) i.e., 15 lpm, 30 lpm and 60 lpm respectively when the magnetic number, 푀푛 = 2.5 T, magnetic source position is in position 2 and the particle diameter is 4 휇푚. At slow breathing condition (15 lpm), microparticle deposition at the targeted position is significantly increased more than any other region, as shown in Fig.4.10 (a). At slow breathing condition, the total percentage of deposition is 27.06 and at the targeted position it is 23.84. At 30 lpm, which represents a medium breathing pattern, the majority of 4휇푚 diameter particles are deposited in the left lung in Fig. 4.10(b). The percentage of overall deposition for a medium breathing condition is 42.92, where in left lung it is 36.55. At 60 lpm, which depicts a fast breathing pattern, the maximum number of particles deposited in the targeted region i.e., wall position 2 as well as the deposition concentration is significantly higher than other flow rates considered here, as shown in Fig.4.10(c). The percentage of overall deposition for fast breathing condition is 76.69 where in the targeted position, the percentage is 36.30 and in the left lung, it is 30.49. During the slow breathing pattern, a fewer number of particles are deposited; the number of deposited particles increases noticeably with the increase of flow rate. It is also observed that some particles have deposited at the carinal angle of the first bifurcation. The microparticle inertia plays a vital role to deposit particles at the carinal angle. A lesser number of 4 µm particles are deposited at the first bifurcation, at the slow breathing pattern. The number of deposited particles at the carinal angle increases noticeably with the increase of flow rate. Fig. 4.10(d) shows the overall deposition efficiency for three different flow rates. The reason for these types of DE pattern is higher flow rates.

48 Chapter 4: Results and Discussion (a) (b)

(d) (c)

Figure 4.11 Particle diameter effect on particle transport outline and DE (%) for

position 2, 푀푛 = 2.5 푇, Q=60 lpm (a) 푑푝 = 2 휇푚; (b) 푑푝 = 4 휇푚; (c) 푑푝 = 6 휇푚; (d) overall deposition efficiency.

To investigate the deposition on a targeted region for different particle sizes, three different sizes of particles, 2 휇푚, 4휇푚, and 6 휇푚 are considered in Fig.4.11 for

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 49 Mn=2.5T, position 2, and Q=60 lpm. The deposition scenario evidently indicates that a significantly larger number of 2 μm diameter particles are deposited in the targeted lung region than any other region, compared to the 4 µm and 6 µm diameter particles.

Smaller diameter particles reach the targeted region by external magnetic field intensity due to lower inertia, despite fast flow rates. The total percentage of deposition for 2 μm particles is 38.45 whereas, at the targeted position, deposition percentage is

12.33 and for the targeted left lung it is 25.01 in Fig 4.11(a). Fig.4.11 (b) shows the deposition scenario for 4 µm particles. For 4 µm particle diameter, the overall deposition percentage is 47.396, whereas, at the targeted position, it is 36.30. The deposition pattern for 6 μm is shown in Fig.4.11(c) and the overall deposition percentage for 6 μm is 64.03 and targeted position percentage is 20.11. It is clear that the influence of the magnetic field on the magnetic drug carrier for 푑푝 = 4 μm is more noticeable in the target position than for other particle sizes, as is shown in Fig.4.11c.

Fig.4.11 (d) shows the overall deposition concentration is higher at large particle size.

Due to the inertial impaction of particles, it is expected that by increasing the particle diameter, the DE will be higher, which satisfies the present study desire. It is also observed that the DE is higher in targeted position 2 (left branch) than the other areas of the present lung model, which satisfies the aim of the present study.

50 Chapter 4: Results and Discussion

(a) (b)

Figure 4.12: Magnetic number effect (Flux value) on particle transport outline and DE

(%) for Position 2, 푑푝 = 4 휇푚, Q=60lpm,(a) 푀푛 = 0.181T;(b)푀푛 = 2.5 T; (c)푀푛 = 3 T; (d) deposition efficiency for magnetic number.

Figs. 4.12 (a, b, c) clarify the effects of a magnetic number for position 2 with 4 휇푚 diameter particle and 60 lpm flow rates. Fig. 4.12 (a) illustrates the lung airway deposition at the targeted position 2 for magnetic number of 0.181. The percentage of

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 51 number of deposition for magnetic number 0.181 T is 12.41. The deposited particle for magnetic number 2.5 T is shown in Fig. 4.12 (b) and the overall deposition percentage is 47.39. The overall deposition percentage for magnetic number 3 T is

51.63. It is estimated that increasing the magnetic number deliberately enhances the deposition on the targeted position. Fig. 4.12(d) shows the overall deposition for magnetic number intensity. Fig 4.12 shows that the increasing effect of the magnetic number maximum particle goes to the target region. Therefore, the larger magnetic number can play an important role in particulate deposition on the targeted region of the lung.

52 Chapter 4: Results and Discussion

(a) (b)

120

100

80 (c)

60 DE(%) 40

Magnet position

Figure 4.13: Effect of source position of magnet on particle transport outline and DE

(%) for 푑푝 = 4 휇푚, Q=30 lpm, 푀푛 = 2.5 푇, (a) Position 1; (b) Position 2;(c) deposition efficiency for magnetic source position.

Figs.4.13 (a, b) represent the effect of external magnetic source in two different positions for 4 휇푚 particle diameter, 30 lpm inhalation flow rate and 2.5 T magnetic number. Due to the position of the magnetic source, the drug particles tend to accelerate in the targeted position in the presence of the magnetic force. Fig.4.13 (a) illustrates the deposition scenario for magnetic intensity in position 1 and the overall deposition percentage is 99.33. Fig.4.13. (b) shows the respiratory deposition scenario

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 53 for Q=30 lpm and magnetic field for position 2. The overall percentage for magnetic source position 2 is 42.92. It is estimated that the deposition efficiency is decreased by increasing the distance from origin along the Z axis, which is shown in Fig.4.13(c).

Therefore, in this histogram, the maximum number of deposited particles is shown in the left lung and targeted position, which is an advantage of the current numerical model for specific region deposition.

40 40 2 60 lpm 35 35 (a) 4 (b) 30 lpm 30 30 6 15 lpm 25 25

20 20 DE(%) 15DE(%) 15 10 10 5 5 0 0

Particle Diameter Flow Rates

30 80 (c) 70 Position 1 25 3 (d) 60 Position 2 2.5 20 50 0.181

15 40 DE(%) DE(%) 30 10 20 5 10 0 0

position 1 position 2 Magnetic Number Magnetic source Position

Figure 4.14: Local deposition efficiency for (a) flow rates; (b) Particle diameter; (c) Magnetic number effect; (d) Magnetic source position. Generation 1 (g1), Left Generation 2 (lg2); Right Generation 2 (rg2).

54 Chapter 4: Results and Discussion Fig.4.14 symbolises the local DE for different flow rates, particle diameter; magnetic number and magnetic source position. Fig.4.14 (a) represents the regional deposition scenario for three different flow rates i.e. 15 lpm, 30 lpm and 60 lpm. The deposition percentage in targeted position (wall position 2) for these three different flow rates are

23.84, 4.027 and 36.30 respectively. The drug particle deposition concentration in the targeted position is higher than other region for 2 μm due to lower inertia. When the flow rate is fast i.e. 60 lpm and the magnetic number is 2.5 T, the maximum number of particles is deposited in wall position 2, which is the targeted position as shown in

Fig.4.14 (a). Fig.4.14 (b) shows the local deposition efficiency for three different particle diameters i.e. 2 μm, 4 μm and 6 μm. From Fig.4.14 (b) the local deposition percentage in targeted position for 2 μm particle diameter is 12.33, 4 μm particle diameter is 36.30 and 6 μm particle diameter is 20.11. For 4 μm particle diameter, the maximum number of particles is deposited in targeted position in Fig.4.14 (b). On the other hand, the overall deposition is higher for 6 μm particle diameter than other particle diameters due to larger inertia. Fig.4.14 (c) illustrates the local deposition scenario for three different magnetic numbers i.e. 0.181 T, 2.5 T, 3 T and percentages of deposition particles in targeted position (wall position 2) are 2.27, 36.30 and 4.14 respectively. Due to the large magnetic number, the overall deposition is higher for magnetic number 3 T. Fig.4.14 (d) shows the local deposition for two different magnetic source positions. When the magnetic field is in position 1, flow rate is medium (30 lpm), and for particle diameter 4 μm most of the particle is deposited on the wall position 1 and generation 1. Similarly, when the magnetic intensity is in position 2, the maximum number of particles is deposited in left branch and wall position 2. The deposition scenario shows higher deposition on left lung and targeted position in Fig.4.14.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 55 4.2 CASE STUDY 2: MAGNETIC NANOPARTICLE

4.2.1 COMPUTATIONAL DOMAIN AND MESH GENERATION:

The 2-generation lung symmetric model is constructed to calculate the complex flow field in a human lung. This 2- generation lung geometry contains 1.5 million elements and 0.54 million nodes. An inflation of 10 boundary layer mesh was constructed near the solid wall.

(a) (b)

Figure 4.15: (a) Anterior view of the 2-generation mesh with 0.54 million unstructured cells, (b) interior view and inflation layer mesh near to the wall, (c) inlet mesh, (d) outlet mesh of 2-generation lung model.

56 Chapter 4: Results and Discussion 4.2.2 GRID INDEPENDENCE TEST:

Due to the sensitive results of regional turbulence effects, a grid resolution test is performed for adequately refining and choosing the appropriate final mesh for this present study. This model is tested for different grid numbers as a function of maximum pressure, which is calculated on the outlet plane. The flow seems converged from the red point and it is conceivable to use any of the grid cells from this point.

However, 0.54 million nodes is adopted for the present simulations.

2 Maximum pressure (pascal) pressure Maximum 0 0 100000 200000 300000 400000 500000 600000 700000 800000

Grid Number

Figure 4.16: Maximum pressure grid convergence

4.2.3 MODEL VALIDATION:

A comprehensive validation has been performed for the present study. The present 2- generation nano-particle simulation result has been compared with various published results of CFD.

Fig.4.17 shows the nano-particle DE compared with experimental results of a double bifurcation model (G3-G5) of Kim (2002) . The results were validated for the first and second bifurcation of the present 2- generation model. The current model have also been compared with the CFD result of Zhang and Kleinstreuer (2004) for a different

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 57 inlet Reynolds number (Re = 200, 500 and 1000) and (Islam et al., 2017) for two different inlet Reynolds number (Re = 200, 550). Fig.4.17 (a) shows comparison of nano-particle deposition for the first bifurcation and Fig.4.17 (b) shows the deposition comparison for the second bifurcation. The present NPs DE shows good agreement with the published experimental data for both bifurcations.

(a) (b)

Figure 4.17. Nano-particle DE comparison with the experimental data of Kim (2002) and the CFD results of Zhang and Kleinstreuer (2004) and (Islam et al., 2017), in a double bifurcation model (G3-G5), (a) first bifurcation, and (b) second bifurcation.

Figure 4.18 Deposition fraction (DF) of Nano-particle comparison with the CFD results of Zhang and Kleinstreuer (2004) across different bifurcation for 30 lpm flow

rates in the bifurcation airway model.

58 Chapter 4: Results and Discussion Fig.4.18 shows the nano-particle DF compared with CFD results of a double bifurcation model of Zhang and Kleinstreuer (2004). The results were validated for 30 lpm flow rate and the first and second bifurcation of the present 2- generation model.

The present result DF is about the same for both bifurcation with the published result.

The present nano-particle DF shows good agreement with the published CFD data for both bifurcations.

Figure 4.19: Geometry specification of 2-generation model (Magnet position 2 has been set on the right lung). The 2- generation lung model specification and external magnetic source position has been indicated in Fig.4.19. Position 1 and Position 2 indicate the external magnetic field source. Magnet position 1 has been set just before the first bifurcation and position 2 has been set on the right lung, as are shown in Fig.4.19. The present model’s left and right side are indicated by lg2 (left generation 2) and rg2 (right generation 2).

4.2.4 POST PROCESSING RESULTS FOR MAGNETIC NANOPARTICLE

The present 2-generation lung airway model has been designed to calculate the nano-particle exact deposition in the targeted position and lung region. Fig.4.20 shows

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 59 the particle TD for flow rate variation along the two selected external magnetic field positions for 1-nm particle diameter and Mn=2.5 T.

(a) (b) (c)

(f) (d) (e)

120 (g) 100 7.5 lpm (g) 9 lpm 80 15 lpm 60

efficiency Deposition 20

0 Position 1 Position 2 Position of magnet

Figure 4.20: Effect of Flow Rates on particle transport outline for position 1 and position 2, Mn=2.5 T, dp=1-nm, (a) 7.5 lpm for position 1; (b) 7.5 lpm for position 2; (c) 9 lpm for position 1; (d) 9 lpm for position 2; (e) 15 lpm for position 1; (f) 15 lpm for position 2; (g) Overall deposition efficiency.

60 Chapter 4: Results and Discussion Fig.4.20 represents the deposition efficiency for three different breathing flow rates

(sleeping, resting and slow) at two different magnetic field positions (position 1 and position 2). Figs.4.20 (a, b) represent the deposition efficiency for 7.5 lpm flow rate for position 1 and position 2 respectively. At sleeping breathing condition (7.5 lpm),

NPs deposition at the targeted position 1 and position 2 are significantly increased more than any other region, as shown in Figs.4.20 (a, b). The total percentage of deposition for sleeping breathing condition, at position 1 and position 2 are 96.24 and

41.14. At 9 lpm, which represents the resting breathing condition, the total deposition percentage for position 1 and position 2 are 56.67 and 39.33, shown in Figs.4.20 (c, d). The total percentages of deposition during slow breathing condition (15 lpm), at position 1 and position 2, are 22.60 and 20.24, shown in Figs.4.20 (e, f). From the deposition scenario of 1-nm diameter particle is found that under the sleeping condition, a higher number of 1-nm particles are deposited in position 1 and position

2 than under other breathing conditions. Fig.4.20 (g) shows the overall deposition efficiency for three different flow rates. The overall deposition pattern shows that the

Brownian motion is effective for smaller flow rates. The effect of Brownian motion is that it increases with the decrease of flow rates. The overall deposition pattern for different flow rates of 1-nm diameter particles satisfies the general assumption of

Brownian motion and shows that depending on the lower flow rates, this Brownian motion is dominant in the upper airways. The DE scenario of MNPs, decreases with the increasing of flow rates because of low residence time.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 61 (a) (b) (c)

(d) (e) (f)

120 (g) 100 Mn=0.181 80 Mn=1.5 Mn=2.5 60

20 Deposition efficiency(%) Deposition 0 Position 1 Position 2 position of magnet

Figure 4.21: Effect of magnetic number on particle transport outline for Position 1 and position 2, 7.5 lpm, dp=1-nm, (a) Mn=0.181 T for position 1; (b) Mn=0.181T for position 2 ; (c) Mn=1.5 T for position 1; (d) Mn=1.5 T for position 2; (e) Mn=2.5 T for position 1; (f) Mn=2.5 T for position 2; (g) Overall deposition efficiency for magnetic position 1 and magnetic position 2.

62 Chapter 4: Results and Discussion Fig.4.21 clarifies the effects of magnetic number (magnetic intensity) at position 1 and position 2 with 1 -nm particle and 7.5 lpm flow rates. Figs.4.21 (a, b) shows the lung airways’ deposition scenario for magnetic number 0.181 T at the targeted position 1 and position 2. The number of total deposition percentages for magnetic number 0.181

T, at the targeted position 1 and position 2, are 74.01 and 32.41. The deposited particles for magnetic number 1.5 T are shown in Figs.4.21 (c, d). The overall percentages for magnetic number 1.5 T at the targeted position 1 and position 2 are 74.05 and 40.72.

Figs. 4.21 (e, f) show the Particle TD at targeted position 1 and position 2 for magnetic number 2.5. The overall deposition percentages for magnetic number 2.5 T, at the targeted position 1 and position 2, are 96.24 and 41.14. It is estimated that increasing the magnetic number deliberately enhances the deposition on the targeted position.

From the deposition scenario of 1-nm diameter particle is found that, under the effect of magnetic number 2.5 and flow rate 7.5 lpm, a higher number of 1-nm particles are deposited in position 1 and position 2 than for other magnetic numbers. Fig.4.21 (g) shows the overall deposition efficiency at the targeted position 1 and position 2 for three different magnetic numbers. Therefore, the larger magnetic number can play an important role in particulate deposition on the targeted region of the lung. The overall deposition pattern for 1-nm diameter particle effect of a magnetic number satisfies the general assumption of magnetic intensity. The DE of MNPs is estimated to enhance with the increase of the magnetic number (Oveis Pourmehran et al., 2016). According to the above MNPs’ deposition scenario, the deposition value at the targeted region

(right lung) is substantially greater than at the other region of lung (left lung). So, the targeting magnetic drug delivery technique satisfies the advantage of the current targeted drug delivery system.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 63

(a) (b)

Turbulent kinetic Energy

(e)

Figure 4.22: Particle Traces Coloured by Turbulent Kinetic Energy (k) (푚2/푆2) for 60 lpm, Mn=2.5 T and magnet position 2, (a) 1- nm; (b) 10- nm; (c) 50- nm; (d) 100- nm;

(e) 500- nm.

64 Chapter 4: Results and Discussion Fig.4.22 shows the particle tracing coloured by Turbulent Kinetic Energy (TKE) at magnet position 2, 60 lpm flow rates and Mn=2.5 T for different particle diameters.

The path of a particle is a unique path for a particle injected at a given location (inlet) in the flow. Particle trajectories are not deterministic and two identical particles, injected from a single point at different times, may follow separate trajectories due to the random nature of the instantaneous fluid velocity. It is the fluctuating component of the fluid velocity that causes the dispersion of particles in a turbulent flow. In turbulent flow, the speed of the fluid at a point is continuously undergoing changes in both magnitude and direction. The intensity of turbulence is measured by TKE. TKE provides the reduction of turbulence with time. This causes the energy to be dissipated from large vortices to small ones. It is recognised that for TKE, airflow rapidly goes faster in the compression region and as a result, the maximum number of particles is deposited on that region. The turbulent kinetic energy is calculated as:

3 (4.1) 푘 = [퐼 max (푈 , |푈 |, 푈 )]2 2 푑푒푓 푠 퐼퐺 휔

퐼푑푒푓 is the default turbulent intensity, 푈푠 is a minimum velocity, 푈퐼퐺 is the velocity initial guess and 푈휔 is the product of the simulation average length scale and the rotation rate.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 65

(a) (b)

Particle residence time

(e)

Figure 4.23: Particle Traces Coloured by particle residence time at magnetic position 2 for 60 lpm and Mn=2.5 T (a) 1- nm; (b) 10- nm; (c) 50- nm; (d) 100- nm; (e) 500- nm.

66 Chapter 4: Results and Discussion

Fig.4.23 shows the particle tracing coloured by particle residence time at magnet position 2, 60 lpm flow rates and Mn=2.5 T for different particle diameters. Figs.4.23

(a, b, c, d, and e) show the particle residence time for 1-nm, 10-nm, 50-nm, 100-nm, and 500-nm particle diameter. Residence time is the average amount of time spent in a control volume by the particles of a fluid. For the medical field, the amount of time that a drug spends in the body is usually referred to by residence time. This is dependent on the amount of the drug and an individual’s body size. The residence time is different for each and every drug based on its chemical composition and technique of administration. Some of the drug molecules stay in this system for a very short time, while others may remain for a lifetime. To find a mean residence time, groups of aerosolised drug particles are tracked and plotted due to hard tracing of residence time for individual particles. Comparing the drug particle residence time in the present study, Fig.4.23 (e) shows that 500-nm MNPs diameter spend more time inside the lung than other particle MNPs diameter residence time.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 67 120

7.5 lpm 100 9 lpm 15 lpm 80 60 lpm

40 Deposition efficiency Deposition

0 position 1 position 2 position 1 position 2 position 1 position 2 position 1 position 2 1 nm 50 nm 100 nm 500 nm Diameter and Magnet position

Figure 4.24: Deposition Efficiency comparisons for nano particles of various diameter and flow rates at position 1 and position 2 for magnetic number 2.5 T.

7.5 lpm 9 lpm 15 lpm 60 lpm

Diameter Posi 1 Posi 2 Posi 1 Posi 2 Posi 1 Posi 2 Posi 1 Posi 2

1-nm 96.24% 41.14% 56.67% 39.33% 22.60% 20.24% 63.97% 39.90%

50- nm 26.20% 13.87% 30.77% 26.82% 70.72% 18.20% 86.91% 41.59%

100- nm 30.79% 11.45% 21.80% 7.70% 44.40% 13.54% 62.81% 52.71%

500- nm 30.83% 10.93% 47.49% 44.80% 84.52% 23.50% 78.35% 70.83%

68 Chapter 4: Results and Discussion The NPs DE comparison in two different magnetic field positions of the 2-generation symmetric lung model at different flow rates and diameter are shown in Fig.4.24. The

DE at two different magnetic field positions is different for particle diameter and flow rates. Overall DE comparison shows higher deposition concentration in the magnetic field position 1 than position 2. Fig.4.24 clearly shows the distinct deposition for different diameter particles at different flow rates for magnetic number 2.5 T. Fig.4.24 also shows the maximum number of particles deposited in position 1 is 96.24% for flow rate 7.5 lpm and 1-nm particle diameter. On the other hand, at the targeted position 2, the number of deposition percentage is at maximum (70.83%) for flow rate

60 lpm and particle diameter 500-nm. The deposition efficiency trend line for flow rates 7.5 lpm shows that when the magnetic source is in position 1, the maximum number of particles is deposited for 1-nm diameter than for other particle sizes.

Table 4.1 shows the total flow rate and diameter TD percentage comparison across two different magnetic field positions for magnetic number 2.5 T. Table 4.1 also shows that the total flow of deposition concentration is higher in magnetic field position 1 than in position 2.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 69 120 1 nm 10 nm 100 50 nm 100 nm 80 500 nm

40 Deposition Efficiency Deposition 20

0 position 1 position 2 position 1 position 2 position 1 position 2 mn=0.18 mn=1.5 mn=2.5

Magnet Position

Figure 4.25: Deposition Efficiency comparisons for nano particles of various diameters and magnetic number at position 1 and position 2 for 15 lpm flow rates.

Table 4.2. Respiratory particle TD comparisons at two different targeted positions for

0.181 T, 1.5 T, and 2.5 T magnetic number as a function of 15lpm breathing

airflow rates and 1-, 50-, 100- and 500-nm diameter particle.

Mn=0.181 T Mn=1.5 T Mn=2.5 T

Diameter Position Position Position 1 Position Position 1 Position 2

1 2 2

1 nm 95.27% 52.82% 51.11% 25.08% 22.60% 20.24%

10 nm 90.22% 15.04% 64.45% 13.62% 27.46% 15.04%

50 nm 92.49% 27.25% 49.13% 14.38% 70.72% 18.20%

100 nm 99.40% 17.14% 77.09% 15.42% 44.40% 13.54%

500 nm 91.64% 0.019% 97.72% 23.27% 84.52% 23.50%

70 Chapter 4: Results and Discussion Fig.4.25 clarifies the effects of magnetic number for targeted drug delivery at magnetic position 1 and position 2 with 15 lpm flow rates and 1-nm, 50-nm, 100-nm and 500- nm diameter particles. The overall deposition is significantly higher for small magnetic number 0.181 T than other magnetic numbers. The DE trend line for 1-nm particle diameter for 15 lpm breathing condition shows a linear trend line for position 1 and position 2. The deposition trend line of 1-nm, 10-nm and 100-nm particle is significantly increased in small magnetic numbers for both magnetic field positions, then decreases as magnetic number increases, shown in Fig.4.25. The deposition trend lines for 50-nm and 500-nm are fluctuating during the changes of magnetic number.

Due to the position of magnetic source, the MNPs tend to accelerate along the targeted position in the presence of magnetic intensity. These specific findings can play an important role in targeted drug delivery.

Table 4.2. Shows the overall particle TD comparisons at two different targeted positions and different particle diameters for 0.181 T, 1.5 T, and 2.5 T magnetic numbers as a function of 15 lpm slow breathing airflow rates. Therefore, the smaller magnetic number can play an important role in particulate deposition on the targeted region of lung during slow breathing condition.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 71 100 60 90 Flow Rate 7.5 lpm and Mn 2.5 Flow Rate 9 lpm and Mn 2.5 50 80 g1 g1 (b) (a) rg2 70 rg2 40 wall position 1 60 wall position 1 lg2 50 lg2 30 40 20 30 20 10

10 Deposition Efficiency Deposition

0 Efficiency Deposition 0

position 1 position 2 position 1 position position 1 position 2 position 2 position 1 position 1 position 2 position 2 position

position 1 position 2 position 1 position 2 position 1 position 2 position 1 position 2 position 1 position 2 position 1- nm 10-nm 50-nm 100-nm 500-nm 1-nm 10-nm 50-nm 100- 500- Diameter and Magnet Position nm nm Diameter and Magnet position

80 Flow Rate 15 lpm and Mn 2.5 90 Flow Rate 60 lpm and Mn 2.5 70 g1 80 g1 60 70 rg2 rg2 (c) wall position 1 (d) 50 wall position 1 60 lg2 40 lg2 50 40 30 30 20 20

10 10

Deposition Efficiency Deposition Deposition Efficiency Deposition

0 0

position 2 position position 1 position 2 position 1 position 1 position 2 position 1 position 2 position 1 position 2 position

position 1 position 2 position 1 position 2 position 1 position 2 position 1 position 2 position 1 position 2 position 1- nm 10- nm 50- nm 100- nm 500- nm 1- nm 10- nm 50- nm 100- nm500- nm Diameter and Magnet Position Diameter and Magnet Position

Figure 4.26: Regional particle deposition efficiency in each zone at different particle sizes, magnet position, magnetic number 2.5 T and inhalation rates. Generation 1 (g1), Left Generation 2 (lg2), Right Generation 2 (rg2).

In order to classify the regional deposition of targeted delivery of NPs, the airway geometry is specified in three regions according to Fig.4.26 and local deposition efficiency in each zone at various inhalation flow rates, particle sizes, and magnetic field position are calculated and shown in Fig.4.26. Figs.4.26 (a, b, c, d) symbolise the local deposition efficiency for 7.5 lpm, 9lpm, 15 lpm and 60 lpm flow rates and magnetic number 2.5. Due to external magnetic field being set on the right lung and

72 Chapter 4: Results and Discussion before the first bifurcation, the deposition percentage is significantly increased in generation 1 of the right lung (rg2). For sleeping (7.5 lpm) and resting (9 lpm) conditions, the regional deposition concentration is higher in generation 1 of 1-nm particle diameters than other regions in Fig.4.26 (a, b). Fig.4.26 (c) shows the region deposition efficiency at two different magnetic positions for slow breathing condition

(15 lpm) and magnetic number 2.5 T. This figure shows that maximum regional deposition is held in generation 1 for 500-nm. Fig.4.26 (d) shows the overall regional deposition for fast breathing condition (60 lpm) and magnetic number 2.5T. During the fast breathing pattern, the maximum number of regional depositions is calculated in generation 1 for 50-nm particles. The present 2-generation symmetrical airway model allows comprehensive NPs deposition data at different regions, which could potentially increase an understanding of targeted region deposition and specifically, the transport of magnetic nanoparticles to the targeted drug delivery system.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 73 Chapter 5 : CONCLUSIONS

5.1 CONCLUSIONS

In this thesis, 2-generation lung models were developed. An advance meshing technique was used to predict the more accurate magnetic drug particle TD in the specific region of the human lung. Pharmaceutical aerosol particle TD has been investigated for different magnetic field positions, magnetic numbers, particle diameters and various breathing conditions.

Magnetic aerosol particle transport and deposition has been investigated for the targeted region of the lung for two different magnetic field positions. A symmetrical model of the lung is constructed from the geometry generation software of solid works and ANSYS 18. Two different magnetic field positions are developed for investigating the targeting of drug delivery of magnetic aerosol particles. A new deposition technique is observed for the present lung model, which could minimise the unwanted side effects and improve the overall DE of the targeted drug delivery to the specific region of lung airways. The study also depicts that magnetic field, magnetic number and inhalation flow rates greatly influence the magnetic aerosol particle deposition in the targeted region of the lung.

Magnetic microparticle TD in the specific position of a 2-generation symmetric bronchial tree model by external magnetic field has been performed for the first time.

The advanced numerical model illustrates the magnetic aerosol particle TD phenomena in the specific region of lung airways. Detailed deposition patterns at two different magnetic field positions are performed for different magnetic numbers, breathing conditions and a wide range of monodisperse particles. Numerical results

74 Chapter 5: Conclusion illustrate that magnetic aerosol particle DE in the left lung (targeted region) is higher than the right lung. A different deposition mechanism is observed and the findings of this study will help the pharmaceutical industry to design new drug delivery devices.

The study will increase the efficiency of the targeted drug delivery to the specific region of a lung model.

A comprehensive MNPs TD analysis has been performed in the targeted region of a 2-generation lung model. Sleeping, resting, slow breathing condition and fast breathing physical conditions are considered, to predict the magnetic targeting of drug delivery in the specific region of the lung. MNPs deposition efficiency in the specific region of 3-generation lung have been performed and a non-linear trend is observed, which could increase the understanding of the health risk assessment of lung diseases.

A significant deposition efficiency is observed in two different specific positions of the lung for various magnetic numbers, physical conditions and particle diameters, and this could potentially help the development of future therapeutics. The findings of the present study would improve the knowledge of magnetic targeting drug delivery and could potentially help in the specific region of drug delivery.

To sum up, the advanced numerical model and the findings of the present study will advance the pharmaceutical drug delivery system. The present findings will help to design drug delivery systems for the pharmaceutical companies to deliver drugs to specific regions of the lung. These particular findings may be used to develop a more realistic drug delivery system in a targeted position of the human lung.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 75 5.2 LIMITATIONS AND FUTURE STUDY

The present advanced CFD approach still has some limitations. Some specific limitations and future recommendations are listed below:

i) The present model used 2-generation geometry. A realistic model, more

generations and a patient-specific sample model need to be used for

better prediction of magnetic particle TD in the specific region of the

human lung.

ii) The present model considers only steady state and does not consider the

transient state. The transient case may increase the understanding of

particle deposition in the specific region of the human lung.

iii) Only monodisperse magnetic particles are considered in this study.

Polydisperse particles could be considered for better prediction.

iv) This study only considers one-way inhalation to predict the magnetic

particle TD in the lung airways. The two-way inhalation and exhalation

effects might aid in the understanding of particle TD.

v) The present magnetic particle TD study did not consider any breath-

holding effects on deposition in the targeted position for different flow

rates.

76 Chapter 5: Conclusion BIBLIOGRAPHY

Ally, J., Martin, B., Behrad Khamesee, M., Roa, W., & Amirfazli, A. (2005). Magnetic targeting of aerosol particles for cancer therapy. Journal of Magnetism and Magnetic Materials, 293(1), 442-449. Anseth, J. W., Goffin, A. J., Fuller, G. G., Ghio, A. J., Kao, P. N., & Upadhyay, D. (2005). Lung surfactant gelation induced by epithelial cells exposed to air pollution or oxidative stress. American journal of respiratory cell and molecular biology, 33(2), 161-168. Arruebo, M., Fernández-Pacheco, R., Ibarra, M. R., & Santamaría, J. (2007). Magnetic nanoparticles for drug delivery. NanoToday, 2(3), 22-32. Asgharian, B., Hofmann, W., & Bergmann, R. (2001). Particle deposition in a multiple-path model of the human lung. Aerosol Science & Technology, 34(4), 332-339. Asgharian, B., & Price, O. T. (2008). Deposition of Ultrafine (NANO) Particles inthe Human Lung. Inhal. Toxicol. 19, 1045–1054. Australian Government. Lung cancer statistices. Retrieved August 8, 2017, from https://lung-cancer.canceraustralia.gov.au/statistics. Azarmi, S., Roa, W. H., & Löbenberg, R. (2008). Targeted delivery of nanoparticles for the treatment of lung diseases. Advanced drug delivery reviews, 60(8), 863- 875. Bowes, S. M., & Swift, D. L. (1989). Deposition of Inhaled Particles in the Oral Airway During Oronasal Breathing. Aerosol Science and Technology, 11(2), 157-167. Brown, P. H., Matusiewicz, S. P., Shearing, C., Tibi, L., Greening, A. P., & Crompton, G. K. (1993). Systemic effects of high dose inhaled steroids: comparison of beclomethasone dipropionate and budesonide in healthy subjects. Thorax, 48(10), 967-973. Carpenter, J. F., Pikal, M. J., Chang, B. S., & Randolph, T. W. (1997). Rational design of stable lyophilized protein formulations: some practical advice. Pharmaceutical research, 14(8), 969-975. Chan, T. L., & Lippmann, M. (1980). Experimental measurements and empirical modelling of the regional deposition of inhaled particles in humans. American Industrial Hygiene Association Journal, 41(6), 399-409. Cheng, Y.-S., Zhou, Y., & Chen, B. T. (2010). Particle deposition in a cast of human oral airways. Aerosol Science and Technology, 31(4), 286-300. Choi, J.-I., & Kim, C. S. (2007). Mathematical analysis of particle deposition in human lungs: an improved single path transport model. Inhalation toxicology, 19(11), 925-939. Chomoucka, J., Drbohlavova, J., Huska, D., Adam, V., Kizek, R., & Hubalek, J. (2010). Magnetic nanoparticles and targeted drug delivering. Pharmacological Research, 62(2), 144-149. Cohen, S. D. (2009). The development of a discrete particle model for 3D unstructured grids: application to magnetic drug targeting . (MSc MSc thesis), Delft University of Technology. Cregg, P. J., Murphy, K., & Mardinoglu, A. (2008). Calculation of nanoparticle capture efficiency in magnetic drug targeting. Journal of Magnetism and Magnetic Materials, 320(23), 3272-3275.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 77 D. Bennett William, S., B. J., L., Z. K., Shu-Chieh Hu, Gerhard Scheuch, & Knut, S. (2004). Targeting delivery of aerosols to different lung regions. Journal of aerosol medicine, 15 Issue 2 Dahmani, C., Gotz, S., Weyh, T., Renner, R., Rosenecker, M., & Rudolph, C. (2009). Respiration triggered magnetic drug targeting in the lungs. Paper presented at the Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE. Dames, P., Gleich, B., Flemmer, A., Hajek, K., Seidl, N., Wiekhorst, F., . . . Rudolph, C. (2007). Targeted delivery of magnetic aerosol droplets to the lung. Nature nanotechnology, 2, 495. Darquenne, C. (2012). Aerosol deposition in health and disease. J Aerosol Med Pulm Drug Deliv, 25(3), 140-147. doi:10.1089/jamp.2011.0916 Denison, D., Waller, J., Turton, C., & Sopwith, T. (1982). 5. Breathing in and breathing out. British journal of diseases of the chest, 76, 237-252. Dikanskii, Y. I. (1998). Magnetosensitive Aerosols and Prospects of Their Application. Magnetohydrodynamics, 34(3), 212-215. Dolovich, M. B., Ahrens, R. C., Hess, D. R., Anderson, P., Dhand, R., Rau, J. L., . . . Guyatt, G. (2005). Device selection and outcomes of aerosol therapy: evidence-based guidelines: American College of Chest Physicians/American College of Asthma, Allergy, and Immunology. CHEST Journal, 127(1), 335- 371. Dolovich, M. B., & Dhand, R. (2011). Aerosol drug delivery: developments in device design and clinical use. The Lancet, 377(9770), 1032-1045. Emmett, P. C., Aitken, R. J., & Hannan, W. J. (1982). Measurements of the total and regional deposition of inhaled particles in the human respiratory tract. Journal of Aerosol Science, 13(6), 549-560. Everard, M. (2001). Guidelines for devices and choices. Journal of aerosol medicine, 14(1, Supplement 1), 59-64. Fernández-Pacheco, R., Marquina, C., Gabriel Valdivia, J., Gutiérrez, M., Soledad Romero, M., Cornudella, R., . . . Ricardo Ibarra, M. (2007). Magnetic nanoparticles for local drug delivery using magnetic implants. Journal of Magnetism and Magnetic Materials, 311(1), 318-322. Goel, A., Baboota, S., Sahni, J. K., & Ali, J. (2013). Exploring targeted pulmonary delivery for treatment of lung cancer. Int J Pharm Investig, 3(1), 8-14. doi:10.4103/2230-973x.108959 Goetz, S. M., Dahmani, C., Rudolph, C., & Weyh, T. (2010). First theoretic analysis of magnetic drug targeting in the lung. IEEE Transactions on Biomedical Engineering, 57(9), 2115-2121. Gray, H., & Goss, C. M. (1878). Anatomy of the human body (Vol. 8): Lea & Febiger. Haverkort, J. (2008). Analytical and computational analysis of magnetic drug targeting in simplified and realistic arterial geometries. Delft University of Technology. Heyder, J. (2004). Deposition of inhaled particles in the human respiratory tract and consequences for regional targeting in respiratory drug delivery. Proceedings of the American Thoracic Society, 1(4), 315-320. Hofmann, W. (2011). Modelling inhaled particle deposition in the human lung—a review. Journal of Aerosol Science, 42(10), 693-724. Hofmann, W., Morawska, L., Winkler-Heil, R., & Moustafa, M. (2009). Deposition of combustion aerosols in the human respiratory tract: Comparison of theoretical

78 Bibliography predictions with experimental data considering nonspherical shape. Inhalation toxicology, 21(14), 1154-1164. Human body. Reaspiratory system diagram. Retrieved April 6, 2017, from http://www.buzzle.com/images/diagrams/human-body/respiratory-system- diagram.jpg. (2017). Ionescu, C. M. (2013). The human respiratory system The Human Respiratory System (pp. 13-22): Springer. Islam, M. S., Saha, S. C., Sauret, E., Gemci, T., Yang, I. A., & Gu, Y. T. (2017). Ultrafine particle transport and deposition in a large scale 17-generation lung model. Journal of biomechanics, 64, 16-25. Kasper, G. (1982). Dynamics and measurement of smokes. I Size characterization of nonspherical particles. Aerosol Science and Technology, 1(2), 187-199. Kim, C. S. (2002). Ultrafine particle deposition in a double bifurcation tube with human G3–G5 airway geometry. US EPA internal report. Kinnula, V. L., & Crapo, J. D. (2003). Superoxide dismutases in the lung and human lung diseases. American Journal of Respiratory and Critical Care Medicine, 167(12), 1600-1619. Kleinstreuer, C., Zhang, Z., Li, Z., Roberts, W. L., & Rojas, C. (2008). A new methodology for targeting drug-aerosols in the human respiratory system. International Journal of Heat and Mass Transfer, 51(23), 5578-5589. Köping‐Höggård, M., Issa, M. M., Köhler, T., Tronde, A., Vårum, K. M., & Artursson, P. (2005). A miniaturized nebulization catheter for improved gene delivery to the mouse lung. The journal of gene medicine, 7(9), 1215-1222. Kumar, A., Jena, P. K., Behera, S., Lockey, R. F., Mohapatra, S., & Mohapatra, S. (2010). Multifunctional magnetic nanoparticles for targeted delivery. Nanomedicine: Nanotechnology, Biology and Medicine, 6(1), 64-69. Kumar, H., Tawhai, M. H., Hoffman, E. A., & Lin, C.-L. (2009). The effects of geometry on airflow in the acinar region of the human lung. Journal of biomechanics, 42(11), 1635-1642. Kuzmov, A., & Minko, T. (2015). Nanotechnology approaches for inhalation treatment of lung diseases. Journal of Controlled Release, 219(Supplement C), 500-518. Li, A., & Ahmadi, G. (1992). Dispersion and deposition of spherical particles from point sources in a turbulent channel flow. Aerosol science and technology, 16(4), 209-226. Li, N., Hao, M., Phalen, R. F., Hinds, W. C., & Nel, A. E. (2003). Particulate air pollutants and asthma: a paradigm for the role of oxidative stress in PM- induced adverse health effects. Clinical Immunology, 109(3), 250-265. Lin, J.-J., Chen, J.-S., Huang, S.-J., Ko, J.-H., Wang, Y.-M., Chen, T.-L., & Wang, L.- F. (2009). Folic acid–Pluronic F127 magnetic nanoparticle clusters for combined targeting, diagnosis, and therapy applications. Biomaterials, 30(28), 5114-5124. Lintermann, A., & Schröder, W. (2017). Simulation of aerosol particle deposition in the upper human tracheobronchial tract. European Journal of Mechanics - B/Fluids, 63, 73-89. Lippmann, M., & Albert, R. E. (1969). The Effect of Particle Size on the Regional Deposition of Inhaled Aerosols in the Human Respiratory Tract. American Industrial Hygiene Association Journal, 30(3), 257-275. Lübbe, A. S., Alexiou, C., & Bergemann, C. (2001). Clinical Applications of Magnetic Drug Targeting. Journal of Surgical Research, 95(2), 200-206.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 79 Lung diseases. Environmental lung diseases. Retrieved April 6, 2017, from http://www.merckmanuals.com/home/lungand-airway- disorders/environmental-lung-diseases/overview-of-environmental- lungdiseases. Ma, B., & Lutchen, K. R. (2006). An anatomically based hybrid computational model of the human lung and its application to low frequency oscillatory mechanics. Annals of biomedical engineering, 34(11), 1691-1704. Ma, B., & Lutchen, K. R. (2009). CFD simulation of aerosol deposition in an anatomically based human large–medium airway model. Annals of biomedical engineering, 37(2), 271. Mansour, H. M., Rhee, Y.-S., & Wu, X. (2009). Nanomedicine in pulmonary delivery. Int J Nanomedicine, 4, 299-319. Matthew Hoffman, M. (2014). Picture of the Lungs. Retrieved from https://www.webmd.com/lung/picture-of-the-lungs#1. Mishra, B., Patel, B., B., Tiwari, & Sanjay. (2010). Colloidal nanocarriers: a review on formulation technology, types and applications toward targeted drug delivery. Nanomedicine: Nanotechnology, Biology and Medicine, 6(1), 9-24. Mortensen, N. P., Durham, P., & Hickey, A. J. (2014). The role of particle physico- chemical properties in pulmonary drug delivery for tuberculosis therapy. Journal of microencapsulation, 31(8), 785-795. Newman, S. P. (1985). Aerosol deposition considerations in inhalation therapy. Chest, 88(2), 152S-160S. Pankhurst, Q., Connolly, J., & Jones, S. J Dobson(2003). Applications of magnetic nano-‐particles in biomedicine. J. Phys. D: Appl. Phys, 36. Patton, J. S., & Byron, P. R. (2007). Inhaling medicines: delivering drugs to the body through the lungs. Nature Reviews Drug Discovery, 6(1), 67-74. Plank, C. (2008). Nanomagnetosols: magnetism opens up new perspectives for targeted aerosol delivery to the lung. Trends in biotechnology, 26(2), 59-63. Pourmehran, O., Gorji, T. B., & Gorji-Bandpy, M. (2016). Magnetic drug targeting through a realistic model of human tracheobronchial airways using computational fluid and particle dynamics. Biomechanics and Modeling in Mechanobiology, 15(5), 1355-1374. doi:10.1007/s10237-016-0768-3 Pourmehran, O., Rahimi-Gorji, M., Gorji-Bandpy, M., & Gorji, T. B. (2015). Simulation of magnetic drug targeting through tracheobronchial airways in the presence of an external non-uniform magnetic field using Lagrangian magnetic particle tracking. Journal of Magnetism and Magnetic Materials, 393, 380- 393. Rahimi-Gorji, M., Gorji, T. B., & Gorji-Bandpy, M. (2016). Details of regional particle deposition and airflow structures in a realistic model of human tracheobronchial airways: two-phase flow simulation. Computers in Biology and Medicine, 74, 1-17. Ratnovsky, A., Elad, D., & Halpern, P. (2008). Mechanics of respiratory muscles. Respiratory physiology & neurobiology, 163(1), 82-89. Respiratory system. Retrieved April 6, 2017, from http://www.livescience.com/22616-respiratorysystem.html. Roa, W. H., Azarmi, S., Al-Hallak, M. H. D. K., Finlay, W. H., Magliocco, A. M., & Löbenberg, R. (2011). Inhalable nanoparticles, a non-invasive approach to treat lung cancer in a mouse model. Journal of Controlled Release, 150(1), 49-55. Saffman, P. (1965). The lift on a small sphere in a slow shear flow. Journal of fluid mechanics, 22(02), 385-400.

80 Bibliography Saillaja AK. (2014). Drug. Anal., 2. pp. 275-279. . Salzman, G. A., & Pyszczynski, D. R. (1988). Oropharyngeal candidiasis in patients treated with beclomethasone dipropionate delivered by metered-dose inhaler alone and with Aerochamber. Journal of allergy and clinical immunology, 81(2), 424-428. Scheuch, G., Kohlhaeufl, M. J., Brand, P., & Siekmeier, R. (2006). Clinical perspectives on pulmonary systemic and macromolecular delivery. Advanced drug delivery reviews, 58(9), 996-1008. Selting, K., Waldrep, J. C., Reinero, C., Branson, K., Gustafson, D., Kim, D. Y., . . . Dhand, R. (2008). Feasibility and safety of targeted cisplatin delivery to a select lung lobe in dogs via the AeroProbe® intracorporeal nebulization catheter. Journal of aerosol medicine and pulmonary drug delivery, 21(3), 255- 268. Sharma, S., Kumar, R., & Gaur, A. (2015). A Model for Magnetic Nanoparticles Transport in a Channel for Targeted Drug Delivery. Procedia Materials Science, 10(Supplement C), 44-49. Shubayev, V. I., Pisanic, T. R., & Jin, S. (2009). Magnetic nanoparticles for theragnostics. Advanced drug delivery reviews, 61(6), 467-477. Sioutas, C., Delfino, R. J., & Singh, M. (2005). Exposure assessment for atmospheric ultrafine particles (UFPs) and implications in epidemiologic research. Environmental health perspectives, 947-955. Smaldone, G. C. (2006). Advances in aerosols: adult respiratory disease. Journal of aerosol medicine, 19(1), 36-46. Soni, B., & Aliabadi, S. (2013). Large-scale CFD simulations of airflow and particle deposition in lung airway. Computers & Fluids, 88, 804-812. Stahlhofen, W., J.Gebhart, & Heyder, J. (1980). Experimental determination of the regional deposition of aerosol particles in the human respiratory tract. American Industrial Hygiene Association Journal, 41(6), 385-398. Stepp, P., & Thomas, F. (2009). In vivo interactions of magnetic nanoparticles with the blood–brain barrier. Journal of Magnetism and Magnetic Materials, 321(10), 1591-1593. Stocke, N. A., Meenach, S. A., Arnold, S. M., Mansour, H. M., & Hilt, J. Z. (2015). Formulation and characterization of inhalable magnetic nanocomposite microparticles (MnMs) for targeted pulmonary delivery via spray drying. International Journal of Pharmaceutics, 479(2), 320-328. Sun, C., Lee, J. S. H., & Zhang, M. (2008). Magnetic nanoparticles in MR imaging and drug delivery. Advanced drug delivery reviews, 60(11), 1252-1265. Taherian, S., Rahai, H., & Waddington, T. (2011). CFD modeling and analysis of pulmonary airways/particles transport and deposition. Paper presented at the 41st AIAA Fluid Dynamics Conference and Exhibit. Tomlinson, S., Tilley, D., & Burrows, C. (1994). Computer simulation of the human breathing process. IEEE Engineering in Medicine and Biology Magazine, 13(1), 115-124. Tsuda, A., Henry, F. S., & Butler, J. P. (2013). Particle transport and deposition: basic physics of particle kinetics. Comprehensive Physiology. Weibel, E. R. (1963). Geometric and dimensional airway models of conductive, transitory and respiratory zones of the human lung Morphometry of the human lung (pp. 136-142): Springer. White, F. M. (2003). Fluid mechanics. 5th. Boston: McGraw-Hill Book Company.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 81 Wilczewska, A. Z., Niemirowicz, K., Markiewicz, K. H., & Car, H. (2012). Nanoparticles as drug delivery systems. Pharmacological Reports, 64(5), 1020-1037. Zhang, Z., & Kleinstreuer, C. (2004). Airflow structures and nano-particle deposition in a human upper airway model. Journal of Computational Physics, 198(1), 178-210.

82 Bibliography APPENDICES

In the main chapter 4, the result of magnetic micro particle and magnetic nano particle have been presented and this appendices chapter shows some sensitive result for case study 1 (magnetic micro particle) and case study 2 (magnetic nano particle).

A: CASE STUDY 1 (MAGNETIC MICRO PARTICLE)

A1: MESH GENERATION

Figure A.1: (a) interior view of the 2-generation mesh.

This 2-generation lung geometry contains 450,429 elements and 179,660 nodes. A proper grid refinement test has been conducted and the final geometry contains

179,660 nodes for magnetic micro particle simulations.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 83 A2: FLOW RATES EFFECT

(a) (b)

Figure A.2: Effect of flow rates on particle transport outline and DE (%) for Position

2, 푑푝 = 4 휇푚, 푀푛 = 0.25 푇 , (a) 15 lpm; (b) 30 lpm; (c) 60 lpm; (d) Total deposition efficiency in terms of flow rates.

Figs. A. 2: (a, b, c) represent the deposition efficiency for three different breathing flow rates (slow, medium and fast) i.e., 15 lpm, 30 lpm and 60 lpm respectively when the magnetic number, 푀푛 = 0.25 T, magnetic source position is in position 2 and the particle diameter is 4 휇푚.

84 Appendices A3: PARTICLE DIAMETER EFFECT

(a) (b)

(d)

(c)

Figure A.3: Effect of particle diameter on particle transport outline and DE (%) for

Position 2, 푀푛 = 0.25 푇, Q=60 lpm (a) 푑푝 = 2 휇푚; (b) 푑푝 = 4 휇푚; (c) 푑푝 = 6 휇푚; (d) deposition efficiency.

Figs. A. 3: (a, b, c) represent the deposition efficiency for three different micro particle diameter i.e., 2 μm, 4 μm and 6 μm respectively when the magnetic number, 푀푛 =

0.25 T, magnetic source position is in position 2 and the flow rates is 60 lpm.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 85 A4: MAGNETIC FIELD (POSITION) EFFECT

(a) Position 1 (b)

Position 2

Figure A.4: Effect of magnetic field on particle TD outline for (a) position 1; (b) particle traces by particle id for magnet position 2.

Figure A.5: Magnitude of 퐵⃗⃗ (magnetic flux density) vector for position 2.

86 Appendices B: CASE STUDY 2 (MAGNETIC NANO PARTICLE)

B1: EFFECT OF FLOW RATES ON PARTICLE TD FOR MAGNETIC FIELD POSITION1, MN=2.5 AND DIFFERENT PARTICLE DIAMETER

Figure A.6: Effect of flow rates on particle transport outline for particle diameter 1-nm, 10- nm, 50-nm,100-nm,500-nm, position 1, Mn=2.5T, (a) 1-nm for 7.5 lpm; (b) 10-nm for 7.5 lpm; (c) 50-nm for 7.5 lpm; (d) 100-nm for 7.5 lpm; (e) 500-nm for 7.5 lpm; (f) 1-nm for 9 lpm; (g) 10-nm for 9 lpm; (h) 50-nm for 9 lpm; (i) 100-nm for 9 lpm; (j) 500-nm for 9 lpm; (k) 1-nm for 15 lpm; (l) 10-nm for 15 lpm; (m) 50-nm for 15 lpm; (n) 100-nm for 15 lpm; (o) 500-nm for 15 lpm; (p) 1-nm for 60 lpm; (q) 10-nm for 60 lpm; (r) 50-nm for 60 lpm; (s) 100-nm for 60 lpm; (t) 500-nm for 60 lpm.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 87 B2: EFFECT OF FLOW RATES ON PARTICLE TD FOR MAGNETIC FIELD POSITION 2, MN=2.5 AND DIFFERENT PARTICLE DIAMETE

Figure A.7: Effect of flow rates on particle transport outline for particle diameter 1-nm, 10- nm, 50-nm,100-nm,500-nm, position 2, Mn=2.5T, (a) 1-nm for 7.5 lpm; (b) 10-nm for 7.5 lpm; (c) 50-nm for 7.5 lpm; (d) 100-nm for 7.5 lpm; (e) 500-nm for 7.5 lpm; (f) 1-nm for 9 lpm; (g) 10-nm for 9 lpm; (h) 50-nm for 9 lpm; (i) 100-nm for 9 lpm; (j) 500-nm for 9 lpm; (k) 1-nm for 15 lpm; (l) 10-nm for 15 lpm; (m) 50-nm for 15 lpm; (n) 100-nm for 15 lpm; (o) 500-nm for 15 lpm; (p) 1-nm for 60 lpm; (q) 10-nm for 60 lpm; (r) 50-nm for 60 lpm; (s) 100-nm for 60 lpm; (t) 500-nm for 60 lpm.

88 Appendices

B3: PARTICLE DIAMETER AND MAGNETIC POSITION EFFECT FOR MN=0.18 AND 15 LPM FLOW RATES

(a) (b) (c)

(f) (d) (e)

Figure A.8: Effect of particle diameter and magnet position on particle transport outline Mn= 0.18T, flow rates 15 lpm, (a) 1-nm for position 1; (b) 1-nm for position 2; (c) 10- nm for position 1; (d) 10-nm for position 2; (e) 50-nm for position 1; (f) 50-nm for position 2.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 89 B4: DEPOSITION EFFICIENCY HISTOGRAM FOR MAGNETIC FIELD POSITION 1

80 7.5 lpm 70 9 lpm 60 15 lpm

50 60 lpm

20 Deposition Efficiency(%) Deposition

0 1 nm 10 nm 50 nm 100 nm 500 nm particle Diameter

Figure A.9: Deposition Efficiency comparisons for NPs of various diameter and flow rates at position 1 for magnetic number 2.5T. B5: DEPOSITION EFFICIENCY HISTOGRAM FOR MAGNETIC FIELD POSITION 2

120 7.5 lpm 100 9 lpm 15 lpm 80 60 lpm

Deposition Efficiency(%) Deposition 20

0 1 nm 10 nm 50 nm 100 nm 500 nm

Particle Diameter

Figure A.10: Deposition Efficiency comparisons for NPs of various diameter and flow rates at position 2 for magnetic number 2.5T.

90 Appendices B6: REGIONAL DEPOSITION EFFICIENCY FOR 15 LPM AND MN 0.181

120 Flow Rate 15 lpm and Mn 0.181 T g1 100 rg2 wall position 1 80 lg2

40 Deposition Efficiency Deposition 20

position 1 position 2 position position 1 position 2 position 1 position 2 position 1 position 2 position 2 position 1 position 1-nm 10-nm 50-nm 100-nm 500-nm

Diameter and Magnet Position

Figure A.11: Regional particle deposition efficiency in each zone at different particle sizes, magnet position, magnetic number 0.181T and 15 lpm flow rates.

Targeting Delivery of Magnetic Aerosol Particles to Specific Regions in The Lung 91 B7: REGIONAL DEPOSITION EFFICIENCY FOR 15 LPM AND MN 1.5

100 Flow Rate 15 lpm and Mn 90 g1 80 rg2 70 wall position 1 60 lg2 50

Deposition Efficiency Deposition 20

0 position position position position position position position position position position 1 2 1 2 1 2 1 2 1 2 1-nm 10-nm 50-nm 100- nm 500-nm Diameter and Magnet Position

Figure A.12: Regional particle deposition efficiency in each zone at different particle sizes, magnet position, magnetic number 1.5 T and 15 lpm flow rates. B8: STATIC PRESSURE FOR POSITION 2

Static pressure

Figure A.13: Static pressure for position 2, Mn=2.5 T, 1-nm, 9 lpm

92 Appendices