targeting delivery of magnetic aerosol particles to …...targeting delivery of magnetic aerosol...

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

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

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.

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

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

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

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.

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

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)

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

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

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

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

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

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/respiratory-

system-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

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

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, 𝑑𝑝 = 4 𝜇𝑚, 𝑀𝑛 = 2.5 𝑇, (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, 𝑀𝑛 = 2.5 𝑇, Q=60 lpm (a) 𝑑𝑝 = 2 𝜇𝑚; (b) 𝑑𝑝 =4 𝜇𝑚; (c) 𝑑𝑝 = 6 𝜇𝑚; (d) overall deposition efficiency. ............................ 49

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

and DE (%) for Position 2, 𝑑𝑝 = 4 𝜇𝑚, Q=60lpm,(a) 𝑀𝑛 =0.181T;(b)𝑀𝑛 = 2.5 T; (c)𝑀𝑛 = 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 𝑑𝑝 = 4 𝜇𝑚, Q=30 lpm, 𝑀𝑛 = 2.5 𝑇, (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

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

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)

(𝑚2/𝑆2) 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


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, 𝑑𝑝 = 4 𝜇𝑚, 𝑀𝑛 = 0.25 𝑇 , (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, 𝑀𝑛 = 0.25 𝑇, Q=60 lpm (a) 𝑑𝑝 = 2 𝜇𝑚; (b) 𝑑𝑝 =4 𝜇𝑚; (c) 𝑑𝑝 = 6 𝜇𝑚; (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 𝐵 (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;

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

(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


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

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

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

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

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

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

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:

Date: 27/03/2018

QUT Verified Signature

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

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.

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

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.

2 Chapter 1: Introduction

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


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

4 Chapter 1: Introduction

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 nano-

particle 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)


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.

6 Chapter 3: Methodology

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).


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).

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

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).


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.

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 &

Figure 2.2 (a) Structural design of lung components (b) The segmented view of the

computational domain (Rahimi-Gorji et al., 2016).


Goss, 1878; Tomlinson et al., 1994) from the air (Denison et al., 1982) and transport

into the blood.

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

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


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-lung-

diseases/overview-of-environmental-lungdiseases,").

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.)

Particle size µm <100

Particle size < µm 10


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


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


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


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).

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

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


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).


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).

Figure 2.6 Schematic representation of magnetic nanoparticle microcomposites

(MnMs) by pulmonary delivery (Stocke et al., 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

Figure 2.7 Advantages and challenges of pulmonary drug delivery (Kuzmov &

Minko, 2015).


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


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


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


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


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-


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.


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:


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- 𝜔 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.


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,


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:

𝜕𝑢𝑖

𝜕𝑥𝑖= 0 (3.1)

Momentum equations:

𝜕𝑢𝑖

𝜕𝑡+ 𝑢𝑗

𝜕𝑢𝑖

𝜕𝑥𝑗= −

1

𝜌𝑓

𝜕𝑝

𝜕𝑥𝑖+

𝜕

𝜕𝑥𝑗[(𝑣𝑓 + 𝑣𝑇) (

𝜕𝑢𝑖

𝜕𝑥𝑗+

𝜕𝑢𝑗

𝜕𝑥𝑖)]

(3.2)

Where 𝑢𝑖 and 𝑢𝑗 (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:


𝜕𝑘

𝜕𝑡+ 𝑢𝑗

𝜕𝑘

𝜕𝑥𝑗= 𝑃 − 𝛽∗𝜔𝑘 +

𝜕

𝜕𝑥𝑗[(𝑣𝑓 + 𝛼𝑘𝛼∗ 𝑘

𝜔)

𝜕𝑘

𝜕𝑥𝑗]

(3.3)

with Pseudo vorticity equation:

𝜕𝜔

𝜕𝑡+ 𝑢𝑗

𝜕𝜔

𝜕𝑥𝑗=

𝛾𝜔

𝑘𝑃 − 𝛽𝜔2 +

𝜕

𝜕𝑥𝑗[(𝑣𝑓 + 𝛼𝜔𝛼∗

𝑘

𝜔)

𝜕𝜔

𝜕𝑥𝑗] +

𝛼𝑑

𝜔

𝜕𝑘

𝜕𝑥𝑗

𝜕𝜔

𝜕𝑥𝑗

(3.4)

where the turbulent viscosity, 𝑣𝑇 = 𝐶𝜇𝑓𝜇𝑘

𝜔 , and the function, 𝑓𝑢 is defined as 𝑓𝑢 =

exp [−3.4

(1+𝑅𝑇50

)2] with 𝑅𝑇 =

𝜌𝑘

(𝜇𝜔) . The other coefficients in the above equations are

chosen from (Oveis Pourmehran et al., 2016) :

𝑅𝛽 = 8, 𝑅𝜔 = 2.61, 𝑅𝑘 = 6, 𝛼0 =1

9 , 𝛽0 = 0.0708 , 𝛽0

∗ = 0.09 , 𝛼∞∗ = 1,

𝜎𝜔 = 𝛼𝑘 = 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:

�� = 𝐹𝐷 + 𝐹𝑀

= 𝑚𝑝.𝑑𝑈𝑝

𝑑𝑡

(3.5)

where 𝑈𝑝 is the particle velocity and 𝐹 is the force term. 𝐹𝐷

, 𝐹𝑀 are drag and magnetic

forces, respectively.

3.2.1 DRAG FORCE

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


𝐹𝐷 =

18𝜇

𝜌𝑝𝑑𝑝2

𝑚𝑝𝑓𝑅𝑒𝑃

24(𝑢𝑓 − 𝑢𝑝) (3.6)

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

from

𝑓 = 𝑎1 +𝑎2

𝑅𝑒𝑃+

𝑎3

𝑅𝑒𝑃2 (3.7)

where 𝑅𝑒𝑃 is the particle Reynolds number, which is defined as 𝑅𝑒𝑃 ≡𝜌𝑓𝑑𝑃|𝑢𝑃−𝑢𝑓|

𝜇𝑓 .

𝑢𝑃, 𝜌𝑓 , 𝜌𝑃 𝜇𝑓 , 𝑢𝑓 and 𝑑𝑃 are the air velocity, fluid density, particle density, particle

velocity, fluid molecular viscosity and particle diameter. Also in (3.7) 𝑎1, 𝑎2 and 𝑎3

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:

∇ ∙ �� = 0 (3.8)

∇ × �� = −𝜕��

𝜕𝑡 (3.9)

∇ ∙ �� = 𝑞 (3.10)

∇ × �� = 𝐽 +𝜕𝑗

𝜕𝑡 (3.11)


The magnetic simulation equation can be derived from Ohm’s law and Maxwell’s

equation, which is:

𝜕��

𝜕𝑡+ (𝑈. ∇)�� =

1

𝜇𝜎∇2�� + (��. ∇)𝑈

(3.12)

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

𝐽 =1

𝜇∇ × �� (3.13)

Generally, the magnetic field, �� ( �� = 𝜇0𝐻) in an MHD problem can be decomposed

into the externally imposed field, 𝐵0 and the induced field, �� due to fluid motion. Only

the induced field, �� must be solved.

From Maxwell’s equations, the imposed field, 𝐵0 satisfies the following equation:

∇2𝐵0 −

𝜇𝜎(𝜕𝐵0 )

𝜕𝑡= 0

(3.14)

3.2.2.1 EXTERNALLY IMPOSED MAGNETIC FIELD GENERATED IN NON-

CONDUCTING MEDIA

In this case, the imposed field 𝐵0 satisfies the following conditions:

∇ × ��0 = 0 (3.15)

∇2��0 = 0 (3.16)

With �� = 𝐵0 + ��, the induction equation (3.14) can be written as:

𝜕��

𝜕𝑡+ (𝑈. ∇)�� =

1

𝜇𝜎∇2�� + ((𝐵0

+ ��). ∇) 𝑈 − (��. ∇)𝐵0 −

𝜕𝐵0

𝜕𝑡

(3.17)

The current density is:


𝑗 =1

𝜇∇ × �� = 0 (3.18)

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:

𝜕𝑘

𝜕𝑡+ 𝑢𝑗

𝜕𝑘

𝜕𝑥𝑗= 𝑃 − 𝛽∗𝜔𝑘 +

𝜕

𝜕𝑥𝑗[(𝑣𝑓 + 𝛼𝑘𝛼∗ 𝑘

𝜔)

𝜕𝑘

𝜕𝑥𝑗]

(3.19)

Pseudo vorticity equation:

𝜕𝜔

𝜕𝑡+ 𝑢𝑗

𝜕𝜔

𝜕𝑥𝑗=

𝛾𝜔

𝑘𝑃 − 𝛽𝜔2 +

𝜕

𝜕𝑥𝑗[(𝑣𝑓 + 𝛼𝜔𝛼∗

𝑘

𝜔)

𝜕𝜔

𝜕𝑥𝑗] +

𝛼𝑑

𝜔

𝜕𝑘

𝜕𝑥𝑗

𝜕𝜔

𝜕𝑥𝑗

(3.20)


Where j

iij

x

uP

; ijij

k

kijij

x

uST

3

2)

3

22(

;

i

j

j

iij

x

u

x

uS

2

1 ;

f0 ; the turbulent viscosity, 𝑣𝑇 = 𝐶𝜇𝑓𝜇𝑘

𝜔 and the function, 𝑓𝑢 is defined as 𝑓𝑢 =

exp [−3.4

(1+𝑅𝑇50

)2] with 𝑅𝑇 =

𝜌𝑘

(𝜇𝜔) . The other coefficients in the above equations are

chosen from ANSYS fluent 18.0:

𝑅𝛽 = 8, 𝑅𝜔 = 2.95, 𝑅𝑘 = 6, 𝛼0 =1

9 , 𝛽0 = 0.0708 , 𝛽0

∗ = 0.09 , 𝛼∞∗ = 1, 𝜎𝜔 = 𝛼𝑘

= 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:

�� = 𝐹𝐷 + 𝐹𝑀

= 𝑚𝑝.𝑑𝑈𝑝

𝑑𝑡

(3.21)

where 𝑈𝑝 is the particle velocity and 𝐹 is the force term. 𝐹𝐷

, 𝐹𝑀 are drag and

magnetic forces respectively.

The following mass and momentum equations respectively were solved to calculate

air flow.

mSt

v

(3.22)

where Sm is the mass source term.

FgITpt

vvv vvv

3

2

(3.23)


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

)1(2)(2

2

R

ruru av

(3.24)

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

p gg p iD i i Brownian Lift i

p

duF u u F F g

dt

(3.25)

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

cpp

g

DCd

F2

18

(3.26)

)4.0257.1(2

1 2/1.1

pd

p

c ed

C

(3.27)

Where cC is the Cunningham correction factor. The specific correction factor values

were used for different diameter particles. 𝜌𝑃 , 𝑑𝑃, are particle density, particle

diameter and λ is the mean free path of the gas molecules. The Brownian force

amplitude is defined as

t

SFBrownian

0

(3.28)


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

c

g

p

pp

Bo

Cd

TkS

252 )(

216

(3.29)

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).

)()(

2

4/1

2/1

p

kllkpp

ij

Lift uuddd

dKvF

(3.30)

where K=2.594 1and ijd 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, 𝐹𝑀 on a small sphere in a nonmagnetic fluid, was calculated as

��𝑀 =1

2𝜇0χ𝑉𝑃∇ (𝐻2 ) (3.31)

Where 𝜇0 is the magnetic permeability of vacuum, χ is the magnetic susceptibility of

the particle, Vp is the particle volume, and 𝐻 is the magnetic field intensity.

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

is defined as:

χ = −0.14𝑑𝑝. 106 + 0.98 (3.32)

Where, 𝑑𝑝 is the particle diameter.


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

𝑀𝑛 = 𝜇0𝐻0 (3.33)

𝐻0 is the characteristic magnetic field strength. Magnetic number is dependent to the

magnetic field intensity.

36 Chapter 4: Results and Discussion

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.


(a)

(b)

(c)

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.

(f)

(e)

(d)


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).


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

Stokes number is defined by 𝑠𝑡 = 𝜌𝑝𝑑𝑝2𝑈/(9𝜇𝐷), 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.

0

1

2

3

4

5

6

7

8

9

10

0 50000 100000 150000 200000 250000 300000

Max

imu

m v

elo

city

(m

/s)

Grid Number or nodes

Figure 4.2 Maximum velocity grid convergence

http://www.sciencedirect.com/science/article/pii/S0017931008002688#fig2


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).


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.

The impaction parameter is defined by 𝑑𝑎𝑒2 𝑄(𝜇𝑚2𝐿𝑚𝑖𝑛−1), where 𝑑𝑎𝑒 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)


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.

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.

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)


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.

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

(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.


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

(a) (b)

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.

(c) (c)

(d)


Figs.4.8 (a, b) clarify the effect of magnetic intensity at two targeted positions. To

identify the magnetic source intensity, the magnitude of �� (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 (��) 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.


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

Turbulent Kinetic Energy Turbulent Kinetic Energy

(b)

(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.

(c) (d)


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)

(c)

(d)

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

2, 𝑑𝑝 = 4 𝜇𝑚, 𝑀𝑛 = 2.5 𝑇, (a) 15 lpm; (b) 30 lpm; (c) 60 lpm; (d) Total deposition

efficiency in terms of flow rates.


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, 𝑀𝑛 = 2.5 T, magnetic source position is in position 2 and the

particle diameter is 4 𝜇𝑚. 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 4𝜇𝑚 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.


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

position 2, 𝑀𝑛 = 2.5 𝑇, Q=60 lpm (a) 𝑑𝑝 = 2 𝜇𝑚; (b) 𝑑𝑝 = 4 𝜇𝑚; (c) 𝑑𝑝 = 6 𝜇𝑚;

(d) overall deposition efficiency.

To investigate the deposition on a targeted region for different particle sizes, three

different sizes of particles, 2 𝜇𝑚, 4𝜇𝑚, and 6 𝜇𝑚 are considered in Fig.4.11 for

(d)

(a) (b)

(c)


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 𝑑𝑝 = 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.


Figs. 4.12 (a, b, c) clarify the effects of a magnetic number for position 2 with 4 𝜇𝑚

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

(a) (b)

(c) (d)

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

(%) for Position 2, 𝑑𝑝 = 4 𝜇𝑚, Q=60lpm,(a) 𝑀𝑛 = 0.181T;(b)𝑀𝑛 = 2.5 T; (c)𝑀𝑛 =

3 T; (d) deposition efficiency for magnetic number.


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.


Figs.4.13 (a, b) represent the effect of external magnetic source in two different

positions for 4 𝜇𝑚 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

0

20

40

60

80

100

120

DE

(%)

Magnet position

(c)

(a) (b)

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

(%) for 𝑑𝑝 = 4 𝜇𝑚, Q=30 lpm, 𝑀𝑛 = 2.5 𝑇, (a) Position 1; (b) Position 2;(c)

deposition efficiency for magnetic source position.


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.

0

5

10

15

20

25

30

35

40

DE

(%)

Flow Rates

60 lpm

30 lpm

15 lpm

0

5

10

15

20

25

30

35

40

DE

(%)

Particle Diameter

2

4

6

(b)

0

5

10

15

20

25

30

DE

(%)

Magnetic Number

3

2.5

0.181

(c)

0

10

20

30

40

50

60

70

80

position 1 position 2

DE

(%)

Magnetic source Position

Position 1

Position 2

(d)

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).

(a)


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.


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.

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.

(a) (b)

(c) (d)


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.

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

0

2

4

6

8

10

12

14

16

0 100000 200000 300000 400000 500000 600000 700000 800000

Max

imum

pre

ssure

(pas

cal)

Grid Number


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.

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.

(a) (b)

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.


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.

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

Figure 4.19: Geometry specification of 2-generation model (Magnet position 2 has been

set on the right lung).


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.

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.

(e) (f)

(g)

0

20

40

60

80

100

120

Position 1 Position 2

Dep

osi

tion

eff

icie

ncy

Position of magnet

7.5 lpm9 lpm15 lpm

(g)

(a) (b)

(d)

(c)


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.


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.

(e) (f)

0

20

40

60

80

100

120


Dep

osi

tion

eff

icie

ncy

(%)

position of magnet

Mn=0.181

Mn=1.5

Mn=2.5

(g)

(a) (b) (c)

(d)


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.


Figure 4.22: Particle Traces Coloured by Turbulent Kinetic Energy (k) (𝑚2/𝑆2) 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.

(a) (b)

(c) (d)

Turbulent kinetic Energy

(e)


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:

𝑘 =3

2[𝐼𝑑𝑒𝑓max (𝑈𝑠, |𝑈𝐼𝐺|, 𝑈𝜔)]2

(4.1)

𝐼𝑑𝑒𝑓 is the default turbulent intensity, 𝑈𝑠 is a minimum velocity, 𝑈𝐼𝐺 is the velocity

initial guess and 𝑈𝜔 is the product of the simulation average length scale and the

rotation rate.


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.

Particle residence time

(a) (b)

(c) (d)

(e)


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.


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.

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).

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%

0

20

40

60

80

100

120

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

1 nm 50 nm 100 nm 500 nm

Dep

osi

tio

n e

ffic

ien

cy

Diameter and Magnet position

7.5 lpm

9 lpm

15 lpm

60 lpm


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.



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

1

Position

2

Position 1 Position

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%

0

20

40

60

80

100

120

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

mn=0.18 mn=1.5 mn=2.5

Dep

osi

tio

n E

ffic

ien

cy

Magnet Position

1 nm

10 nm

50 nm

100 nm

500 nm


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.


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

0

10

20

30

40

50

60

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

1-nm 10-nm 50-nm 100-

nm

500-

nm

Dep

osi

tio

n E

ffic

ien

cy

Diameter and Magnet position

g1

rg2

wall position 1

lg2

Flow Rate 9 lpm and Mn 2.5

(b)

0

10

20

30

40

50

60

70

80

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

1- nm 10- nm 50- nm 100- nm 500- nm

Dep

osi

tion E

ffic

iency

Diameter and Magnet Position

g1

rg2

wall position 1

lg2


0

10

20

30

40

50

60

70

80

90

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

21- nm 10- nm 50- nm 100- nm500- nm

Dep

osi

tion E

ffic

iency


g1rg2wall position 1lg2


(d)

0

10

20

30

40

50

60

70

80

90

100

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

posi

tion

1

posi

tion

2

1- nm 10-nm 50-nm 100-nm 500-nm

Dep

osi

tio

n E

ffic

ien

cy


g1

rg2

wall position 1

lg2

Flow Rate 7.5 lpm and Mn 2.5

(a)

(c)


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.

74 Chapter 5: Conclusion

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


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.

76 Chapter 5: Conclusion

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.


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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.

84 Appendices

A2: FLOW RATES EFFECT

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, 𝑀𝑛 = 0.25 T, magnetic source position is in position 2 and the

particle diameter is 4 𝜇𝑚.

(a) (b)

(c) (d)

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

2, 𝑑𝑝 = 4 𝜇𝑚, 𝑀𝑛 = 0.25 𝑇 , (a) 15 lpm; (b) 30 lpm; (c) 60 lpm; (d) Total deposition

efficiency in terms of flow rates.


A3: PARTICLE DIAMETER EFFECT

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, 𝑀𝑛 =

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

(a) (b)

(d)

(c)

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

Position 2, 𝑀𝑛 = 0.25 𝑇, Q=60 lpm (a) 𝑑𝑝 = 2 𝜇𝑚; (b) 𝑑𝑝 = 4 𝜇𝑚; (c) 𝑑𝑝 = 6 𝜇𝑚;

(d) deposition efficiency.

86 Appendices

A4: MAGNETIC FIELD (POSITION) EFFECT

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.

Position 1

Position 2

(a) (b)

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


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.

88 Appendices

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.


B3: PARTICLE DIAMETER AND MAGNETIC POSITION EFFECT FOR

MN=0.18 AND 15 LPM FLOW RATES

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.

(a) (b) (c)

(d) (e) (f)

90 Appendices

B4: DEPOSITION EFFICIENCY HISTOGRAM FOR MAGNETIC FIELD

POSITION 1

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

Figure A.10: Deposition Efficiency comparisons for NPs of various diameter and

flow rates at position 2 for magnetic number 2.5T.

0

10

20

30

40

50

60

70

80

1 nm 10 nm 50 nm 100 nm 500 nm

Dep

osi

tio

n E

ffic

ien

cy(%

)

particle Diameter

7.5 lpm

9 lpm

15 lpm

60 lpm

0

20

40

60

80

100

120

1 nm 10 nm 50 nm 100 nm 500 nm

Dep

osi

tion

Eff

icie

ncy

(%)

Particle Diameter

7.5 lpm

9 lpm

15 lpm

60 lpm


B6: REGIONAL DEPOSITION EFFICIENCY FOR 15 LPM AND MN 0.181


particle sizes, magnet position, magnetic number 0.181T and 15 lpm flow rates.

0

20

40

60

80

100

120

posi

tion 1

posi

tion 2

posi

tion 1

posi

tion 2

posi

tion 1

posi

tion 2

po

siti

on 1

posi

tion 2

posi

tion 1

po

siti

on 2

1-nm 10-nm 50-nm 100-nm 500-nm

Dep

osi

tion E

ffic

iency


g1

rg2

wall position 1

lg2

Flow Rate 15 lpm and Mn 0.181 T

92 Appendices

B7: REGIONAL DEPOSITION EFFICIENCY FOR 15 LPM AND MN 1.5


particle sizes, magnet position, magnetic number 1.5 T and 15 lpm flow rates.

B8: STATIC PRESSURE FOR POSITION 2

0

10

20

30

40

50

60

70

80

90

100

position

1

position

2

position

1

position

2

position

1

position

2

position

1

position

2

position

1

position

2

1-nm 10-nm 50-nm 100- nm 500-nm

Dep

osi

tion E

ffic

iency


g1

rg2

wall position 1

lg2

Flow Rate 15 lpm and Mn

Static pressure

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

targeting delivery of magnetic aerosol particles to …...targeting delivery of magnetic aerosol...

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