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Pharmacometric Evaluation of Bioequivalence Approaches for Orally Inhaled Drug Products

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Title:
Pharmacometric Evaluation of Bioequivalence Approaches for Orally Inhaled Drug Products
Creator:
Kandala, Bhargava
Place of Publication:
[Gainesville, Fla.]
Publisher:
University of Florida
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english
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1 online resource (101 p.)

Thesis/Dissertation Information

Degree:
Doctorate ( Ph.D.)
Degree Grantor:
University of Florida
Degree Disciplines:
Pharmaceutical Sciences
Pharmaceutics
Committee Chair:
HOCHHAUS,GUENTHER
Committee Co-Chair:
PALMIERI,ANTHONY,III
Committee Members:
DERENDORF,HARTMUT C
WINNER,LAWRENCE HERMAN
Graduation Date:
5/3/2014

Subjects

Subjects / Keywords:
Corticosteroids ( jstor )
Dosage ( jstor )
Drug design ( jstor )
Drug evaluation ( jstor )
Lungs ( jstor )
Modeling ( jstor )
Pharmacokinetics ( jstor )
Propionates ( jstor )
Simulations ( jstor )
Transponders ( jstor )
Pharmaceutics -- Dissertations, Academic -- UF
bioequivalence -- inhalation -- pharmacodynamics -- pharmacokinetics
Genre:
Electronic Thesis or Dissertation
born-digital ( sobekcm )
Pharmaceutical Sciences thesis, Ph.D.

Notes

Abstract:
Background: To establish bioequivalence (BE) of orally inhaled drug products (OIDPs), the US Food and Drug Administration (FDA) recommends pharmacodynamic (PD)/clinical studies to establish equivalence in clinical efficacy. The feasibility of such studies is debated in the scientific community. Objectives: a) To develop a clinical trial simulation model suitable to evaluate the feasibility of PD BE studies of generic OIDPs by (1) incorporating variability of the biomarker (exhaled nitric oxide, methacholine challenge) in defined patient populations and to predict their response to OIDPs, (2) applying a bootstrap based non-parametric approach to construct distributions of relative bioavailability for test vs. reference formulations, (3) performing power calculations for the simulated studies considering non-linear dose response relationships. b) Analysis of a PD crossover study to evaluate equivalence in clinical efficacy of two dry powder inhalers, Formoterol Aerolizer (FA) and Formoterol Novolizer (FN) in patients with stable asthma using PC20 as the primary end-point. Results: For FeNO crossover studies, highest power was achieved when the test dose is close to ED50. 90% power was obtained for 32 high responders as opposed to 128 intermediate responders. For the scenario wherein the test dose is on the top of the dose response curve 90% power is obtained with 128 high responders in the study whereas with the same number of intermediate responders 20% power was obtained. The 90% CI interval of relative bioavailability for the 12 mcg dose of FN relative to FA was 0.94-1.45. The 90% Fieller CI for relative potency of the Novolizer compared to the Aerolizer was estimated to be 0.97-1.34. Discussion: PD approach for establishing BE of OIDPs seems feasible in terms of the sample sizes only when 1) Study population consists of high responders and are less variable, 2) Test dose is close to the estimated ED50 value of the drug and biomarker combination, 3) BE criteria are relaxed. Most of the generic formulations have doses much larger than the relevant ED50 values warranting large sample sizes to demonstrate bioequivalence. FN was shown to be BE to FA. Modeling and simulation suggest that it will be a challenge performing bioequivalence studies for corticosteroids using FeNO, while the methacholine challenge is a viable pulmonary bioassay for beta-2 agonists. ( en )
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In the series University of Florida Digital Collections.
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Includes vita.
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Includes bibliographical references.
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Description based on online resource; title from PDF title page.
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This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Thesis:
Thesis (Ph.D.)--University of Florida, 2014.
Local:
Adviser: HOCHHAUS,GUENTHER.
Local:
Co-adviser: PALMIERI,ANTHONY,III.
Electronic Access:
RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2014-11-30
Statement of Responsibility:
by Bhargava Kandala.

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University of Florida
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University of Florida
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Applicable rights reserved.
Embargo Date:
11/30/2014
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LD1780 2014 ( lcc )

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PHARMACOMETRIC EVALUATION OF BIOEQUIVALENCE APPROACHES FOR ORALLY INHALED DRUG P RODUCTS By B HARGAVA KANDALA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2014

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2014 Bhargava Kandala

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This work is dedicated to my parents, brother, and family for their love and support

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4 ACKNOWLEDGMENTS I would like to express my sincere gratitude to my research advisor Dr. Gu e nther Hochhaus, for accepting me into his research group and for his guidance and support during my PhD training at University of Florida. I would also like to thank my committee members Dr s. Hartmut Derendorf, Anthony Palmieri III, and Lawrence Winner for their incessant support and insights during the course of the program. I am also thankful to Dr. Leslie Hendeles for giving me the opportunity to work on the pharmacodynamic bioequivalence study data that helped me shape my thesis. I would like to express special appreciation to Drs. Lee Sau Robert Lionberger, and Navin Goyal for giving me a wonderful opportunity to intern with them and having a profound impact on the development of my scientific acumen. I would also like to thank the office staff in the Department of Pharmaceutics for their constant support. I am indebted to the Department of Pharmaceutics, Department of Statistics, and the University of Florida for my personal and professional development and laying a solid platform for a successful career. I would like to extend special t hanks to my lab mates, especially Drs. Benjamin Weber, Wan Sun Mongjen Chen and Sharvari and my fellow graduate students Drs. Daniela Conrado, Daniel Gonzalez and Karin Haug. I would like to thank my interns Brian Maas, Roy Joseph and Shen Yong for their support. It was a pleasure mentoring you. I would also like to thank all my friends and my cricket team for making my stay in Gainesville special and memorable. Finally, I would like to thank my family for their constant support, love and motivation.

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5 TABL E OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................. 4 LIST OF TABLES ............................................................................................................ 8 LIST OF FIGURES .......................................................................................................... 9 LIST OF ABBREVIATIONS ........................................................................................... 10 ABSTRACT ................................................................................................................... 11 CHAPTER 1 INTRODUCTION .................................................................................................... 13 Pharma cometric Methods for Orally Inhaled Drug Products ................................... 13 Factors influencing regional lung kinetics following inhalation therapy ................... 13 Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling of Inhaled Drugs .............. 15 Pharmacokinetic (PK) Modeling of Inhaled d rugs (Pulmonary Models) ............ 15 Pharmacokinetic/Pharmacodynamic Factors Influencing Pulmonary Targeting ..... 17 Pharmacodynamic Factors ............................................................................... 18 Receptor Binding Affinity ............................................................................ 18 Pharmacokinetic Factors .................................................................................. 19 Oral Bioavailability ..................................................................................... 19 Systemic Clearance ................................................................................... 19 Plasma protein binding .............................................................................. 20 Pulmonary Deposition ................................................................................ 21 Pulmonary Residence Time ....................................................................... 21 Pharmacokinetic/Pharmacodynamic Modeling of Cortisol Suppression after administration of Exogenous Corticosteroids ................................................ 23 Pharmacokinetic/Pharmacodynamic Modeling to Study the Relationship between Growth Velocity and Systemic Corticosteroid Exposure ................. 27 Bioequivalence of Orally Inhaled Drug Products .............................................. 29 2 EVALUATION OF THE FEASIBILITY OF PHARMACODYNAMIC BIOEQUIVALENCE STUDIES OF INHALED CORTICOSTEROIDS THROUGH MONTE CARLO SIMULATIONS ............................................................................ 34 Background ............................................................................................................. 34 Specific Aim 1: .................................................................................................. 35 Specific Aim 2: (chapter 4) ............................................................................... 36 Specific Aim 1: .................................................................................................. 36 Methods .................................................................................................................. 36 Dose Scale Method .......................................................................................... 36 Data Simul ation Strategy .................................................................................. 38

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6 Pharmacodynamic Crossover Study .......................................................... 38 Linear mixed effect model Literature based parameter estimates ................. 39 Emax model parameter estimates ................................................................ 39 Variance Estimates .................................................................................... 41 Analysis of Simulated Data ............................................................................... 42 Power Calculations ........................................................................................... 42 Results .................................................................................................................... 43 Impact of sample size ....................................................................................... 43 Impact of Choice of Test Dose ......................................................................... 43 Impact of BE criteria ......................................................................................... 44 Impact of the study population .......................................................................... 44 Discussion and Significance ................................................................................... 45 3 ANALYSIS OF A PHARMACODYNAMIC CROSSOVER STUDY CONDUCTED TO ESTABLISH BIOEQUIVALENCE OF FORMOTEROL AEROLIZER AND FORMOTEROL NOVOLIZER ................................................................................. 58 Background ............................................................................................................. 58 Research O bjective ................................................................................................ 58 Methods .................................................................................................................. 59 Study Design .................................................................................................... 59 PC20 Measurement ........................................................................................... 59 Dose Scale Approach ...................................................................................... 60 Finney (2, 2) parallel line assay ........................................................................ 61 Results .................................................................................................................... 63 Conclusions ............................................................................................................ 63 4 EVALUATION OF THE SENSITIVITY OF PHARMACOKINETICS TO DIFFERENCES IN THE AERODYNAMIC PARTICLE SIZE DISTRIBUTION OF THREE DIFFERENT FO RMULATIONS OF FLUTICASONE PROPIONATE DRY POWDER INHALERS .................................................................................... 71 Specific Aim 2: ........................................................................................................ 71 Background ............................................................................................................. 71 Pharmacokinetic Approach ............................................................................... 71 Form ulation Development ................................................................................ 72 Methods .................................................................................................................. 77 Study Design .................................................................................................... 77 Assignment to treatment and randomization .................................................... 78 Dose and Device .............................................................................................. 78 Randomization ................................................................................................. 78 Benefit/risk considerations ................................................................................ 79 Selection of Study Population ........................................................................... 80 Study Procedures and scheduling .................................................................... 81 Screening Visit ........................................................................................... 81 Treatment Visits 1, 2, 3 and 4 .................................................................... 82 Blood sample collection ............................................................................. 83

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7 Labeling ..................................................................................................... 83 Handling and Storage ................................................................................ 83 Bio anal ytical Method ....................................................................................... 84 Statistical Methods and Analysis of Data .......................................................... 84 Sample size calculation ............................................................................. 84 In vitro analysis .......................................................................................... 85 Non Compartmental Analysis (NCA) ......................................................... 86 Compartmental Analysis ............................................................................ 87 5 CONCLUSION ........................................................................................................ 92 LIST OF REFERENCES ............................................................................................... 94 BIOGRAPHICAL SKETCH .......................................................................................... 101

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8 LIST OF TABLES Table page 2 1 Simulation Scenarios Parameter Estimates ........................................................ 57 4 1 Formulations in the study ....................................................................................... 88 4 2 Sequences of the four treatments .......................................................................... 89 4 3 A sample randomization scheme ........................................................................... 90 4 4 Procedures performed during the screening and treatment visits .......................... 91

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9 LIST OF FIGURES Figure page 1 1 Fate of an Inhaled Drug ..................................................................................... 31 1 2 Aggregate Weight of Evidence Approach ........................................................... 32 1 3 EMA approach for establishing BE of OIDPs ..................................................... 33 2 1 Dose Scale Approach ......................................................................................... 47 2 2 Pharmacodynamic crossover study design ....................................................... 48 2 3 Dose response relationship of high responders and intermediate responders .. 49 2 4 Literature Research FeNO trials ...................................................................... 50 2 5 Power as a function of sample size and choice of test dose (Range = Low) ...... 51 2 6 Power as a function of sample size and choice of test dose .............................. 52 2 7 Power Calcul ations Comparison of BE criteria ................................................ 53 2 8 Power Calculations High vs. Intermediate responders .................................... 54 2 9 Power Calculations High vs. Low variable population ..................................... 55 2 10 Distribution of parameters High vs. Low variable population ........................... 56 3 1 Crossover Study Design ..................................................................................... 64 3 2 Methacholine Challenge .................................................................................... 65 3 3 Diagnostic plots for the log transformed 20 data ............................................ 66 3 4 Distribution of log (PC20) values ......................................................................... 67 3 5 Dose Scale approach 12mcg dose .................................................................. 68 3 6 Bootstrap FDS values 12mcg dose ................................................................... 69 3 7 ANCOVA model evaluating the doseformulation interaction ............................. 70

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10 LIST OF ABBREVIATIONS BE Bioequivalence COPD Chronic obstructive pulmonary disease DPI Dry Powder Inhaler FA Formoterol Aerolizer FDA Food and Drug Administration FDA Relative Bioavailability FeNO Fractional Exhaled Nitric Oxide FN Formoterol Novolizer FP Fluticasone Propionate ICS Inhaled C orticosteroids OIDP Orally Inhaled Drug Product PC 20 Provocative concentration of methacholine to reduce FEV 1 by 20% PK Pharmacokinetics PD Pharmacodynamic R Reference T Test

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11 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy P HARMACOMETRIC EVALUATION OF BIOEQUIVALENCE APPROACHES FOR ORALLY INHALED DRUG P RODUCTS By Bhargava Kandala May 2014 Chair: Gu e nther Hochhaus Major: Pharmaceutical Sciences Background: To establish bioequivalence (BE) of orally inhaled drug products (OIDPs), the US Food and Drug Administration (FDA) recommends pharmacodynamic (PD)/clinical studies to establish equivalence in clinical efficacy. The feasibility of such studies is debated in the scientific community. Objectives: a) To develop a clinical trial simulation model suitable to evaluate the feasibility of PD BE studies of generic OIDPs by (1) incorporating variability of the biomarker (exhaled nitric oxide, methacholine challenge) in defined patient populations and to predict their response to OIDPs, (2) applying a bootstrap based nonparametric approach to construct distributions of relative bioavailability for test vs. reference formulations, (3) performing power calculations f or the simulated studies considering nonlinear dose response relationships. b) Analysis of a PD crossover study to evaluate equivalence in clinical efficacy of two dry powder inhalers Formoterol Aerolizer (FA) and Formoterol Novolizer (FN) in patients with stable asthma using PC20 as the primary endpoint Results: For FeNO crossover studies, highest power was achieved when the test dose is close to ED50. 90% power was obtained for 32 high responders as opposed to 128 intermediate responder s. For the scenario wherein the test dose is on the top of the

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12 dose response curve (5* ) 90% power is obtained with 128 high responders in the study whereas with the same number of intermediate responders 20% power was obtained. The 90% CI interval of relative bioavailability for the 12 g dose of FN relative to FA was 0.941.45. The 90% Fieller CI for relative potency of the Novolizer compared to the Aerolizer was estimated to be 0.971.34. Discussion: PD approach for establishing BE of OIDPs seems feasible in terms of the sample sizes only when 1) Study population consists of high responders and are less variable, 2) Test dose is close to the estimated ED50 value of the drug and biomarker combination, 3) BE criteria are relaxed. Most of the generic formulations have doses much larger than the relevant ED50 values warranting large sample sizes to demonstrate bioequivalence. FN was shown to be BE to FA. Modeling and simulation suggest that it will be a challenge performing bioequivalence studies for c orticosteroids using FeNO, while the methacholine challenge is a viable pulmonary bioassay for beta2 agonists.

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13 CHAPTER 1 INTRODUCTION Pharmacometric Methods for Orally Inhaled Drug Products Pharmacometrics is an emerging science that quantifies disease, drug effects, and clinical trial information to aid in efficient and rational drug development. Within the context of orally inhaled drug products, pharmacometric methods have been applied ove r a variety of problems. A few examples include, to develop pulmonary pharmacokinetic (PK) models taking into account the impact of physiological factors of the lung, patient factors and physicochemical characteristics on the systemic fate of the drug, evaluating the PK/PD factors that influence targeting of OIDPs, PK/PD modeling to compare the efficacy and safety profiles of different OIDPs, and establishing BE between a generic and an innovator OIDP. A few examples are touched upon in this section, but the subsequent chapters in this dissertatio n focus on the BE issue of OIDPs Factors influencing regional lung kinetics following inhalation therapy Factors such as physiological aspects of inhalation therapy (1), physicochemical properties of the drug (2), and patient factors (3) determine the degree of lung deposition, regional lung deposition patterns, the lung residence time, and the distribution throughout the body of the inhaled drug particle. A brief d escription of these factors and thei r impact on inhalation therapy is presented below. (1) To gain a better understanding of the impact of the physiological factors on the fate of an inhaled drug it is imperative to classify the lung into central airways (trachea to the terminal bronchioles) and the peripheral airways (respiratory bronchioles and the alveolus)1 2. Differences in the cellular profile and certain anatomical features between these two regions warrant such a distinction to be made. The lumenal surface

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14 of the epithelium of the central airways is covered by a layer of mucus3 that facilitates the removal of undissolved particles by the mucociliary escalator. Such a clearance mechanism is absent in the peripheral regions because of a dearth of mucous secreting goblet cells in these airways4. Another important physical change is the increase in surface area as we go down the bronchial tree. The large surface area of the alveoli and its proximity to the blood may point toward a faster rate of absorption of drug from the alveolus than from the tracheobronchial region5 6. It is also important to state that the distribution of the metabolizing enzymes in the central and the peripheral regions may be different7. These differences indicate that the fate of an inhaled drug in terms of its pulmonary absorption, distribution and clearance will vary in the two regions of the lung. (2) Particle size is an important physicochemical property of the aerosol which is a function of the combination of the inhalation device and the formulation present i n it. The particle size and its distribution influence the degree and site of lung deposition. The inhaled dose can be divided into three fractions depending upon its aerodynamic particle size distribution. Particles that are greater than 5 7m which are deposited predominantly in the oropharyngeal region by impaction and are swallowed; particles having a submicron size that are exhaled and do not deposit on the airways; and the fraction of particles having the ideal size range for the lung deposition i. e. 1 5m8 9. Depending upon the particle size distribution within this size range, the particles can either deposit in the central airways by impaction or in the smaller airways and the alveoli by gravitational sedimentation or diffusion10. Lipophilicity11 is another property that determines the dissolution and pulmonary absorption rates of the inhaled partic les and, hence, the lung residence times.

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15 (3) The interaction between a patient and the inhalation device is a significant factor in determining the lung deposition profile of the inhaled particle. Inhalation flow rate affects the velocity of the inhaled particles and hence their lung deposition12, 13. Higher speeds increase the deposition in the throat and in the larger airways by impaction and decrease the deposition by sedimentation and diffusion by reducing the residence times. Applying a breath holding time13 can enhance the deposition of particles especially in the small airways and the alveoli. The delivery of the aerosols at specific points in the breathing cycle can influence the regional lung deposition. Other important factors related to the patient ar e the anatomy of the airways and the state of the lung, whether healthy or diseased. The airway caliber of the patient influences the site and degree of deposition. Experimental studies have shown that the lung deposition in patients with asthma or COPD is more central14, 15 i.e. in the large airways, than in the smaller airways and the alveoli because of the decrease in airway caliber. Conditions like ciliary dysfunstion can affect the mucociliary clearance of drug particles and, thus, the lung residence times of the inhaled particles. Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling of Inhaled Drugs Pharmacokinetic (PK) Modeling of Inhaled d rugs (Pulmonary Models) The PK behavior of inhaled (locally acting) drugs is more complicated than that of other forms of administration (systemically acting drugs). It is imperative to acknowledge the effects of the above mentioned physiological (differences in the cellular prof ile and the anatomical features between the central and the peripheral lung; mucociliary escalator in the central lung region), formulation (influence of particle size distribution on the degree and site of lung deposition; particle dissolution rate), and patient factors (differences in breathing patterns and airway caliber between a healthy and a diseased

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16 lung and its impact on the variability between and within subjects) on the systemic PK of inhaled drugs. Within the same context, a general compartment m odel that adequately describes the fate of an ICS by incorporating these parameters is necessary to accurately characterize the systemic PK of inhaled drugs. Byron1 developed a mathematical model to predict drug residence kinetics in various regions of the human respiratory tract following inhalation of therapeutic aerosols. Gonda2 furthered the model incorporating release kinetics of the drug from the dosage form to study its influence on the duration of effective drug levels in the respiratory tract. But these models specifically focused on the drug kinetics in the respiratory tract and not in plasma and did not consider variability. The model by Hochhaus et al16. using the above mentioned models as a basis, provided a novel approach to evaluate the factors responsible for pulmonary targeting by int egrating physiological aspects of pulmonary inhalation with PK and PD drug properties. But the model did not distinguish between central and peripheral regions of the lung and did not have a random component to it (between and within subject variability). Weber et al17. addressed the shortcomings of previously published inhalation models by developing a pharmacokinetic trial simulation tool that adequately describes the fate of ICS while incorporating variability between and within subjects and allowing for a distinction between central and peripheral lung regions, mucociliary removal of the undissolved particles from the central lung region and accounting for drug entering the systemic circulation via the lung and the gastrointestinal tract in the compartment model, hence considering the fate of an ICS18( Fig 1 1 ) in the human body

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17 The primary goal of the authors was to provide a simulation tool that accurately predicts the influence of changes in relevant physiological and formulation factors on systemic PK of ICS. Furthermore, the simulation tool is provided as an extension package (Inhaled Corticosteroids Pharmacokinetic Trial Simulation, ICSpkTS) to the statistical software R and is available for download via http://www.cop.ufl.edu/pc/research/areas of research/inhaledglucocorticoids/icspktsr extension/ The package has inbuilt modules for commercially available ICS (budesonide (BUD), flunisolide, fluticasone propionate (FP), and triamcinolone acetonide). The package enables the users to simulate PK trials for any ICS delivered via different inhalers to healthy subjects or patients by providing the flexibility to users to specify their own model parameters. Pharmacokinetic/ Pharmacodynamic Factors Influencing Pulmonary Targeting The primary goal of inhalation therapy has been to achieve pronounced pulmonary selectivity by maximizing the pulmonary effects whilst reducing the systemic side effects. The different kinetic processes that determine the fate of an orally inhaled drug product (OIDP) point towards a range of PK and PD factors that would impact the degree of pulmonary targeting of OIDPs. As mentioned previously, Hochhaus et al16 developed a PK/PD model to evaluate pulmonary selectivity by providing a link between ICS concentrations (unbound) in the lung and the systemic circulations with pharmacological effects using a simple Emax model. Simulations using this model were extended for beta2 agonists by Issar et al. An array of PK and PD properties influencing pulmonary selectivity are presented below.

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18 Pharmacodynamic Factors Receptor Binding Affinity It is widely accepted that the therapeutic effects and systemic side effects of inhalation drugs are mediated through cytosolic or membrane r eceptors. For e.g. all inhaled corticosteroids (ICS), exert their pharmacological effects through glucocorticoid receptors within the lungs albeit with different receptor binding affinities/potency. These receptors are extensively present in the lungs with high density in airway epithelial cells and bronchial vascular cells. The activity of ICS at the site of action i.e. potency is correlated to the receptor binding affinity of the drug19, 20, 21 2 adrenergic drugs, whose therapeutic eff 2 adrenergic receptor, a strong association exists between in vitro pointers of drug activity in cell culture and the pharmacological activity in vivo22. Therefore, i n vitro parameters and receptor binding affinities/potency are often used as yardsticks while comparing the pharmacological effects of inhalation drugs in the lung. It is interesting to explore the role of receptor potency in pulmonary targeting using ICS 2 adrenergic drugs as examples. In the case of ICS, wherein pulmonary effects and systemic side effects are mediated through the same glucocorticoid receptors in the lungs and systemic tissues, it has been shown that pulmonary targeting is not influenced by different receptor binding affinities as long as the differences in affinities are adjusted by dose of ICS. Therefore, an ICS with a lower receptor binding affinity is not necessarily an inferior drug. The anti inflammatory effect of a low receptor binding affinity ICS can be moderated by 2 adrenergic drugs, the pulmonary and 1 adrenergic receptors respectively. In

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19 such a scenario a high binding selectivity 2 receptors and 1 receptors is favorable for pulmonary selectivity. Pharmacokinetic Factors Oral Bioavailability An OIDP can enter the systemic circulation via the lung as well as from the GI tract. Sum of the fractions of the drug that is deposited in the oropharynx and swallowed, and pulmonary deposited drug removed by mucociliary clearance constitute the overall amount of drug reaching the GI tract. The oral bioavailability of the drug (F), determined by the first pass metabolism regulates the amount of drug entering the systemic circulation via the GI tract. This GI available fraction of OIDP will not elicit any therapeutic effect but will contribute towards systemic side effects. Ideally F should be clo se to 0 to reduce the overall systemic exposure of the drug and hence the potential for adverse events. Fluticasone Propionate and Ciclesonide have the lowest oral bioavailability amongst ICS of < 1%23. Bioavailability estimates of current ICS range from 0% 40%24 25, 26, 27 2 agonists range from 1.5% to 50%. These differences are likely to have an impact on pulmonary selectivity. Systemic Clearance The fraction of the inhaled drug that reaches the systemic circulation i.e. systemically available drug will contribute toward systemic side effects by interacting with the receptors outside the lung. Therefore pronounced systemic clearance will reduce the systemic exposure of OIDPs and garner pulmonary selectivity. Most ICS are extensively metabolized in the liver with clearance values close to the liver blood flow25, 28, 26. An alternative approach to increase systemic clearance would be to develop ICS with extrahepatic clearance mechanisms, for example, ICS that are metabolized in

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20 the blood. A challenge with such an approach is to identify such enzymes that are present in high concentrations in the blood but absent in pulmonary cells to ensure that pulmonary efficacy is not compromised while maximizing systemic safety. Desisobutyrl ciclesonide has an apparent clearance of 228L/hr29 indicating presence of extrahepatic modes of metabolism. Plasma protein binding Freely circulating unbound drug binds to receptors within and outside the lung and is responsible for both local and systemic sideeffects respectively. Plas ma protein 1 acid glycoprotein) can decrease the potential for systemic side effects by reducing the number of pharmacologically active free drug moieties interacting with receptors outside the lung. Indeed, protein bi nding rates have been utilized as valuable markers in predicting the cortisol suppression of ICS. Ciclesonide and desisobutyryl ciclesonide have both demonstrated protein binding rates of ~99%30 and that may explain their minimal effect on HPA axis function and cortisol levels. Therefore, there has been an increased tendency to develop OIDPs that show increased plasma and tissue protein binding. Such a property not only reduces systemic side effects but also reduces the desired pulmonary effects. Systemic side effects generally show a sensitive or a steep doseresponse relationship and hence are easily detected in clinical studies. On the other hand, pul monary effects exhibit flat or insensitive doseresponse relationships and are hard to detect. Therefore, such high binding drugs when given at identical doses as their low binding counterparts, exhibit very high safety profiles (low systemic sideeffects) while their pulmonary effects (anti -

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21 asthmatic effects) are not statistically significantly different, owing to insensitive pulmonary biomarkers/clinical endpoints. Pulmonary Deposition High pulmonary deposition is warranted for OIDPs intended for local ac tion in the lung, as it increases the amount of drug at the site of action and elicits the desired therapeutic effect. Increased pulmonary deposition also reduces the deposition in the oropharynx, thus reducing the dose available for absorption from the GI tract. Pulmonary deposition varies significantly between various inhalation devices. Recent advancements in the design of delivery devices have increased the pulmonary deposition from 1020% to up to 40%31. Although higher pulmonary deposition is beneficial in general for pulmonary targeting, it has a greater upside for drugs with higher bioavailability as a lesser fraction of the dose is available for oral absorption16. For drugs with lower oral bioavailability, the drug entering the GI tract will not be able to induce systemic side effects. However in this case a lower dose of the OIDP can be administered. Pulmonary Residence Time Drug par ticles deposited in the lung will dissolve in pulmonary fluids when released from delivery systems, such as microspheres and liposomes and diffuse to the site of action, where they exert the desired pharmacological effect and subsequently be absorbed into the systemic circulation. Given the physiology of the lung it seems logical to assume that the dissolution rate of the inhaled particle or the release rate of the drug from the delivery system are the rate limiting steps that determine lung residence time. The longer the pulmonary residence time of an OIDP, i.e. the longer it stays in the lung, longer will be their therapeutic effect. If a drug particle is given as a solution or

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22 it dissolves quickly, it is immediately absorbed into the systemic circulation and hence pulmonary selectivity is lost. In this case the pulmonary effects will be accompanied by significant systemic side effects. On the other hand lowering the pulmonary dissolution rate ensures that the drug concentrations in the lung will be greater compared to plasma levels for an extended period of time which is beneficial for pulmonary targeting. However, an optimal dissolution rate exists due to the presence of mucociliary transport in the central lung which removes undissolved drug particles leading to loss of efficacy and pulmonary targeting. A longer retention time in the lung will not reduce the overall systemic exposure of the drug, but might reduce the maximal systemic exposure of the drug. The potential for beneficial effects has warranted the genesis of a number of approaches to improve lung residence of OIDPs32. Examples of approaches include the use of liposomes33, 34, microsph eres35, 36, 37, ultrathin coating around dry powder formulations and the use of excipients such as oligolactic acid and trehalose derivatives32 as well as use of slow dissolving lipophilic drugs and the formation of lipid conjugates38 39, 40, 41 42. Intracellular ICS conjugation to lipids prolongs the pulmonary residence time by creating a depot of ICS that gradually is reactivated into active ICS and hence available to elicit anti inflammatory activity. Similarly, long acting beta 2 adrenergic drugs bind tightly to pulmonary cell membranes43, creating a reservoir of the drug which slowly releases the act ive moiety to the receptor. This prolonged residence time might allow for once daily dosing due to the extended therapeutic effect enhancing patient compliance.

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23 Pharmacokinetic/Pharmacodynamic Modeling of Cortisol Suppres sion after administration of Exogenous Corticosteroids In the previous section we have highlighted the vital pharmacokinetic parameters of OIDPs, and the roles of higher pulmonary deposition and longer pulmonary residence times in enhancing the lung selectivity i.e. a favorable pulmonary therapeutic effects to systemic side effects ratio. While most of the ICS demonstrate a series of beneficial properties they are not completely devoid of systemic sideeffects. Suppression of endogenous cortisol production is one of the major side effects of corticosteroids44 45. To quantify the degree of systemic steroid activity endogenous cortisol levels are used as a suitable marker. However, due to the marked circadian rhythm46 in cortisol release and the asymmetric nature of baseline cortisol concentrations, a precise quantification of cortisol suppression becomes an intricate exercise. Cortisol reaches a peak (acrophase) in the morning (610 a.m.) and a trough during the night (8 p.m. 2 a.m.) Furthermore, exogenous corticoster oids can suppress the release of cortisol by a negative feedback mechanism47. Hence there is a need to develop a consistent PK/PD model to characterize the effect of therapeutic corticosteroids. The first step in modeling the steroid induced suppression of endogenous cortisol is the characterization of the asymmetric baseline circadian concentrations of cortisol. Then by assuming that the exogenous corticosteroid inhibits the cortisol secretion rate the complete PK/PD model for cortisol suppression can be developed as an application of the inhibition indirect response model48. Therefore, the resulting change in cortisol concentration under baseline conditions (i.e. absence of drug) is given by =

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24 Where C is the cortisol concentration and is the elimination rate constant for cortisol. And in the presence of corticosteroids the change in cortisol concentrations can be expressed as = 1 + Where is maximum fractional inhibition of is the concentration of steroid that causes 50% of the maximal suppression of Due to the circadian nature of the cortisol release rate various time dependent 24hr periodic functions have been used to describe it. Rohatagi et al.49 investigated five different models to characterize the cortisol concentrations as a function of time and concentration of the exogenous steroid triamcinolone acetonide (TCA). A cosine50, ex ponential, monoexponential and a biexponential self suppression model were compared to a proposed linear release rate PK/PD model49 to characterize the mean cortisol baseline data for 24 hr and the cortisol levels after single dose administration of TCA. The linear release rate or the dual ramps model, which takes into account the elimination of cortisol, was shown to characterize the cortisol baseline and cortisol suppression in a better way compared to the other models based on certain goodness of fit and model selection criteria. After transforming the cortisol plasma levels to cortisol release rates by using PK parameters of cortisol, the linear rate model assumes a linear decrease in cortisol production during the day from the time of acrophase (with maximum release r ate (amount/time) at time ) to almost 0 at time of minimum release ( ) Hence for the time between the acrophase to the decrease in release rate is modeled according to

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25 = ( 2 4 ) ( ) Where t is the time after cortisol monitoring was started and is the volume of distribution of cortisol. For the time between and the increase in release rate is described by = ( ) ( ) The resulting change in cortisol concentrations in the absence and presence of the corticosteroid are modeled using equations1 and 2. The linear release rate PK/PD model was used to study the effect of various ICS Ciclesonide51, Fluticasone Propionate52, Triamcinolone Acetonide53, and Fluocortolone54 on cortisol suppression. Chakraborty et al.48 also compared several methods to model circadian cortisol concentrations. An indirect response model with six different biorhythmic functions namely, single cosine, dual ramps, dual zeroorder, dual cosines, and Fourier series with 2 and nharmonics were evaluated to model cortisol release rate. It was shown that apart from the single Cosine, all methods reasonably captured the cortisol profiles and the inhibition data were fitted similarly by all models. Fourier analysis had the added flexibility of using the placebo data to recover equations for cortisol release rate unlike other models with preassigned functions and can be extended to other drug induced changes in normal periodic rhythms. Cortisol (hydrocortisone, 11, 17, 21trihydroxypreg 4 ene3,20 dio ne) is the primary endogenous glucocorticoid synthesized in the human body from cholesterol via several enzymecatalyzed steps46. Secretion of cortisol by the adrenal cortex is regulated by the adrenocorticotropic hormone (ACTH) which is produced by the anterior

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26 pituitary gland. ACTH production is in turn regulated by corticotrophinreleasing factor (CRF) produced by the hypothalamus. Finally, the circulating cortisol molecules have a negative feedback mechanism on the hypothalamus to regulate the formation of CRF and also the anterior pituitary to regulate the release of ACTH thus maintaining homeostasis. So there is clearly a need for a physiological based model to describe the system since the mechanism involves a sequential cascade of effects and circadian rhythm. All the previously described models did not take into account the combined effect of ACTH and cortisol. Lonnebo et al.55 proposed a surge based PK/PD model similar to the one developed by Nagaraja et al.56 to describe the effect of budesonide on ACTH and cortisol. The release rate and the serum concentration of ACTH, and consequently cortisol were observed to fluctuate with a prominent circadian rhythm with two surges every 24hr one AM surge and one PM surge. In the surge based model the circadian rhythm in hormonal production was described by a constant zero or der production coupled with surges. Also ACTH was assumed to drive the production of cortisol and the effect of budesonide was assumed to solely effect the production of ACTH through an inhibitory Emax ( Imax) model. The surgebased model is described as fo llows: = 1 ( ) ( 1 ( ) ) + ( ) ( 1 ( ) ( 1 ( ) ) = ( )

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27 Where and are the first order elimination rate constants for ACTH and cortisol, is the baseline production rate of ACTH in the absence of surges without any drug, is obtained as the product of the two estimated parameters and ( ) and ( ) are described by Imax models, whereas h(ACTH) is a (sigmoidal) Emax model. Negative feedback of cortisol on ACTH production ( ( ) ( ) ) was introduced in equation using Imax models. ( ) = 1 + ( ) = ( ) ( + ) Surges which were characterized by the parameters SA (surge amplitude), SW (surge width), T (clock time) and PT (peak time) were used to define the function g(clock time) according to ( ) = ( + 1 ) The authors believe that the surge model gives a physiological description of the system and serves as a tool for further understanding of the HPA axis. Pharmacokinetic/Pharmacodynamic Modeling to Study the Relationship between Growth Velocity and Systemic Corticosteroid Exposure Corticosteroids are essential for life as they regulate and support a variety of cardiovascular, metabolic, immunologic and homeostatic functions. They play a major role in fetal development and are required for the maintenance of normal growth. But a deficiency or an excess of corticosteroids can lead to a reduction in growth rate. When therapeutic (exogenous) corticosteroids are given for a prolonged period of time, like in the treatment of chronic asthma, there is a risk of adrenal insufficiency and systemic

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28 adverse effects including reduced growth velocity in children57. Hence it is imperative to understand the relationship between corticosteroid exposure and growth velocity in children, simultaneously assessing the differential effects of various commercially available ICS. This approach may assist in the selection of ICS that maximizes the therapeutic ratio in patients. Daley Yates et al.58 consolidated data from 32 published studies of the effect of growth of inhaled, intranasal and oral Corticosteroids delivered through different routes of administration using a physiologically based pharmacokinetic/pharmacodynamic approach to study the relationship between growth velocity and corticosteroid exposure. To allow the comparison between different compounds and routes of administration amongst these studies, corticosteroid exposure was transformed to cortisol equivalents using the following equation: = Where is the steady state unbound AUC in cortisol equivalents; F is the bioavailability; dose is the daily corticosteroid dose; is the unbound fraction in plasma; represents potency (glucocorticoidreceptor binding) relative to cortisol; and CL is the systemic clearance. Further, the relationship between change in growth velocity and corticosteroid exposure in cortisol equivalents was described using a nonlinear si gmoid Emax model, as shown in the equation below: = + Where is the change in growth velocity in the absence of the drug, is the theoretical maximum reduction in GV, is the in cortisol equivalents for 50% reduction in GV The developed model was further used to predict the annual

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29 change in GV for different ICS over a range of doses. Higher systemic exposures were predicted for corticosteroids with higher oral bioavailability (11% 41%) beclamethasone dipropionate, budesonide and triamcinolone actetonide and hence were predicted to produce systemic levels above the clinical equivalence limit for change in GV when administered at standard pediatric doses. On the other hand, corticosteroids with low oral bioavailability (<1%) fluticasone propionate and mometasone furoate were predicted to show levels below the threshold. Therefore, the model was able to establish a correlation between overall systemic bioavailabil ity of ICS and short term growth effects in children. Bioequivalence of Orally Inhaled Drug Products Orally inhaled drug products present a unique challenge in the context of BE, due to the incomplete understanding of the relevance of plasma/blood concent rations to equivalence in drug delivery at the site of action (lung) and multiple ports of entry of the drug into the blood stream. The regulatory bodies like the FDA and EMA have not come to a consensus on the methods to be used for establishing BE of OID Ps. The BE approach seems to be an ever evolving landscape owing to the improved understanding of the approaches over the past few years. Nevertheless, it is worthwhile to take a peek at the current thinking of the FDA and the EMA regarding this issue. The FDA proposed an aggregate weight of evidence approach (Fig 12), which utilizes in vitro studies to ensure comparable physicochemical properties between the test and reference product, pharmacokinetic studies to establish equivalence in systemic safety and pharmacodynamic/clinical studies to demonstrate equivalence in local action. All the criteria have to be met for a test product to be deemed BE to the innovator product.

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30 In contrast, EMA uses a different strategy to establish BE (Fig 13). In principle, a generic company can conduct any one of the three tests (in vitro, PK, or PD study) to demonstrate equivalence. Hence, only one of these three criteria has to be met. In addition, if one of the tests fails then the generic company could still pass a diff erent test and gain approval. The work done in the dissertation focuses on evaluating the feasibility of using PD studies in establishing BE of OIDP, in particular inhaled corticosteroids (ICS) and 2 agonists. In chapter 2, the feasibility of using FeNO as a biomarker for local delivery of ICS and hence be used for BE testing was explored. In chapter 3, analysis of a PD BE study was conducted to establish BE of two dry powder inhalers containing a long acting 2 agonists and hence evaluate the viability of methacholine challenge as a bioassay. In chapter 4, a PK study in healthy volunteers is proposed that evaluates the sensitivity of PK metrics like AUC and Cmax to regional differences in drug deposition of different dry powder inhalers. If successful, PK studies can have an enhanced role in the aggregate weight of evidence approach and can bring about a paradigm shift in the current notion with respect to establishing BE of ICS.

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31 Figure 1 1 Fate of an Inhaled Drug 40 90 % Swallowed(reduced by spacer or mouth rinsing)GI tract Liver Oral bioavailability Absorption from gut First pass inactivation Mouth and pharynx 10 60 % Deposited in lung Lung Complete absorption from the lung Systemic Side Effects CLmucSystemic circulation

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32 Figure 12 Aggregate Weight of Evidence Approach

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33 Figure 13 EMA approach for establishing BE of OIDPs Comparative In vitro tests Systemic Exposure Studies PD or Clinical Endpoint Studies BE of OIDPs

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34 CHAPTER 2 EVALUATION OF THE FEASIBILITY OF PHARMACODYNAMIC BIOEQUIVALENCE STUDIES OF INHALED CORTICOSTEROIDS THROUGH MONTE CARLO SIMULATIONS Background Pharmacokinetic studies are the method of choice to carry out bioequivalence (BE) testing of a test and a r eference product for systemically acting drugs. The same approach is not used to establish BE of locally (lung) acting drugs such as Inhaled Corticosteroids (ICS), primarily due to the incomplete understanding of the relevance of plasma/blood concentrations to equivalence in drug delivery at the site of action (lung) and multiple ports of entry of the drug into the blood stream. In this case, the FDA endorses an aggregate weight of evidence approach for establishing BE of ICS. The approach utilizes in vitro studies to ensure comparable physicochemical properties between the test and reference product, pharmacokinetic studies to establish equivalence in systemic safety and pharmacodynamic/clinical studies to demonstrate equivalence in local action62. In 2007, the FDA introduced the critical path initiative for generic d rugs, that identified specific challenges and hence opportunities in the development of generic drugs This included the develop ment of methods for assessing BE of locally acting drugs such as topical and inhalation products63. One solution proposed by the FDA was to identify novel pharmacodynamic markers that are sensitive to local drug concentrations and hence can be used for BE testing. Within the same context, fractional exhaled nitric oxide (FeNO) was extensively investigated by the FDA as a marker of local delivery of an ICS. Such pharmacodynamic approaches to establish BE

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35 of locally acting drugs, though have been relatively successful for the dose response assessment of albuterol, long acting 2 adrenergic dr ugs and anti muscarinic agents64,65,66 are more challenging for inhaled glucocorticoids The various biomarkers that have been evaluated for gl ucocorticoids include sputum eosinophilia, exhaled nitric oxide, methacholine challenge etc., but most of these studies suffer from insensitive doseresponse relationships and/or high variability in the biomarkers67,68,69. Hypothesis Our eventual hypothesis is that pharmacokinetic studies should be the preferred method for establishing equivalence in local efficacy of orally inhaled corticosteroids. To evaluate this hypothesis we have the following specific aims: Specific Aim 1: Evaluation of the feasibility of pharmacodynamic crossover studies conducted to establish BE of ICS To achieve this goal Monte Carlo simulation s of pharmacodynamic crossover studies were performed and equivalence in local efficacy was evaluated using the D ose scale method, wherein the BE assessment is made through relative bioavailability which is defined in terms of the dose of the test product required to produce an equivalent PD response as the reference product. The betweensubject and within subject variability estimates for the simulations were obtained from literature. Power calculations were performed to estimate the number of subjects required to show BE between a test and reference product for a set of predetermined criteria, a nd power was the primary yardstick to evaluate the feasibility of PD BE studies.

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36 Specific Aim 2: (chapter 4) Demonstrate sensitivity of Pharmacokinetic metrics to differential distribution of the drug in the central/peripheral regions of the lung The goal is to manufacture three DPI formulations containing Fluticasone Propionate in a Plastiape Monodose DPI device, which provide distinct in vitro deposition patterns on a Next Generation Cascade Impactor. It is desirable to develop three formulations with the same emitted dose (ED), impactor size mass (ISM) but different mass median aerodynamic diameter (MMAD). A pharmacokinetic study in healthy subjects will be conducted using formulations that meet these design criteria to evaluate if pharmacokinetic paramet ers are sensitive to regional differences in drug deposition whilst having the dose deposited in the lung from different formulations being the same. Specific Aim 1: Evaluation of the feasibility of pharmacodynamic crossover studies conducted to establish BE of ICS Methods Dose Scale Method A Dose Scale method incorporating the Emax model was us ed to analyze the data from simulated pharmacodynamic (PD) BE studies. The FDA developed the DoseScale approach to establish equivalence in local efficacy using PD end points wherein nonlinear dose response relationships are observed. Based on this method the assessment of BE is made in terms of the relative bioav ailability (FDS) of the test and the reference formulations at the site of action. FDS is determined in terms of the dose of the test product required to produce an equivalent response as the reference product.

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37 In this approach, the Emax model is assumed t o be the structural model describing the relationship between dose () and response () of the reference product = ( ) = + Baseline FeNO response in the absence of the drug Max imum effect attributable to the drug (reference product) Reference dose producing 50% of the maximum effect T he mean or the pooled data from multiple doses of the reference product were used for Emax model fitting () and the estimates of the parameters and were obtained. In order to estimate the dose of the test product that would produce an equivalent PD response as the reference product, the inverse of the Emax function was ( ) applied to the mean response of the test product () ( ) = ( ) ( ) The relative bioavailability is then calculated by taking the ratio of the test dose obtained by applying the inverse of the Emax curve to that of the claimed test dose (claimed reference dose) = ( ) So by definition a value of close to 1 indicates that the two products are equivalent in terms of clinical efficacy. The above mentioned steps encompass the first stage (Fig 2 1) of the Dose Scale approach which is to establish a within study dose

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38 response using the mean/pooled data of the reference product and obtain a point estimate for using the mean response of the test product. The second stage of the Dose scale a pproach is to apply a bootstrap based nonparametric approach to construct distributions of relative bioavailability (FDS) (90%CI) and make conclusions regarding the outcome of the BE trial. Data Simulation Strategy Pharmacodynamic Crossover Study PD B E studies were simulated in a 4period, 4sequence, and 4treatment crossover design as shown in Fig 2 2 The active treatments included 3 doses of the reference product to establish a within study dose response relationship and one dose of the test product to calculate the relative bioavailability estimate ( FDS). T he PD biomarker values (FeNO) for each subject receiving a particular treatment were simulated from a linear mixed effect model = + ( ) + + + + Where = 1 2 , ; = 1 2 , ; = 1 2 , ; = 1 2 , Equation 1 represents a general model comprising treatment sequences, periods, treatments and subjects in the ith sequence. is the general mean; is the effect of the ith treatment sequence; is the random effect with variance 2 bfor the jth subject of the ith treatment sequence; is the period effect; is the random error with variance 2 for the subject in period k; ( ) is the direct effect of th e treatment administered in period k of sequence group i Since we make the assumption that the structural model that describes the relation

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39 between dose and response of the reference product is the Emax function, we simulate the effect of the mean plus the treatment effect ( + ( ) ) from an Emax model. Also for the purposes of simulation we neglect the effect of the period and the sequence + Therefore, the transformed linear mixed effect m odel used for simulating individual PD data can be written as follows = + + + Where ~ ( 0 ) and ~ ( 0 ) and is variance of the between subject variability and is varia nce of the residual variability of FeNO in defined patient populations. The parameter estimates of the Emax model ( , ) and the variances ( ) are obtained from literature and are described in the following section. Li near mixed effect model Literature based parameter estimates Emax model parameter estimates A primary objective of the simulations was to predict the response of FeNO to different doses of ICS in defined patient populations, distinguishing between high responders and intermediate responders. We defined high responders as patients with elevated FeNO baseline levels ( = 90 ppb) and hence have a higher likelihood of responsiveness to inhaled corticosteroids (= 75 ppb) as shown in Fig 2 3 They represent the patient population in studies that evaluated the dose response to ICS in a phenotype enriched sample of patients with elevated levels of FeNO2 3 4 5 6. Literature research (Fig 2 4 ) was conducted not only to identify such trials but also to isolate

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40 studies that characterized FeNO levels in healthy volunteers7 8 9 in order to define the maximum scope of improvement () with corticosteroids in asthmatics in our simulation s. = ( ) ( ) In contrast intermediate responders are defined as patients with intermediate FeNO baseline levels ( = 52.5 ppb) and hence have a lower likelihood of responsiveness to inhaled corticosteroids (= 37.5 ppb) as shown in Fig 23 They are analogous to studies where no special inclusion criteria were used in selecting the asthmatic patients. An estimate of that is a mid point between the levels of high responders and healthy volunteers was used in our simulations. There are very few studies in literature that reported values of while studying the FeNO dose response to ICS Hence an informed estimate was made and a releva nt range of values between 2 0 and 250 were identified for the simulations The doses of the reference product were als o chosen to be in the range of 2 0 and 250. The dose of the test product can be any one of the three doses of the reference product. Hence it is imperative to study the impact of the choice of the test dose on the power of the PD BE study. The doses of the test product in the simulations were expressed as multiples of ranging from 0.2* to 5* in order to study the impact of their position on the within study dose response curve on the resulting power. The literaturebased parameter estimates of the Emax model are summarized in table 2 1.

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41 Variance Estimates The estimate of within subject (residual) variability was obtained from a study that investigated the dosedependent anti inflammatory effects of a combination of beclamethasone dipropionate/formoterol (BDP/F) using FeNO as the marker for inflammat ion. To our knowledge, this was the only ICS FeNO PD study in literature that carried out an analysis of covariance for a cross over study design with patient (sequence and patient within sequence), period and treatment as factors and reported least square means of the pairwise treatment effect and the corresponding 95% CI, that enabled us to back calculate the mean square error using the correct degrees of freedom. The following equations were used and the value of was estimated to be 11.7 ppb. The value of was set to an estimate of 10 ppb. ( ) = 2 ( ) = 2 Where and are the upper and lower limits of the 95% CI for the pairwise difference. is the appropriate degrees of freedom for residual error. is the number of subjects in the study. Anderson et al. reported a within subject SD of 5.4 ppb in their power calculations, wherein they studied the dose response to ICS in patients with elevated FeNO levels. We also simulated clinical PD studies with of 5.4 ppb and labelled those scenarios as the studies involving low variable population (Fig 2 9 Fig 2 10). We believe that a estimate of 11.7 ppb is more representative of reality and hence the focus of our results and discussion.

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42 Analysis of Simulated Data The PD crossover BE studies were simulated using literature based estimates summarized in Table 1. The simulated datasets were evaluated using the two stage d ose scale approach wherein BE assessment is made in terms of the relative bioavailability FDS. For each simulated cross over study a withinstudy dose response relationship was obtained by fitting the means of the reference product to an Emax model. The in verse of this Emax model was applied to the mean response of the test product and a point estimate for was obtained. A 90% CI for was obtained by a bootstrap procedure. Each bootstrap step involves the generation of a sample crossover study by sampling with replacement and its analysis as described above culminating in the calculation of 1000 bootstrap samples were generated for each simulated scenario and hence 1000 were obtained from each sample. A 90% confidence i nterval f or was obtained by chopping off the 5th and the 95th percentile values of If the confidence i nterval of falls within the pre determined limits then we conclude BE. Power Calculations Each combinati on of the parameters listed in T able 1 comprises a simulation scenario. 200 datasets were simulated for each scenario and for each simulated dataset 90% CI for was obtained by a bootstrap procedure. The percent of the 200 simulated datasets for which the 90% CI for falls within the prespecified BE limits was defined as the power for that scenario.

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43 Results Impact of sample size PD BE crossover studies were simulated with sample sizes ranging from 32128 subjects. In all the results ( Fig 2 5 Fig 2 6 Fig 2 7 Fig 2 8, and Fig 2 9 ) we see that the power increases with increasing sample size in the simulated studies. The phenomenon is expected, but the power as a function of sample size has no relevance in our current simulations when not evaluated in the context of its interaction with the choice of the test dose, the study population, BE criteria or the variability of FeNO in the study subjects. Hence the interplay of sample size with other study factors was evaluated. Impact of Choice of Test Dose The first stage of the Dose Scale approach involves establishing a within study dose response using the mean/pooled data of the reference product and subsequently obtain a point estimate for using the mean response of the test product. The choice of the test dose can be any one of the three doses of the reference product. Hence it was imperative to study the impact of the choice of the study dose on power. The doses of the test product in the simulations were expressed as multiples of ranging from 0.2 to 5* in order to easily correlate the resulting power to their position on the within study dose response curve. We observed that the power increases for a given sample size when the test dose increases from 0.2 t o 1* (Fig 2 5 ) and power decreases when the test dose further increases towards 5* (Fig 2 6 ). This shows that the maximum power is obtained when the test dose is close to the 50 This is because when the test dose is close to the it is in

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44 the sensitive region of the dose response curve, whereas when the test dose increases towards 5* it is on the top of the dose response curve wherein small differences in FeNO res ponse translate to large differences in dose. In reality, for PD studies studying the impact of ICS on FeNO, the doses are larger than the and hence we focused on the region from t o 5* while evaluating the impact of other factors on power. Impact of BE criteria All the simulated BE studies were evaluated using a standard BE criteria of 0.81.2, while assessing the 90% CI of relative bioavailability (FDS). In addition, a relaxed criterion of 0.671.5 (draft guidance Albuterol Sulfate) was also applied to study the impact of widened BE limits on power. When the test dose is equal to and the study subjects were high responders a power of 90% was obtained when the sample size was 128 when standard BE criteria of 0.8 1.2 were employed while assessing the 90% CI of relative bioavailability (FDS). On the other hand, when the test dose was on the top of the dose response curve i.e. 5* the p ower was just 21% with the same sample size of 128 high responders. For the same scenario when the BE criteria was relaxed to 0.67 1.5, the power was 90 % (Fig 2 7 ). Impact of the study population PD BE crossover studies were simulated with high responders and intermediate responders to mimic real studies which have inclusion criteria to enrich study population with high FeNO baseline values and those which do not have such criteria in place. The results show that at a qualitative level for any given test dose and sample size the high responders have higher power compared to the intermediate responders. This is

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45 because they have a higher probability of responding to ICS owing to their high baseline FeNO values and hence exhibiting sensitive dose response r elationships. When the test dose is equal to 90% power was obtained for 32 high responders as opposed to 128 intermediate responders. For the scenario wherein the test dose is on the top of the dose response curve (5* ) 90% power is obtai ned with 128 high responders in the study whereas with the same number of intermediate responders 20% power was obtained (Fig 28). Discussion and Significance T he prime objective of this analysis was t o develop a clinical trial simulation model which is suitable to evaluate the feasibility of PD (FeNO) crossover studies for assessing pulmonary BE of ICS The trials were simulated by i ncorporating variability of FeNO in defined patient populations ( high responders vs. intermediate responders ) and to predict their response to ICS T he outcome of the simulated BE studies was evaluated using a Dose Scale approach applying a bootstrap based nonparametric approach to construct distributions of relative bioavailability (FDS) (90%CI) for test vs. reference formulations The purpose of the simulations was also geared towards identifying the optimum parameters that give a generic company the highest probability of establishing BE. That objective was met by studying the interplay between various factors such as choice of the test dose, BE criteria, enriched patient population and their impact on sample size estimates (power). The results from the simulations show that the highest power was obtained when the test dos e is equal to the and the power reduces when the test dose is on the top of the dose response curve. An

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46 example of this is Advair Diskus manufactured by GlaxoSmithKline which was the 4th largest selling drug product in the US in 2012 with sales of 4.5billion USD, is available in three dose strengths of Fluticasone Propionate (100mcg, 150 mcg, 500 mcg). For PD BE studies establishing the dose response to ICS in patient s using FeNO as the biomarker, a n estimate for the relevant ED50 is 20mcg 100 mcg. Hence, when a Dosescale approach is applied to establish BE of ADVAIR, even the lowest dose of 100 mcg might be on the top of the dose response curve ( 5* ). Our simulations show that in such a scenario 90% power is obtained only when the BE li mits are relaxed to 0.671.5 and 128 high responders are used. Previously published literature has shown that the probability of finding high responders is about 30%, which means that to recruit 128 high responders, about 450 asthmatic patients have to be screened prior to the study. Hence the PD approach for establishing BE of ICS using FeNO as the biomarker seems feasible only when the test dose is in the sensitive region of the dose response curve, the BE limits are relaxed and the studies are powered for FeNO.

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47 Figure 21 Dose Scale Approach 0 100 200 300 400 500 600 0 20 40 60 80 100 Non-Linear Dose Response Dose PD Response (% of Emax)

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48 Figure 2 2 Pharmacodynamic crossover study design R1 R2 R3 T R1 R2 R3 T R1 R2 R3 T R1 R2 R3 T Subjects (n) Randomized Period 1 Period 2 Period 3 Period 4 Run in Baseline1 Baseline2 Baseline3 Baseline4 Washout Washout Washout

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49 Fig ure 2 3 Dose response relationship of high responders and intermediate responders 0 100 200 300 400 500 600 20 40 60 80 100 120 Dose (mg) FeNO (ppb) High Responders Intermediate Responders E0= 90 ppb E0= 52.5 ppb Emax= 75 Emax= 37.5

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50 Figure 2 4 Literature Research FeNO trials FeNO (ppb) Baseline Sample Size (n) Subject selection c riteria Reference M edian Range 103.5 79 137 15 FeNO > 60 ppb Silkoff et al., 2001 70.5 53 88 40 Loss of control Jones et al., 2002 > 47 --17 FeNO > 47 ppb Smith et al., 2005 82 27 120 18 FeNO > 25 ppb Connor et al., 2011 71 61 83 20 FeNO > 30 ppb Anderson et al., 2012 17.1 13 24 1090 Healthy Olin et al., 2006 16.6 6 47 1131 Healthy Olin et al., 2007 17.9 8 41 193 Healthy Travers et al., 2007

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51 Figure 2 5 Power as a function of sample size and choice of test dose (Range = Low)

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52 Figure 2 6 Power as a function of sample size and choice of test dose

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53 Figure 2 7 Power Calculations Comparison of BE criteria

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54 Figure 2 8 Power Calculations High vs. Intermediate responders

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55 Figure 2 9 Power Calculations High vs. Low variable population

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56 Figure 2 10 Distribution of parameters High vs. Low variable population

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57 Table 21 Simulation Scenarios Parameter Estimates Parameters of E max model Biomarker FeNO Units High responders Intermediate Responders ppb 90 52.5 ppb 75 37.5 mcg 20, 50,100,250 20, 50,100,250 ppb 10 10 p pb High 11.7 Low 5.4 High 11.7 Low 5.4 Test Dose as multiple of mcg 0.2,0.4,0.5,1,2,2.5,5 0.2,0.4,0.5,1,2,2.5,5 Number of Subjects (n) 32,48,64,128 32,48,64,128

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58 CHAPTER 3 ANALYSIS OF A PHARMACODYNAMIC CROSSOVER STUDY CONDUCTED TO ESTABLISH BIOEQUIVALENCE OF FORMOTEROL AEROLIZER AND FORMOTEROL N OVOLIZER Background To establish bioequivalence ( BE ) of generic orally inhaled drug products at the site of action, the FDA recommends pharmacodynamic ( PD )/clinical endpoint studies. For e.g. bronchopr ovocation (methacholine challenge) studies are recommended for 2 agonists. The primary objective of this work was to evaluate the equivalence in clinical efficacy of two dry powder inhalers containing formoterol, a long acting 2 agonist in patients with stable asthma using PC20 as the primary endpoint. PC20, is defined as the provocative concentration of methacholine required to reduce the F orced Expiratory Volume in 1 sec (FEV1) by 20% following administration of differing doses of the beta2 agonist or placebo by inhalation. Research Objective T he primary goal of the project was to analyze a PD crossover study conducted to demonstrate BE between formoterol Aerolizer 12 mc g (reference ( FA )) and formoterol Novolizer 12 mc g (test ( FN )) by p erforming statistical analysis of the crossover study using PC20 as the primary endpoint A Dose scale approach was used to estimate the relative bioavailability (FDS) of FN relative to FA. Further, a bootstrap based nonparametric approach was used to co nstruct distributions of FDS (90%CI) for FA vs. FN A Finney bioassay was also was also performed to estimate the relative potency of FN relative to FA. A Fieller 90% CI was constructed for relative potency. T he outcome was evaluated based on ( 0.67 1.5 ) BE limits

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59 Methods Study Design The study comprised of 6 visits 2 Screening Visits and 4 Treatment Visits Screening Visit 1 Methacholine challenge was performed on subjects with at least 70% predicted FEV1. A 20% decrease in FEV1 had to be reached at PC20 8mg/ml Screening Visit 2 Patients had to inhale 24 g from FA and the PC20 had to increase at least 4Treatment Visits After screening, the selected patients were administered the active treatments in a crossover fashion (Fig 3 1). PC20 Measurement PC20 values were recorded at each treatment visit as shown in the flowchart (Fig 32). The patients inhaled a saline dilution and 30 to 60 seconds later, spirometry was performed. The lowest dilution of methacholine or the conc entration below the highest dilution used to obtain baseline PC20 during visit 1 was administered. The concentration of methacholine was increased, in doubling increments in 5minute intervals until the FEV1 decreased 20% from the post saline value. The concentration of methacholine that resulted in a 20% drop in FEV1 compared to the post saline value is by definition the PC20 At visit1, the unprotected (baseline) PC20 was determined and during visit 2, since the airways were under the protective effect of the 24 g FA, the protected PC20 was determined. PC20 values were log transformed to meet the assumptions of normality and hom oscedasticity (Fig 33 and Fig 34).

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60 Dose Scale Approach A Dose Scale method incorporating the Emax model was used to analyze t he data from PD crossove r study. The FDA developed the d ose Scale approach to establish equivalence in local efficacy using PD end points wherein nonlinear dose response relationships are observed. Based on this method the assessment of BE is made in term s of the relative bioavailability (FDS) of the test and the reference formulations at the site of action. FDS is determined in terms of the dose of the test product required to produce an equivalent response as the reference product. In this approach, the Emax model is assumed to be the structural model describing the relationship between dose () and response ( ) of the formoterol Aerolizer (FA) = ( ) = + + Baseline PC20 response in the absence of the drug Maximum effect attributable to the drug (reference product) Reference dose producing 50% of the maximum effect T he pooled data from the baseline, 12 mcg and 24 mcg doses of the reference product FA were used for Emax model fitting () and the estimates of the parameters and were obtained. In order to estimate the dose of the test product that would produce an equivalent PD response as the reference product, the inverse of the Emax function was ( ) applied to the mean response of the 12 mcg dose of the test product ( ) formoterol Novalizer.

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61 = ( ) ( ) The relative bioavailability was then calculated by taking the ratio of the test dose obtained by applying the inverse of the Emax curve to that of the claimed test dose (claimed reference dose) = So by definition a value of close to 1 indicates that the two products are equivalent in terms of clini cal efficacy. The above mentioned steps encompass the first stage of the DoseScale approach wherein a within study dose response was established using the mean/pooled data of FA and a point estimate for was obtained using the mean response of FN. T he second stage of the Dosescale approach is to apply a bootstrap based nonparametric approach to construct distributions of relative bioavailability (FDS) (90%CI) and make conclusions regarding the outcome of the BE trial. Finney (2, 2) parallel line assay Relative potency was also estimated from a 4 point parallel line Finney assay (2 formulations at 2 dose levels) as outlined in the Appendix 4 of the Canadian guidance. The first step was to check the validity of the bioassay. An analysis of covarianc e (ANCOVA) model with fixed effects sequence, period, formulation, log2(dose), log2(dose)*formulation interaction and random effects subject (sequence), and subject(sequence)* log2(dose) was applied to log transformed PC20 values. The following analysis was performed to ensure that there was a significant doseresponse (significant log2(dose) effect) and the assumption of parallelism (non significant

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62 log2(dose)*formulation interaction) was met. Once the assumptions were met, the second stage of the analysis was performed which also comprised of applying an ANCOVA model with fixed effects sequence, period, formulation, and log2(dose) and random effect subjects(sequence) to log transformed PC20 values. The relative potency of the Novolizer to that of the Aerol izer was estimated from the analysis using the following mathematical expressions. log ( ( ) ) = A Fiellers type CI interval was estimated for log ( relative potency) ( log ( ) ) = 2 + ( ) / ( 1 ) Where R is the estimate of log ( ( ) ) b is the estimate of the common slope corresponding to ( ) = is the v ariance of is the covariance of and b is the variance of b t is the 95% percentile of the t distribution The estimate and the CI for relat ive potency are obtained by exponentiation of the log transformed estimates. If the 90% CI for is between 0.671.5 then BE is concluded between the Novolizer and the Aerolizer.

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63 Results While a nalyzing the data with a dosescale approach, a within study dose response relationship was established using the PC20 values after administration of the Aerolizer reference product (FA) ( ED50 = 7.8 g) (Fig 3 5). T he relative bioavailability (FDS) of the 12 g dose of FN relative to F A was calculated to be 1.18. The 90% CI interval of FDS for the 12 g dose was 0.941. 45 (Fig 35). Hence the 90% CI interval of FDS was within the wider BE limits of 0.67 1.5 but not within the traditional limits of 0.81.25 ( Fig 3 6). A Finney bioassay was also applied to analyze the data. Preliminary analysis showed a significant dose response (pvalue <0.001) and a statistically insignificant doseformulation interaction (pvalue = 0.5278) (Fig 37). Hence the assumptions of the parallel line assay were met. The second stage of the approach was applied and the point estimate of relative potency was obtained to be 1.131. The 90 % Fieller CI for relative potency of the Novolizer compared to the Aerolizer was estimated to be (0.971.34). Conclusions Formoterol Novolizer was shown to be bioequivalent to the formoterol Aerolizer using the dosescale approach and the Finney bioassay, as the 90% CI interval of FDS for the 12 g dose and 90% CI of relative potency were within the BE limits of 0.67 1.5. Results show that PC20 is a sensitive biomarker and hence methacholine challenge is a viable assay for 2 agonists

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64 Figure 3 1 Crossover Study Design

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65 Figure 3 2 Methacholine Challenge Perform Spirometry 20% Decrease in FEV1? Maximum Methacholine Concentration? Methacholine Dose Yes No1 2 5 4 3 Record Methacholine Concentration Spirometry Performed Beta -Agonist Administered Saline Administered PC20No

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66 Figure 33 Diagnostic plots for the log transformed data

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67 Figure 3 4 Distribution of log (PC20) values

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68 Figure 3 5 Dose Scale approach 12mcg dose

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69 Figure 3 6 Bootstrap FDS values 12mcg dose

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70 Type 3 Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F SEQ 3 71 0.87 0.4603 PERIOD 3 71 3.29 0.0254 FORM 1 71 0.62 0.4337 LNDOSE 1 37 52.95 <.0001 LNDOSE*FORM 1 71 0.40 0.5278 Figure 37 ANCOVA model evaluating the doseformulation interaction

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71 CHAPTER 4 EVALUATION OF THE SENSITIVITY OF PHARMACOKINETICS TO DIFFERENCES IN THE AERODYNAMIC PARTICLE SIZE DISTRIBUTION OF THREE DIFFERENT FORMULATIONS OF FLUTICASONE PROPIONATE DRY POWDER INHALERS Specific Aim 2: Demonstrate sensitivity of Pharmacokinetic metrics to differential distribution of the drug in the central/peripheral regions of the lung Background Pharmacokinetic Approach Pharmacokinetic studies, if useful for the assessment of topical bioequivalence of orally inhaled products should provide information on three key questions, which are relevant for assessing the bioequivalence of inhaled drugs: Is the dose available to the lung equivalent? How long does the drug stay in the lung (Pulmonary residence time)? Where is the drug deposited in the lung? (Central ( C ) to Peripheral ( P ) lung distribution)? It is generally accepted that questions 1 and 2, can be answered by pharmacokinetic studies when the oral absorption is negligible or blocked, e.g. through co administration of charcoal. For drugs with negligible oral bioavailability like fluticasone propionate, systemic exposure (AUC) is a direct measure of the drug available to the lung. Evidence from the literature suggest s that PK parameters are sensitive to differences in t he dose available to the lung. Differences in pulmonary residence time of the test and reference inhaled drug may be associated with differences in their physicochemical properties resulting in varied dissolution rates. Previous studies over a large range of asthmatic patients have established that the

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72 pulmonary absorption of small particles is faster and more extensive (Cmax and AUC) than that of large particles. Hence the current proposal will investigate the potential of pharmacokinetic approaches to ass ess differences in the regional lung deposition in terms of the central to peripheral (c/p) ratio. Clinical trial simulations and available clinical studies suggested that for slow dissolving drugs like FP (water solubility of < 0.1g/ml), pharmacokinetic studies might be able to detect differences in the c/p ratio, because of the presence of mucociliary clearance mechanisms in the central regions of the lung, supporting the hypothesis that a more central deposition will affect the AUC and Cmax parameters. The proposed clinical study will involve administration of fluticasone propionate, a slow dissolving drug, via DPI. Formulation Development Aerodynamic particle size has a significant impact on the regional lung deposition of the drug. It is observed that large particles(> 6m) deposit in the oropharyngeal region and the large airways by impaction, smaller particles (26m) deposit in the bronchioles by gravitational sedimentation and particles of size less than 2m deposit in the terminal bronchioles and alveolar region mainly by diffusion. An array of invitro tests will be performed to optimally characterize the formulations with respect to their aerodynamic lung deposition behavior that will ensure differences in regional pulmonary deposition. A very si milar question concerning the assessment of regional deposition occurs always when gamma scintigraphy is used to image pulmonary deposition. This technique is based on wet chemistry dependent alterations of the aerosol/DPI formulation to label the formulat ion with radioactive technetium. This labeling procedure

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73 has the potential to change the aerosol/DPI properties of the nave formulation and affect regional deposition. To ensure that the labeling technique does not result in a changed regional deposition behavior for such formulations, in vitro impactor tests (e.g. Anderson and NGI impactors) have been accepted to show an unchanged behavior between nave and labeled material as a quality control measure1516. While in the case of gamma scintigraphy, the equivalency of two aerosol/DPI formulations has to be documented, we use the same and even additional techniques to demonstrate nonequivalence of the deposition behavior. Overall, we believe that our array of in vitro deposition studies represents the best way to assess differences in regional pulmonary deposition: Cascade impactor studies with standard USP throat to assess aerodynamic particle s ize distribution: This method is generally used to determine sui tability of labeled gamma scintigraphy formulations (see above). In principle, cascade impactor derived aerodynamic particle size distribution (APSD) data, determined by this method are thought to provide information that is predictive of lung deposition. As an example, this method has been able to differentiate between CFC and HFA beclomethasone propionate, two formulations that differ in their central to peripheral ratio. Next generation impactor studies with anatomical mouththroat models (VCU throat + Finlay throat): This variation using NGI impactors with anatomical throats has been selected to obtain estimates of the pulmonary deposited dose. Upper airway models : In addition, an upper airway model, developed by the Peter Byron and his group will be used to assess not only mouth and throat deposition, but to further ensure differences in in the airway deposition.

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74 All together, the combined use of these three in vitro tests is unique and will ensure that the formulations will be optimally characterized far beyond generally employed investigations (e.g. for scintigraphy only standard cascade impactor studies are employed). This will ensure that the deposition properties of these formulations will be adequately investigated and differences in the deposit ion profile will be ensured. A Pharmacokinetic study will only be performed if these in vitro tests will ensure differences in their aerodynamic deposition profile. The aim of the pharmaceutical development was to manufacture three DPI formulations containing Fluticasone Propionate in a Plastiape Monodose DPI device, which provide distinct in vitro deposition patterns on a NGI. NGI is a high performance cascade impactor used to characterize aerosol particles by particle size. It is desirable to develop thre e formulations with the same emitted dose (ED), impactor size mass (ISM) but different mass median aerodynamic diameter (MMAD). Meeting these design criteria for the formulations would help to see if pharmacokinetic parameters are sensitive to regional dif ferences in drug deposition whilst having the dose deposited in the lung from different formulations being the same. Dry powder inhaler (DPI) formulations are adhesive mixtures of micronized drug particles blended with large carrier particles of lactose monohydrate. The production of this formulation mixture enables accurate metering of the dose and improves flow properties to aid device filling. The force generated upon the patients inspiration then aids the fluidization and deaggregation of the fine drug particles from the lactose. It is however, the complex nature of the surface interfacial interactions between drug and excipient within a DPI blend that governs the overall relationship between device and

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75 deaggregation efficiency of the formulation and therefore, directly affects the deposition profile of the drug across the respiratory tract. The aerosolization performance of DPI formulations maybe controlled and manipulated by varying the blending protocol and/or selecting different grades of lactose. A common approach utilized to modify the deaggregation efficiency and, thus, the therapeutic efficacy of a DPI formulation is via the addition of ternary agents. For such preparations, a small quantity of fine excipient particles (of similar geometric siz e to the active ingredient) are either coprocessed with the active and coarse carrier particles or are generated during the processing of the excipient. Extensive research into the role of fine excipient particles suggests that their inclusion results in increased liberation of drug particulates, for which a number of mechanisms have been proposed. The dramatic influence of the presence or the addition of fine excipient particles on the aerosolization performance of ternary formulations has been related to the formation of drug/fines agglomerates. The addition of different grades of lactose fines to DPI formulation has been reported to directly affect the formulation structure at a microscale. Microstructure is defined as the number and the location of interparticulate contacts within the powder bulk, and defines how the force created upon impaction in the device is transferred through agglomerates entrained in the airflow. It has been previously shown that changing the particle size of lactose fines included in DPI formulations, will affect the microstructure of the formulation and consequentially, different degrees, of powder deagglomeration upon delivery. As result of this, the inclusion of fine excipient particles of defined particle size can shift the m ass median aerodynamic diameter of the

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76 drug. Our recent data suggests that this is due to the formation of drug/lactose fines agglomerates that shifts the deposition pattern of the drug. In a dry blending operation (e.g. turbula blending, highshear mixing), the powder mixing takes place through a combination of shear mixing, convection, and dispersion. In addition, there are significant press on forces that are able to influence the surface interfacial force balance of DPI formulations. The magnitude of t hese processes during blending are a result of the energy imparted into the powder during blending. The energy input into the powder during highshear blending of DPI formulations can be modeled and correlated to blend homogeneity and DPI drug product perf ormance. Hence, there is an intrinsic relationship between surface interfacial properties of the API/excipient, blending energy and DPI blend homogeneity and performance. The approach to be utilized during pharmaceutical development to achieve the aim of producing three formulations with different APSD will rely on manipulating the blending process and the selection of lactose with different particle size distribution. The grades of lactose selected for investigation in this pharmaceutical development have been chosen as the ideal candidates to help create three formulations with the same emitted dose (ED), impactor size mass (ISM) but different MMAD. Preliminary results from the analysis of the in vitro data suggest that, such a design of the formulations is feasible. University of Bath will enter into an analytical and formulation methods transfer program with Catalent, who have their inhalation cGMP unit based in the North Carolina, USA. Catalent will produce R&D batches and conduct release testing of drug,

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77 excipient and capsules. These data will be collected under cGMP and will provide the certificate of analysis and R&D formulation development data for the investigator IND. Methods Study Design The aim of the study is to determine the sensitivity of pharmacokinetics (PK) to differences in the regional lung deposition of three different formulations of fluticasone propionate (FP) dry powder inhalers (DPI). This is a single center, double blind, single dose (500 g), randomized, four period, four sequence cross over PK study to evaluate the local (lung) Bioequivalence (BE) of 100 g fluticasone propionate formulation 1(FPF I), 100 g fluticasone propionate formulation 2(FPF II) and 100g fluticasone propionate formulation 3(FPF III). FPF III will be repl icated in the study, to demonstrate that the study has enough power to conclude bioequivalence when FPF III is tested against itself. The three formulation labels (FPI, FPII, and FPIII) are just placeholders and they will be randomly assigned to the three actual formulations. Once FPIII is chosen randomly, a different batch of the same formulations will be chosen as its replicate (FPIII*). The inhalation device and the capsule for the three formulations are identical and hence the subject will be unable t o distinguish between the three formulations. Also, since the formulations will be labeled with sequence number, period number and patient ID, the person administering the drug will be blinded for the formulation as well. Hence a double blind study. The number of subjects required was calculated to be 44, which takes into account a 10% drop out rate to ensure 40 subjects complete the study. Subjects will include healthy males and females aged 18 and 50 years who meet the inclusion and exclusion criter ia.

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78 Assignment to treatment and randomization The study comprises of 5 visits: 1 screening visit and 4 treatment visits. On each treatment day, subjects will get 5 inhalations from one of the three formulations (Table 41). The sequences to be used in the study are described in Table 4 2. Note that in this design every treatment appears once in each period. Also every treatment is immediately followed only once by each of the other treatments. Dose and Device Fluticasone Propionate is used for the mainte nance treatment of asthma as a prophylactic therapy in patients 4 years and older. On each treatment day, subjects will get 5 inhalations from each formulation containing 100 g of FP. A time interval of 30 seconds which includes a breath holding time of 10 seconds, is given between each inhalation. After each complete dose (5 inhalations), the subject is asked to rinse their mouth with water without swallowing. A new device is used for every subject. The 500 g daily dose was selected to ensure measurable concentrations in the plasma for 24 hours. The LLOQ of the bioanalytical method is 10pg/ml. Also, 500 g is well under the highest recommended dose of 1000 g daily (Labeling information of FLOVENT DISKUS ). And since it is a single dose study, the select ed dose is safe. The Plastiape Monodose DPI is a breath activated dry powder inhalation device. The Drug Master File (DMF) number is 18418. The medication is contained in a capsule. It is equivalent to the AEROLIZER which is an approved device in the US, currently marketed as FORADIL AEROLIZER. An IND will be filed for the formulations. Randomization The subjects will be randomly assigned to the four sequences, listed in the table above. Following each treatment visit, the subjects will be crossed over to the

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79 subsequent treatment arm with a washout period of at least 5 days (> 5 terminal t1/2 of ~14 hours22) between treatment visits. The half life of fluticasone propionate after intravenous administration is reported to be 7.8 hr23. But the value o f 7.8hr is not used to decide the length of the washout period. After oral inhalation of the drug, there could be flipflop kinetics depending on the absorption rate of the drug. The t1/2 of 14hr was reported in a single dose fluticasone propionate inhalat ion study in healthy volunteers, which is similar to the design of our current study. A washout period of 5 days was chosen to make sure there was no carryover of the drug into the next period. A sample randomization scheme is shown in Table 43. Benefit/r isk considerations Participation in a human pharmacokinetic study like the present one cannot be of benefit to healthy volunteers. Nevertheless, the information form the physical examination, vital signs, ECG and the breathing tests will be shared with your personal physician if you choose. The subjects contribution to the study is of major importance to agencies like the U.S. Food and Drug Administration (FDA) for helping them better evaluate the generic alternatives and thus make available cheaper and ef fective formulations for asthmatic subjects. The subjects are exposed to risks associated with the pharmacological properties of the investigational product and the study procedures. One dose of fluticasone propionate rarely has side effects. Bad reactions can happen, but are very rare. Some of the bad reactions we know about happen in people using the drug for a long time and with larger doses (12 weeks; 500g daily dose).

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80 These reactions are pharyngitis (sore throat), nasal congestion, allergic rhinitis ( Runny nose), oral candidiasis (Yeast infections in the mouth) and upper respiratory infection. Women of childbearing age: This drug will not be given to anyone who is pregnant. All women must take a pregnancy test before getting any treatment on this stu dy. All woman of child bearing potential enrolled on this study must use effective birth control during treatment. These include: no sexual intercourse, an IUD, using contraceptive foam AND a condom (doublebarrier). You must notify the doctor if you become pregnant during the course of the study. Intravenous (IV) catheter insertion: during the insertion of the IV catheter, soreness or bruising at the insertion site can occur but is unlikely. Infection at the IV site is possible but unlikely. Dizziness and lightheadedness can occur during insertion of IV catheter or during the blood draws. Selection of Study Population Asthma subjects typically experience a higher degree of central deposition of the inhaled drug than healthy subjects. Because of the skew ed central/peripheral ratio towards a more central deposition, asthmatics are a less sensitive study population; therefore healthy volunteers will be used as they will be more sensitive to detect potential differences in the deposition profile between the three formulations. Healthy volunteers also represent a homogeneous study population for investigations of bioequivalence, owing to a lesser scope for variability as compared to subjects with asthma. Higher variability leads to lesser sensitivity in detect ing differences. Healthy male or female subjects aged 18 to 50 years will be included in the study. Inclusion/exclusion criteria typically used for corticosteroid inhalation studies will be applied. Initial screening of the subjects will encompass the following: medical hi story

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81 and demographics, review of eligibility criteria, physical examination, height and body weight measurements, calculation of Body Mass Index (BMI), vital signs (systolic and diastolic blood pressure, pulse rate and temperature) following 5 minutes in the supine position; clinical laboratory testing including CBC, urinalysis, metabolic panel and for female subjects, a pregnancy test. Study Procedures and scheduling The study is comprised of 5 visits in total a screening visit and 4 treatment visits. A t least 5 days should lapse between the treatment visits. Screening Visit During the screening visit, the inclusion and exclusion criteria will be reviewed to ensure the subject is appropriate for the study. The informed consent will be reviewed with the subject by a member of the study team and the subject will be encouraged to ask questions to ensure the subject has a good understanding of the study. If the subject is eligible and agrees to participate, the subject will be asked to sign the informed consent form prior to any study specific procedures including randomization. After the subject signs the in formed consent, the subject will be interviewed and demographic data, medical history and concomitant medications will be collected and recorded. A physical examination will be performed after the vital sign measurements are obtained. A pregnancy test for female subjects will be obtained. Spirometry testing and inhalation training will be performed by a qualified study clinician/investigator to ensure the suitability of subjects. Laboratory tests including a CBC, urinalysis and metabolic panel will be collected via venipuncture and processed in the lab. Screening tests will be performed within 14 days of treatment visit 1 and no later than 2 days before treatment visit 1. All screening results will be evaluated by the study

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82 clinician/investigator against the inclusion/exclusion criteria to confirm the eligibility of the subjects. Inhalation training: Inhalation training will be performed by a qualified study clinician at the screening visit and at each study visit. The training will be accomplished by instructions and subsequent inhalation via training devices containing empty capsules. The instructions on how to use the device correctly are similar to the Foradil Aerolizer DPI product information label. ( http://www.rxlist.com/foradildrug/medicationguide.htm ) Treatment Visits 1, 2, 3 and 4 Eligible subjects will be asked to return for treatment visit 1. A minimum period of 5 days should lapse between the subsequent treatment visits. Eac h treatment visit is scheduled for 28 hours over two days. The study will be conducted at the UF CRC (Clinical Research Center). It is an outpatient study and the subject will be asked to come back the following day for the 24 hour blood sample. The subjec t will be asked to stay in an outpatient room during the treatment visit. The same activities are carried out at the other treatment visits. At each treatment visit, eligibility criteria will be reviewed and confirmed to ensure subject is appropriate for s tudy. Changes in medical history including concomitant medications will be documented. Vital signs will be obtained. Inhalation training will be provided to the subjects as mentioned in the section above. An IV catheter will be inserted in a vein located i n the forearm region of the subject. The IV catheter is used to avoid multiple pricks while collecting blood samples. The IV catheter is not used for the administration of the drug. The subject inhales 5 times from a given inhaler during each treatment vis it. Each inhaler will be used only once and by only one subject to ensure

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83 the subjects safety from infectious agents. The Table 44 summarizes the procedures performed at the screening visit and a single treatment visit. Blood sample collection Blood sam ples will be drawn by inserting an indwelling catheter into the subjects median cubital vein in the forearm region. Blood samples will be taken 15 minutes prior to the dosing of the product (predose sample) and 5, 10, 15, 20, 30, 45, 60 minutes, 1.5, 2, 3, 4, 6, 8, 10, 12, 14 and 24 hours post dosing. At each time point 9ml of blood sample will be collected of which the first 1ml will be discarded and the remaining 8 ml will be stored in a vacutainer tube for plasma preparation and storage. Labeling The v acutainers and the cryovials containing whole blood and plasma samples respectively will be labeled with subject number, date and time of sampling Handling and Storage 7.5ml of whole blood will be drawn into a vacutainer containing K2EDTA as the anticoagul ant. Immediately after collection the vacutainer tubes will be placed on ice and centrifuged at 1500g (~3000 rpm) for 15 minutes. (the tubes will be centrifuged within 30 minutes of collection by the study team member) After separation of the whole blood, the plasma will be transferred using a plastic pipette into an internally threaded cryovial identified with labels and will be stored in a 20C freezer.

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84 Bio analytical Method A HPLC MS MS method capable of quantifying FP in human plasma at levels down to 10 pg/mL will be used. The method was validated over a linear range from 10 to 1000 pg/mL1. The inter and intra batch precision (coefficient of variation) and accuracy (% bias) of the quality controls samples (20, 25, 50, 100, 200, 500 and 1000 pg/mL) were less than 15% and 11%, respectively. Bioanalysis will be performed at the Department of Pharmaceutics GLP Drug analysis Laboratory. Statistical Methods and Analysis of Data Sample size calculation Using in house and literature PK data for fluticasone propionate the variability in the PK parameters Cmax and tmax were estimated to be between 20% to 40% (%CV)242526. If the CV is 30% and the products differ by only 5%, a sample size of 40 is needed to have 80% power to show that the products are equivalent27. = 2 + [ /( ) ]^ 2 N= total number of subjects required to be in the study t = the appropriate value from the t distribution 1 CV = the coefficient of variation V = the bioequivalence limit (ln 1.25 = 0.223) = 0.0488)

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85 The number of subjects in the study will be 44 taking into account a dropout rate of 10% Study population to be analyzed: Analyses and summaries of pharmacokinetic data will be based on subjects who are administered all doses, complete at least 75% of blood sampling and follow the protocol procedures. In vitro analysis The aerodynamic particle size distribution (APSD) of ten different inhalation formulations will be analyzed using a multi stage cascade impactor (Next Generation Impactor). For each of the ten formulat ions, the cascade impactor profiles of 40 units will be obtained at a previously defined operation flow rate. All 400 cascade impactor runs will be performed independently of each other in a randomized order. The mass median aerodynamic diameter (MMAD), geometric standard deviation (GSD), and fine particle mass (FPM) will be calculated for each 400 cascade impactor profiles. The averages and standard deviations of the three metrics (MMAD, GSD, and FPM) will be reported for each of the ten formulations and, subsequently, compared for a first assessment of differences between the formulations. A modified chi square ratio statistic (mCSRS, Equation 1) will b e applied to the cascade impactor profiles for a stageby stage comparison between two formulations. The mCSRS will only be applied to cascade impactor stages with defined upper size cut off value (impactor sized mass (ISM) stages). An average or populat ion bioequivalence type statistical test will be performed additionally to detect significant differences in the ISM between two formulations. The mCSRS was designed to compare a test to a reference formulation. However, none of the ten formulations under investigation will be formally defined as a

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86 reference formulation. Thus, the mCSRS will be applied to all possible pairs of the ten formulations with each formulation being once defined as test and reference formulation. Hence, a total of 100 mCSRS w ill be obtained. Nonparametric confidence intervals for each of the 100 mCSRS will be obtained by a bias correctedand accelerated (BCA) bootstrapping method. All mCSRS computations will be performed in the statistical software R. The three formulations whose cascade impactor profiles are the most different from each other in terms of their mCSRS will be selected as candidates for the pharmacokinetic study. ( ) Modified chi square ratio statistic, where n is the number of CI stages, Tij and Rik is the deposition (%) on the ith stage of the (j, k)th pair of T and R profiles, respectively, and Ri_bar is the sample average across all R profiles on the ith stage. The median of the distribution of all possible k*j pairs of T and R products was defined as the test statistic. Non Compartmental Analysis (NCA) Hypothesis of the proposed research is that the three test formulations (differing in the c/p ratio) will differ in AUC and Cmax estimates. Three multiple compar isons will be performed i.e. Reference against the reference, reference against test 1 and reference against test 2. A multiplicity adjustment (e.g. bonferroni type) will be made for the 3 multiple comparisons. No additional adjustment will be made for the use of multiple metrics. NCA will be performed in WinNonlin using an inbuilt extravascular PK

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87 model. Standard PK metrics such as AUC(0 30min), AUC(0 t), AUC(0 inf), Cmax, tmax, terminal slope/half life, CL/F, Vdss/F, AUMC(0 t), AUMC(0 inf), and MRT will be calculated for each individual plasmaconcentrationtime profile. ANOVA model will be used to construct univariate 90% confidence intervals for AUC(0 t) and Cmax ratios and applied to conventional 0.8 1.25 average BE limits. If needed, alternative BE evaluation methodology and or BE criteria may be investigated. Data will also be assessed by ANOVA methods (SAS 9.2) to test for statistical differences (p<0.05). Compartmental Analysis In addition to NCA analysis, compartmental data analysi s methodology will be applied to the observed in vivo pharmacokinetic (PK) data. Compartmental PK analysis using NONMEM will incorporate information on physiological processes such as pulmonary absorption, mucociliary clearance rates and dissolution rates (bulk and after cascade impactor separation), and cascade impactor information.

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88 Table 41. Formulations in the study Treatment Device Formulation 1 Plastiape Monodose DPI Fluticasone Propionate Formulation 1(FPF I) 2 Plastiape Monodose DPI Fluticasone Propionate Formulation 2(FPF II) 3 Plastiape Monodose DPI Fluticasone Propionate Formulation 3(FPF III)

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89 Table 42. Sequences of the four treatments Sequence Treatment Visit 1 Treatment Visit 2 Treatment Visit 3 Treatment Visit 4 1 FPF I FPF II FPF III FPF III* 2 FPF II FPF III* FPF I FPF III 3 FPF III FPF I FPF III* FPF II 4 FPF III* FPF III FPF II FPF I

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90 Table 43. A sample randomization scheme Sequence Subjects 1 10,39,28,5,35,21,18,27,15,4,26 2 7,34,42,2,37,33,40,12,1,19,14 3 38,22,3,44,32,20,16,36,23,11,30 4 8,43,31,25,17,13,24,6,41,29,9

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91 Table 44. Procedures performed during the screening and treatment visits Activity Screening visit Treatment visit 2 14 days prior treatment Day 1 Day 2 Patient Information X Informed consent X Review Inclusion/Exclusion criteria X X Demographic data X Medical history X X Concomitant medications X X X Measure BMI X Vital signs X X Physical Examination X X Lung function measurements (FEV1) X X Pregnancy test X Laboratory assessments X ECG X X Adverse Events X X X Proper inhalation technique X X Inhalation of study formulation X Blood sampling for PK X X

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92 CHAPTER 5 CONCLUSION The US FDA recommends an aggregate weight of evidence approach to establish bioequivalence (BE) of orally inhaled drug products. The approach utilizes in vitro studies to ensure comparable physicochemical properties between the test and reference product, pharmacokinetic (PK) studies to establish equivalence in systemic safety and pharmacodynamic/clinical studies to demonstrate equivalence in local action62. In contrast the European Medical Agency (EMA) endorses a stepwise approach wherein invitro studies are the primary method of testing for bioequivalence. P K studies are recommended only if in vitro tests fail to establish BE and subsequently pharmacodynamic (PD) /clinical studies are recommended if the PK studies are insufficient to establish BE. Nevertheless, PD/clinical studies are an important component of the BE testing approaches of the FDA and EMA. Such PD approaches to establish BE of locally acting drugs, though have been relatively successful for the dose response assessment of albuterol, long acting 2 adrenergic dr ugs and anti muscarinic agents64, 65, 66 are more challenging for inhaled glucocorticoids (ICS). The overall objective of the thesis was to evaluate the feasibility of PD approaches for establishing BE o f inhaled corticosteroids and 2 adrenergic dr ugs through modeling and simulation. Clinical trial simulations were performed to evaluate if exhaled nitric oxide (FeNO) would be a suitable marker for local delivery of ICS and hence be used for BE testing. Simulations (chapter 2 ) have shown that the PD approach for establishing BE of ICS using FeNO as the biomarker seems feasible only when the test dose is in the sensitive region of the dose response curve i.e. close to the ED50, the BE limits are relaxed and the studies are powered for FeNO. However, most of the generic

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93 formulations have doses much larger than the relevant ED50 values warranting large sample sizes to demonstrate BE. Our conclusion is in agreement with the current thinking of the FDA, wherein they recommend clinical endpoint studies in their draft guidance, moving away from FeNO BE studies. Analysis of a PD crossover study (chapter 3) was conducted to evaluate equivalence in clinical efficacy of two dry powder inhalers Formoterol Aerolizer and Formoterol Novolizer containing formoterol, a long acting 2 agonist in patients with stable asthma using PC20 as the primary end point BE was established between the two products using both the dosescale approach and the Finney bioassay indicating that PC20 is a sensitive biomarker and hence demonstrating that methacholine challenge is a viable assay for 2 agonists Given that the PD/Clinical endpoint studies are challenging for establishing BE of ICS, the FDA is reevaluating the role of PK studies to see if they can provide more information within the horizon of the aggregate weight of evidence approach than merely be used for establishing equivalence in systemic safety. The PK study in healthy volunteers (chapter 4) which is funded by the FDA, if successful in demonstrating that the PK metrics like AUC and Cmax are sensitive to regional differences in drug deposition can bring about a paradigm shift in the current notion with respect to establishing BE of ICS.

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101 BIOGRAPHICAL SKETCH Bhargava Kandala was born in Hyderabad, India in 1986. In 2008, he received an M.Pharm. from the Bir la Institute of Technology and Science, Pilani, India. In A ugust 2009, he began his graduate studies in the Department of Pharmaceutics at the University of Florida, Gainesville under the direction of Dr. Guenther Hochhaus His research interests include PK/PD modeling, clinical trial simulations, and bioequivalence of orally inhaled formulations. In his dissertation, Bhargava focuses on evaluating different bioequivalence approaches for orally inhaled drug products through pharmacometric methods. During his Ph.D. he also received a Master of Statistics (2012) from the University of Florida. In addition, Bhargava gained regulatory as well as industry experience as an ORISE fellow at the Office of Generic Drugs, FDA and as a research fellow in Clinical Pharmacology Modeling and Simulation group at GSK. He gave several poster and oral presentations at various international conferences. He is a n active memb er of AAPS, ACCP, ASCPT and ISoP. Bhargava was also a member of the University of Florida cricket team that won the South east championship in 2012. He received his Ph.D. from University of Florida in the spring of 2014.