Intravenous Microdialysis and Physiologically-based Pharmacokinetic Modeling as Tools to Evaluate Pharmacokinetics and D...

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Intravenous Microdialysis and Physiologically-based Pharmacokinetic Modeling as Tools to Evaluate Pharmacokinetics and Drug-drug Interactions
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Vieira,Manuela D
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Doctorate ( Ph.D.)
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University of Florida
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Pharmaceutical Sciences, Pharmaceutics
Committee Chair:
Derendorf, Hartmut C
Committee Members:
Butterweck, Veronika
Palmieri, Anthony
Grant, Maria A

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intravenous -- microdialysis -- pbpk
Pharmaceutics -- Dissertations, Academic -- UF
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Abstract:
The purpose of this thesis was to evaluate the usefulness and accuracy of two distinct tools to support drug development: Intravenous Microdialysis (IV MD) and Physiologically-based Pharmacokinetic (PBPK) modeling. The IV MD technique is proposed to be a promising in vivo tool for continuous free drug monitoring in (pre)clinical settings due to its various advantages compared to traditional blood sampling. The feasibility and accuracy of IV MD was evaluated by determining free concentrations of a lipophilic and highly protein-bound drug, triamcinolone acetonide (TA), under steady-state pharmacokinetics in anesthetized rodents. Microdialysis in vivo calibration was estimated by the retrodialysis method using budesonide as the calibrator compound. The mean steady-state total and unbound (microdialysate) concentrations were 3.64 ? 0.74 and 0.343 ? 0.072 ?g/mL, respectively. The calculated unbound TA concentration in plasma corrected for protein binding was 0.378 ? 0.077 ?g/mL, which is significantly not different to that determined by IV MD (?=0.05). The results demonstrated that IV MD is an accurate method to determine unbound concentrations of TA following drug infusion at steady-state, thus a feasible approach for free drug monitoring. PBPK modeling is proposed to be a valuable in silico tool for addressing linear and nonlinear pharmacokinetics and prediction of drug-drug interaction risk due to its advantageous integration of systemic properties and drug-dependent parameters to characterize pharmacokinetics (PK) of interacting drugs. A PBPK model for telithromycin, a substrate and inhibitor of the enzyme cytochrome P450 3A4 (CYP3A4) with nonlinear PK, was constructed using either reversible or time-dependent inhibition (TDI) of CYP3A4. The model incorporating TDI of CYP3A4 suggested that rather than saturation of metabolic and efflux transport pathways, auto-inhibition of clearance via time-dependent CYP3A4 inhibition is the plausible mechanism for the observed time- and dose-dependent telithromycin PK. The TDI model successfully predicted the magnitude of drug-drug interaction perpetrated by telithromycin with midazolam (a probe CYP3A4 substrate): the predicted vs. observed geometric mean AUC ratios (+/- telithromycin) of midazolam after intravenous and oral administration were 3.26 vs. 2.20 and 6.72 vs. 6.11, respectively. In contrast, the PBPK model with reversible inhibition mechanism under-predicts the observed increase in midazolam exposure (geometric mean AUC ratios of 1.01 and 1.08 after intravenous and oral midazolam, respectively). In conclusion, IV MD and PBPK modeling are useful and promising applications for evaluating pharmacokinetics and drug-drug interactions, thus aiding to guide successful drug development.
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by Manuela D Vieira.
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Thesis (Ph.D.)--University of Florida, 2011.
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Adviser: Derendorf, Hartmut C.
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INTRAVENOUS MICRODIALYSIS AND PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODELING AS TOOLS TO EVALUATE PHARMACOKINETICS AND DRUG-DRUG INTERACTIONS By MANUELA DE LIMA TOCCAFONDO VIEIRA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORID A IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2011 1

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2011 Manuela de Lima Toccafondo Vieira 2

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To my Grandmother, Mother and Sister 3

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ACKNOWLEDGEMENTS I would like to express my appreciation and gratitude to my supervisor Dr. Hartmut Derendorf for his continuous support and in telligent guidance throughout my graduate program. My gratitude is extended to my superviso ry committee Dr. Veronika Butterweck, Dr Maria Grant, and Dr. Anthony Palmieri for thei r constructive guidance and availability. I would like to thank the offi ce staff of the Department of Pharmaceutics, Patricia Khan, Robin Keirnan-Sanchez and Sarah Foxx, for their kindly support on administrative matters, as well as facult y, post-doc fellows and graduate students for their friendship and support. A special gratefulness is extended to Daniela Conrado who helped me during the most challenging moment s of my experiment s. Her friendship, availability and remarkable knowledge when I needed the most will never be forgotten. I also want to express my appreciation to Dr. Rajendra P. Singh and Dr. Linung Zhuang for their assistance on my experiments. I am also thankful to Dr. Shiew-Mei Huang and Dr. Ping Zhao, for their valuable guidance throughout my academic traini ng, encouragement and appreciative support. The CAPES/Fulbright program is acknowledged for funding my doctoral studies. Special thanks to the staff of the Institute of In ternational Education, Joanne Forster and Anna Rendon, for the kindly suppo rt in administrative issues. I also express my gratitude for all animals t hat participated in this research project. Finally, I would like to thank my friends and family, especially my mother, brother and sister, for their love, encouragement and suppor t always. I am also very thankful to my boyfriend, Christian, for his love patience, encouragement and help during the course of my work. 4

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TABLE OF CONTENTS page ACKNOWLEDG EMENTS...............................................................................................4LIST OF TABLES............................................................................................................9LIST OF FI GURES ........................................................................................................11ABSTRACT ...................................................................................................................131 INTRODUC TION....................................................................................................15Specific Aims..........................................................................................................16Specific Aim 1...................................................................................................16Specific Aim 1a: Bioanalytical assay development and validat ion.............16Specific Aim 1b: Triamcinolone acetonide microdialysis calibration...........17Specific Aim 1c: Investigation of budesonide as a microdialysis calibrato r.................................................................................................17Specific Aim 1d: Intravenous mi crodialysis st udy of TA.............................17Specific Aim 2...................................................................................................17Intravenous Microdialysi s........................................................................................17Principles of Microdial ysis................................................................................17Application of Intrav enous Microdi alysis ...........................................................20PBPK Mode ling.......................................................................................................24Principles of PBPK Modelin g............................................................................24Application of PBPK Modelin g..........................................................................252 DEVELOPMENT AND VALIDATION OF BIOANALYTICA L METHODS................30Backgroun d.............................................................................................................30Specific Aim............................................................................................................31Materials.................................................................................................................31Chemicals and Reagents.................................................................................31Equipment and Dis posables.............................................................................31Chromatographic Inst rumentat ion....................................................................31Methods ..................................................................................................................32Chromatographic Conditi ons............................................................................32Preparation of Stock and Working Solu tions....................................................33Preparation of Calibrati on Standards and Quality Control Sa mples.................33Plasma Sample Pre-treat ment: SPE Pr ocedure...............................................34Method Vali dation.............................................................................................35Specific ity...................................................................................................35Linearit y.....................................................................................................35Accuracy and pr ecisio n..............................................................................35Plasma extracti on recovery........................................................................36Stabili ty......................................................................................................36 5

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Data anal ysis.............................................................................................37Results and Discussion...........................................................................................37Plasma Internal Standard Sele ction.................................................................37Development of Chro matographic Method.......................................................37Development of the Sample Pre-treatment Procedur e.....................................37Method Vali dation.............................................................................................38Specific ity...................................................................................................38Linearit y.....................................................................................................39Accuracy and pr ecisio n..............................................................................40Extraction recovery....................................................................................40Stabili ty......................................................................................................413 TRIAMCINOLONE ACETONIDE MICRODIALYSIS CA LIBRATION......................48Backgroun d.............................................................................................................48Specific Aim............................................................................................................49Materials.................................................................................................................49Chemicals and Reagents.................................................................................49Equipment and Dis posables.............................................................................49Animals.............................................................................................................50Methods ..................................................................................................................51Preparation of Standard So lutions and Quality Cont rol (QC) Samples............51Preparation of Calibration Solu tions for Micr odialysi s......................................51In vitro Microdialysis Calibrat ion.......................................................................51Apparatus setup.........................................................................................51Extraction efficien cy method (EE)..............................................................52Retrodialysis method ( RD)......................................................................... 52Sample an alysis.........................................................................................53In vivo Microdialysis Ca librati on.......................................................................54Animal pre paratio n.....................................................................................54Probe insert ion...........................................................................................55In vivo retrodialysi s method........................................................................55Sample an alysis.........................................................................................56Data Anal ysis...................................................................................................56Results and Discussion...........................................................................................56HPLC Method Va lidatio n..................................................................................56In vitro Microdialysis Calibrat ion.......................................................................57In vivo Microdialysis Calibrati on.......................................................................594 INVESTIGATION OF BUDESONIDE AS A MICRODIALYSIS CALIBRATOR........69Backgroun d.............................................................................................................69Specific Aim............................................................................................................70Materials.................................................................................................................70Chemicals and Reagents.................................................................................70Equipment and Dis posables.............................................................................70Animals.............................................................................................................71 6

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Methods ..................................................................................................................72Preparation of Calibration Solu tions for Micr odialysi s......................................72In vitro Microdial ysis.........................................................................................72Apparatus setup.........................................................................................72Extraction efficiency of TA and retrodialysis of budesonide at a constant flow rate..................................................................................................72Extraction efficiency of TA and retrodialysis of budesonide at different flow rates................................................................................................73In vitro retrodialysis of TA and budesonide................................................74In vivo Microdialysis Calibrati on.......................................................................75In vivo retrodialysis of TA and budesonide................................................75Sample An alysis...............................................................................................76Data Anal ysis...................................................................................................76Results and Discussion...........................................................................................765 INTRAVENOUS MICRODIAL YSIS STUDY OF TA................................................87Backgroun d.............................................................................................................87Specific Aim............................................................................................................88Materials.................................................................................................................88Chemicals and Reagents.................................................................................88Equipment and Dis posables.............................................................................88Animals.............................................................................................................89Methods ..................................................................................................................90Ultrafiltra tion .....................................................................................................90Preparation of stock and working solutions ................................................90Preparation of sample s..............................................................................90Sample proc essing ....................................................................................91Sample an alysis.........................................................................................91Data anal ysis.............................................................................................92In vivo Microdialysis Recove ry.........................................................................92Intravenous Microdi alysis of TA........................................................................93Sample An alysis...............................................................................................94Data Anal ysis...................................................................................................94Results and Discussion...........................................................................................96Determination of Unbound Fraction of TA by Ultra filtrati on..............................96In vivo Microdialysis Recove ry.........................................................................97Intravenous Microdi alysis of TA........................................................................986 UTILITY OF PBPK MODELING IN ADDRESSING NONLINEAR PHARMACOKINETICS AND DRUG INHIBITION MECHANISMS OF TELITHROMY CIN................................................................................................109Backgroun d...........................................................................................................109Specific Aim..........................................................................................................111Methods ................................................................................................................111Initial M odel....................................................................................................111 7

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Modified M odel...............................................................................................114Simulation s.....................................................................................................116Results ..................................................................................................................117Prediction of Nonlinear Pharmaco kinetics of Telit hromycin............................117Prediction of the Magnitude of Drug-Drug Inte raction....................................121Discussio n............................................................................................................1227 CONCLUS ION......................................................................................................140LIST OF REFE RENCES.............................................................................................143BIOGRAPHICAL SKETCH ..........................................................................................157 8

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LIST OF TABLES Table page 2-1 Linear regression par ameters for triamcinolo ne acetonide in plasma and microdialysate calib ration st andards ...................................................................422-2 Linear regression par ameters for budesonide in mi crodialysate calibration standards ............................................................................................................422-3 Summary of observed TA conc entration in microdialysate and plasma calibration standards ..........................................................................................432-4 Summary of observed budesonide concentration in microdialysate calibration standards ............................................................................................................432-5 Intraand inter-day accuracy (% RE) and precision (%CV) of observed TA concentrations in microdialysate quality contro ls................................................442-6 Intraand inter-day accuracy (%RE) and precision (%CV) of observed TA concentrations in plas ma quality c ontrols ...........................................................442-7 Stability results of TA in ra t plasma and microdialysate under various condition s...........................................................................................................453-1 Intra-day and inter-day accuracy (%RE) and precision (%CV) of observed TA concentrations in microdialysate quality controls during the three dayvalidatio n............................................................................................................663-2 Comparison of the in vitro microdialysis recoveries (%R) of TA by the retrodialysis and extraction efficiency methods..................................................673-3 In vivo microdialysis recovery (%R) of TA by the retrodi alysis me thod...............683-4 In vitro microdialysis recovery (%R) of TA by the retrodi alysis method..............684-1 Comparison of the in vitro recovery of TA versus budesonide at a constant flow rate (1.5 L/min)..........................................................................................854-2 Comparison of the in vitro recovery of TA versus budesonide at different flow rates...................................................................................................................854-3 Comparison of in vitro recovery of TA versus budes onide by retrodialysis.........864-4 Comparison of in vivo recovery of TA versus bude sonide by retrodialysis.........865-1 Triamcinolone acet onide unbound fraction in rat plasma determined by ultrafiltra tion...................................................................................................... 107 9

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5-2 In vivo recovery of budes onide and TA............................................................1075-3 Individual pharmacoki netic parameter estimates of TA in rats after i.v. constant rate infusion .......................................................................................1085-4 Individual steady-state plas ma concentrations of TA, total (Css,T) and unbound (Css,u) determined by utrafiltration or IV MD corrected by the two methods of probe calibration, in rats a fter i.v. constant rate infu sion................1086-1 Predicted PK parameter s of single (SD) and multiple once-daily doses (MD) of telithromycin using the modified model incorporating time-dependent inhibition of CYP3A4.........................................................................................1356-2 Drug-dependent paramet ers of telithromycin for the construction of PBPK model using SimCYP (V10.10) ........................................................................1366-3 Observed vs. predicted apparent oral clearance (CL/F) after single (SD) and multiple (MD) ascending doses considering higher intrinsic clearance by CYP3A4 and time-dependent inhibition of this metabolic pathway (KI and kinact parameter s)..............................................................................................1376-4 Contribution of the intestinal efflux transpor ter P-gp on initia l model predicted telithromycin pharmacokinetics after in creasing single doses (SD)..................1386-5 Predicted effect on midazolam exposure using the modified telithromycin model incorporating time-dependent CYP3A4 i nhibition. .................................139 10

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LIST OF FIGURES Figure page 1-1 Schematic representation of the whole-body physiologically-based pharmacokinetic model.......................................................................................292-1 Representativ e microdialysis chro matograms ................................................... 462-2 Representative pl asma chroma tograms.............................................................473-1 Schematic figure of a flexible microdialysis probe of concentric design.............623-2 Dependence of relative recovery on concentration of TA in perfusate or medium during retrodialysis or extraction effici ency methods............................633-3 The in vivo and in vitro probe recoveries of TA for probes 1 and 2 by retrodialysis ov er time.........................................................................................643-4 The in vivo and in vitro probe recoveries of TA for probes 3 and 4 by retrodialysis ov er time.........................................................................................643-5 Dependence of the in vivo and in vitro recoveries of TA on time (1st half= 0180 min and 2nd half= 181-360 min) for the microdialysis probes 3 and 4 using the retrodi alysis me thod............................................................................654-1 Schematic illustration of a flexible microdialysis probe of concentric design......814-2 Dependence of relative recovery ra tio TA to budesonide on concentration of TA in medium under cons tant flow rate (1.5 L/min)..........................................824-3 The effect of flow rate on recovery by gain of TA and by loss of budesonide during extraction efficient (EE) and retrodialysis (RD) calibration in vitro respecti vely.........................................................................................................834-4 Individual recovery ratios of TA to budesonide for four probes obtained by in vitro retrodialysis over time.................................................................................844-5 Individual recovery ratios of TA to budesonide for fi ve probes obtained by in vivo retrodialysis ov er time.................................................................................845-1 Representative chromatogram s of IV MD samples..........................................1025-2 Representative chromatograms of rat plasma samp les....................................1035-3 Plasma concentration time-profiles of TA in rats (n=5) after constant rate infusion (5 mg/kg bolus + 2.3 mg/kg/h).............................................................104 11

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5-4 Concentration-time pr ofiles of TA for two representative animals after constant rate infusion (5 mg/kg bolus + 2.3 mg/k g/h). ....................................1055-5 Steady-state plasma concentration ti me-profiles of TA in rats (n=5) after constant rate infusion (5 mg/k g bolus + 2.3 mg /kg/h).. .....................................1066-1 Schematic representation of telithromycin PBPK model. ..................................1276-2 Changes in telithrom ycin apparent oral clearance (Dose/AUC) as a function of increasing values of CYP3A4 intrinsic clearance and time-dependent inhibition (KI and Kinact) of the enzymatic pathway ............................................1286-3 Predicted mean plasma concentrationtime profile of te lithromycin using the initial PBPK model (dashed line) or modified model (incorporating TDI of CYP3A4, solid line)...........................................................................................1296-4 PBPK model predicted mean values of transport and enzymatic pathways of a single 400 mg dose of telit hromycin over time...............................................1306-5 Prediction of mean conc entration time-profile of telithromycin after ascending multiple oral doses (400, 800 and 1600 mg q.d.) in healthy subjects using initial model (dashed lines) and modified model incorporating time-dependent CYP3A4 inhibition (s olid lines )..........................................................................1316-6 PBPK predicted by in itial and modified TDI model and observed telithromycin nonlinear dose dependence after se ven once-daily doses...............................1326-7 Predicted mean plasma pr ofile of telithromycin after multiple oral doses (800 mg q.d.) in healthy subjects using in itial and modified TD I model. Symbols represent mean observed data from six different trials. ....................................1336-8 Geometric mean of A UC ratios (5th and 95th percent iles) of midazolam in the presence and absence of telit hromycin (800 mg q.d for 6 days) in 10 different randomly selected groups of virtual subjects (n=12) ( ) and observed (n=12) ( ) values..........................................................................................................134 12

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Abstract of Dissertation Pr esented to the Graduate School of the University of Florida in Partial Fulf illment of the Requirements for t he degree of Doctor of Philosophy INTRAVENOUS MICRODIALYSIS AND PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODELING AS TOOLS TO EVALUATE PHARMACOKINETICS AND DRUG-DRUG INTERACTIONS By Manuela de Lima Toccafondo Vieira August 2011 Chair: Hartmut Derendorf Major: Pharmaceutical Sciences The purpose of this thesis was to ev aluate the usefulness and accuracy of two distinct tools to support drug developmen t: Intravenous Microdialysis (IV MD) and Physiologically-based Pharmacokinetic (PBPK) modeling. The IV MD technique is proposed to be a promising in vivo tool for continuous free drug monitoring in (pre)clinical settings due to its various advantages compared to traditional blood sampling. The feasibility a nd accuracy of IV MD was evaluated by determining free concentrations of a lipophilic and highly protein-bound drug, triamcinolone acetonide (TA), under steady -state pharmacokinetics in anesthetized rodents. Microdialysis in vivo calibration was estimated by the retrodialysis method using budesonide as the calibrator compound. The mean steady-state total and unbound (microdialysate) concentrations we re 3.64 0.74 and 0.343 0.072 g/mL, respectively. The calculated unbound TA concent ration in plasma corrected for protein binding was 0.378 0.077 g/mL, which is signifi cantly not different to that determined by IV MD ( =0.05). The results demonstrated that IV MD is an accurate method to 13

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14 determine unbound concentrations of TA followi ng drug infusion at steady-state, thus a feasible approach for free drug monitoring. PBPK modeling is proposed to be a valuable in silico tool for addressing linear and nonlinear pharmacokinetics and prediction of drug-drug in teraction risk due to its advantageous integration of systemic properties and drug-dependent parameters to characterize pharmacokinetics ( PK) of interacting drugs. A PBPK model for telithromycin, a s ubstrate and inhibitor of the enzyme cytochrome P450 3A4 (CYP3A4 ) with nonlinear PK, was constructed using either reversible or time-dependent inhibition (TDI ) of CYP3A4. The model incorporating TDI of CYP3A4 suggested that ra ther than saturation of met abolic and efflux transport pathways, auto-inhibition of clearance via time-dependent CYP3A4 inhibition is the plausible mechanism for the observed ti meand dose-dependent te lithromycin PK. The TDI model successfully predicted the magnitude of drug-drug interaction perpetrated by telithromycin with midazolam (a probe CYP3A4 substrate): the predicted vs. observed geometric mean AUC ratios (+/telithromycin) of midazolam after intravenous and oral administration were 3.26 vs. 2.20 and 6.72 vs. 6.11, respectively. In contrast, the PBPK model with reversible inhibition mechanism under-predicts the observed increase in midazolam exposure (geometric mean AUC ratios of 1.01 and 1.08 after intravenous and oral midazolam, respectively). In conclusion, IV MD and PBPK modeling are useful and promising applications for evaluating pharmacokinetics and drug-drug interactions, thus aiding to guide successful drug development.

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CHAPTER 1 INTRODUCTION The long-term objective of the studies described here is to demonstrate the utility of intravenous microdialysis (IV MD) technique and physiologically-based pharmacokinetic (PBPK) modeling, specifically in the areas of preclinical and pediatric pharmacokinetics and drug-drug interactions. Microdialysis [1-3] and PBPK [4,5] mode ling are gaining appreciation in drug development process seen through increasing application of both tec hniques as a part of an overall preclinical and c linical pharmacology package. Following the recognition of the utility of ti ssue microdialysis, IV MD may represent a promising tool for continuous free drug m onitoring in (pre)clinical settings. When compared with traditional blood sampling, IV MD offers several advantages. First, continuous sampling is possible since the microdialysis process does not change the blood volume [6]. This not only allows pharmacokinetic studies in pediatric populations but also greatly reduces the number of experimental animals usually required for frequent PK sampling. Second, IV MD direct ly provides the unbound drug concentration which is generally considered pharmacologically more relevant [7]. Third, microdialysis sampling excludes proteins, therefore reduc ing enzymatic degradati on of the drug and making sample preparation redundant [8]. Howeve r, the application of the microdialysis technique to lipophilic drugs seems to be problematic [9,10]. Based on these observations, the first aim of the proposed study was to evaluate the feasibility and accuracy of intravenous microdialysis tec hnique to determine unbound concentration of lipophilic and highly protei n-bound drugs using triamcinolone acetonide (TA) as a model compound. 15

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Many of PBPK modeling and simulation applic ations in literature [11,12] and drug application submissions in the US regulatory agency [5] addr essed questions related to drug-drug interactions (DDIs). The clinical consequences of DDIs range from lack of therapeutic efficacy to severe safety concerns. Thus, significant drug-drug interactions can lead to termination of a new drug developmen t, withdrawal from the market, or strict restrictions of its use [13 ]. An understanding of the risk for DDIs by prediction models is an important component of the drug research and development processes. However, prediction of in vivo drug-drug interaction magnit ude using enzymatic parameters generated in vitro remains challenging, due to the possi bility of false-negative results from in vitro study not properly designed [14]. Ba sed on these observations, the second aim of the proposed study is to evaluate t he utility of PBPK modeling and simulation in predicting drug-drug interact ion potential inferred from the assessment of a drugs nonlinear pharmacokinetics. Specific Aims Specific Aim 1 The first specific aim was designed to provide an assessment of the limitations and accuracy of the intravenous microdialysis technique using in vitro systems and rodent studies. Specific Aim 1a: Bioanalytical assay development and validation Develop and validate an efficient assa y for simultaneous and selective analysis of TA and budesonide (microdialysis calibrator) in microdialysate and rat plasma samples using HPLC-PDA. 16

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Specific Aim 1b: Triamcinolone acet onide microdialysis calibration Determine the relative recovery of TA by a series of in vitro and in vivo microdialysis studies to evaluate the feasibi lity of using IV MD as a sampling technique to TA. Specific Aim 1c: Investigation of budes onide as a microdialysis calibrator Determine the relative recovery of budesonide by a series of in vitro and in vivo microdialysis studies and the factor by which it is related to TA recovery to verify the use of budesonide as a continuous internal recovery control. Specific Aim 1d: Intravenous microdialysis study of TA Perform an intravenous microdialysis study in rats to determine the accuracy of the sampling technique on the estimation of unbound triamcinolone acetonide levels compared to conventional blood sampling. Specific Aim 2 The second specific aim was design to demonstrate the utility and predictive accuracy of PBPK modeling and simulation in mechanistically addressing telithromycin nonlinear pharmacokinetics and its dr ug-drug interaction potential. Intravenous Microdialysis Principles of Microdialysis Microdialysis (MD) is a sampling technique to measure the protei n-free fraction of endogenous and/or exogenous compounds in the blood [15,16] and extracellular fluid of several tissues (e.g. adipose tissue [17], muscl e [18], brain [19], lung [20], bones [21,22] and liver [23,24]. The principles of microdialysis have been described in detail previously [2,6,25]. Briefly, a microdialysis probe, consisting of a small semi-permeable hollow fiber 17

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membrane connected to outlet and inlet tubing, is inserted into a selected tissue or fluidfilled space. The MD probe is constantly perfused with a physiological solution (perfusate) at a low and constant flow rate (0.1-5 L/min). By means of diffusion according to their concentration gradient (Csampling site) and size, solutes cross the semipermeable membrane [26,27] and are taken with the perfusion flow [6]. The resulting concentration of the analyte in the solution leaving the probe (Cdialysate) will reflect the unbound diffusible level on the tissue [27]. After continuous sampling at regular intervals, microdialysate samples are analyzed. Due to the continuous perfusi on of the microdialysis pr obe, a complete equilibrium between the sampling site and the perfusion m edium cannot be estab lished; therefore, the concentrations in the dialysate samples are lower than those measured at the distant sampling site (Csampling site > Cdialysate) [2]. In other word s, to correlate concentrations measured in the dialysate wi th those present at the sampling site, a calibration factor, named recovery, is needed. The analytes recovery can be determined at steady-state using the constant rate of analyte exchange across the microdialysis semipermeable membrane, namely extraction efficiency. The extraction efficiency is defined as the ratio between the loss/gain of analyt e during its passage through the probe (Cperfusate Cdialysate) and the difference in concentration between perfusate and the sampling target such as tissue fluid or in vitro medium (Cperfusate Csampling site), as shown in the equation [2,28]: EE= (C perfusate C dialysate ) (Cperfusate Csampling site) At steady-state, the extraction efficiency of a microdialysis probe has the same value independent of the analyte concentration i.e. it does not matter whether the 18

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analyte is enriched or depleted in the perfusate. Thus, microdialysis probes can be calibrated by either drug-cont aining perfusate or drug-containing sample solutions [2]. Several calibration methods are available to date: the low-flow-rate method, the no-net-flux method [29,30], the dynamic no-net-flux method [31] and the retrodialysis by drug or by calibrator methods [32]. The retrodialysis by drug is the most common calibration method for exogeno us compounds in preclinical and clinical settings [2]. Several factors influence an analytes reco very, including perfu sion flow rate, probes characteristics such as membrane composition and effective surface area, temperature [7], physicochemical properti es of the analyte [ 33] and nature of the dialyzed tissue [34,35]. This latter factor precludes the use of in vitro calibration as a surrogate for in vivo recovery [2,34]. Microdialysis sampling has become an important technique allowing the in vivo measurement of endogenous and exogenous substances in the extracellular environment. As a practical, data rich, animal sparing in vivo method, MD is a useful tool that is increasingly applied in academ ia and drug research and development by the pharmaceutical industry [2]. Clinical microdi alysis has also been shown as a ethically acceptable, safe and reproducible technique [2], especially in the fields of intensive care research [36-38], dermatology [1,39], clin ical pharmacology [3,27], and metabolic and endocrinology research [24,40,41]. In additi on, the MD technique also holds great promise for evaluation of pharmacokinet ics and pharmacodynamics in laboratory animals and man as demonstrated in the areas of Central Nervous System research [42] and intravenous microdialysis [43]. 19

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Application of Intravenous Microdialysis Initially determination of drug concentrati on by intravenous microdialysis does not seem of much interest as there is alwa ys the possibility to sample blood directly. However, intravenous microdialysis technique offers numerous advantages over conventional blood draw. Since MD is a volume neutral technique, i.e. no net fluid (blood) loss, rich-data sampling from pediatric patients and small r odents is feasible. The limited total blood volume of children and small animals is one of the major problems in pharmacokinetic investigations in these populations. Blood loss from diagnostic sampling is reported to be the most common cause of anemia in hospitalized infants [44], therefore reducing or even avoiding blood sampling for drug analysis is clinically important. As for rodents, blood removal exceeding 20% of the total body volume us ually produces signs of hypovolemia [45]. Consequently, a large number of small an imals are used to obtain proper drug concentration-time profiles in p harmacokinetic studies. In addition, the physiological changes that result from blood sampling may alter drug pharmacokinetics. Intravenous microdialysis seems a promis ing approach to reduce disturbance of homeostasis associated with blood sampli ng, thus allowing pharmacokinetic and therapeutic monitoring in pediatric populat ion and reducing the number of animals necessary for pharmacokinetic studies. In addition, the continuous sampling of dr ug concentrations facilitated by the IV MD technique results in higher temporal re solution compared to blood sampling [6]. Furthermore, the MD semi-permeable membrane enables only the protein-free fraction of the drug to be diffused and thus, monitored. Since in general the unbound drug concentration is directly correlated to pharmacological effects, the assessment of 20

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its concentration is more appropriate for PK/PD investigations [7] and free drug therapeutic monitoring [46]. The exclusion of proteins from the microdialysis samples allows little or no-sample preparation steps [8] whereas whole blood sample pre-treatment is usually timeconsuming and tedious. Auto mated on-line analysis of mi crodialysate is therefore possible [47-50]. In addition, the risk of c ontamination of personnel is reduced. The exclusion of enzymes also diminishes the potential for sample degradation [48]. IV MD has been employed to study dr ug pharmacokinetic in rats [51-53]. Simultaneous microdialysis measurements in blood and other sampling sites (e.g. brain, liver) have been used to estimate the distri bution and metabolism characteristics of a drug [7]. Interesting examples are the invest igations of the disposition mechanism of metronidazole [47] and the metabolism of acetaminophen [54]. Intravenous microdialysis is also well suited for the determination of in vivo plasma protein binding of drugs such as ceftazidime [55] methotrexate [56] and flurbiprofen [57] which displayed concentration dependent protein binding. Other preclinical studies have been conducted with the goal of further developm ent of the techniq ue [58-60], including development of new IV microdialysis probes for placement in the inferior vena cava [61] or carotid artery [62], and application of microdia lysis calibrator [40]. The use of IV MD sampling in humans has also been demonstrated. A pilot study showed the utility of the technique to det ermine the pharmacokinetics of drugs, using sotalol as a model compound [16]. The applic ation of the technique for monitoring endogenous parameters like drug induced alterations in serotonin plasma levels [63,64] or lactate, pyruvate and glucose plasma co ncentrations in healthy [65,66] and intensive 21

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care patients has been demonstrated [67 ]. Levodopa and 3-O-methyldopa plasma levels were continuously monitored (2 to 6 hours) in Parkinsons disease patients to optimize management of levodopa therapy and to better characterize the pharmacokinetic profile of different formulations of the drug [15]. The majority of the preclin ical and clinical studies employed the IV MD technique to monitor hydrophilic and/or low protein binding compounds. In fact, the use of microdialysis to measure lipophilic drugs seems to be one of the major limitations of the technique. Some reports of tissue microdialys is studies addressed this difficulty with the low recovery, deemed as the key factor restricting the accurate quantification [9,10,33,50]. As previously addressed, the physicochemic al properties of the analyte, specially the partition coefficient which affects the per meability, have a significant influence on the diffusion process on the membrane and on the solubility in the hydrophilic perfusate medium; consequently, on the rela tive recovery [33]. Furthermo re, the extent of protein binding is other factor that affects the microdialysis diffu sion process quantitatively [9]. Higher protein binding results in lower unbound drug fraction that will diffuse and reduces the absolute amount of the drug that will be recovered. In this context, the present project aims to investigate the feasibility of IV microdialysis to determine unbound concentrat ions of lipophilic and highly proteinbound drugs. Triamcinolone acetonide, a cortic osteroid with moderate lipophilicity (Log Po:w of 2.5) (Chemspider databas e, Royal Society of Chemistry, Cambridge, UK) and high protein binding (90% in rat plasma [ 68] and 70-80% in human plasma [69,70]) was thus chosen as a model drug. 22

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Another limitation of the MD technique t hat the proposed project aims to address is the time-dependence of the recovery. The reduction of probe efficiency during the course of IV MD experiments has been repor ted [58,60,71]. Accordingly, results and interpretations might be misleading. We will ev aluate the continuous use of retrodialysis by a calibrator (microdialysis internal standar d). This calibration method provides the advantage that changes in recovery during the experiment can be detected, as a change in the relative recovery of the analyte would always go along with a change in the loss of the calibrator [7]. In addition of providing more accurate data, the calibrator method should be a starting point to simplif y microdialysis studies in animals and patients since this approach reduces the im posed calibration burden to a minimum. Our research can provide a preliminary assessment for the application of the IV MD technique in clinical settings of t herapeutic free drug monitoring in adults and pediatric patients. Direct measurement of free concentrations of strongly protein-bound drugs for therapeutic management is reco mmended in certain di sease states and possible drug-drug interactions [46]. In addition, therapeutic drug monitoring in infants is more difficult to perform than in adults because of blood sample limitations [44] and the discomfort and invasiveness of the conventional sampling procedures [72].Thus, intravenous microdialysis may be a new and prom ising approach in this area given that it provides a continuous analysis of free drug levels without painful stress and disturbance of blood volume, drug concent ration and binding equilibrium. Consequently, preclinical evaluation of the intravenous microdialysis as a promising tool for sampling of lipophilic and highly protein-bound dr ugs will provide an 23

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important foundation required to verify this technique suitable for therapeutic drug management and pharmacokinetic investigations, especially in pediatric population. PBPK Modeling Principles of PBPK Modeling In classical pharmacokinetic modeling, the ai m is to fit a mathematical function to the experimental data in order to determine pharmacokinetic paramet ers from the fitted curve. These parameters are then used to characterize the behavior of the compound and to make extrapolations to situations not yet investigated. PBPK-modeling, on the contrary, starts from the mathematical description of physiological processes and performs a genuine simulation of the pharmacokinetic behavior using this description [73]. The general concept of PBPK, introduced as early as 1937 by Teorell [74], is based on the recognition that the body handle s a drug as an integrated system [75]. Accordingly, the whole body is divided into physiologically relevant compartments (main organs and tissues) which are mathematical ly connected by linear exchange reactions according to their physiology. Figure 1 illustrates the human organism to be modeled and the division of its single organs, including the oral absorpt ion components (the GI tract), systemic distribution components and elimi nation components (usually the liver and the kidneys). To depict the distribution of a drug in the body, the organs are connected via their arteries and veins to the arterial and venous blood pool. Inter-compartmental mass transport occurs via organ-specific blood flow rates with the mass transfer from the vascular space into the tissue interstitial space by passive permeation and partitioning between organ tissues and blood plasma; while the intracellular mass transfer occurs 24

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via passive diffusion or active transport. Elimination processes are described as sink reactions or metabolic pathways in the eliminating organs [73]. From the previous description, we can delineate three major components of a PBPK model: model structure, drug-independent syst em properties and drug properties. The structural model includes all inter dependent mass balance equat ions which are set up for each compartment to describe the fate of the compound within that organ/tissue. The system properties include the relevant ph ysiological input param eters of the human body, such as organ mass or volume, body flui d dynamics (e.g., secretion of gastric acid and bile, blood flow, urine flow), and ti ssue composition (water lipid and protein content), in particular drug receptors, drug-metabolizing enzymes, and membrane transporters [5,75,76]. The drug dependent components include physicchemical properties (lipophilicity, molecular weight and acid dissociation constant ), tissue affinity, plasma protein binding constant, membrane permeability, and enzymatic and transport activities [75]. The latter information includes the drug specific clear ance, a required parameter in the PBPK model either from in vivo estimation or intrinsic clearances determined from in vitro experiments [73]. Application of PBPK Modeling By integration of prior knowl edge about the drug-depend ent and the system dependent (the human organism) parameters, PBPK enables the study of the absorption, distribution, metabolism and excretion (ADME) processes at the cellular level. Accordingly, the drugs concentration time -profile in blood and tissues of interest can be predicted. 25

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As previously outlined by Zhao et al [5], PBPK modeling and simulations generally include four basic steps: In step 1, drugdependent parameters are inco rporated into the PBPK model including the drug s clearance pathways. In step 2, the predicted concentrationtime profiles are compared with those obtained from available in vivo human studies. In step 3, the PBPK model is refined according to the results from step 2. Finally, in step 4, the refined PBPK model is used for predicting PK profiles under various scenarios that have not been studied experimentally [5]. Therefore, PBPK modelin g is a powerful tool to inve stigate the influence of drug specific properties as well as the effect of intrinsic (e.g. age, gender, genetics, organ dysfunction, disease state) and extrinsic fact ors (e.g. drug-drug interactions) on the ADME processes. PBPK modeling and simulation has demons trated its potential in the risk assessment of environmental toxins [77], and has being increasingly applied in the academia and drug research and development pr ograms [76]. Several examples in the literature described t he utility of PBPK mode ling and simulation as tools for predicting human pharmacokinetics in critical areas of clinical pharmacology, including pediatrics [78-80],organ impairment [ 81], and drugdrug interaction [11,12]. The use of PBPK modeling and simulation to support regulatory re view process also increased in the last decade with predictive potential of the te chnique been explored by both sponsors and FDA reviewers [5]. Particularly for evaluating drug-drug intera ction risk of an investigational drug, PBPK may provide a more accurate pr ediction of the po tential for drugdrug interactions than the tradition ally used static approach (such as the use of [I]/Ki, where 26

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[I] is the inhibitor concentration and Ki is the reversible inhibition constant) since PBPKbased prediction considers multiple factors a nd mechanisms that impact interactions [5]. For instance, PBPK model includes the fracti onal enzymatic metabolism of the victim drug and allows changes over time of the inhibitor concentration [82]. A critical component in the use of PBPK modelin g and simulation is the availability of software tools that allows facile solution of the model equations [75]. The software systems vary from high-level programming or matrix computing (e.g. Matlab ,The MathWorks Inc.) and biomathematical modeli ng (e.g ADAPT, Biomedical Simulations Resource, University of Southern Califor nia) to custom-des igned PBPK modeling and simulation such as SimCYP (SimCYP Ltd) [ 83], GastroPlus (Simulations Plus Inc) [84], and PK-Sim (Bayer Technology Servic es GmbH) [73]. These latter proprietary PBPK software systems are highly sophist icated population-based PBPK modeling and simulations tools which continuously integr ate the increasing knowledge of physiology, genetics and anthropometric prop erties (system-dependent param eters) to assess interindividual variability on dr ug pharmacokinetics [85,86]. The present project aims to investigate the utility of PBPK modeling and simulation in predicting enzyme inhibition potential inferred from the assessment of a drug nonlinear pharmacokinetics. Prediction of cytochrome P 450 3A4 (CYP3A4) interaction potential are particularly significant as CYP3A4 is the most important enzyme in drug metabolism, thus, it is the most frequent target for pharmacokinetic drug-drug interactions (DDIs) [82]. DDIs occur when one drug alters the metabo lism of a co-administered drug. The pharmacokinetic outcome is an increase or decrease in the systemic clearance and/or 27

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bioavailability, and a corresponding change in t he exposure of a co-administered drug. The clinical consequences of DDIs range from lack of ther apeutic efficacy to severe drug adverse events. Becaus e the impact of DDIs on patient health and safety, the knowledge of the risk for DDIs associated wi th a drug is an important component of drug research and development processes [82]. Significant drug-drug interactions may result in a possible termination of developmen t, withdrawal from the market or strict restrictions on its use [87] Telithromycin, a ketolide antibiotic, is a CYP3A4 substrate and inhibitor with doseand time-dependent nonlinear pharmacokine tics [88,89]. Thus, telithromycin was chosen as an inhibitor model drug. The study also aims to demonstrate the ut ility of the combinat ion of the bottomup and top-down approaches in the PBPK modeling by integrating available in vitro and in silico predicted drug interaction and enzyme/transporter kinetic data (bottomup) with in vivo human pharmacokinetic and drug-dr ug interaction information (topdown) in the building of a drug PBPK model. 28

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29 Figure 1-1. Schematic repr esentation of the wholebody physiologically-based pharmacokinetic model. Modified from [73].

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CHAPTER 2 DEVELOPMENT AND VALIDATION OF BIOANALYTICAL METHODS1 Background Microdialysis studies rely on an efficient analytical method to determine free drug concentrations in microdialysate and at the same time, total concentration in plasma to assess the relationship between the unbound and bound levels. In addition, the assay must be sensitive to measure considerably low concentration of the analyte in small sample volumes since only a few microliter s are obtained from microdialysis sampling. Another prerequisite of the method is the simultaneous quantif ication of the analyte and the calibration standard added to the micr odialysis perfusion solution. Some LC methods for determination of triamc inolone acetonide have been reported [70,90-93]. HPLC methods determi ned TA concentrations in human plasma after intravenous, intramuscular, oral or inhaled administration and were characterized by a laborious plasma extraction procedur e and limited concentration ranges [70,90-92]. Also, these methods were not suitable fo r the purpose of the proposed PK study, since none of them simultaneously determines TA and budesonide (microdialysis calibration standard). An ultra sensitive reversed-phas e capillary LC coupled to tandem mass spectrometry ( LC/MS/MS) was able to quantified TA in porcine plasma following suprachoroidal administration; however, this approach required more sophisticated instrumentation [93]. Nevertheless, the main disadvant age of previously reported methods rests on the large plasma volume required for sample preparation, minimum of 750 L, and/or the sample volume, minimum of 20 L, subjected to the HPLC analysis. 1Reprinted with permission from Vieira M de LT, Singh RP, Derendorf H. Simultaneous HPLC analysis of triamcinolone acetonide and budesonide in microdialysate and rat plasma: Application to a pharmacokinetic study. J Chromatogr B Analyt Technol Biomed Sci 2010, 878: 2967-2973. 30

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Specific Aim The aim of this study was to develop and validate an efficient and sensitive assay for reliable quantification of TA and budesonide in microdialysate and rat plasma using common laboratory equi pment (HPLC-PDA). Materials Chemicals and Reagents Blank male rat plasma Lampire Bi ological Lab. (Pipersville, PA, USA) Budesonide Purity 99%, Sigma (St. Louis, MO, USA) Fluticasone propionate Purity 98%, Sigma (St. Louis, MO, USA) HPLC grade methanol Fischer Scientific (Fair Lawn, NJ, USA) HPLC grade phosphoric acid Fischer Scientific (Fair Lawn, NJ, USA) Lactated Ringers Injecti on USP Baxter Health Ca re (Deerfield, IL, USA) Triamcinolone acetonide Purity 99%, Sigma (St. Louis, MO, USA) Equipment and Disposables Balance Mettler AE240, Toledo (Hightstown, NJ, USA) Cellulose membrane filter 0.45 m poresize, Millipore (Bedford, MA,USA) Centrifuge Fisher Scient ific model Marathon 16KM (Pittsburg,PA, USA) Micropipettes Eppendorf Research SPE cartridges Bakerbond SPETM, C18 phase, 1mL capacity, sorbent, JT Baker (Deventer,Netherlands) SPE manifold Vac Elut S PS 24, Varian (Palo Alto, CA,USA) Ultrasonic bath Fisher Scientific model FS110H (Pittsburgh,PA,USA) Vortex Kraft Apparatus Inc., Fisher Scientific model PV-5 (Pittsburgh,PA,USA) Chromatographic Instrumentation Analytical column Krom asil C18, 4.6 mm id, 25 cm, 5 m particle, Hichrom (Reading, UK) 31

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Analytical software Agilent ChemStation Autosampler Agilent 1100 series model G1329A Column oven Agilent 1100 series, model G1316A Degasser Agilent 1100 series, model G1379A Guard column Kromasil C18, 3.2 mm id,10 cm, 5 m particle, Hichrom (Reading, UK) HPLC system Agilent 1100 Series (Waldbronn, Germany) Photodiode array (PDA) detector Agilent 1100 series, model G1315B Quaternary pump Agilent 1100 series, model G1311A Workstation Hewllet-Packard Compaq p4 Methods Chromatographic Conditions Chromatographic separations were obtai ned using a Kromasil C18 analytical column which was protected by Kromasil C18 guard column. The column temperature was maintained at 25 C and the detection wave length was set at 254 nm. The isocratic mobile phase consisted of methanol: water in t he ratio of 72:28 (v/v) at a flow rate of 0.8 mL/min was used to achieve desired chromatographic separation. The mobile phase was filtered through 0.45 m cellulose membrane filter and degassed in an ultrasonic bath prior to use. The injection volume was 10 L for microdialysates and 20 L for extracted plasma samples. Samples were main tained at 4 C in the autosampler prior to injection. Before every run mobile phase was pum ped through the system until a stabile base line was achieved. A blank injection of either lactated Ringers solution for microdialysate samples or methanol for pl asma samples was made at the start to 32

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ensure system equilibration. A standard retention time and peak symmetry (between 0.8 and 1.2) were then verified. Blank lactat ed Ringers solution or methanol injections were made periodically throughout run. At the end of the runs, the system was washed with mobile phase for at least 30 mi nutes. Mobile phase was not recycled. Preparation of Stock and Working Solutions Primary stock solutions of TA, fluticasone propionate (plasma internal standard, IS) and budesonide (microdialysis calibration standard) were prepared in methanol to yield for each solution concentrations of 1 mg /mL. These stock solutions were further diluted in methanol to get inte rmediate concentrations of 100 g/mL for TA, 75 g/mL for IS and 75 g/mL for budesonide. Working solutions of TA (1.5 750 g/mL) and budesonide (7.5 150 g/mL) required for spiking plasma and microdialysate calibration and quality control samples were subsequently diluted in methanol from primary and intermediate stock solutions. All methanolic solutions were stored at 20 C, protected from the light, until use. Preparation of Calibration Standa rds and Quality Control Samples To obtain the desired concentration of TA for calibration and quality control (QC) samples, either blank rat plasma or Ri ngers solution were spiked with 7% of TA working solutions of appropriate concentrations. Four levels of quality control samples at the lowest limit of quant ification (LLOQ), low (LQC), medium (MQC) and high (HQC) end of the calibration curve were prepared for both matrices. Microdialysate calibration standards (0.1, 0.25, 0.5, 1, 2.5, 5 and 10 g/mL) and QC samples (LLOQ= 0.1 g/mL, LQC= 0.2 g/mL, MQC= 2 g/mL and HQC= 7 g/mL) were prepared prior to each analytical run, whereas plasma calibration standards (0.5, 1, 2.5, 5, 10, 25 and 50 33

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g/mL) and QC samples (LLOQ= 0.5 g/mL, LQC= 1 g/mL, MQC= 20 g/mL and HCQ= 40 g/mL ) were stored at -70 C until analysis. A 7% spiking with budesonide working so lutions of appropriate concentrations were done in Ringers solution to obtain t he desired level of budesonide for calibration (0.5, 1, 2.5, 5, 10 g/mL) and QC samples (LLOQ=0.5 g/mL, MQC=2 g/mL, HQC=7 g/mL). Plasma Sample Pre-treatment: SPE Procedure Spiked plasma samples were complete ly thawed in a water bath at room temperature and vortex adequately. To 140 L of the plasma sample, 10 L of internal standards solution (75 g/mL of fluticasone propionate containing 75 g/mL of budesonide) were added to yield a concentration of 5 g/mL. Samples were mixed 1:1 with 4% phosphoric acid solution to releas e protein-bound drug. After thorough mixing, samples were extracted using solid phase-extraction cartridges with C18 phase. The extraction was carried out on a SPE extr action manifold. Each cartridge was conditioned by 1 column volume of methanol followed by 1 column volume of water. The diluted plasma samples were loaded onto the conditioned SPE cartridges at a flow rate of 1mL/min. Washi ng was done with 600 L of 2% phosphoric acid. Then, a low vacuum (2-5 mmHg) was applied for 2-5 mi nutes to remove t he aqueous part. The analytes were eluted using 300 L of methanol and a 20 L aliquot of each sample was subjected to HPLC analysis. 34

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Method Validation Specificity Six different sources of blank rat microdialysate and rat plasma were screened to investigate potential e ndogenous interferences in the retention times of TA, budesonide and fluticasone propionate (IS). Linearity The linearity range of the method for TA was evaluated by seven-point standard curves in the concentration range of 0.1-10 g/mL for microdialysate and 0.5-50 g/mL for plasma on three validation days. Budeson ide calibration curves in microdialysate were prepared in the range of 0.5-10 g/mL. Microdialysate calibration curves were constructed by plotting the analyte peak area vs concentration using 1/x2 linear regression; whereas for plasma calibration curves, the TA/IS (fluticasone propionate) peak area ratios vs TA concentrations were plotted using 1/x2 linear regression. The linear model was accepted if the relati ve error (%RE, percent difference of the back-calculated concentration fr om the nominal concentration) were within 20% at the lower limit of quantification and within 15% at a ll other calibration levels. In addition, the similarity of slope and intercept (significanc e level of 0.05) among calibration curves (n=6, for each matrix) were verified. The lower limit of quantification (LL OQ) was established as the lowest concentration used in the calibration curve for each matrix. Accuracy and precision The intra-day precision and accuracy of the method for quantifying TA were determined by analysis of four sets of pl asma and six sets of microdialysate QC samples at the LLOQ, LQC, MQC and HQC levels in a single day. The inter-day 35

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precision and accuracy were estimated by a nalysis of all QC samples over the three validation days. Accuracy and precision of the method for budesonide were determined by the analysis of six sets of microdialysi s QC samples at the LLOQ, MQC and HQC. Accuracy was calculated as the mean relative error (RE) of the obs erved concentration (Cobs) from the nominal concentration (Cnom) at each QC level according to the equation: %RE = (C obs -C nom ) x 100 Cnom Precision was expressed as percent of coefficient of variation and calculated as: %CV = standard deviation of the mean x 100 Mean Cobs Plasma extraction recovery The extraction recovery from plasma were carried out in plasma QC samples at low, medium and high TA concentrations (1, 20 and 40 g/mL) and at one concentration (5 g/mL) of the IS (fluticasone propionat e). The absolute percentage recovery was determined by comparing the mean peak area of four replicates of extracted samples with mean peak areas of un-extracted standards of equivalent concentration as follows: %AR = peak area sample x 100 peak area standard Stability Stability tests were performed under settings that simulate the conditions likely to be encountered during sample collection, storage, preparation and analysis: microdialysate kept at r oom temperature (25 2 C ) for 12h, process stability (autosampler at 4 C for 24h), long-term stability of plasma at -70 C for 2 months and plasma samples freeze-thaw stability (three cycles). Experiments were performed using three replicates of LQC, MQC and HQC samp les of the corresponding matrix. Stability 36

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was expressed as the mean percentage ra tio of the observed concentration (Cobs) to the nominal concentration (Cnom) at each QC level according to the equation: %RE = C nom x 100 Cobs Data analysis Linear regression analyses were perform ed by GraphPad Prism version 4.00 for Windows (GraphPad Software, San Diego, CA USA). The statistical analyses of calibration standards and quality controls we re performed using EXCEL 2007 (Microsoft Corporation). Data ar e expressed as means standard deviation, unless otherwise stated. Results and Discussion Plasma Internal Standard Selection Structural analogs of TA were screened to find suitable compounds for plasma internal standard. Fluticasone propionate was finally chosen as the internal standard for its better sensitivity and good corre ction as shown by the data. Development of Chromatographic Method Due to the relatively small number of samp les but two different matrices (plasma and microdialysate) and two different analytes, it was not the goal to perform extensive method optimization but to provide sample analysis with adequate specificity, accuracy and precision. It was preferr ed to apply the same analysis te chnique for both matrices to allow a rapid switching from one assay to another. Development of the Sample Pre-treatment Procedure For microdialysate samples, due to the la ck of proteins, no sample pre-treatment procedure was necessary. Thus samples were directly injected into the HPLC system. 37

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However, the pre-analytical treatment of plasma samples was essential to obtain cleaner extracts. Different liquid-liquid and solid-phase extraction (SPE) procedures were tested. Liquid-liquid extraction using et hyl-acetate, dichloromethane and tert-butyl methyl ether as previously used by other in vestigators [90,91,94] we re tested. However, our results showed relatively low recovery for TA, around 60%, poor reproducibility and specificity. Subsequently, SPE procedures we re tested using octadecyl phase sorbent because of its extreme ret entive nature for hydrophobic compounds. Initially, the pretreatment of the plasma samples with 4% phosphate acid aimed on the release of TA from plasma proteins. The optimizati on of the SPE procedure was done by varying the proportion of methanol in water used as washing solvent to mini mize polar matrix interferences. The method proved to be uns uccessful as it did not improve the specificity of the method. However, an ac idic condition washing (2% phosphoric acid) removed interfering endogenous substances wit hout causing elution of the analytes. The volume of methanol as elution solvent was also optimized to improve the recovery of the analytes. A higher volume of eluat e (300 L instead of 150 L) resulted in excellent recovery and minimal residual matrix All these efforts helped us achieve an efficient SPE procedure with one wash and one elution step with no drying and reconstitution. Thus, this is a simple and economical plasma extraction procedure with increased sensitivity, specific ity and throughput for determina tion of corticosteroids in small volume of plasma samples. Method Validation Specificity The specificity is the abilit y of an analytical method to differentiate and quantify the analyte in the presence of potentia l interfering compounds. 38

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Typical chromatograms obtained from blank rat microdialysate, blank rat plasma, the peak response of TA at the medium end of the calibration curve in plasma and artificial microdialysate (l actated Ringers solution), and intravenous microdialysate and plasma samples obtained after constant-rate in fusion of TA (23 mg/kg/h) to a rat are shown in Figures 2-1 and 2-2. TA, budes onide and IS (fluticasone propionate) were eluted at 6.8, 12.3 and 14.0 minutes, respectively. The results demonstrated there is no interference in the determination of the anal ytes, granting good method selectivity. Linearity The weighted linear regression (w eighting factor: 1/concentration2) analysis was used since this option provided an impr ovement in the residuals with a similar coefficient of determination (r2) to the linear model. Calibration curves for TA in both matrices exhibited good coe fficients of determination, r2 0.992 for all microdialysate curves and r2 0.996 for all plasma curves. Detail ed results for linear ity parameters for TA in microdialysate and plasma are listed in Table 2-1. Slope and intercept among microdialysate calibration curves (n=6) were not significantly different ( =0.05) allowing the constructi on of one common curve with slope of 15.49 ( 0.12) and interc ept of -0.1046 ( 0.0297), r2 =0.9959. Since differences among slopes and intercepts of plasma calibr ation curves (n=6) were not significant ( =0.05), the pooled slope equals 0.2138 ( 0.0027) and intercept -0.0041( 0.0031) with r2 =0.9962. Good linearity values were al so found for budesonide in microdialysate curves (Table 2-2). The common curve ( =0.05) has a slope of 17.07 ( 0.22) and intercept of -4.053 ( 0.218) with r2 =0.9932. The lowest standard on the calibration curves for each matrix and analyte, TA and budesonide, were defined as the LLOQ since the analytes response were identifiable, 39

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discrete (Figures 2-1 and 2-2), and reproduc ible with precision and accuracy less than % (Tables 2-3 and 2-4). The mean back-calculated concentrations of TA in microdialysate and plasma calibration standards with resulted accuracy (%RE) and precision (%CV) are listed in Table 2-3. The accuracy values of budesonide for various concentrations in microdialysate calibration standards ranged from -4.81% to 5.21% with precision between 1.74% and 5.51% (Table 2-4). Accuracy and precision The intra-day precision of TA QC samples for both matrices was less than 6.62%, and the accuracy ranged between -5 .28% and 9.14%. The inter-day precision was less than 6.46%, and the accuracy values ranged between -3.19% and 6.30%. The mean observed value, coefficient of variation and relative errors of the microdialysate and plasma QC samples used on the three validation days are presented in Tables 2-5 and 2-6, respectively. The intra-day accuracy of budesonide in mi crodialysate QC samples (n=6 at each concentration) ranged from -1.42% to 9.14% and precision values were between 1.80% and 4.50%. The inter-day accuracy values were 0.73% for LLOQ and 3.18% for MQC with CV of 3.39% and 4.89%, respectively. The accuracy and precision values were well within acceptable limits stated for bioanalytical method validation: % at low, medium and high range of concentrations and 20% at the LLOQ. Extraction recovery The extent of recovery of the TA and IS from plasma was reproducible and equivalent. The mean absolute recovery (n=4 at each concentration) at low, medium 40

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and high QC samples were 109%, 103% and 99.6% with precision of 2.02%, 4.57% and 3.94%, respectively. The mean recovery of the IS was 95.7% with CV of 1.81%. Stability The results of stability test of TA in plasma and microdialysate QC samples are listed in Table 2-7. TA and budesonide in sp iked microdialysate proved to be stable after sample preparation and storage in the samp le tray of the autos ampler at 4 C for 24h and at room temperature fo r at least 12h. Average stab ility for budesonide at MQC was 99.2% with precision of 3.95% and 109% with precision of 6.57% under these respective conditions. The results of process stability of plasma QC samples demonstrated that the post-extracti on solution is stable at 4 C for at least 24h. Storing samples containing TA in plasma at -70 C for 2 months or a fter three freeze-thaw cycles did not cause any degradation. Overall, the results indicated reliable stability for TA and budesonide under the investigated conditions since the observed concentrations were all within 85-115% of the nominal concentrations. In summary, a simple and specific HPLC-PDA method was developed for simultaneously quantifying TA and its mi crodialysis calibrator, budesonide, in microdialysate and rat plasma samples. Vali dation results showed that the method is highly reproducible for both matrices and meets the requirements for the pharmacokinetic investigations. The analytes are stable under the conditions which will be encountered during the proposed studies. 41

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Table 2-1. Linear regression parameters for triamcinolone acetonide in plasma and microdialysate calibration standards TA Plasma TA Microdialysate Curve Intercept Slope r2 Intercept Slope r2 1 -0.0019 0.2156 0.9996 -0.0386 15.27 0.9916 2 -0.0047 0.2234 0.9997 -0.1201 15.15 0.9935 3 -0.0064 0.2163 0.9973 -0.1697 15.43 0.9952 4 -0.0083 0.2205 0.9961 -0.0262 15.34 0.9975 5 0.0003 0.2023 0.9979 -0.2037 16.10 0.9987 6 -0.0038 0.2053 0.9996 -0.0692 15.63 0.9992 Mean 0.2138 15.49 SD 0.0083 0.36 CV (%) 3.9 2.3 Table 2-2. Linear regression parameters fo r budesonide in microdialysate calibration standards Budesonide Microdialysate Curve Intercept Slope r2 1 -4.388 17.22 0.9917 2 -3.807 16.91 0.9887 3 -4.458 17.89 0.9992 4 -3.821 17.03 0.9941 5 -4.210 17.08 0.9934 6 -3.634 16.33 0.9995 Mean 17.07 SD 0.50 CV (%) 3.0 42

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Table 2-3. Summary of observed TA c oncentration in microdialysate and plasma calibration standards Microdialysate Plasma Cnom Mean Cobs SD %RE %CV Cnom Mean Cobs SD %RE %CV 0.1 0.100 0.004 0.36 3.52 0.5 0.485 0.015 -3.06 3.12 0.25 0.253 0.010 1.26 3.75 1 1.05 0.04 5.16 3.69 0.5 0.481 0.007 -3.75 1.41 2.5 2.65 0.20 6.15 7.51 1 0.987 0.031 -1.30 3.11 5 4.71 0.12 -5.76 2.59 2.5 2.45 0.11 -2.03 4.59 10 9.52 0.41 -4.84 4.35 5 5.01 0.18 0.14 3.49 25 25.1 1.1 0.34 4.19 10 10.5 0.2 5.35 1.59 50 50.9 2.6 1.86 5.12 Cnom= Nominal concentration ( g/mL) and Cobs= Observed concentration ( g/mL) Mean values: n=6 at each concentration Table 2-4. Summary of obser ved budesonide concentration in microdialysate calibration standards Cnom Mean Cobs SD %RE %CV 0.5 0.503 0.008 0.60 1.59 1 1.00 0.05 0.58 4.53 2.5 2.38 0.13 -4.81 5.51 5 4.93 0.09 -1.46 1.74 10 10.5 0.4 5.21 3.96 Cnom= Nominal concentration ( g/mL) and Cobs= Observed concentration ( g/mL) Mean values: n=6 at each concentration 43

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Table 2-5. Intraand inter-day accuracy (%RE) and precision (%CV) of observed TA concentrations in microdialysate quality controls Cnom Validation day Mean Cobs SD %RE %CV 1 (n=6) 0.103 0.004 2.72 4.00 2 (n=6) 0.102 0.006 2.42 5.53 3 (n=6) 0.106 0.005 6.44 5.02 0.1 Inter-day (n=18) 0.104 0.005 3.84 4.72 1 (n=6) 0.211 0.014 5.51 6.65 2 (n=6) 0.207 0.009 3.42 4.22 3 (n=6) 0.201 0.005 0.67 2.45 0.2 Inter-day (n=18) 0.206 0.011 3.21 5.26 1 (n=6) 2.06 0.02 2.98 1.15 2 (n=6) 1.97 0.06 -1.74 3.10 3 (n=6) 1.89 0.11 -5.67 5.59 2 Inter-day (n=18) 1.97 0.11 -1.47 5.36 1 (n=6) 7.08 0.04 1.11 0.49 2 (n=6) 6.75 0.12 -3.55 1.83 3 (n=6) 7.27 0.36 3.80 4.90 7 Inter-day (n=18) 7.03 0.24 0.41 3.35 Cnom= Nominal concentration ( g/mL) and Cobs= Observed concentration ( g/mL) Table 2-6. Intraand inter-day accuracy (%RE) and precision (%CV) of observed TA concentrations in plasma quality controls Cnom Validation day Mean Cobs SD %RE% %CV 1 (n=4) 0.510 0.034 2.03 6.59 2 (n=4) 0.498 0.026 -0.43 5.20 3 (n=4) 0.495 0.025 -0.91 4.99 0.5 Inter-assay (n=12) 0.501 0.032 0.25 6.46 1 (n=4) 1.09 0.019 9.14 1.77 2 (n=4) 1.05 0.051 4.46 4.92 3 (n=4) 1.05 0.023 4.64 2.20 1 Inter-assay (n=12) 1.06 0.056 6.30 5.29 1 (n=4) 19.3 0.915 -3.48 4.74 2 (n=4) 19.4 1.060 -3.02 5.46 3 (n=4) 19.4 0.425 -3.01 2.19 20 Inter-assay (n=12) 19.4 1.004 -3.19 5.19 1 (n=4) 38.7 0.732 -3.34 1.89 2 (n=4) 39.5 1.454 -1.31 3.68 3 (n=4) 39.6 0.350 -1.08 0.89 40 Inter-assay (n=12) 39.2 1.444 -1.94 3.68 Cnom= Nominal concentration ( g/mL) and Cobs= Observed concentration ( g/mL) 44

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Table 2-7. Stability results of TA in rat plasma and microdialysate under various conditions LQC MQC HQC Storage Condition Cobs (Cnom) % RE % CV Cobs (Cnom) % RE % CV Cobs (Cnom) % RE % CV Plasma 3 freeze-thaw cycles 0.98 (1) 97.9 2.68 20.5 (20) 103 3.58 39.6 (40) 99.1 6.17 2 months at 70 C 1.00 (1) 100 2.79 19.0 (20) 95.1 2.62 39.0 (40) 97.4 0.90 Process 4C, 24h 1.02 (1) 102 2.78 19.2 (20) 96.0 0.75 40.6 (40) 102 3.03 Microdialysate Room temp. (25 C), 12h 0.222 (0.2) 111 1.68 2.16 (2) 108 6.55 7.05 (7) 100 2.62 Process 4C, 24h 0.202 (0.2) 101 1.84 1.96 (2) 97.9 4.07 7.04 (7) 100 1.72 Cobs= Observed concentration ( g/mL) and Cnom= Nominal concentration ( g/mL) Mean values: n=3 at each concentration ( g/mL) for each storage condition 45

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mi n 0 2 4 6 8 10 12 14 mAU 0 0.5 1 1.5 2 2.5 3 A mi n 0 2 4 6 8 10 12 14 mAU 0 0.5 1 1.5 2 2.5 3 6.788 12.402B TABudesonide mi n mAU 0 2 4 6 8 10 12 14 0 0.5 1 1.5 2 2.5 6.790 12.419C3 BudesonideTA Figure 2-1. Representative microdialysis chromatograms. A) Blank intravenous microdialysate. B) Microdialysate calibration standard spiked with TA (1 g/mL) and budesonide (1 g/mL). C) Intravenous microdialysate sample containing TA (2.86 g/mL) and budesonide (1.92 g/mL) after drug infusion in a rat. 46

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47 mi n 2 4 6 8 10 12 14 mAU 0 2.5 5 7.5 10 12.5 15 17.5 A mi n 2 4 6 8 10 12 14 mAU 0 2.5 5 7.5 10 12.5 15 17.5 6.729 12.243 13.989TABudesonideIS B mi n 2 4 6 8 10 12 14 mAU 0 10 20 30 40 50 60 70 TA 6.726 14.053IS C Figure 2-2. Representative plasma chromato grams. A) Blank rat plasma. B) Plasma calibration standard spiked with TA (5 g/mL), budesonide (5 g/mL) and IS (Fluticasone propionate, 5 g/mL). C) Plasma sample containing TA (42.6 g/mL) after drug infusion.

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CHAPTER 3 TRIAMCINOLONE ACETONIDE MICRODIALYSIS CALIBRATION Background It is recommended to perform supportive in vitro MD experiments prior to animal use to obtain basic information on the feasibil ity of the method. The applicability of the MD technique can be limited by drug lipophilici ty which can impair the diffusion through the microdialysis membrane and overall recovery [2,10,33] Triamcinolone acetonide, our model compound has moder ate lipophilicity (Log Po:w of 2.5) and is poorly soluble in water (21 g/mL) (Chemspider database, Royal Soci ety of Chemistry, Cambridge, UK). One critical step to apply microdialysis is to determine the relative recovery of the analyte of interest. As MD probe is conti nuously perfused at a constant flow rate, complete equilibrium across t he MD membrane cannot be established. Thus, the levels measured in the dialysate will always be lower t han the actual levels in the investigated media (Canalyte sampling site > Canalyte dialysate). The factor by which the concentrations are interrelated during sampling (Cperfusate=0) is termed relative recovery [2]. The recovery value is determined a priori to calculate the actual concent ration at the investigated media from the concentration in the dialysate as follows: Canalyte sampling site= C analyte dialysate Recovery A general measured of the degree of equilibration at a constant flow rate (or the steadystate rate of exchange across the MD memb rane) is named extraction efficiency which has the same value for all drug concentrations in the perfusate (Cperfusate). Microdialysis probes can consequently be calibrated by either measuring the loss of analyte using drug-containing perfusate (Cperfusate > 0, Retrodialysis method) or the gain of the analyte using drug-containing sample solutions (Cperfusate=0, Extraction Effici ency method) [2]. 48

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The processes occurring during retrodialysi s and extraction efficiency methods of microdialysis calibration are illustrated in Figure 3-1. The in vitro recovery of TA was determined using the two calibration methods: the extraction efficiency (EE) and retrodialysis (RD). The in vitro studies were carried out to investigate the effects that drug characteristics may have on recovery, including the ability of the compound to di ffuse through the MD membrane, whether the diffusion is symmetrical in both directions and i ndependent of the dr ug concentrations. However, the recovery obtained by the in vitro experiments do not replace the in vivo determinations [32,95]. The overall diffusion resistance of the in vitro medium might be much different from that one observed in vivo due to additional resistance derived from the interstitial space. Therefore, the in vivo recovery of the probes was determined by the most common method of in vivo calibration, retrodialysis by drug. Specific Aim The aim of this study was to determine the relative recovery of TA by a series of in vitro and in vivo studies to evaluate the feasibility of using microdialysis as a sampling technique for TA. Materials Chemicals and Reagents 0.9% Sodium Chloride Inj. USP Baxter Health Care (Deerfield, IL, USA) 1000 UI/mL Heparin Elkins-S inn, Inc. (Cherry Hill, NJ, USA) Budesonide Sigma (St. Louis, MO, USA) HPLC grade methanol Fischer Scientific (Fair Lawn, NJ, USA) Isoflurane USP Webster Veterinary (Charlotte, NC, USA) Lactated Ringers Injection USP Baxter (Deerfield, IL, USA) Triamcinolone acetonide Sigma (St. Louis, MO, USA) Equipment and Disposables Balance Mettler AE240, Toledo (Hightstown, NJ, USA) 49

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Heated Stir Plate Fisherbrand Isotemp Microfraction collector CMA/142, CMA Microdialysis (Stockholm, Sweden) Micropipettes Eppendorf Research Precision Infusion Pump Harvard Apparatus Model 22, (South Natick, Mass., USA) Syringes Becton Dickinson 309603 (Franklin Lakes,NJ, USA) Thermometer Fisherbrand 76mm Immersion 14-997 Tubing Adapter CMA Micr odialysis (Stockholm, Sweden) Vortex Kraft Apparatus Inc., model PV-5, Fisher Scientific FEP tubing ID 0.12mm, CMA Microdialysis (Stockholm, Sweden) Cellulose membrane filter 0.22 m pore size, Millex GV Millipore (Carrigtwohill, Co. Co Cork, Ireland) Microdialysis Probe CMA/20 Elit e, 14/10 PAES, cut-off 20kDa; membrane length 10 mm; CMA Microdialysis (Stockholm, Sweden) Animals Adult male Sprague-Dawley rats, weighti ng 250-300 grams, were purchased from Harlan Sprague-Dawley Inc. (I ndianapolis, IN, USA). Animals were acclimatized to standard ACS housing in a 12-h light-dark cycl e and constant temperature environment for a minimum of three days before being used. Animals had free access to food and water. The animal experimental procedures were approved by the In stitutional Animal Care and Use Committee of University of Florida. 50

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Methods Preparation of Standard Solutions and Quality Control (QC) Samples 10 mg of TA were weighted and dissolved in 10 mL of methanol. The 1 mg/mL stock solution was diluted to a secondary stock of 100 g/mL in lactated Ringers solution. Further dilutions were performed to obtain the seven standard solutions of TA at the concentrations of 10, 5, 2.5, 1, 0.5, 0.25 and 0.1 g/mL in lactated Ringers solution. Four levels of QC samples at t he lowest limit of quantif ication (LLOQ), low, medium and high end of the calibration curve (0.1, 0.25, 1 and 5 g/mL) were also prepared. Preparation of Calibration Solutions for Microdialysis Stock solution of 1mg/mL of TA in methanol was prepared. Then a 100 g/mL solution was obtained by dilution in lactated Ringers solution. Further dilutions were performed to obtain the three calibration soluti ons of TA at the concentrations of 10, 5 and 1 g/mL in lactated Ringers solution. Thes e concentrations were chosen based on the expected concentrations in the main preclinical study. In vitro Microdialysis Calibration Apparatus setup During setup, a 5 mL syringe was filled eit her with blank lactated Ringers solution (EE method) or analyte solution (RD method) and the enclosed air was cleared from the syringe. The syringe was placed on the precis ion pump, connected to the inlet of the probe and run at a flow rate of 1.5 L/min for 30 minutes to a llow for equilibration. The microdialysis probe was immersed in a 10 mL centrifuge tube c ontaining approximately 8 mL of either blank lactated Ringers so lution (RD method) or analyte solution (EE method). The sampling solution was st irred at 300 rpm to guarantee equal 51

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concentrations throughout the whole tube and temperature was controlled at 37 1C on a heated plate. The microdialysate samples were collected with the aid of the microfraction collector. Extraction efficiency method (EE) The MD probe was perfused with Blank lact ated Ringers solution at a constant flow rate of 1.5 L/min and placed into the sampling tube containing TA solution, starting with the lowest concentration. Drug di ffused from the sampling solution into the MD probe and was taken with the perfusion fl ow. The gain of the analyte through the membrane was then determined from the TA concentration in the microdialysate (Cdialysate). Three microdialysate samples were co llected with 20 minutes intervals after the end of a 30 minutes equilibr ation period. To determine the actual TA concentration in the calibration solution to perform t he calculations and to ensure that the concentration was consistent throughout t he sampling period, two samples of the sampling solution were taken, one befor e the sampling period and one after (Csampling sol). The same procedure was done for the remaining two concentrations, 5 and 10 g/mL. The analyte concentrations in the samples were determined by a validated HPLC method. The experiments were perfo rmed using three different microdialysis probes. The percent recovery (%R) for the EE method was calculated as follows: %R = C dialysate x 100 Csampling sol Retrodialysis method (RD) The MD probe was perfused with the analyte so lution at a constant flow rate of 1.5 L/min. and placed into a calibration tube fill ed with blank lactated Ringers solution. The drug diffused out of the pr obe into the calibration solu tion. The loss of the analyte 52

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through the membrane was then determined from the TA concentration in the microdialysate (Cdialysate). Three microdialysate samples were collected with 20 minutes intervals after the end of a 30 minutes equi libration period. To obtain the actual concentration of the TA in the perfusion solution and to ensure that the concentration was consistent throughout the sampling period, two samples of the perfusate were taken, one before the sampling period and one after (Cperfusate). The lowest concentration, 1 g/mL, was sampled first followed by the others with the exchange of calibration tube with fresh blank lactated Rin gers solution. Experiments were performed using three different probes. The percent recovery (%R) for the RD method was calculated as follows: %R = C perfusate C dialysate x 100 Cperfusate Sample analysis The concentration of TA in the in vitro microdialysate samples and calibration solutions were determined by the HPLC method described below. The HPLC system consisted of an Agilent 1100 series which included an autosampler (G1329A), a column oven (G1316A), a degasser (G1379A), a quaternary pump (G1311A) and a DAD detector (G1315B). Instrument control, data acquisition and processing were performed using ChemStation software. Chromat ographic separations were obtained using LiChrospher 100 RP-18 analytical column (5 m particle size, Merck KGaA, Darmstadt, Germany) protect ed by a guard column (LiChroCART Merck, KGaA, Darmstadt, Germany). The column temper ature was maintained at 25 C and the detection wavelength was set at 254 nm. The isocratic mobile phase consisted of methanol and water in the ratio of 70:30 (v/v) at a flow rate of 0.8 mL/min. A volume of 53

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10 L of each microdialysate sample and calibrati on solutions was directly injected into the column without previous preparation. Samples were maintained at 4 C in the autosampler prior to injection. In vivo Microdialysis Calibration Animal preparation In vivo microdialysis calibration was perform ed with the animals under anesthesia. Isoflurane was employed as an inhalation anesthetic as previously described [96,97]. Experimental procedures were in accordance with the criteria of the Canadian Council of Animal Care [98]. Animals were anesthet ized by using Isotec-4 isoflurane vaporizer (SurgiVet/ Smiths Medical, Waukesha, WI). The rat was placed in an induction chamber which is supplied with an air-isoflurane (4%) mi xture at a flow rate of 500 mL/min. After complete induction (2-3 minutes), the anima l was transferred to the nonrebreathing circuit (face mask).The surgical level of anesthesia was confirmed by the absence of reflexes using noxious stimuli. Isoflurane anesthesia was ma intained at 2.5-3% during acute surgical procedures and at 1.5% during prolonged experimental observations. Anesthetic depth and animal general well bei ng were monitored by observing the rats respiratory pattern, tissue per fusion, internal temperatur e and response to stimulation by pinching the toe pads. Animal body tem perature was maintained at 99.5-101F by a heating pad. To maintain the body flui d balance, sterile isotonic saline were administered at a constant rate of 0.5 mL /h through a catheter inserted on the tail ventral artery. The surgery si te (pectoral area) was shaved and disinfected by swiping the area with 70% isopropyl alcohol. The rat wa s placed in the dorsal position with the tail towards the experimenter. 54

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Probe insertion A vertical incision was made in the skin over the pectoral muscle on the right side of the midline to expose the pectoral muscle and the jugular vein above it. A needle placed into a split introducer was inserted through the pectoral muscle into the right jugular vein. By removing the needle, t he blood seeped back through the split tube. Rapidly, the microdialysis probe was insert ed through the split introducer. The probe was secured by suturing its wings to the pec toral muscle using surgical silk, and the split introducer was then removed. The ski n incision was closed by a suture. During surgery the inlet tubing of the probe was connected to a precision infusion pump and perfused with 10 IU heparin in lactated Ringers solution at flow rate of 1.5 L/min. After probe insertion the flow rate was increased to 8 L/min for 5 minutes in order to remove air bubbles. The outlet tubing of the probe was checked to ensure the liquid was flowing. In vivo retrodialysis method After 5 minutes, the perfusate was c hanged to the calibration solution of triamcinolone acetonide (5 g/mL) in lactated Ringers with the flow rate reduced to 1.5 L/min. The probe was perfused for 60 minutes to equilibrate the system. Following this stabilization period, microdialysate samples we re collected by the microfraction collector at 20 minutes intervals for 1-6 hours. Samples were stored at 4 C until HPLC analysis was performed (within 24 hours) At the beginning and the end of the experiment, TA concentration in the perfusate was determined. The retrodialysis recovery of TA was calculated according to the equation: %R = C perfusate C dialysate x 100 Cperfusate 55

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where %R is the percent recovery, Cperfusate is the average TA concentration in the perfusate before and after the experiment, and Cdialysate is the TA concentration in the microdialysate sample. Sample analysis The concentration of TA in in vivo microdialysate samples and calibration solutions in lactated Ringers solution were determined using the HPLC method described in Chapter 2. Data Analysis Linear regression and statistical analyses were performed using GraphPad Prism version 4.00 for Windows (GraphPad Softwar e, San Diego, CA, USA).The significance level was set at 0.05. Data are expressed as means standard deviation. Results and Discussion HPLC Method Validation A seven-point linear calibration curve for TA was obtained in the range of 0.1-10 g/mL. The analysis was performed with weighted linear regression (1/Y2). The slope for the standards was 16.14 ( 0.28) and t he intercept was 0.2671 ( 0.0717) with r2 value of 0.9969. The method was validated by performing three calibration curves on each of the three consecutive days and by analyzing quality control samples (LLOQ= 0.1 g/mL, LQC= 0.25 g/mL, MQC= 1 g/mL, and HQC= 5 g/mL, n=6 at each concentration per day). The intraand interday precision (%CV) values were smaller than 6.09% and 8.85%, respectively. The inte r-day accuracy ranged from -4.34% to 11.5%. The results are listed in Table 3-1. The retention ti me of TA was approximately 5.3 minutes. The analytical method was specific, accurate and precise supporting the analysis of the in vitro microdialysis samples. 56

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After the in vitro studies deemed TA suitable for use with microdialysis sampling, another HPLC-PDA method wa s developed and validated to determine TA in both microdialysate and rat plasma samples. In vitro Microdialysis Calibration The temporal resolution of microdialysis is determined by the perfusion rate and sensitivity of the analytical assay. Si nce there is a minimum sample volume requirement for the assay technique, a highe r flow rate would provide shorter sampling intervals. However, the recovery is r educed because there is not enough time for equilibration between the solution inside the probe and the surrounding media to occur. Thus, the analyte concentration in the micr odialysate is decreased. Therefore, a compromise has to be made between flow rate and sample volume. A flow rate of 1.5 L/min and a sampling time of 20 minutes would provide 30 L of sample. A volume of 10 L was directly injected into the HPLC column without previous preparation. Prior to animal studies, diffusion characteri stics of TA through the semi-permeable membrane of the microdialysi s probe were investigated in vitro In the present study two concentration-ranging in vitro microdialysis methods were used, extraction efficiency (EE) and retrodialysi s (RD). Both methods are acceptable to characterize the diffusion process of t he analyte through the MD membrane since the general assumption for the all calibration met hods is that the recovery is the same regardless of whether the so lute exchange occurs through ei ther loss or gain. The mean in vitro recovery of triamcinolone acetonide by the RD and EE methods were 65.5% 5.3% and 66.8% 8.5%, respectively (see Table 3-2 for results). Linear regression analysis was performed usi ng the recoveries from either RD or EE methods versus TA concentration on the perfusate or medium, respectively (Figure 57

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3-2). The mean regression line for the RD and EE methods were y= (-0.056 0.314) x + (65.9 2.15) and y= (-0.800 0.425) x + (71.1 2.75) ( x=TA concentration, y = recovery), respectively. The slope and interc ept between the calibration methods were not significantly different ( =0.05) allowing the conclusion t hat the efficiency of diffusion is quantitatively the same in both directi ons through the membrane and the recovery is independent of the dr ug concentration. Therefore, the retrodialysis method seems adequate to be used as a MD probe cali bration method for TA in the in vivo experiment and a linear recovery (constant value) dur ing the drug concentra tion-time profile determination is to be expected. Our results are in agreement to reports in the literatur e which observed that MD relative recovery is concentration independent [99] Furthermore, in vitro experiments demonstrated t hat no relevant adsorption processes to MD probe membrane or tubing took place. There is not a minimum recovery require ment to perform microdialysis technique. However, percent recoveries inferior to 10% could result in analyte levels in the microdialysate samples to low to be accu rately quantified [10]. As previously demonstrated [59], a relative recovery s uperior to 20% is recommended for more reliable estimation of the unbound drug concentrations. Low relative recovery (<20%) has been reported for moderat e and highly lipophilic drugs such as bethametasone propionate [33], caspofungin [100 ], and variconazole [99] which may be attributed to the low solubility of the compounds in the perfusate solution and/or unspecific binding to the MD probe device. 58

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In general, it is worthwhile to aim at higher recoveries in microdialysis studies and be aware that the recoveries obtained in vitro may overestimate those observed in vivo [71]. The in vitro experiments were done as a preliminary study to an in vivo calibration. In vivo Microdialysis Calibration An accurate measure of recovery requires that the calibration is done in vivo The retrodialysis method was a very simple and convenient method for recovery determination in vivo. The obtained in vivo recovery of TA by retrodialysis will be used next to back-calculate the actual plasma unbound concentrations from IV microdialysate samples (Chapter 5). The average recovery of TA obtained from four different animals for up to 6 hours of sample collection using the retrodialysis method was 59.9 6.1% (range from 44.1% to 70.0%) as shown in Table 3-3. The in vivo RD recovery of TA was in the same range observed on the preliminary in vitro experiments, 65.5 5.3% (58.7-80.8%) and 66.8 8.5% (48.9-80.1%) (mean SD, with range between parenthes es), for the retrodialysis and extraction efficiency met hods, respectively. To confirm the integrit y of the probes used the in vivo calibration and assess the difference in relative recovery by retrodialysis in vitro and in vivo in vitro retrodialysis were conducted after the anima l experiment. Those additional in vitro studies were performed following the same procedures described in the retrodialysis method section of this chapter, but with an increase of the sample collection time for up to 6 hours. The average in vitro retrodialysis recovery of TA for probes 1-4 was 65.5 3.2% (Table 3-4). The average value is greatly comparable to the average in vivo recovery using the same probes, 59.9 6.1%, and to the in vitro recoveries of 65.5 5.3% and 59

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66.8 8.5% obtained by the RD and EE methods, respectively, using a different set of probes. These results also allowed the c onclusion that the probes 1-4 were fully functional and with no loss of integrity after the in vivo calibration studies. Both, the difference in recovery between individual probes and fluctuation within each probe contribute to the variability found in the average recovery value on both in vivo (Tables 3-3) and in vitro (Table 3-4) scenarios. The coefficient of variation within each probe is depicted in the data. Overall, a smaller coe fficient of variation was found for the in vitro recovery than for the recovery of TA determined in vivo by the retrodialysis method. The recoveries over time for all four probes under in vivo and in vitro conditions are illustrated in Figures 3-3 and 3-4. A slightly fluctuation in recovery over 180 minutes sample collection was observed both in vivo and in vitro (Figure 3-3); whereas a moderate fluctuation was observed under longer time frame (Figure 3-4). The largest fluctuation in vivo was displayed during the 360 minutes sampling using probe 3 in the present experiment. To evaluate the depend ence of recovery on time, the mean recovery value by retrodialysis obtained in t he first half of microdialysis collection time (0-180min) was compared to the mean valu e obtained in the second half of the experiment (200-360 min) under in vivo and in vitro conditions. For both probes 3 and 4, the in vitro recoveries determined within the first ti me frame of the ex periment were not statistically different ( =0.05) to those obtai ned later; whereas, the in vivo recoveries obtained in the second half of the experimen t were significantly lower than the ones determined in the first half. The results are ill ustrated in Figure 3-5. Within six hours, the 60

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recovery in blood gradually decreased by 17% for probe 3. A similar phenomenon has been observed by other investigators [58,60,71,101,102]. Based in our current results of the comparison of in vivo and in vivo recoveries over time, we may infer that changes in probe clearance over time are likely related to the probe microenvironment rather than to the loss of probe in tegrity. The reduction in probe membrane clearance may be attributed to fiber clotting, plasma protein and/or cell deposition on the surface on the membrane. In addition, the convective blood flow around the probe implanted in the jugular vein may be small and variable, thus alterations in blood flow due to local vasoconstriction or long last narcosis results in fluctuations and decline in the probe recovery [57]. Some authors also found that the magnitude of the reduction in recovery is dependent on the particular tissue. For example, Sjoberg et al observed a gradual decrease in recovery over five hours of microdialysis sample collection in the blood but not in brain [102]. Acknowledgement of a possible time-dependent recovery is suggested for an adequate evaluation of the accuracy of the intravenous microdialysis technique. In conclusion, this study demonstrated that TA has the ability to freely cross the microdialysis membrane with percent recoveries well over 10%. In our current study, the in vitro recoveries of TA were independent of drug concentrations and direction across the membrane. The in vivo recovery of TA by retrodial ysis was in the same range that the one obtained in in vitro conditions; however a time-dependency of in vivo recovery was observed. The experimental results indi cated that triamcinolone acetonide is a suitable drug to be evaluated by microdialys is, despite its moderate lipophilicity. 61

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Figure 3-1. Schematic figure of a flexible microdialysis probe of concentric design. The magnified membrane region illustrates the diffusion of an analyte of interest from the perfusate () into the medium during retr odialysis (white arrow) or the diffusion of the analyte from the sampling solution () into the probe and taken with the perfusate during extracti on efficiency (dark arrow) methods of probe calibration (Source: http://en.wikipedia.org/ wiki/File:Schematic_ illustration_of_a_mic rodialysis_probe.png accessed May 15, 2011). 62

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Figure 3-2. Dependence of relative recovery on concentration of TA in perfusate or medium during retrodialysis or extraction efficiency methods. Flow rate of 1.5 L/min. Linear regression lines: yRD= -0.056x + 65.9 and yEE= -0.800 x + 71.1.Three replicates for 3 di fferent probes are shown. 63

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Figure 3-3. The in vivo and in vitro probe recoveries of TA for probes 1 and 2 by retrodialysis over time. Figure 3-4. The in vivo and in vitro probe recoveries of TA for probes 3 and 4 by retrodialysis over time. 64

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Figure 3-5. Dependence of the in vivo and in vitro recoveries of TA on time (1st half= 0180 min and 2nd half= 181-360 min) for the microdialysis probes 3 and 4 using the retrodialysis method. Means SD of 9 determinations are shown. *P<0.05; ***P<0.001. 65

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Table 3-1. Intra-day and inter-day accu racy (%RE) and precision (%CV) of observed TA concentrations in microdialysate quality controls during the three dayvalidation Cnom Validation day Mean Cobs SD %RE %CV Intra-day (n=6) 0.096 0.005 -4.28 6.09 0.1 Inter-day (n=18) 0.096 0.008 -4.33 8.85 Intra-day (n=6) 0.271 0.008 8.71 2.90 0.25 Inter-day (n=18) 0.278 0.010 11.51 3.49 Intra-day (n=6) 1.01 0.06 0.97 5.84 1 Inter-day (n=18) 1.00 0.05 0.78 4.90 Intra-day (n=6) 4.95 0.13 -1.05 2.53 5 Inter-day (n=18) 4.97 0.18 -0.58 3.66 Cnom= Nominal concentration ( g/mL) and Cobs= Observed concentration ( g/mL) 66

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Table 3-2. Comparison of the in vitro microdialysis recoveries (%R) of TA by the retrodialysis and extraction efficiency methods Retrodialysis Extraction Efficiency Cnom ( g/mL) Mean %R SD %CV Range Mean %R SD %CV Range 1 63.8 3.7 5.75 59.067.1 74.3 5.8 7.76 62.980.1 5 68.1 7.2 10.5 58.780.8 59.8 5.1 8.47 48.967.1 10 64.3 3.2 5.06 59.569.7 66.3 7.7 11.5 54.976.2 Overall 65.5 5.3 8.14 58.780.8 66.8 8.5 12.8 48.980.1 Cnom=Nominal concentration 67

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68 Table 3-3. In vivo microdialysis recovery (%R) of TA by the retrodialysis method In vivo Retrodialysis of TA Probe n Mean %R SD %CV Range [Min-Max] 1 9 62.3 2.3 3.75 58.2 65.3 2 9 64.0 5.1 8.01 53.1 69.9 3 17 50.8 5.5 10.8 44.1 60.5 4 17 62.4 3.3 5.24 70.0 56.4 Overall 59.9 6.1 10.2 44.1 70.0 Table 3-4. In vitro microdialysis recovery (%R) of TA by the retrodialysis method In vitro Retrodialysis of TA Probe n Mean %R SD %CV Range [Min-Max] 1 12 65.0 4.2 6.50 57.0 72.6 2 12 70.8 5.1 7.21 66.3 81.4 3 18 62.6 4.1 6.59 57.5 72.4 4 18 63.6 3.6 5.68 57.9 67.0 Overall 65.5 3.2 4.88 55.5 81.4

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CHAPTER 4 INVESTIGATION OF BUDESONIDE AS A MICRODIALYSIS CALIBRATOR Background The shortcoming of retrodialysis for probe calibration is that variations of the recovery during the experiment are not mo nitored. Changes in the probe membrane and/or its microenvironment may occur during the study resulting in reduction of probe efficiency with time. In fact, several intravenous MD preclinical studies reported reduction of probe efficiency with time [58,60,71,101,102]. Possible causes are alterations in blood flow due to local vaso constriction and/or mech anical disturbances which can reduce membrane permeability like molecules and/or cell deposition on the surface of the membrane [60,71]. This drawback can be overcome by using a continuous internal recovery control as firs t introduced for brain microdialysis [32] and further applied in blood micr odialysis studies [16,59,103]. The microdialysis calibration standard is added to the perfusate during the experimental period and it is assumed that the relative reco very by loss of the calibrator into the investigated media is representative for the recovery by gain of the analyte from the media during the experiment [26]. An illustration of the retrodialysis by calibrator process is presented in Figure 4-1. The ideal retrodialysis calibrator in microdi alysis is the compound of interest itself. However, individual recovery estimates cannot be made with the drug of interest present in the perfusion solution when that drug is also administered systemically. A radiolabeled or deuterated analog of the drug may be a suitable choice for calibrator; however its availability is limited and require s also a more refined analytical detector such as mass spectrometer. Therefore, a compound similar to the drug of interest in 69

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terms of its molecular size, degree of i onization and lipophilicity may serve as a calibrator [32,59]. To improve the accuracy of the estimated TA concentrations, we proposed to use the retrodialysis by calibrator method to m onitor the recovery continuously and to correct for changes in TA recovery during the experimental period. Budesonide, a corticosteroid with physicoch emical properties (MW 430.54 g/mol, Log Po:w of 2.9, neutral at pH 7.4, protein binding 92% in rat) similar to our investigated compound TA (MW 434.50 g/mol, Log Po:w of 2.5, neutral at pH 7. 4, protein binding 90% in rat) (Chemspider database, Royal Societ y of Chemistry, Cambridge, UK) was then chosen as a calibrator. Specific Aim The aim of this study was to verify the use of budesonide as a microdialysis calibrator for triamcinolone acetonide. The mi crodialysis probe recovery of budesonide was estimated in vitro as well as in vivo and correlated to TA. Materials Chemicals and Reagents 0.9% Sodium Chloride Inj. USP Baxter Health Care (Deerfield, IL, USA) 1000 UI/mL Heparin Elkins-S inn, Inc. (Cherry Hill, NJ, USA) Budesonide Sigma (St. Louis, MO, USA) HPLC grade methanol Fischer Scientific (Fair Lawn, NJ, USA) Isoflurane USP Webster Veterinary (Charlotte, NC, USA) Lactated Ringers Injection USP Baxter Health Care (Deerfield, IL, USA) Triamcinolone acetonide Sigma (St. Louis, MO, USA) Equipment and Disposables Balance Mettler AE240, Toledo (Hightstown, NJ, USA) Cellulose membrane filter 0.22 m pore size, Millex GV Millipore (Carrigtwohill, Co. Co Cork, Ireland) 70

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FEP tubing ID 0.12mm, CMA Microdialysis (Stockholm, Sweden) Heated stir plate Fisherbrand Isotemp IV catheters Monoject Angel Wing Butterfly, Becton Dickinson (Franklin Lakes,NJ, USA) Microdialysis probe CMA/20 Elit e, 14/10 PAES, cut-off 20kDa; membrane length 10 mm; CMA Microdialysis (Stockholm, Sweden) Microfraction collector CMA/ 142, CMA Microdialysis (Stockholm, Sweden) Precision infusion pump Harvard Apparatus Model 22, (South Natick, Mass., USA) Small animals surgery tools Surgical Grade Stainless Steel, various suppliers Syringes Becton Dickinson 5 mL (Franklin Lakes,NJ, USA) Thermometer Fisherbrand 76mm Immersion 14-997 Tubing adapter CMA Micr odialysis (Stockholm, Sweden) Vortex Kraft Apparatus Inc., model PV-5, Fisher Scientific Animals Adult male Sprague-Dawley rats, weighti ng 250-300 grams, were purchased from Harlan Sprague-Dawley Inc. (I ndianapolis, IN, USA). Animals were acclimatized to standard ACS housing in a 12-h light-dark cycl e and constant temperature environment for a minimum of three days before being used. Animals had free access to food and water. The animal experimental procedures were approved by the In stitutional Animal Care and Use Committee of University of Florida. 71

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Methods Preparation of Calibration Solutions for Microdialysis Stock solutions of 1 mg/mL of TA and budesonide in methanol were prepared. From the stock solutions, 100 g/mL solutions of each analyte were obtained by dilution in lactated Ringers solution. Further dilu tions in lactated Ringers solution were performed to obtain the calibration solutions of TA in the concentrations of 1, 5 and 10 g/mL and budesonide, 10 g/mL. A lactated Ringers soluti on containing both TA (5 g/mL) and budesonide (10 g/mL) was also prepared. In vitro Microdialysis Apparatus setup During setup, a 5 mL syringe was filled wi th perfusate (analyte solution) and the enclosed air was cleared from the syringe. The syringe wa s placed on the precision pump, connected to the inlet of the probe and run at a flow rate of 1.5 L/min for 30 minutes to allow for equilibration. The microdialysis probe was immersed in a 10mL centrifuge tube containing approx imately 8 mL of either bl ank lactated Ringers solution or analyte solution, depending on the experimental design. The sampling solution was stirred at 300 rpm to guarantee equal conc entrations throughout the whole tube and temperature was controlled at 37 1C on a heated plate. The microdialysate samples were collected with the aid of an aut omated microfraction collector. Extraction efficiency of TA and retrodialysis of budesonide at a c onstant flow rate The in vitro microdialysis probe recovery of budesonide was determined by retrodialysis (RD), while triamcinolone acet onide recovery was estimated by the extraction efficient (EE) method of probe calibration in a dose-range fashion. The 72

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scenario of recovery by loss of calibrator and by gain of drug emulat es the condition of the main IV microdialysis study (Chapter 5). MD probe was perfused with budesonide solution (10 g/mL) at a constant flow rate of 1.5 L/min and placed into the sampling t ube containing TA solution, starting with the lowest concentration (1 g/mL). TA diffused from t he sampling solution into the MD probe and was taken with the perfusion fl ow. Budesonide diffused out of the probe into the solution. The gain of TA and the loss of budesonide through the membrane were then determined from the respective concentrations of each analyte in the microdialysate samples (CTA dialysate and Cbud dialysate). Three microdialysate samples were collected with 20 minutes intervals after the end of a 30 minutes equilibration period. To determine the actual TA and budesonide concentrations in the sampling (CTA sampling sol) and perfusion (Cbud perfusate) solutions respectively, two samples of the each solution were taken, one before the sampling period and one after. The same procedure was done for the remaining two sampli ng solutions of TA, 5 and 10 g/mL. The concentrations of the analytes in the samp les were determined by a validated HPLC method. The experiments were performed us ing two different microdialysis probes. The percent recovery (%R) for each analyte was calculated as follows: %RTA = C TA dialysate x 100 CTA sampling sol %RBudesonide = ( C bud perfusate C bud dialysate ) x 100 Cbud perfusate Extraction efficiency of TA and retrodialysis of budesonide at diff erent flow rates The MD probe was placed into the samp ling tube containing TA solution (10 g/mL). Then, the probe was per fused with budesonide solution (10 g/mL) at each of 4 flow rates (1.5, 2, 2.5 and 3 L/min). The gain of TA and the loss of budesonide through 73

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the membrane were then determined from the respective concentrations of each analyte in the microdialysate samples (CTA dialysate and Cbud dialysate). Time was allowed for system equilibration when the flow rate was changed. At each flow rate, three microdialysate samples of 30 L volume were collected using different sampling intervals (20, 15, 12 or 10 minutes for t he respective ascending flow rates). To determine the actual TA and budesonide concentrations in the sampling (CTA sampling sol) and perfusion (Cbud perfusate) solutions respectively, two samples of the each solution were taken, one before the sampling period and one after. The lowest flow rate, 1.5 L/min, was evaluated first followed by t he others with the exch ange of sampling tube with fresh TA solution. The concentrations of the analytes in the samples were determined by a validated HPLC method. T he experiments were performed using two different microdialysis probes. The percent re covery (%R) for each analyte at each flow rate was calculated as follows: %RTA = C TA dialysate x 100 Csampling sol %Rbudesonide = ( C perfusate C bud dialysate ) x 100 Cperfusate In vitro retrodialysis of TA and budesonide The MD probe was perfused with a solution of TA (5 g/mL) and budesonide (10 g/mL) in lactated Ringers at a constant flow rate of 1.5 L/min. The probe was placed into a tube filled with blank lactated Ringers solution. Both analytes diffused out of the probe into the blank solution. The loss of the each analyte through the membrane was then determined from the Cdialysate. After the end of a 30 minut es equilibration period, microdialysate samples were collected with 20 minutes intervals during 3-6 hours. The actual concentration of the TA and budeson ide in the perfusion solution were 74

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determined by sampling the perfusate before and after the sampling period (CTA perfusate and Cbud perfusate). Experiments were performed using four different probes. The percent recovery (%R) for each analyte was calculated as follows: %RTA= ( C TA perfusate C TA dialysate ) x 100 CTA perfusate %Rbudesonide= ( C bud perfusate C bud dialysate ) x 100 Cbud perfusate Where %R is the percent recovery, Cperfusate is the average analyte concentration in the perfusate before and after the experiment, and Cdialysate is the analyte concentration in the microdialysate sample. In vivo Microdialysis Calibration In vivo retrodialysis of TA and budesonide In vivo calibration was performed accordi ng to the procedure described in the section in vivo Microdialysis of Chapter 3. Briefly, the animals (n=5) were anesthetized with isoflurane and placed in a heating pad in the dorsal position. A microdialysis probe was placed into the right jugular vein with the aid of a needle and guide cannula. The probe was perfused with 10 UI heparin soluti on in Ringers at 8 L/min for 5 minutes. After 5 minutes, the perfusate was c hanged to the calibration solution of triamcinolone acetonide (5 g/mL) and budesonide (10 g/mL) in lactated Ringers. The flow rate was reduced to 1.5 L/min. Fo llowing 1 hour equilibration, microdialysate samples were collected by the microfracti on collector at 20 minutes intervals for 1-6 hours. At the beginnin g and end of the experiment, TA and budesonide concentration in the perfusate (Cperfusate) were determined by a validat ed HPLC method. The percent recovery (%R) for each analyte was calculated according to the equations: 75

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%RTA = ( C TA perfusate C TA dialysate ) x 100 CTA perfusate %Rbudesonide = ( C Bud perfusate C Bud dialysate ) x 100 CBud perfusate Where %R is the percent recovery, Cperfusate is the average analyte concentration in the perfusate before and after the experiment, and Cdialysate is the analyte concentration in the microdialysate sample. Sample Analysis TA and budesonide concentration in mi crodialysate samples and calibration solutions in lactated Ringers solution were determined using the HPLC method described in Chapter 2. Data Analysis Linear regression and statistical analyses were performed using GraphPad Prism version 4.00 for Windows (GraphPad So ftware, San Diego, CA, USA). Group comparisons were made using analysis of va riance. The significance level was set at 0.05. Results and Discussion In the present study the relative recove ry of TA and budesonide and its correlation were estimated in a series of in vitro and in vivo microdialysis studies. In the first set of in vitro experiments, the in vitro relative recovery of TA was determined by the extraction efficient method (EE) while budesonide by the retrodialysis (RD) to mimic the proposed in vivo condition of the main study. The mean (percent of coefficient of variation) recovery of TA determined by EE was 66.3 (CV= 10.2%) while the average recovery of budesonide by retrodialysis was 77.4 (CV= 7.3%). The calculated ratio of TA:budesonide recovery is 0.86 (CV= 9. 3%) (Table 4-1). Although both recoveries 76

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differed significantly (P < 0.05), this, how ever, is not a hinder to the practical implementation of the proposed microdialys is calibration seeing that a steady correlation between the recovery of drug and ca librator is observed. This assumption is based on the recommendations for applicat ion of endogenous compounds (e.g. urea) as microdialysis calibrators [104,105]. Further analysis and experiments were perfo rmed to verify the stability of the recovery ratio of TA:budesonide (RR TA:bud). Dependence of the RR TA:bud on the drug concentration is displayed in Figure 4-2. Linear regression analysis of in vitro RR TA:bud versus TA concentration in the surrounding medium yielded a regression line with a slope of -0.0018 ( 0.0082) and an intercept of 0.8495 ( 0.0534) .The slope did not differ significantly from zero (95% CI: -0.1029 to 0.1064, =0.05) allowing the conclusion that the recovery ratio is concentration independent over the range investigated. Concentration independence in pilot in vitro studies would indicate that the calibrator would correct the recovery of TA from the extracellular space in vivo in a linear fashion with a constant factor. To investigate the stabil ity of the correlation of the recoveries of TA and budesonide under influential factor s that affect recovery, in vitro recoveries of both analytes were determined under different flow ra tes. Relative recoveries by gain (by EE method) and by loss (by RD method) are influenced by the perfusion fluid flow rate used with the inverse effect of fl ow rate on the relative reco veries, for both hydrophilic and lipophilic drugs [7,26,106]. Figure 4-3 A illust rates the relationship between recovery and flow rate. As flow rates were increased from 1.5 to 3 L/min, the relative recovery by loss of calibrator budesonide reduced from approximately 78% to 53%. Likewise, the 77

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recovery by gain of TA were decreased fr om around 66% to 41% over the ascending flow rate range (Table 4-2). A linear r egression analysis was conducted (natural logarithm transformation of the recovery va lues versus flow ra te) to verify the assumption of constant ratio under a reco very changing factor (Figure 4-3 B). Mean regression function of TA was y= (0.3323 0.0645) x (0.0420 0.1496), r2 =0.9299 (x= flow rate, y= TA recovery), while mean regression function of budesonide was y= (0.2645 0.0320) x (0.1342 0.0743), r2 =0.9715 (x= flow ra te, y= budesonide recovery). The slopes were not significantly different ( =0.05) suggesting that the recovery of both compounds are affected in the same magnitude, hence the correlation of TA and budesonide recoveries (i.e. RRTA:bud) would remain constant under circumstances that would affect the re covery of both TA and budesonide. In the third set of in vitro experiments, the microdialysis probe recovery of budesonide and TA were determined by the re trodialysis method under constant flow rate (1.5 L/min) for up to 6 hours to verify the steadiness of the RRTA:bud over time. The mean ( standard deviation) relative recovery of TA was 65.5 3.2%, while the average recovery of budesonide was 78.6 3.4% with a mean calculated RRTA:bud of 0.83 .03. Results of four different probes are listed at Table 4-3. The recovery ratios of TA:budesonide obtained under recovery by loss of TA or recovery by gain of TA were not significantly different ( =0.05; RRTA:bud of 0.83 vs 0.86, respectively). Hence, the steadiness of correlation of the relative recoveries of TA and budesonide in in vitro settings was demonstrated. It is recommended [107,108] that by proper calibration, in traindividual coefficients of variation for microdialysis measurem ents should range around 20%. Mean ratio of 78

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recovery TA to budesonide 20% was defined as quality criterion fo r the interindividual and intraindividual precision of the retrodialysis by calibrator technique. Practicability of budesonide as a microdialysis calibrator could be assumed if 90% of all determined ratios were within this interval as prev ious suggested [108]. Figure 4-4 displays the individual recovery ratios of TA to budesoni de for four different probes obtained by in vitro retrodialysis for up to 6 hours. The correl ation of TA to budesonide recovery was satisfactorily constant over time with all intraand inter-probe RRTA:bud well within 20% interval defined as quality criterion. The coeffi cient of variation of the recovery ratio of TA to budesonide within probes and ov erall are presented in Table 4-3. As it is often the case, MD pr obe relative recovery determined in in vitro medium may not be a good surrogate for the in vivo recovery due to the complexity of the in vivo sampling matrix [32]. Thus, t he recoveries of the analyte and the calibrator, and their correlation (Recovery Ratio analyte:calib rator), were subsequently determined in rodents. For five animals, the mean retrodia lysis recoveries of TA and the calibrator budesonide were 59.0% (CV= 9.5%) and 84.9% (CV= 5.4%), respectively, with a mean in vivo ratio of recovery of TA to budesonide (RRTA:bud) of 0.70. The overall RRTA:bud variability of five different probes was 9.0% (T able 4-4). Additionally, all intraindividual and interindividual RRTA:bud fell within the 20% precision interval, defined as quality criterion of recovery ratio. The individual recovery ratios of five probes over 1 to 6 hours dialysate collection are presented in Figure 4-5. The intraindividual RRTAbud was fairly constant over time converse to the relative recovery of TA, as previous observed in our current investigation. 79

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To improve the accuracy in the estimated concentrations by microdialysis, a recovery of the calibrator of 20% or higher is preferable for more reliable estimation [59]. In the current study, the in vivo recovery of the proposed calibrator, budesonide, far exceeded the 20% recovery threshold (overall retrodialysis recovery of 85% with CV of 5.4%). In summary, we here presented a valuable c haracterization of the retrodialysis by calibrator technique under in vitro and in vivo conditions. Together, the data suggested that budesonide may be considered an appropria te calibrator for TA. Although the estimated recovery of the calibrator and t he recovery of the test drug, TA, are significantly different in both in vitro and in vivo conditions, the average ratio of the recoveries were fairly constant under di verse tested scenarios, including over time in vivo In the subsequent experimental evaluation of the IV MD technique (Chapter 5), the in vivo probe recovery was monito red continuously using the retrodialysis by calibrator method. 80

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Figure 4-1. Schematic illustration of a flexib le microdialysis probe of concentric design. The magnified membrane region illustrat es net diffusion of an analyte of interest () into the probe (white arrow), and the diffusion of the calibrator () which has been added to the perfusate, from the probe to the sampling site (dark arrow). (Source: http://en.wikipedia.org/wiki/Fi le:Schematic_illustration_ of_a_microdialysis_probe.png accessed May 15, 2011). 81

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Figure 4-2. Dependence of relative recovery ratio TA to budesonide on concentration of TA in medium under cons tant flow rate (1.5 L/min). Linear regression line: y = -0.0018x + 0.8495 (95% CI slope: -0.103 to 0.106). Means SD of 6 determinations of two probes are shown. 82

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A B Figure 4-3. The effect of fl ow rate on recovery by gain of TA and by loss of budesonide during extraction efficient (EE) and retrodialysis (RD) calibration in vitro respectively. A) Dependence of relative reco very on flow rate of perfusate. B) Linear relationship between the logarithm ic transformation of recovery and flow rate. Linear regression lines: yTA= 0.3323 x 0.0420 and ybudesonide= 0.2645 x -0.1342. Means SD of 6 determinations of two probes are shown. 83

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Figure 4-4. Individual recovery ratios of TA to budesonide for four probes obtained by in vitro retrodialysis over time. Line: Mean RRTA:bud =0.83; dotted lines: mean ratio 20%. Figure 4-5. Individual recovery ratios of TA to budesonide for five probes obtained by in vivo retrodialysis over time. Line: Mean RRTA:bud =0.70; dotted lines: mean ratio 20%. 84

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Table 4-1. Comparison of the in vitro recovery of TA versus budesonide at a constant flow rate (1.5 L/min) Extraction efficiency of TA Retrodialysis of budesonide Recovery Ratio TA:budesonide TA Cnom ( g/mL) Mean Recovery (%) SD %CV Mean Recovery (%) SD %CV Mean SD %CV 1 70.6 4.9 6.94 81.1 4.4 5.43 0.88 0.07 11.5 5 61.6 6.3 10.2 75.6 7.3 9.66 0.82 0.05 6.10 10 66.8 6.5 9.73 75.4 3.0 3.98 0.87 0.10 11.5 Overall 66.3 6.8 10.2 77.4 5.6 7.24 0.86 0.08 9.30 Cnom= Nominal concentration Mean values: n=6 at each concentration using two different probes Table 4-2. Comparison of the in vitro recovery of TA versus bude sonide at different flow rates Extraction efficiency of TA Retrodialysis of budesonide Recovery Ratio TA:budesonide Flow Rate ( L/min) Mean Recovery (%) SD %CV Mean Recovery (%) SD %CV Mean SD %CV 1.5 65.7 2.5 3.77 77.8 1. 4 1.77 0.84 0.04 4.88 2 53.1 5.4 10.2 67.7 1.5 2.16 0.78 0.07 8.29 2.5 42.2 2.5 5.84 56.6 1. 1 2.00 0.74 0.04 5.12 3 40.8 3.5 8.52 53.2 4.2 7.93 0.77 0.09 12.7 Overall 0.80 0.07 9.06 Mean values: n=6 recovery determinations at each flow rate using two different probes 85

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Table 4-3. Comparison of in vitro recovery of TA versus budesonide by retrodialysis Retrodialysis of TA Retrodialysis of budesonide Recovery Ratio TA:budesonide Probe Mean Recovery (%) SD % CV Mean Recovery (%) SD %CV Mean SD %CV 1 (n=12) 65.0 4.2 6.46 81.5 5.4 6.63 0.80 0.03 3.75 2 (n=12) 70.8 5.1 7.20 81.4 5.2 6.39 0.87 0.02 2.30 3 (n=18) 62.6 4.1 6.54 74.8 4.5 6.01 0.84 0.03 3.57 4 (n=18) 63.6 3.6 5.66 76.6 5.0 6.53 0.83 0.03 3.61 Overall 65.5 3.2 4.89 78.6 3.4 4.33 0.83 0.03 3.61 n= microdialysate fractions collected for recovery determinations. Table 4-4. Comparison of in vivo recovery of TA versus budesonide by retrodialysis Retrodialysis of TA Retrodialysis of budesonide Recovery Ratio TA:budesonide Probe Mean Recovery (%) SD %CV Mean Recovery (%) SD %CV Mean SD %CV 1 (n=9) 62.3 2.3 3.69 89.7 2.0 2.23 0.69 0.02 2.90 2 (n=9) 64.0 5.1 7.97 87.0 4.1 4.71 0.73 0.03 4.11 3 (n=18) 50.8 5.5 10.8 79. 9 8.0 10.0 0.64 0.02 3.13 4 (n=18) 62.4 3.3 5.29 80.1 5.6 6.99 0.78 0.03 3.85 5 (n=3) 55.8 1.4 2.51 87.6 3.0 3.42 0.64 0.01 1.56 Overall 59.0 5.6 9.49 84.9 4.6 5.41 0.70 0.06 8.57 n= microdialysate fractions collected for recovery determinations. 86

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CHAPTER 5 INTRAVENOUS MICRODIALYSIS STUDY OF TA Background When compared to traditional blood sampling methods, IV MD provides a powerful tool to continuously monitor the extracellular free drug concentration in the blood. The advantageous no net-fluid loss of the IV MD technique result s in rich data collection while sparing the animals. In addition, it does not alter the drugs PK due to physiological changes that result from blood sampling [6]. Several reports have been published describing the successful applicati on of IV MD sampling in rodents and man and at the same time addressing the current limitations of the technique, such as a possible time-dependent change in recovery [58,71]. While most IV MD studies used hydrophilic and low-protein bind ing drugs, in this work we aim to evaluate the application of the technique for a moderately lipophilic and high-protein binding compound. The present intravenous microdialysis st udy will be conducted to measure the protein-unbound TA concentrations in the blood, following continuous intravenous drug infusion in rats. The free drug levels will be compared to total plasma concentrations obtained by traditional blood sampling. To acc ount for changes in the relative recovery, continuous use of retrodialysis by the calibrator budesonide was introduced. Since microdialysis samples the unbound fraction, the extent of binding of the drug to plasma proteins must be known to compare the microdi alysis results to those from blood. The extent of binding of TA to rat plasma pr oteins will be determined by the gold-standard method, ultrafiltration. 87

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Specific Aim The aim of this study is to evaluate the accuracy of the IV MD sampling technique on the estimation of unbound triamcinolone acetonide levels compared to the total concentrations, corrected for protein binding, obtained by conventional sampling. The performance of two calibration methods, retrodial ysis by drug or by calibrator was also assessed. Materials Chemicals and Reagents 0.9% Sodium chloride inj. USP Baxt er Health Care (Deerfield, IL, USA) 1000 UI/mL Heparin Elkins-S inn, Inc. (Cherry Hill, NJ, USA) Blank male rat plasma Lampire Bi ological Lab. (Pipersville, PA, USA) Budesonide Sigma (St. Louis, MO, USA) HPLC grade methanol Fischer Scientific (Fair Lawn, NJ, USA) Isoflurane USP Webster Veterinary (Charlotte, NC, USA) Lactated Ringers injection USP Baxter (Deerfield, IL, USA) Triamcinolone acetonide Purity 99%, Sigma (St. Louis, MO, USA) Volon A soluble injection Tria mcinolone acetonide dihydrogenphosphate dipotassium salt, Dermapharm, Germany) Equipment and Disposables Balance Mettler AE240, Toledo (Hightstown, NJ, USA) Cellulose membrane filter 0.22 m pore size, Millex GV Millipore (Carrigtwohill, Co. Co Cork, Ireland) Centrifugal filter device Ult rafree-MC, 30,000 NMWL, Millipore Amicon (Bedford, MA, USA) Centrifuge Fisher Scient ific model Marathon 16KM (Pittsburgh, PA, USA) 88

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FEP tubing ID 0.12 mm, CM A Microdialysis (Stockholm, Sweden) IV catheters Monoject Angel Wing Butterfly, Becton Dickinson (Franklin Lakes,NJ, USA) Microdialysis probe CMA/20 Elite, 14/10 PAES, cut-off 20kDa; membrane length 10 mm; CMA Microdialysis (Stockholm, Sweden) Microfraction collector CMA/ 142, CMA Microdialysis (Stockholm, Sweden) Precision infusion pump Harvard Apparatus Model 22, (South Natick, Mass., USA) Small animals surgery tools Surg ical grade stainless steel, various suppliers Syringes Becton Dickinson 1, 5 and 10 mL (Franklin Lakes,NJ, USA) Thermometer Fisherbrand 76 mm Immersion 14-997 Tubing adapter CMA Micr odialysis (Stockholm, Sweden) Ultrasonic bath Fisher Scientific model FS110H (Pittsburgh, PA, USA) Vortex Kraft Apparatus Inc., model PV-5, Fisher Scientific Animals Adult male Sprague-Dawley rats, weighti ng 250-300 grams, were purchased from Harlan Sprague-Dawley Inc. (Indianapolis, IN, USA). Animals were housed to 12-h lightdark cycle and at constant temp erature for a minimum of th ree days before being used with free access to food and water. In the ex periment, the rats were weighted before the surgical procedure for dose adjustment based on weight. The animals were numbered in the sequence of the experim ents without identifying device s (non-survival surgical 89

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experiment). The experimental procedures were approved by the Institutional Animal Care and Use Committee of University of Florida. Methods Ultrafiltration Preparation of stock a nd working solutions Primary stock solutions of TA (1 mg/mL) and flut icasone propionate (plasma internal standard, IS) (1 mg /mL) were prepared in meth anol. Each stock solution was further diluted in methanol to get intermediate concentrations of 100 g/mL for TA and 75 g/mL for IS. Working solutions of TA (1.5150 g/mL) required for spiking plasma and lactated Ringers solution were subsequently diluted in methanol from primary and intermediate stock solutions. All methanolic solutions were stored at -20 C, protected from the light, until use. Preparation of samples Pooled blank rat plasma was spiked with TA standard solutions of different concentrations to obtain total concentrations of 2.5, 5 and 10 g/mL to cover the expected concentration range in the in vivo experiments. The same concentrations were also prepared in la ctated Ringers solution. Blank plasma ultrafiltrate was obtained by centrifugation of pooled blank rat plasma in ultrafiltration units at 4000 rp m for 15 min. The procedure was performed with multiple samples to generate enough matrix volume. The calibration standards and quality controls were prepared in ultrafilt rate, lactated Ringers solution and plasma, respectively. Calibration curves were constructed over the appropriate analytical range for each matrix. 90

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Sample processing A 0.6 mL sample volume at each concentration was incubated at 37C for 30 minutes to allow for equilibration. A 140 L al iquot of plasma was then taken to assess total TA concentration (Cplasma total). The remaining volume was transferred to an ultrafiltration device and c entrifuged at 4000 rpm for 2 mi nutes. Less than 10% of the total volume was filtered to prevent dist urbance of the protein binding equilibrium. Experiments were performed in triplicate for each concentration. Samples of TA in lactated Ringers solution, at the concentrations of 2.5, 5 and 10 g/mL were submitted to the steps described above to assess the binding of the analyte to the membrane of the ultrafiltration device. Sample analysis The ultrafiltrate samples and plasma sa mples after 30 minutes incubation were analyzed by the HPLC method described in Chapter 2. The concentrations of ultrafiltrate samples (Cultrafiltrate) represent the unbound concentrations of TA in plasma. The concentrations of plasma samples r epresent the total plasma concentrations (Cplasma total). The concentrations in the ultrafiltrate from lactated Ringers solution were compared to the concentrations on the init ial solutions and expressed in terms of percent recovery. The calibration standards and quality contro ls were prepared in ultrafiltrate, lactated Ringers solution and plasma, respecti vely. All samples were analyzed by the HPLC method described in Chapter 2. Briefly, the plasma samples were pre-treated by solid-phase extraction before injection and the ul trafiltrate samples were directly injected into the analytical column of the HPLC system for analysis. 91

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Data analysis As the total drug concentration equals t he sum of the concentrations bound and unbound, the unbound fraction ( fu) of TA in rat plasma is calculated as: fu = C ultrafiltrate Cplasma total In vivo Microdialysis Recovery Microdialysis probe recovery in vivo was estimated in each animal by retrodialysis during all experimental procedur e, utilizing budesonide as a retrodialysis calibrator. In vivo calibration was performed according to the procedure described in details in the section in vivo Microdialysis of Chapter 3. Briefly, the animals (n=5) were anesthetized with the inhalation anesthetic isoflurane and placed in a heating pad in the dorsal position. A microdialysis probe was placed into the right jugular vein with the aid of a needle and guide cannula. The probe was perfused with 10 UI heparin solution in Ringers at 8 L/mi n for 5 minutes. After 5 minutes, the perfusate was c hanged to the calibration solution of budesonide (10 g/mL) in lactated Ringers. T he flow rate was reduced to 1.5 L/min. Blanks were collected for at least 1 hour following insertion of the probe. After equilibration, microdialysate samples were co llected using a microfraction collector at 20 minutes intervals for the whole experim ental period (3 hours). At the beginning and end of the experiment, budesonide c oncentration in the perfusate (Cperfusate) was determined by a validated HPLC method. T he percent relative recovery (%R) of budesonide for each dialysate fraction (Cbud dialysate i) was calculated as follows: %Rbudesonide i = ( C bud perfusate C bud dialysate i ) x 100 Cbud perfusate 92

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where %R budesonide is budeson ide probe recovery for the i th collection determined by retrodialysis, Cbud perfusate is the average budesonide conc entration in the perfusate before and after the experiment, and Cbud dialysate is budesonide concentration in the dialysate for the i th collection. Intravenous Microdialysis of TA One hour following the surg ical implantation of the microdialysis probe in the animals right jugular vein and equilibration of the calibrator recovery, the phosphate salt of TA was administered as an intravenous bolus of 5 mg/kg followed by a 2.3 mg/kg/h continuous infusion at a rate of 1 mL/h via an i.v. catheter placed in the caudal ventral artery. The loading bolus dose (D) was det ermined by the product of the aimed total plasma concentration at steady-state (Css= 3 mg/L) and the volume of distribution of TA in rats after i.v. administration (V= 1.67 L/kg) as previously reported [109] D= Css x V The continuous infusion rate (R0) was calculated based on reported total body clearance after i.v. admini stration in rats (CLiv) of 0.7 L/h/kg [109] as follows: R0= Css x CLiv Intravenous microdialysis sampling wa s carried out for 3 hours after drug administration. Microdialysate samples (Cdialysate) were continuously collected every 20 minutes with the aid of an autom ated microfraction collector. Samples were stored at 4 C and analyzed within 24 hours. Venous blood samples were drawn at baseline (time zero) and after dose administration at the midpoint of the microdialysis sampling interval with correction for the microdialysis probe and outle t tubing dead volume in order to make dialysis samples and blood samples comparable in time [110]. B lood samples (300 L) were collected in 93

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tubes containing heparin via the lateral c audal veins and centrifuged at 3000 rpm for 8 minutes to separate plasma. Then, plasma sa mples were stored at -70 C until assay. Sample Analysis TA and budesonide concentration in micr odialysate samples and calibration solutions in lactated Ringers solution were determined directly using the HPLC method described in Chapter 2. TA concentration in plasma samples were determined after plasma extraction and HPLC analysis using the methods described in Chapter 2. The concentration-response calibration curve fo r each matrix was obt ained following each experiment. Data Analysis TA total plasma concentration-time profile s were fitted to a bi exponential equation for intravenous data [70,92] by nonlinear regression using the program Scientist (Micromath, Salt Lake City, UT USA). Measured concentrations of TA were fitted to the following equation: Ct = A e(t) + B e (t) where Ct is the total TA plasma concentration, A and B are hybrid constants, and are the first-order rate c onstants of distribution and e limination, respectively. The following pharmacokinetic parameters were then obtained from the best-fit coefficients and exponents: the in tercompartmental rate constants k12 and k21, the elimination rate constant fr om the central compartment (k10), the terminal distribution and elimination half-lives (t and t, respectively), and the volu me of distribution at steady-state (Vdss), using the respective equations: k21 = A + B A + B 94

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k10= x k21 k12 = + k10 k21 t= 0.693 t = 0.693 Vdss= (1 + k 12 ) x D k21 (A+B) The total body clearance of TA (CL) was calculated based on plasma level data: CL= R 0 Css where R0 is the infusion rate and Css is the model predicted steady-state plasma concentration. TA phosphate is almost completely and rapi dly converted into TA [111], therefore this conversion could be neglected in the pharmacokinetic analysis as had been described before [70,92]. The unbound TA concentrations in plasma (Cu) determined by microdialysis were calculated using the microdialysis probe reco very for each collection interval using budesonide retrodialysis and the factor by each in vivo recovery of TA and budesonide are related as follows: Cu = (C TA dialysate j x RR TA:Bud ) x 100 %Rbudesonide i where Cu is the calculated unbound TA concentration, C TA dialysate i is TA concentration in the dialysate for i th collection, %Rbudesonide i is budesonide probe recovery for i th collection by retrodialysis, and RRTA:Bud is the recovery ratio of TA:Bud in vivo. 95

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TA unbound plasma concentrations at st eady-state obtained by IV MD were compared with plasma levels, corrected for protein binding, using a paired t-test. Statistical analyses were performed by GraphPad Prism version 4.00 for Windows (GraphPad Software, San Diego, CA, USA) with the significance level set at 0.05. Unless otherwise stated, all data are expressed as means standard deviation. Results and Discussion Determination of Unbound Fraction of TA by Ultrafiltration The results of protein binding of TA in presence of diffe rent drug concentrations in rat plasma are summarized in Table 5-1. T he overall mean of unbound fraction of TA in rat plasma was 0.104 0.011. The average pl asma protein binding of TA was then calculated to be 89.6 1.1%, which is consist ent with values previously reported of 81% [112] and 90.1% [68]. The estimate values of protein binding remained relatively constant over plasma triamcinolone acetonide concentration range of 2.5-10 g/mL, suggesting linear protein binding. Nonspecific adsorption of TA to the ultrafiltration device was determined by ultrafiltration of TA in lactat ed Ringers solution. The concent rations in the ultrafiltrate samples were compared to the concentration s on the initial solutions tested. The mean recovery was 98.7 3.8% confirming no loss due to nonspecific binding. Our results are in agreement with a previ ous study where TA protein binding in human plasma was independent of the tested concentration range and the drug showed no binding to the ultraf iltration device [69,70]. The mean free fraction value of 0.104 wa s used in subsequent comparisons of microdialysis and rat plasma samples. 96

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In vivo Microdialysis Recovery In the present study, the retrodialysis by calibrator is suggested to determine the unbound concentrations of TA. The in vivo probe recovery is monitored continuously during the time-frame of the experiment by the relative recovery of the calibrator, budesonide. The overall mean b udesonide recovery determined by retrodialysis in rats during the 3-hour IV MD study of TA was 80.0 4.0 (CV= 5.02%). This value was consistent with the one obtained during the validation phase in vivo study (Chapter 4), overall mean recovery of 84.9 4.6 (CV= 5.40%).Table 5-2 lists the individual budesonide recovery of five ra ts treated with TA. In general, the intraand inter-animal precisions of recovery were sa tisfactorily high as all coeffi cient of variation values were less than 10%. The highest variability in recovery was encountered for animal R8, probably as a consequence of the gradual de crease of probe recovery overtime. Budesonide recovery decreas ed from around 87% to 68% in the time-frame of the experiment (22% reduction). Likewis e, animal R10 had approximately 15% timedependent reduction in probe recovery in the 3-hour IV MD sampling. No considerable changes in in vivo probe recovery were observed fo r the remaining animals/probes. Nevertheless, the observed reduc tion of probe efficiency may not be of relevance in the current IV MD study as intra-probe variations of 20% are accepted under in vivo conditions [107].Yet, the calibra tor is valuable as a quality c ontrol during the experiment. Budesonide recovery determined by retrodi alysis during the course of the IV MD experiment was used to back-estimate t he recovery of TA. The overall mean TA recovery using retrodialysis by calibrator was 55.5 2.8 (CV= 5.02%). The individual TA recoveries for each animal are listed in Table 5-2. 97

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The performance of two retrodialysis methods, retrodialysis by drug and retrodialysis by calibrator, in estimating unb ound plasma concentrations of TA from IV MD data was subsequent evaluated. The conc entration-time profiles of TA were calculated from the microdialysate concentrations corrected (I) by the mean in vivo recovery of TA (%RTA= 59.0%) estimated by retrodialysis in Chapter 2 or (II) by the recovery of budesonide at each collection interval adjusted by the in vivo recovery ratio TA:budesonide (RRTA:bud= 0.7). Intravenous Microdialysis of TA Total and unbound plasma concentration-time profiles of TA after constant rate infusion (5 mg/kg i.v. bolus + 2.3 mg/kg/h in fusion) are shown in Figure 5-1. The mean total plasma concentration over a period of 180 min was 3.64 0.74 g/mL, and the measured microdialysate concentrations correc ted for recovery by retrodialysis by calibrator was 0.343 0.072 g/mL. The total plasma concentrations were analyzed by a two-compartment body model with the pharmacokinetic model adequately fitted the concentration-time profile. Figure 5-2 shows two representative examples of individual curve fits. The evaluation of goodness of fit was done by the respective model selection criteria (MSC) and the coefficient of determi nation (CD). The MSC is a modified Akaike information criterion that allows comparis on of the appropriateness of a model: the greater the value of the MS C, the better the fit. The re sults of the individual pharmacokinetic parameter estima tes are shown in Table 5-3. TA has a considerable fast distribution of 13.7 min and a fairly s hort half-life of 76 min as determined by the compartmental analysis. These values ar e in agreement with literature where a distribution half-life of around 5 min [70] and elimination hal f-life of 115 [70] and 180 min [113] were reported after intravenous administration of TA phosphate in humans. The 98

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model estimated mean clearance value of 10.8 mL/min/kg is also comparable to value of 11.2 mL/min/kg previously observed in rats after i.v administration [109]. As can be seen from Figure 5-1, the fi rst TA concentration determined from microdialysis sampling was lower than expected after an i.v. bolus dose and infusion, as observed with the plasma total concentrati on. Similarly, other investigators also observed lower IV microdialysate concentrati on, corrected for the recovery, compared to the total plasma level at the firs t sampling point after a 5-min intravenous administration of theophylline in rats, during IV MD [60]. In fact, this behavior may be likely following i.v administration of drugs wit h fast distribution pharmacokinetics, such as TA and theophylline, as previously stated in a review of the microdialysis technique [53]. This possible drawback of IV MD sampling to characterize the systemic pharmacokinetics of a drug is related to the fa ct that the first analyte concentration is obtained at the midpoint of the first collect ion interval. Thus, if the intravenous pharmacokinetics of a drug with a rapid distributi on into the peripheral tissues is studied, the first analyte concentration may only be obtained at 10 min (in case of a 20-min collection interval) following administrati on which may not give a very accurate description of the early distribution phase of the substance [53]. Since the purpose of the study was to evaluate the accuracy of the IV MD technique by comparison of the unbound concentrations obtai ned by microdialysis with the plasma levels from conventional bloo d sampling corrected for protein binding, concentration-time profiles at steady-state were investigated. Furthermore, under steady-state conditions, fluctuations in pr obe recovery can be better monitored and the performance of two alternative methods of in vivo MD calibration can also be compared. 99

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The average unbound steady-state concent rations determined by intravenous microdialysis corrected for retrodialysis by drug and retrodi alysis by calibrator were 0.310 0.084 and 0.343 0.072 g/mL, respectively. The calculated unbound TA concentration in plasma corrected for prot ein binding was 0.378 0.077 g/mL, which is not significantly different to thos e determined by microdialysis sampling ( =0.05). The individual plasma concentrations of TA at steady-state are listed in Table 5-4. The systemic clearance of TA was calculat ed based on plasma level as the ratio of the infusion rate (R0) to the observed mean steady-state concentration (Css). The mean CL obtained from total plasma levels was 10.9 2.2 mL/min/kg which was comparable to the model fitted CL (10.8 2.0 mL/min/kg, Table 5-3). The mean CL values calculated from steady-state mi crodialysate concentrations, corrected for recovery using retrodialysis by drug or retrodialysis by calibrator, were found to be 13.9 3.9 and12.0 2.6 mL/min/kg, respectively. Both CL va lues were not significantly different ( =0.05) from the one obtained from conv entional blood sampling. The use of the retrodialysis by calibrator calibration method gave fairly comparable corrected unbound concentrations as the use of retrodialysis by drug. Therefore, an experimental design with calibrator is valuable for monitoring and if necessary compensating for changes in probe recovery over time. The errors introduced by an unaccounted fluctuation of the drug recovery propagate to some extent to overall variability in the estimated unbound concent rations, and ultimately pharmacokinetic parameters. In our current study the coefficient of variati on of the estimated CL from microdialysis sampling correct ed by recovery by calibrato r was 22%, whereas corrected by recovery by drug was 28%. If the recovery of the calibrat or shows no significant trend 100

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during the experiment, the estimated drug re covery using the retrodialysis by drug calibration method seems sufficient to us e for the estimation of reliable unbound concentrations. In conclusion, intravenous microdialysis is an accurate method to determine unbound concentrations of TA following drug infusion at steady-state. The microdialysis recovery of TA can be monitored using either retrodialysis by drug or retrodialysis by the calibrator budesonide. Intravenous microdi alysis sampling appears to be a feasible approach for free drug monitoring of lipoph ilic and highly protein-bound drugs. 101

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mi n 0 2 4 6 8 10 12 mAU 0 0.5 1 1.5 2 2.5 A mi n 0 2 4 6 8 10 12 mAU 0 0.5 1 1.5 2 2.5 6.830 12.469TA Budesonide B Figure 5-1. Representative ch romatograms of IV MD sample s. A) Blank microdialysate prior to dosing. B) Mi crodialysate sample containing the drug TA (0.24 g/mL) and the calibrator budesonide (2.1 g/mL) after i.v. infusion at steady state. 102

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mi n mAU 0 2 4 6 8 10 12 12 10 14 0 2 4 6 8 A mi n 0 2 4 6 8 10 12 14 mAU 0 2 4 6 8 10 12 6.794 14.285TA IS B Figure 5-2. Representative chromatograms of rat plasma samples. A) Blank plasma prior to dosing. B) Plasma samp le containing the drug TA (3.2 g/mL) and the plasma internal standard (IS) afte r i.v infusion at steady state. 103

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Figure 5-3. Plasma concentration time-profile s of TA in rats (n=5 ) after constant rate infusion (5 mg/kg bolus + 2.3 mg/kg/h). Means SD of total plasma concentration (CT, ) obtained by conventional blood sampling and unbound concentration (Cu, ) obtained by IV MD techni que corrected for recovery using the retrodialysis by calibrator method are shown. 104

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A B Figure 5-4. Concentration-time profiles of TA for two representative animals after constant rate infusion (5 mg/kg bolu s + 2.3 mg/kg/h). A) Compartmental fitting of total plasma ( ) profile of animal R6 (coe fficient of determination of 0.999 and MSC of 6.82). B) Compartm ental fitting of total plasma ( ) profile of animal R10 (coefficient of deter mination of 0.958 and MSC of 2.28). 105

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Figure 5-5. Steady-state plasma concentration time-profiles of TA in rats (n=5) after constant rate infusion (5 mg/k g bolus + 2.3 mg/kg/h). Means SD of total plasma concentration (CT, ) obtained by conventional sampling and unbound concentrations determined by ultrafiltration (Cu, ), and obtained by IV MD sampling, corrected for recovery using the retrodialysis by drug (Cu, ) or retrodialysis by calibrator (Cu, ) methods are shown. 106

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Table 5-1. Triamcinolone acetonide unbound fraction in rat plasma determined by ultrafiltration Replicates/ Concentration ( g/mL) 2.5 5 10 1 0.092 0.114 0.104 2 0.103 0.116 0.096 3 0.094 0.122 0.099 Mean 0.096 0.117 0.099 SD 0.006 0.004 0.004 Table 5-2. In vivo recovery of budesonide and TA Determined Recovery of budesonide by retrodialysis Estimated Recovery of TA by retrodialysis by calibrator Recovery Animal Mean SD Range Mean SD Range %CV R5 82.9 2.1 85.8-79.4 57. 5 1.5 59.5-55.3 2.56 R6 83.2 2.8 86.9-80.5 57. 7 2.0 61.4-56.5 3.39 R8 73.3 6.7 86.9-68.0 50. 8 4.7 60.2-46.3 9.15 R9 80.3 1.3 81.8-78.6 55. 7 0.9 54.8-56.8 1.59 R10 80.1 4.7 87.7-74.1 55. 6 3.3 60.8-51.4 5.91 Overall 80.0 4.0 87.7-68.0 55.5 2.8 61.4-46.3 5.02 Mean of n= 9 dialysate fractions for each animal 107

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108 Table 5-3. Individual pharma cokinetic parameter estimates of TA in rats after i.v. constant rate infusion Parameter/ Animal R5 R6 R8 R9 R10 Mean SD Css ( g/mL) 4.21 4.57 3.35 3. 39 2.81 3.67 0.711 Vdss (mL/kg) 496 422 493 524 971 581 221 CL(mL/min/kg) 9.10 8.38 11.5 11.3 13.7 10.8 2.09 K21 (min-1) 0.008 0.013 0.015 0.017 0.015 0.014 0.003 K12 (min-1) 0.009 0.008 0.010 0.019 0.011 0.012 0.004 t (min) 14.1 15.2 13.4 9.54 16.3 13.7 2.59 t (min) 106.8 70.2 61.2 63.0 78.6 76.0 18.6 Css: total plasma concentration at steady state; Vdss: volume of distribution at steady-state; CL: systemic clearance; K12 and K21: intercompartmental rate constants; t : distribution half-life; t :elimination halflife. Table 5-4. Individual steady-state plasma concentrations of TA, total (Css,T) and unbound (Css,u) determined by utrafiltration or IV MD corrected by the two methods of probe calibration, in rats after i.v. constant rate infusion Css, T Css, u (corrected for fu by ultrafiltration) Css, u IV MD (retrodialysis by drug) Css, u IV MD (retrodialysis by calibrator) Animal Mean SD Mean SD Mean SD Mean SD R5 4.29 0.11 0.446 0.012 0.357 0.022 0.388 0.014 R6 4.55 0.11 0.473 0.012 0.410 0.014 0.437 0.018 R8 3.22 0.12 0.335 0.013 0.221 0.025 0.301 0.048 R9 3.32 0.04 0.344 0.004 0.317 0.022 0.347 0.030 R10 2.81 0.23 0.292 0.024 0.221 0.012 0.251 0.008 Overall 3.64 0.75 0.378 0. 077 0.310 0.084 0.343 0.072 Mean of n=5 determinations at steady-state

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CHAPTER 6 UTILITY OF PBPK MODELING IN ADDRE SSING NONLINEAR PHARMACOKINETICS AND DRUG INHIBITION MECHA NISMS OF TELITHROMYCIN Background Telithromycin, an antibacterial agent of t he ketolide class, is a CYP3A inhibitor in vitro Inhibition in vivo has been demonstrated with a number of substrates cleared by CYP3A4. For example, telithromycin incr eased the area under the concentration-time curve (AUC) of CYP3A probe drugs simvastati n, midazolam and cisapride by 9-, 6-, and 2-fold, respectively [88]. According to the draft FDA drug-drug interaction guidance [114-116] telithromycin can be categorized as a strong CYP3A inhibitor in vivo In vitro studies reported telithromycin inhibition of CYP3A4 activity via an apparent competitive mechanism with a reversible inhibition constant Ki of 58 M [117,118]. In addition, there is no report to-date on the use of human in vitro data in predictive models to assess the interaction magnitude pr oduced by telithromycin. Telithromycin is also a substrate of CYP3A4 (Figure 6-1). Human absorption, distribution, metabolism and excretion (ADME) studies showed that the metabolic, renal and biliary/intestinal excret ion clearance account for approximately 65%, 23% and 12% of the total drug clearance, respectively, a fter 400 mg i.v. infusion over 1.5 hr [88]. Based on in vitro data, it is estimated that around 50% of telithromycin metabolism is mediated by CYP3A4 and the remainder is CYP-independent [119]. Telithromycin is a substrate of the efflux trans porter P-glycoprotein (P-gp) as well, as demonstrated in an in vitro Caco-2 cell transport study [120]. After an oral dosing of 800 mg telithro mycin, the absorption into gut wall is estimated to be higher than 90% with an absolut e bioavailability of 57% that considers impact of first-pass gut and liver met abolism [121]. Food does not affect its 109

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bioavailability [122]. In addition, telithromycin displays nonlinear pharmacokinetics: doubling from 400 to 800 mg q. d. and from 800 to 1600 mg q.d. in both singleand multiple-dosing scenarios resulted in an increas e of approximately 3-fold in exposure (a larger than dose proportional increase in AUC) [89]. Also, accumulation of telithromycin was observed after multiple doses with AUC24,SS (area under the plasma concentrationtime curve from 0 to 24 hours at steady-sta te) exceeding the projections from singledose kinetics (AUC24,SD) by 1.4-fold (Accumulation ratio (Rac)= AUC24,SS/AUC24,SD) (Table 6-1) with an increase in the main (ini tial) elimination half-life by 20-30%. The Rac value was independent of dose [89]. I ndependent compartment al PK analysis and simulations (WinNonlin Ente rprise version 5.2, Pharsi ght, Sunnyvalle, CA) confirmed that accumulation was not to be expected a fter once-daily seven days of 800 mg dosing (Rac=1.01). The deviation from dose pr oportionality and timedependent kinetics of telithromycin have been attri buted to a reduction in t he metabolic clearance with increasing doses while the renal clearance remained unchanged [88,89] The nonlinearity of telithr omycin pharmacokinetics may be attr ibuted to either saturation (metabolic enzymes and/or efflux tr ansporters) and/or ti me-dependent enzyme inhibition. Physiologically-based pharmacokinetic (PBP K) models have been increasingly applied in the drug research and development program as tools for predicting human pharmacokinetics and drug-drug interaction risks associated with the investigational drug [123]. By integrating system properties and drug-dependent parameters, a PBPK model has the advantage of evaluat ing the effect of multiple mechanisms that determine pharmacokinetics of an investigational drug. 110

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Specific Aim The purpose of this study is to apply PBPK modeling and simulation to predict the enzyme inhibition potential derived fr om the nonlinear p harmacokinetics of telithromycin. Specifically, a series of PBPK model for telithromycin were sequentially constructed using available in vitro metabolism and interaction data, and results from clinical pharmacokinetic studies to describe the nonlinear kinetics resulting from timedependent inhibition (TDI) mechanism of CYP3 A4. The model was used to predict the magnitude of drug-drug intera ction of telithromycin with the CYP3A4 probe substrate, midazolam. Methods In the present study, PBPK modeling and simulations were carried out using the software SimCYP Population-Based ADME Simulator (V10.10, SimCYP Ltd, Sheffield, UK) to take advantage of the s ophistication of this particular software, such as the use of the dynamic estimates of in vivo concentrations of the precipitant drug, the accountability for inter-individual variability among the population and, in particular the CYP3A4 substrate midazol am PBPK compound profile. Initial Model A PBPK model for telithromycin both as a substrate and interacting drug of CYP3A4 was constructed within the software SimCYP. Drug-dependent component comprises parameters necessary to describe the absorption, distribution, metabolism and excretion (ADME) (Figur e 6-1) and the drug-drug inte raction mechanisms. Data describing the physicochemical properties (molecular weight and pKa) and plasma protein binding of telithrom ycin (unbound plasma fraction, f u) were obtained from the literature (Table 6-2). The logar ithm of the octanol-water partition coefficient (Log P) 111

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value was obtained from the Chemspider database (Royal Society of Chemistry, Cambridge, UK). Human blood-to-plasma par tition ratio (B/P) va lue was estimated (Parameter Estimation function within SimCYP) using the mean plasma concentrationtime data after intravenous administration ( 400 mg, 2.5 h infusion time) in healthy volunteers [121]. Initial estimate of B/P value is based on rodent data [124]. The volume of distribution at steady-state (Vss) and values for the tissue-to-plasma partitioning of telithromycin into adipose, bone, brain, gu t, heart, kidney, liver, lung, muscle, skin, and spleen were calculated in silico from the drug physicochemical properties, f u and the composition of the tissues using the equations developed by Rodgers and coworkers [125-127]. The Ad vanced Dissolution, Absorption and Metabolism (ADAM) model was used to predict the fraction absorbed (f a) and first order absorption rate constant (ka) from in vitro permeability data in Caco-2 cells (Table 6-2). Description of the different ial equations and the parameter relationships within the software are described in details elsew here [128-130]. Besides CYP3A4, telithromycin is also a substrate of the efflux transporter, P-glycoprotein (P-gp). The kinetic constants (Km and Vmax) of P-gp-mediated effl ux of telithromycin in vitro were obtained from the literature [120]. Telithromycin clearance (CL) is comprised of hepatic, biliary and renal contributions (CLH, CLBile, CLR) as outlined in Figure 6-1. Hepatic intrinsic clearance (CLu,int,H) at the enzyme level was back-calcul ated from systemic clearance values obtained from intravenous data [121] by re trograde calculation. The method employs the re-arranged well-stirred model equation [131] as follows: ) (, , int, H BHB BHBH HCLQfu QCL CLu 112

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where QH,B is the hepatic blood flow (84.8 L/h), f uB= f u/(B/P) is the fraction unbound in the blood (values were 0.3 and 0.7 for fu and B/P, respectively), and CLH,B= CLH/(B/P) is the hepatic metabolic clearance in blood (53.6 L/h) derived from CLiv,B (82.4 L/h) after subtraction of CLR,B and CLBile,B (Table 6-1) As net unbound hepatic intrinsic clearance (CLuint,H) is the sum of all intrinsic clearances by all enzymatic and transporter pathways, the CLuint,H of CYP3A4 was calculated from the fractional metabolism of CYP3A (50% CLH) reported from in vitro and in vivo results from a human mass balance study using an oral solution of telithromycin 800 mg [88]. The remaining hepatic metabolism (50% of CLH) was assigned to the non-CYP pathway. An array of scaling factors for hepatocellularity was used, including different am ount of microsomal protein per gram of liver, s pecific enzyme abundance, relative enzyme activity, and liver weight [83]. The maximum rate of metabolism of the enzyme CYP3A4 (Vmax,CYP3A4) was calculated as follows: 43, 43int, 43max, ACYP mACYP ACYPK CLu V assuming the same Km,CYP3A4 as the reported Ki,CYP3A4 from in vitro inhibition study [118]. The value was corrected for the unbound fracti on of the drug in microsomal incubation ( f umic= 0.447) predicted in silico from compound lipophilicity and assumed microsomal protein concentration of 1 mg/mL. Defining clearance based on Vmax and Km enables us to evaluate potential dose-depen dent non-linearity and saturati on of clearance for larger doses as well as for multiple administrations. The transporter-mediated intestinal/biliary excretion was incorporated in the model using the published Michaelis-Menten constant (Km) for P-gp [120] and by retrograde calculation of maximu m rate of transport (Jmax, in pmol/min/million cells) from the in vivo 113

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biliary clearance of 6.9 L/h (assuming aver age liver weight of 1600 g and 117.5 million cells/g liver)[132]. The initial model also incorporated a reversible Ki,CYP3A4 (25 M after correction for nonspecific binding) allowing the simultaneous inhibition of CYP3A4. The roles of potential saturation of intestinal and hepatic CYP3A4 and/ or P-gp on the drug nonlinearity were evaluated by simu lations using the initial model. Modified Model Model building is a continuous exercise as more data are incorporated and further information on verifying the performance ar e obtained by contrasting the simulation outcome and observed data. Following the confirmation of neg ligible contribution of saturation in CYP3A4 and Pgp on the nonlinear PK observed in vivo (see Results section in relation to outcome of initial model), the model was further developed to investigate the contribution of auto-inhibition via time -dependent CYP3A4 inhibition mechanism to nonlinear pharmacokinetics of telithromycin (Table 6-1). The kinetic parameters describing TDI process are the inactivation rate constant kinact (maximal inactivation rate at satura ting concentration of the inhibitor), the potency of the inactivation (KI, inhibitor concentration causing hal fmaximal inactivation) and the turnover rate of the enzyme in vivo kdeg (first-order rate c onstant for degradation). Details of the enzyme mechanism-based inhibition process can be found in a previous report [133]. In the modifi ed model, a much higher CYP3A4 contribution on the metabolic pathway of telithromycin should be considered to overcome the inactivation of this enzyme over the time course of drug ad ministration following single dose. In other words, the observed contributi on of 50% for metabolic elimination by CYP3A4 could be considered a time-averaged value where initia l contribution was high, but it reduced as the active enzymes level went down due to TDI. Thus, to assign higher CYP3A4 114

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metabolism, the Vmax of CYP3A4 within the initial mode l (7.3 pmol/min/pmol of isoform) was increased by 2.66-, 4.00-, 4.66or 5.33 folds, assuming that a higher intrinsic value of Vmax becomes an apparent Vmax in the presence of TDI. Under each new value of Vmax (2.66-, 4.00-, 4.66 or 5.33-fold initial value), sensitivity analyses were conducted to determine the effect of a range of kinact (range 1-10 hr-1) and KI (1-25 M) values on the apparent oral clearance (Dose/AUC0-24h) of a single oral dose of telithromycin (400, 800, or 1600 mg q.d. were tested). Three di mensional (3D) plots were generated for each Vmax value with the concurring TDI over the 400-1600 mg SD range. Figure 6-2 shows two representative 3D plots of 2.66and 4.66-fold increase in Vmax of CYP3A4 within the range of KI and kinact values. As can be seen from the 3D plots, the increase in Vmax with concurrent TDI led to an increase in Dose/AUC0-24h in a dose-dependent manner. The pharmacokinetic profiles of telithromycin after seven days of therapy (400, 800 or 1600 mg q.d.) were simulated us ing different combinations of Vmax and TDI parameter (KI and kinact) values to evaluate their effect on the clearance at steady-state (Dose/AUC144-168h ). The most plausible combinat ions of the three parameters (Vmax, KI and kinact of CYP3A4) and resulting apparent or al clearance values predicted from simulations under ascending single and multiple doses were compared to the observed clearance reported in the NDA review [ 119] (Table 6-3). The values of KI of 6 M, kinact of 10 h-1 and Vmax of 35 M (4.66-fold of initial value from initial model) were selected as the most representative for the doseand time-dependent PK of telithromycin. Simulations were performed using the software default values (V10.10) of the intrinsic turnover of CYP3A4, kdeg of 0.019 and 0.030 h-1 for liver [134] and gut [135], respectively. 115

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Both the initial and the modified models were qualified by visually comparing simulated telithromycin plasma concentration -time profiles with mean plasma profiles and pharmacokinetic parameters from six clinical studies [89,136-140]. Mean plasma profile data from literature were digitized using GetData Digitizer (Version 2.24). A detailed description of telithromycin PBPK m odel and parameters are illustrated in Figure 6-1 and listed in Table 6-2. Simulations Pharmacokinetic simulations were conducted using various clinical study conditions (10 trials of 10 subjects eac h, unless specified otherwise). Mean and distribution of demographic covariates (e.g. age, gender, body weight, body surface area, organ weight, and tissue composition) and drug parameters were generated using Monte-Carlo approach, under pr edefined study designs, within the PBPK software. The effects of telithromycin on a concom itantly administered CYP3A4 substrate midazolam were evaluated using midazol am drug-dependent param eters compiled in the compound library of the PBPK software. DDI simulations were performed using both the initial and modified telithromycin models to compare the magnitude of drugdrug interaction via the reversible (com petitive) and time-dependent mechanism of CYP3A4 inhibition. The reported inhibition constant Ki CYP3A4 of 58 M was evaluated after correction for the nonspecific microsomal binding. Two extremes of microsomal protein concentration in the in vitro incubations, representing the most likely and the unlikely scenarios, respectively, are 1 or 10 mg/mL microsomal protein. The in silico estimates of the unbound fraction of telithromycin ( f umic) were 0.447 and 0.075, resulting in unbound Ki values of 25 and 4.3 M, respective ly. Both values were tested as 116

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reversible inhibition inputs. The CYP3A4 TDI parameters incorporated in the modified telithromycin model were KI of 6 M and kinact of 10 h-1 (Table 6-1). Extra DDI simulations were performed us ing modified telithromycin PBPK model (with TDI mechanism) and midazolam model modified by adjusting the contribution of the CYP3A4 metabolism ( f mCYP3A4). CYP3A4 was assumed to be the only CYP3A isoform to accommodate the inhibition of this enzyme by telit hromycin during PBPK simulation. As the SimCYP default f mCYP3A4 for midazolam is 0.96, two other f mCYP3A4 values, 0.86 and 0.94, were tested in TDI prediction model. The f mCYP3A4 values of 0.86 and 0.94 were estimated from ketoconazole interaction after i.v. and oral administration of midazolam, respectively (University of Washington Metabolism and Transport Drug Interaction Database, Version 4.0). All drug-drug interaction simulations were conducted using time-based simulations according to the trial design reported, incl uding the dose regimen, number of subjects, age range and gender ratio in virtual healthy vol unteer populations [119]. In this study, a single intravenous infusion (i.v.) or oral (p .o.) dose of midazolam was administered to male healthy volunteers (n=12) on day 5 after oral administration of telithromycin (800 mg q.d. for 6 days). Each trial was simulat ed 10 times to assess inte r-study variability. Geometric mean of the ratios (both with and without an enzyme inhibitor under reversible or time-dependent mechanisms) of midazolam PK parameters were calculated and compared with the observed values. Results Prediction of Nonlinear Pharmacokinetics of Telithromycin Using the initial PBPK model, the simula ted pharmacokinetic profile was compared to observed data from healthy subjects after a single intravenous infusion (400 mg for 117

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2.5 h) (Figure 6-3A) or single 800 mg or al dose (Figure 6-3B). The simulated intravenous pharmacokinetic profile reasonabl y described the observed data regarding the distribution and eliminati on phases (dotted line). The model also satisfactorily predicted the concentration-time profiles after single oral administration, suggesting the robustness of the model to reflect absorpt ion characteristics of telithromycin. To delineate the contribution of the P-gp efflux on the drug bioavailability and nonlinearity, simulations were perform ed under the conditions with and without the apical intestinal transporter in the initial model. Table 6-4 shows a comparison of the predicted parameters, Cmax, AUC, fraction absorbed in the small intestine ( f a jejunum), and apparent oral clearance (CL/F) acro ss the doses of 400, 800 and 1600 mg SD under these different scenarios. The intestinal P-gp efflux pump showed minimal impact on the oral absorption of the drug as a consequence of the intrinsic high passive permeability of telit hromycin (Papp: 21 x 10-6 cm/s) [120], its high oral dose level (gastro-intestinal luminal fl uid concentration > 1 mM) and it s apparent high affinity for Pgp (Km of 9.8 M) with low maximum rate of transport (Jmax value of 5 pmol/min) [120]. Figure 6-4A shows the transient saturation of the efflux clearance of P-gp in the apical membrane of the jejunum when a low dose was administered. Thus, the efflux transport would not likely contribut e to the observed deviati on of dose-proportionality. The potential saturation of CYP3A4 elimi nation pathway was tested. Since the kinetic values of the enzymatic metabo lism of telithromycin by CYP3A4 were unavailable, we assumed similar affinity fo r the enzyme as reported for the inhibition constant (Km, CYP3A4 of 25 M after correction for nonspec ific microsomal binding). The initial model predict ed apparent oral clearance of the doses 400, 800 and 1600 mg after 118

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single dose administration were 116, 115 and 113 L/h, respectively; while after seven once-daily doses were 105, 104 and 102 L/h, respectively. The maximum predicted accumulation ratio (Rac = AUC24,ss/AUC24) of 1.1 and AUC/dose ratio of 1.0 (across three doses) did not translate to the mean observed Rac of 1.4 and AUC/dose ratio of 1.6 (Table 6-1), respectively [89]. The inte stinal and hepatic intrinsic clearances of CYP3A4 showed transient saturation already at the lowest dose (400 mg, Figure 6-4B). Due to the uncertainty of the Km,CYP3A4 value, the enzyme saturation was further tested using a much higher affinity for the enzyme by a 100-fold reduction of this value. The new Km,CYP3A4 led to an additional reduction of the apparent oral clearance, 91, 84 and 80 L/h after single doses and 85, 79 and 74 L/h after multiple doses of 400, 800 and 1600 mg q.d., respectively. However the predicted decrease was modest and the decrease seems proportional with the ascending doses. Thus, the proposed CYP3A4 enzymatic saturation did not appear to be a plausible mechanism to the observed deviation from dose-proportionality and time-dependent kinetics of telithromycin (Table 6-1). Based on the greater apparent oral clearance (Table 6-1) observed at 400 mg single dose as compared to higher doses, it was reasonably assumed in fact a higher intrinsic clearance of CYP3A4, and exposu re/dose nonlinearity was caused by autoinhibition of CYP3A4. The initial model wa s modified by optimizing CYP3A4 metabolism and auto-inhibition via timedependent CYP3A4 inhibition. Sensitivity analyses were conducted to simultaneously evaluate the im pact of the changes in the intrinsic clearance of CYP3A4 (ascendi ng values of initial Vmax), and in the parameters of TDI, KI and kinact, on telithromycin PK nonlin earity (Figure 6-2). The per formance of the modified 119

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model by incorporating the time-dependent CYP3A4 inhibiti on in predicting the steadystate kinetics of telithromycin after ascending doses compared to the initial model is illustrated in Figure 6-5. Previ ously published data [ 89] of once-daily adm inistration at all three dose levels were collected to aid model modification. The corresponding pharmacokinetic profiles (solid line) usi ng modified (with TDI) model are in fair agreement with the observed pharmacokinetic pr ofile of telithromycin on day 1 and day 7; whereas the initial model (dotted line) under-predicts the dose-and timedependent kinetics at all dose levels. Although the m odified model still over-p redict telithromycin exposure (higher predicted AUC compared to observed AUC) after multiple doses of 400 mg, optimizing CYP3A4 metabolism and incorporating TDI mechanism could reasonably reconcile the higher apparent oral clearance of the single-dose of 400 mg, as well as the doseand timedependency of clearance. The clinically observed, greater than expected accumulation was accu rately estimated by the modified model (observed versus simulated mean Rac of 1.4and 1.4-fold, respectively). Likewise, the estimated mean deviation from dos e-proportionality, AUC/dose ra tio of 1.3, is in good agreement with the mean clinical value of 1.6 (81% accura cy) (Table 6-1). Figure 6-6 illustrates a comparison of t he observed and simulated AUC as a function of dose by the initial and modified model s. The initial model predicti on of exposure/dose parallels the linear dose dependency; whereas the m odified TDI model was in close agreement with the observed deviation from dose-proportionality. The si gnificant difference of the amount of unchanged drug excreted renally (as % dose) across doses was also predicted by the modified model (Table 6-1). T he effect of auto-inhi bition via TDI on the clearance and oral bioavailabilit y of telithromycin at steady-s tate was satisfactorily 120

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estimated according to Figure 6-7, whic h shows the comparison between simulated PK profile of the therapeutic dose of 800 mg afte r seven doses and clinical data from six different trials. Therefore, the time-dependent CYP3A4inhi bition was deemed plausible in explaining the pharmacokinetic nonlinearity of telithromycin. Prediction of the Magnitude of Drug-Drug Interaction To further verify the telithromycin PBPK model that pr edicts its nonlinear PK, the magnitude exposure change for the CYP3A4 substrate midazolam ( f mCYP3A4 of 0.96) upon co-administration of telithromycin was simu lated using both the in itial and modified telithromycin models. The prediction of the drug-drug interacti on by telithromycin using the reported reversible Ki (within initial model) was unsuccessf ul. Namely, using the most likely unbound Ki of 25 M as an input interaction paramet er, the simulated midazolam AUC ratios (AUCR= AUCinhibited/AUCcontrol) were 1.00 and 1.08 after single infusion (i.v.), and single oral (p.o.) midazolam, respectively. Similarly, AUCR values predicted using the unlikely unbound Ki of 4.3 M were 1.04 and 1.33 after i.v and p.o. dosing of midazolam, respectively. In comparison, the observed AUCR valu es were 2.2 and 6.1 after i.v. and p.o. mida zolam, respectively. Conversely, the modified telithromycin model incorporating time-dependent inhibition of CYP3A4 reasonably predict ed the observed increase in midazolam exposure produced by telithromycin interaction. Table 6-5 summarizes the predicted and observed ratio increases in maximum plasma concentration (Cmax), AUC(0, ) and hepatic and intesti nal availability (FH and FG) after i.v. and p.o. midazolam concomitantly with telithromycin (800 mg q.d., 6 days). The modified model predicted the inhibition of CYP3A4 dependent metabolism of midazolam by telithromycin both at intestinal and 121

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hepatic levels: a predicted geomet ric mean AUC ratios of midazolam (GMR) of 3.2 after i.v. dosing of midazolam (decrease in CLH), and a predicted GMR of 6.7 after p.o. dosing of midazolam (decrease in CLH and increase in FG and FH). These values are in good agreement with observed GMRs (2.2 and 6.1 after i.v. and p.o., respectively). The predicted GMR for each of the 10 simulated trials ranged from 2.2-4.9 and 4.1-9.1 after i.v. and p.o. midazolam, re spectively (Figure 6-8). The outcome of DDI simulations depends both on the information related to victim drug as well as those of perpetrator. Hence, additional DDI simu lations were conducted with a modified midazolam PBPK model by adj usting the contribution of the CYP3A4 metabolism from the SimCYP compound profile ( f mCYP3A4 of 0.96). The f mCYP3A4 values of 0.86 and 0.93 were tested. This exercise was to assess similar DDI potential by telithromycin under varying importance of CYP3A4 for the victim drug since the accuracy of this parameter has a significant impact on drugdrug interactions involving strong inhibitors [141]. The AUC GMR obtai ned with i.v. midazolam were 2.52 (range from 2.2 to 2.9 among 10 simulated trials) and 3.23 (range 2.79-3.85) for f mCYP3A4 values of 0.86 and 0.93, respectively; whil e the AUC GMR after oral midazolam were 5.54 (range 4.29-7.30) and 7. 12 (range 6.23-8.78) for f mCYP3A4 values of 0.86 and 0.93, respectively. The predicted increases in exposure were similar to the ones obtained under the scenario of 96% contribution of CYP3A4 on midazolam metabolism (SimCYP compound profile) and observed values, as described above and listed in Table 6-5. Discussion The utility of the PBPK modeling and simula tion to predict the pharmacokinetic consequences of CYP3A4 inactivation by telithromycin by integrating in vitro and in vivo pharmacokinetics and interaction data has been demonstrated in this report. The 122

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metabolic and efflux transporter saturation as mechanistic hypotheses for the observed timeand dose-dependent telithromycin pha rmacokinetics were tested to be implausible. On the contra ry, the time-dependent inhibi tion of CYP3A4 reasonably predicted the changes in CL/F at ascendi ng single and multiple-doses. The modified model incorporating time-depend ent CYP3A4 inhibition was fu rther used to successfully predict the magnitude of inte raction with midazolam (a probe CYP3A4 substrate, Table 6-5), suggesting that inactivation of CYP3A4 rather than reversible inhibition of the enzyme largely explains the interaction mechanism. In vitro -toin vivo extrapolation (IVI VE) models such as PBPK have been applied in the prediction and evaluation of drug-drug interactions via competitive and/or mechanism-based inhibition [142-144]. Howeve r, the successful predictability of PBPK is dependent on the knowledge of the drugdependent parameter values for the structural model and drug inte raction data. Hence the m odels are not fixed and they develop as more information is gathered and integrated to the system. Once reliable in vitro and in vivo absorption, distribution, metabolism, elimination (ADME ) data are obtained during various stages of drug development, PBPK may reasonably predict the full disposition-time profile [145], the complexities of oral drug absorption and elimination [128,129,146], and the interindividual variability in clearance by incorporating age-dependent and genetic variations in enzyme abundance and activity [147]. In spite of the spar se availability of in vitro metabolism data of telithromycin, our investigation demonstrated the utility of PBPK modeling and simulation in informing mechanisms of drug nonlinear pharmacokinetics based on in vivo data. The current model indicates that rather than saturation of metabolic and transporter pathways, the 123

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time-dependent inhibition of the metabolic clearance could be responsible for the pharmacokinetic nonlinearity. The modified telithromycin PBPK model with TDI parameters (KI and kinact obtained using multiple sens itivity analyses) and the Kdeg,CYP3A of 0.019 h-1 (default value of SimCYP, V10.10) sufficiently predicted the pharmacokinetic nonlinearity of telithromycin; whereas the in itial model incorporating only modest saturation of CYP3A4 and intest inal P-gp did not recover the changes in the apparent oral clearance of telithromycin (Figure 6-5 and 6-6). The accurate prediction of an in vivo enzyme inhibition using a PBPK model may be restricted by the difficulties in dete rmining the inhibition mechanism and obtaining accurate inhibition parameters in vitro (e.g., Ki for reversible and/or and kinact /KI for TDI) [148,149] If the in vitro TDI experiment, usually used to distinguish between reversible inhibition and mechanism-based inactivati on and to screen out compounds with this type of CYP inactivation property, is not proper ly designed, it can result in false positive results due to reversible inhibiti on from a metabolite(s) generated in situ, or false negative results from inadequate resolution of the method to separate potent reversible inhibitors from potent time -dependent inhibitors [14]. Our investigation demonstrated the stepwise nature of building PBPK models and utility of simulation in informing the potential clinical DDI using available in vivo pharmacokinetic data when in vitro interaction data are ambiguous. The telithrom ycin inhibition mechanism for CYP3A was further supported by the in vivo drug interaction data. According to the draft drugdrug interaction guidance [115 ], the ratio of the total maximum plasma concentration of i nhibitor ([I]) over reversible Ki in vitro of more than 0.1 would suggest the need for further in viv o drug interaction evaluation [150]. For 124

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telithromycin, the [I]/ Ki, CYP3A4 at 800 mg once daily dosing regimen was calculated to be 0.11 0.66. The initial PBPK m odel of telithromycin considering reversible inhibition predicted less than 22% increase in midazolam exposure. Based on the analysis of pharmacokinetic nonlinearity, the modifi ed model incorporating TDI mechanism suggested the clinical drug-drug interaction potential of telithromycin as a strong CYP3A4 inhibitor by increasi ng AUC of the sensitive CYP3 A4 substrate midazolam by more than 500% (predicted GMR of AUC is 6. 72, Table 6-5), which was confirmed by the observed GMR of mi dazolam AUC of 6.11 [88,151] Paroxetine is another example of a subs trate and inhibitor for the same CYP (CYP2D6), which displays nonlinear pharmacokinet ics attributed to metabolic saturation [152]. Paroxetine signific antly inhibits CYP2D6 in vivo yet IVIVE using in vitro reversible inhibition data suggested marginal CYP2D6 inhibition. Recent in vitro data provided evidence for TDI of CYP2D6 by paroxeti ne [153]. Accordingly, IVIVE of the in vitro TDI data, using a scaling mathematical model, a ccurately predicted the fold-increases in several CYP2D6 victim drugs AUC by parox etine and the 5fold drug accumulation at steady-state [123]. The third exampl e is clarithromycin whose nonlinear pharmacokinetics can also be explained by auto-inactivation of CYP3A4-mediated clearance. Application of a semi-PBPK m odel incorporating CYP3A4 TDI mechanism accurately predicted the nonlinear PK of clarithromycin and the clinical observed interaction magnitude with midazolam [154]. Systems approaches such as PBPK m odeling and simulation consider the pharmacokinetic properties of the substrat e and interacting drugs, which may be useful to fully understand the mechanisms and time courses of drug interactions observed in 125

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clinical studies. Furthermore, the predict ion method provide important information for making informed decisions to minimize the potential disadvantages of new drug candidates (e.g. restriction to a specific population in the l abel, discontinuation of further development) and ultimately it may help design proper in vivo interaction studies, including dose selection, the timing of dosage of interacting drugs. Although TDI mechanism is clearly superior to the reversible inhibition mechanism in explaining telithromyicins time and dosedependent pharmacokinetics, and predicting midazolam interaction studies in vivo the modified TDI model is yet not perfect. For example, it is recognized that the modified model slightly over-predicted both telithromycin exposure after multiple doses of 400 mg q.d (Table 6-1), and AUCR of midazolam after i.v. dosing (Table 6-5). Nonetheless, these demonstrate the great utility of a PBPK model in re vealing knowledge gaps and informing further studies if necessary. In summary, this study demonstrates t he utility and predictive accuracy of PBPK modeling and simulation to address telit hromycin pharmacokinetic nonlinearity and CYP3A4 interaction potential on midazolam in vivo The integration of in vivo human pharmacokinetic data and in vitro and in silico data using PBPK approach in this study exemplifies the combinati on of top-down and bottom-up approaches, which may be especially helpful when there is scarcity or uncertainty in metabolic and drug interaction data during early stage of drug devel opment. Any discrepancy observed between simulations and experiments suggests knowledge gaps on processes that have not been considered during simulation and indicate s additional studies needed to bridge the gap. 126

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Lung Elimination Dosing Telithromycin Full PBPK Model CLR= fuGFR+ CLnet,sec ~ 13 L/h (~20% CL) Filtration:Secretion~1:6 CLnet,secpossibly by P-gpand/or BCRP Rapidlyperfused organs Intestine Liver Blood Slowlyperfused organs Kidney CLH= CLCYP3A+ CLhydro +CLbile ~ 45 L/h (~80% CL) CYP3A:Hydrolysis:Biliary ~42:42:16 CLbilemainly by P-gp Foral=FAFGFH~60% Mainly by first pass metabolism via CYP3A and/or hydrolysis Predicted FA~0.9 Intestinal P-gp minor at therapeutic doses Log P = 3.6; Diproticbase fu=0.3; B/P=0.7 (estimated) CLIV= 58 L/h; CLPO=100 L/h SD Vdss= 2.9 L/kg Blood Figure 6-1. Schematic repr esentation of telithromycin PBPK model. Abbreviations: B/P: blood-to-plasma ratio; CLiv: systemic clearance after intravenous administration; CLpo: apparent oral clearance; F: bioavailability (subscripts A, G and H, denote absorption, gu t, hepatic, respectively); fu: plasma unbound fraction; GFR: glomerular filtration rate; Vdss: volume of distribution at steady state. 127

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60 80 100 120 140 160 180 200 2 4 6 8 10 5 10 15 20 25D o s e / A U C ( L / h )ki n a c t ( 1 / h r )KI ( M )2.66-fold initial V max A 60 80 100 120 140 160 180 200 2 4 6 8 10 5 10 15 20 25D o s e / A U C ( L / h )ki n a c t ( 1 / h r )KI ( M )4.66-fold initial V max B Figure 6-2. Changes in telit hromycin apparent oral clearanc e (Dose/AUC) as a function of increasing values of CYP3A4 intrinsic clearance and time-dependent inhibition (KI and Kinact) of the enzymatic pathway. A) 2.66-fold increase on the initial Vmax value. B) 4.66-fold increase on the initial Vmax value. The three horizontal planes show apparent oral clearance values of 174, 102 and 71 L/h, with the purpose of in cluding the values observed from the ascending single-doses of 400, 800 and 1600 mg, respectively [89,119]. 128

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A B Figure 6-3. Predicted mean plasma concentrati on-time profile of te lithromycin using the initial PBPK model (dashed line) or modified model (incorporating TDI of CYP3A4, solid line). A) After intravenous infusion (400 mg for 2.5h). B) After oral administration (800 mg SD). Symbols represent mean observed data from the literature as referenced in the graph legends. 129

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A B Figure 6-4. PBPK model predicted mean val ues of transport and enzymatic pathways of a single 400 mg dose of telithromycin over time. A) Intestinal efflux clearance by P-gp. B) Hepatic in trinsic clearance of CYP3A4.(Km values incorporated in the model are 9.8 M and 25 M for P-gp and CYP3A4, respectively. 130

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Figure 6-5. Prediction of mean concentrati on time-profile of telithromycin after ascending multiple oral doses ( 400, 800 and 1600 mg q.d.) in healthy subjects using initial m odel (dashed lines) and modified model incorporating time-dependent CYP3A4 inhibition (so lid lines). Symbols represent mean observed data [89]. 131

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Figure 6-6. PBPK predicted by init ial and modified TDI model and observed telithromycin nonlinear dose dependence a fter seven once-daily doses. The line of identity (solid line) would occur in the presence of linear dose dependence. Symbols repres ent mean observed [89] or predicted data. 132

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Figure 6-7. Predicted mean plasma profile of telithromycin after multiple oral doses (800 mg q.d.) in healthy subjects using initial and modified TDI model. Symbols represent mean observed dat a from six different trials. 133

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134 A B Figure 6-8. Geometric mean of AUC ratios (5th and 95th percentiles) of midazolam in the presence and absence of telithromyci n (800 mg q.d for 6 days) in 10 different randomly selected groups of virtual subjects (n=12) () and observed (n=12) () values. A) After intravenous admin istration of midazolam. B) After oral administration of midazolam. The solid line represents the AUC Geometric mean ratio of the virt ual population (n=120); dashed lines represent the 5th and 95th percent iles of the virtual population.

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Table 6-1. Predicted PK parameters of singl e (SD) and multiple once-daily doses (MD ) of telithromycin using the modified model incorporating time-depend ent inhibition of CYP3A4 Ae: accumula tive amount of drug excr ete in the urine 0-24hce e from time 0 to 24 h; AUC/dose: area under the plasma concentrati on-time curve normalized to the dose. Cmax: maximum plasma concentration; CL/F: apparent oral clearance; CLR: renal clearance; Rac: accumulation ratio where AUC24: area under the plasma concentration-time curve from 0 to 24 h and AUC24,SS :AUC24 at steady state; tmax: time to Cmax; NA: not applicable. d after 24h; AUC : area under the pl asma con ntrat ion-time curvSD 400 mg MD 400mg SD 800 mg MD 800 mg SD 1600 mg MD 1600 mg PK Parameters a Obs b Pred a Obs b Pred a Obs b Pred a Obs b Pred a Obs b Pred a Obs b Pred Cmax (mg/L) 0.80 (57) 0.77 (46) 0.83 (42) 1.04 (40) 1.90 (42) 1.76 (46) 2.27 (31) 2.36 (35) 4.07 (30) 4.29 (41) 4.48 (33) 5.18 (31) AUC0-24h (mg/L. h) 2.57 (40) 3.50 (62) 3.50 (31) 5.36 (51) 8.25 (31) 8.31 (58) 12.50 (43) 12.29 (43) 23.1 (34) 20.2 (48) 30.2 (22) 26.7 (39) c tmax (h) 1.0 (0.54.0) 1.1 (0.62.5) 1.0 (0.54.0) 1.0 (1.02.9) 1.0 (0.54.0) 1.2 (0.62.8) 1.0 (0.53.0) 1.0 (1.02.9) 1.0 (0.54.0) 1.3 (0.62.7) 1.0 (0.53.0) 1.0 (1.02.9) CL/F (L/h) 174 152 (49) 125 95 (53) 102 (31) 129 (54) 71 (29) 78 (47) 71 89 (53) 54 69 (39) AUC/dose (mg/L. h) 5.1d 7.0 7.0e 10.7 8.4d 8.3 12.5e 12.3 12.4d 10.1 15.1e 13.4 Rac NA NA 1.40 1.53 NA NA 1.49 1.48 NA NA 1.37 1.33 Ae0-24h (% dose) 7.2 d (32) 12.1 (55) 9.6e (35) 16.3 (47) 12.7d (33) 14.3 (51) 17.7e (27) 19.2 (39) 18.4d (27) 17.59 (42) 24.4e (33) 21.3 (35) CLR 0-24h (L/h) 12.2 (26) 14.5 (23) 11.2 (28) 14.5 (23) 12.3 (17) 14.5 (23) 12.5 (34) 14.5 (23) 13.3 (23) 14.5 (23) 13.1 (31) 14.5 (23) a Obs=Observed [89,119] values are means (% coeffi cient of variation) unless specified otherwise b Pred= Predicted values are means (% coefficient of variation) from simulations using virtual population of 10 trials of healthy subjects. c Values are medians (range). d Values are significantly different among the other doses (P < 0.001) e Values are significantly different among the other doses (P < 0.001) 135

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Table 6-2. Drug-dependent parameters of telithromycin fo r the construction of PBPK model using SimCYP (V10.10) Parameter Value Methods/references Molecular Weight (g/mol) 812.03 [88] Log P 3.6 Predicted by Chemspider pKa 5, 8.7 [88] B/P 0.7 Parameter estimationa f u 0.3 [88] f umic 0.447 Predicted by SimCYP f a 0.92 Predicted by SimCYP ka (hr-1) 0.95 Predicted by SimCYP Papp Caco-2 (10-6 cm/s) 21 [120] Jmax P-gp intestine (pmol/min) 5 [120] Km P-gp ( M) 9.8 [120] Vss (L/kg) 2.3 [121] CLiv (L/h) 57.7 [121] CLR (L/h) 13.2 [121] CLH (L/h) 37.5 [88] CLadd (L/h) 6.9 [88] Non-CYP CLint ( L/min/mg protein) 39.5 Retrograde calculation Km CYP3A4( M) 58 Assumed equal to Ki [118] Vmax CYP3A (pmol/min/pmol isoform) 35 Obtained by sensitivity analysis Jmax P-gp liver (pmol/min/million cells) 6 Retrograde calculationb KI CYP3A4 ( M) 6 Obtained by sensitivity analysis kinact CYP3A4 (hr-1) 10 Obtained by sensitivity analysis a Using telithromycin mean plasma concentration from intravenous pharmacokinetic study in male healthy subjects [121]. b Retrograde calculation from bilia ry clearance of 6.9 L/hr. 136

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Table 6-3. Observed vs. predicted apparent oral clearance (CL/F) after single (SD) and multiple (MD) ascending doses consider ing higher intrinsic clearance by CYP3A4 and time-dependent inhibition of this metabolic pathway (KI and kinact parameters). b Predicted CL/F (L/h) a Observed CL/F (L/h) 4x Vmax KI 3 M, kinact 6 hr-1 4.66x Vmax KI 6 M kinact 10 hr-1 5.33x Vmax KI 3 M kinact 7 hr-1 Dose SD MD SD MD SD MD SD MD 400 mg 174 125 155 89 178 98 177 90 800 mg 102 71 116 77 133 80 126 76 1600 mg 71 54 94 72 98 73 97 69 a Observed values [89,119]. b Values from simulations using healthy volunteers population representatives. 137

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Table 6-4. Contribution of t he intestinal efflux transporter P-gp on initial model predicted telithromycin pharmacokinetics after increasing single doses (SD) SD 400 mg SD 800 mg SD 1600 mg a Predicted Parameter -P-gp +P-gp -P-gp +P-gp -P-gp +P-gp Cmax (mg/L) 0.86 0.83 1.75 1.71 3.57 3.52 AUC0-24h (mg/L. h) 3.24 3.44 6.56 6.96 13.34 14.16 tmax (h) 1.05 1.05 1. 05 1.05 1.05 1.05 f a (jejunum) 0.53 0.52 0.53 0.52 0.53 0.52 CL/F (L/h) 123 116 122 115 120 113 AUC0-24h : area under the plasma concentration-time curve from time 0 to 24 h; Cmax: maximum plasma concentration; f a: fraction absorbed in the jejune segment of small intestinal; CL/F: apparent oral clearance; tmax: time to Cmax. a Predicted from simulations using healthy volunteers population representatives. Study design attempted to match that reported [89]. 138

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Table 6-5. Predicted effect on midazolam exposure using the modified telithromycin model incorporating timedependent CYP3A4 inhibition. GMR: Values are expressed as geometric mean of the individual ratios of each parameter taking into account the parameters of mi dazolam alone as reference. Single IV infusion of midazolam (2 mg, 0.5 h) + telithromycin (800mg q.d.) Single oral dose of midazolam (6 mg) + telithromycin (800 mg q.d ) Midazolam PK Parameters a Observed GMR b Predicted GMR a Observed GMR b Predicted GMR Cmax 1.05 1.13 2.62 2.39 AUC02.20 3.26 6.11 6.72 FG NA NA 1.92 1.59 FH NA NA 1.45 1.63 AUC0: area under the plasma concentration-time curve from time 0 to infinity; Cmax: maximum plasma concentration; FG and FH: intestinal and hepatic bioavailability, respectively. a Observed from study#1056, NDA 21144 [119]. b Predicted from simulations using virtual population of 10 trials of healthy male subjects. NA= Not applicable. 139

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CHAPTER7 CONCLUSION The overall objective of this thesis was to evaluate the usefulness and accuracy of two distinct tools in the assessment of pharmacokinetics and drug-drug interaction: Intravenous Microdialysis (IV MD) and Physiol ogically-based Pharmacokinetic (PBPK) modeling. First, the feasibility and accuracy of intravenous microdialysis technique to determine plasma free concentrations of lipophi lic and highly protei n-bound drugs, using triamcinolone acetonide (TA) as a test compound, was evaluated. Initially, a simple and specific HPLC-PDA method was developed fo r simultaneously quantifying TA and its microdialysis calibrator, budesonide, in microdialysate and rat plasma samples. Validation results showed that the method is highly reproducible for both matrices and meets the requirements for the in vitro probe calibration studies and pharmacokinetic investigations. Subsequently, the practicability of using the microdialysis technique for TA was tested by a series of in vitro and in vivo microdialysis calibration studies. The overall results demonstrated that TA has the ability to freely and bidirectional cross the microdialysis probe membrane with recoveries around 55-65%; thus, TA is a suitable drug to be evaluated by microdialysis, despi te its moderate lipophilicity and observed time-dependent recovery in IV MD calibrati on. An alternative method of MD probe calibration was then proposed and characterized to continuously monitor recovery during the time-frame of experiment, the retrodialysis by calibrator. Budesonide was verified as an appropriate calibrator to TA as the average ratios of the probe recoveries (Recovery Ratio TA: budesonide) were fairly constant under in vitro and in vivo scenarios, including over time in vivo In the subsequent in vivo experimental evaluation 140

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of the IV MD technique, the unbound plasma concentrations of TA under steady-state pharmacokinetics in anesthetized rodents was estimated and compared to the total concentrations, corrected for protein binding, obtained by conventional blood sampling. The unbound TA concentration in plasma obtained by conventional sampling was statistically similar to the unbound c oncentrations determined by intravenous microdialysis ( =0.05) technique using both met hods of MD probe calibration, retrodialysis by drug and by calibrator. The a ccuracy of IV MD in our study led to the conclusion that IV MD sampling may be a feas ible approach for free drug monitoring of lipophilic and highly protein-bound drugs. Accordingly, IV MD tec hnique may be a promising in vivo tool for continuous free drug monitoring in (pre)clinical settings due to its several advantages compared to traditional blood sampling, specially relat ed to the reduction of the number of experimental animals used in drug resear ch and facilitate clinical pharmacokinetic studies in the pediatric population. Additi onally, IV MD may be a very valuable technique in the areas of ther apeutic drug monitoring of highly-protein binding drugs, for example, antiretroviral agents which demonstr ated elevated drug-drug interaction risks. Second, the utility of PBPK modeling as an in silico tool to evaluate the drug-drug interaction potential inferred from t he drugs nonlinear pharmacokinetics was demonstrated. Telithromycin, a substrate and inhibitor of the enzyme CYP3A4 with doseand time-dependent PK non linearity was used as model drug. A telithromycin PBPK model, integrati ng available human PK in vitro metabolic and in silico predicted enzymatic interaction param eters of time-dependent CYP3A4 inhibition, successful addressed the mechanisms of th e drug nonlinearity and accurate ly predicted the clinical 141

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142 observed drug-drug interaction magnitude with midazolam (a substrate for CYP3A4). Our results demonstrated the efficacy and predictive accuracy of PBPK modeling and simulation in informing the potential clinical DDI using available in vivo pharmacokinetic data, which is especially helpful when there is scarcity or uncertainty in metabolic and drug interaction data during early stage of drug development. In conclusion, IV MD and PBPK modelin g are useful and promising tools for evaluating pharmacokinetics and drug-drug intera ctions, thus aiding to guide successful drug development.

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BIOGRAPHICAL SKETCH Manuela de Lima Toccafondo Vieira was born in 1976, in Belo Horizonte, Brazil. She earned her bachelors degree in pharmacy with graduate diploma in Industry from the Federal University of Minas Gerais, Brazil in 1999. Manuela earned a diploma in homeopathy pharmacy from the Association of Homeopathic Pharmacists of Brazil in 2000. She practiced as a pharmacist from 1999 to 2004. In 2006, she graduated with a Master of Science degree in pharmaceutical sciences from the College of Pharmacy of the Federal University of Minas Gerais. In August 2007, she joined the PhD program in the Department of Pharmaceutics, College of Pharmacy of t he University of Florida, working under the supervision of Dr Hartmu t Derendorf. Manuela received her Doctor of Philosophy degree in pharmaceutical sciences in August 2011. 157