POPULATION PHARMACOKINETICS OF REPAGLINIDE IN HEALTHY SUBJECTS AND GENETIC POLYMORPHISMS OF CYP3A4 AND CYP2CB

by

RUZILAWATI ABU BAKAR

Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy

OCTOBER 2008 DEDICATION

([)ituju kjias 6uat arwafi ayafianaa tercinta, jl{{afiyarfiam Jfaji }l6u (]3aRgr I6rafiim ...... yang sentiasa aaCam ingatan. }lf-Patifiafi (18/10/1993). . ACKNOWLEDGEMENT

All praise and thanks are due to ALLAH; the possessor of all Excellancies, for gratuitously giving me the ingredients of success. Invoke the blessings of Allah on the noble Prophet in peace be upon him, who taught us to be thankful.

This study was carried out in the Department of Pharmacology, School of Medical

Sciences during May 2004- October 2007. I am deeply indebted to all those who have helped me during this study.

Above all, I wish to express my sincere thanks to my main supervisor, Dr. Gan

Siew Hua for her tremendous support, unconditional guidance and valuable comments and supervision throughout the experiment work, journal and thesis writing.

I would also like to express my special thanks to my co-supervisor, Dr. Mohd.

Suhaimi Abd. Wahab for his valuable comments, helpful discussions and assistance in clinical studies. I would like to thank Prof Zabidah Ismail (UCSI) for her advices and supervision.

I am thankful to Staff Nurse Maria (Wad 6U, HUSM) and Staff Nurse Asma (Kiinik

Rawatan Keluarga) for the countless times they have provided assistance in clinical studies. I am also grateful to all the volunteers who participated in the studies. Without you all, this work would not have been possible.

ii I would also like to thank all the staff in Chemical Pathology Lab, Hematology Lab,

Central Research Lab and Clinical Trial Unit.

I feel very grateful to my friends and the staff at Pharmacology Lab especially

Encik Rosli, Cik Dzuzaini, Encik Amin, Dr. Yvonne, Encik Ruzman, Puan Halijah,

Encik Azman, Dr Wan Nazirah, Encik Khairul and Puan Ezumi who have provided assistance and offered suggestions whenever required during the course of this study.

I would like to acknowledge Universiti Sains Malaysia for the financial support. This work was financially supported by IRPA, grant no. 305/PPSP/6112222 and

Universiti Sains Malaysia short-term grant (grant no. 304/PPSP/6131450), all of which are gratefully acknowledged.

A special thanks to my mother, Puan Hajjah Azizah Haji Ismail, who provided me with the inspiration to pursue my study. Last but not least, I sincerely acknowledge the greatest support, encouragement, love, understanding and patience from my husband, Dr. 'lmran Ahmad and our children, Amirul 'lrfan, Aiman 'lbad, Adib

'lzzat, the missed Jannati (12/7/2007) and lnsyirah 'lzzati.

1?..JJ,ziCawati )f. 6u (]Jafi.g,r, W.ei2008

iii TABLE OF CONTENTS

Page ACKNOWLEDGEMENT ii

TABLE OF CONTENTS iv

LIST OF TABLES X

LIST OF FIGURES xiii

LIST OF ABBREVIATIONS xvii

ABSTRACT XX

ABSTRAK xxii

LIST OF PUBLICATIONS & PRESENTATIONS xxiv

CHAPTER 1 : INTRODUCTION & LITERATURE REVIEW 1

1.1 Diabetes mellitus 1 1.1.1 Classification of diabetes mellitus 1 1.1.2 Oral antidiabetic drugs 3 1. 1.2.1 General aspects 3 1.1.2.2 Sulphonylureas 3 1.1.2.3 Biguanides 4 1.1.2.4 Alpha-glucosidase inhibitor 5 1.1.2.5 Thiazolidinedione 5 1.1.2.6 Meglitinides analogue 6

1.2 Repaglinide 6 1.2.1 Therapeutic uses 7 1.2.2 Formulation, chemical properties and stability 8 1.2.3 Mechanism of action 8 1.2.4 Pharmacokinetics properties 10 1.2.5 Dosage and administration 13 1.2.6 Drug interactions 15 1.2.7 Adverse effect 16 1.2.8 Contraindications 16

1.3 Pharmacokinetics, drug metabolism and pharmacogenetics 17 1.3.1 Pharmacokinetics 17 1.3.2 Drug metabolism and CYP enzyme system 17

iv 1.3.3 Pharmacogenetics 19 1.3.3.1 Genetic polymorphisms of CYP2C8 22 1.3.3.2 Genetic polymorphisms of CYP3A4 26

1.4 Population pharmacokinetics 29 1.4.1 Definition and rationale 29 1.4.2 Advantages and disadvantages of population 31 pharmacokinetics 1.4.3 Approaches 31 1.4.3.1 Parametric approach 31 1.4.3.2 Nonparametric approach 35 1.4.4 Optimal model 37 1.4.5 Bayes' Theorem 38 1.4.6 Data collection 39

1.5 Study hypothesis and objectives 40

CHAPTER2: METHODOLOGY 42

2.1 HPLC determination of repaglinide in human plasma 42 2.1.1 Introduction 42 2.1.2 Chemicals and reagents 43 2.1.3 Chomatographic equipment and parameters 43 2.1.4 Preparations of buffers 43 2.1.4.1 Ammonium formate (0.01 M) 43 2.1.4.2 Potassium dihydrogen orthophosphate(KH2P04), 46 pH 5.9 2.1.5 Formula and chemical properties of the standard and 46 internal standard 2.1.5.1 Repaglinide 46 2.1.5.2 Indomethacin 47 2.1.6 Preparation of stock solutions of repaglinide and 47 indomethacin 2.1.6.1 Stock and working solutions of repaglinide 47 2.1.6.2 Stock and working solutions of indomethacin 50 2.1.7 Preparation of plasma standard and samples 50 2.1.8 Optimisation of chromatographic conditions 50 2.1.9 Optimisation of extraction methods 52 2.1.10 Method validation 54

2.2 Genetic polymorphism of CYP2C8 and CYP3A4 55 2.2.1 Introduction 55 2.2.2 Materials and methods 55 2.2.3 DNA extraction 55 2.2.3.1 DNA extraction from blood 55 2.2.3.2 Measurement of DNA purity and concentration 59

v 2.3.9 Pharmacodynamic measurements of repaglinide 89 2.3.1 0 Subject monitoring 89 2.3.11 Statistical analysis 90

2.4 Population pharmacokinetic modeling 91 2.4.1 Pharmacokinetic analysis 91 2.4.2 Model parameterisation 91 2.4.3 BOXES model 91 2.4.4 Iterative Bayesian Parametric Population Model (IT2B) 92 2.4.5 Nonparametric Adaptive Grid Population Model (NPAG) 94 2.4.6 Pharmacokinetic parameters 94 2.4.7 Statistical analysis 95

CHAPTER 3 : RESULTS 96

3.1 HPLC determination of repaglinide in human serum 96 3.1.1 Spectrophotometry analysis 96 3.1.2 Optimisation of chromatographic conditions 96 3.1.2.1 Mobile phase 96 3.1.2.2 pH 99 3.1.2.3 Column temperature 99 3.1.2.4 Flow rate 99 3.1.2.5 Final chromatographic conditions 104 3.1.3 Optimisation of liquid-liquid extraction method 104 3.1.3.1 The effect of using different extracting solvents 104 3.1.3.2 The effect of varying the pHs on extraction 111 efficiency 3.1.3.3 Final method of liquid-liquid extraction 111 3.1.4 HPLC Method validation 111 3.1.4.1 Linearity and range 111 3.1.4.2 Recovery 116 3.1.4.3 Precision and accuracy 116 3.1.4.4 Detection limit(LOD) and limit of quantitation 118 (LOQ) 3.1.4.5 Selectivity 118 3.1.4.6 Stability 125

3.2 PCR genotyping for CYP2CB and CYP3A4 129 3.2.1 Estimation of DNA content and purity 129 3.2.2 Uniplex PCR genotyping for CYP2C8 129 3.2.3 Optimisation of PCR parameters 129 3.2.3.1 The effect of varying primer concentrations for 129 CYP2C8 3.2.3.2 The effect of varying primer concentrations for 134 CYP3A4 3.2.3.3 The effect of varying annealing temperatures 134 for CYP2C8 vii 2.2.4 Polymerase Chain Reaction 60 2.2.4.1 Preparation of primer stock solutions 60 2.2.4.2 Preparation of PCR master mix 60 2.2.4.3 Optimisation of PCR methods 61 2.2.4.3.1 The effect of varying primer 61 concentrations 2.2.4.3.2 The effect of varying annealing 61 temperatures 2.2.4.3.3 The effect of varying the enzyme 62 concentrations 2.2.4.3.4 The effect of varying magnesium 62 chloride concentrations 2.2.4.4 PCR genotyping for CYP2C8 62 2.2.4.4.1 PCR genotyping for CYP2C8*2, *3 and 62 *4 2.2.4.4.2 PCR genotyping for CYP2C8*5 66 2.2.4.5 PCR-RFLP for CYP3A4 genotyping 66 2.2.4.5.1 PCR-RFLP for CYP3A4*4 genotyping 72 2.2.4.5.2 PCR-RFLP for CYP3A4*5 genotyping 72 2.2.4.5.3 PCR-RFLP for CYP3A4*18 genotyping 73 2.2.4.6 Application of optimised PCR genotyping 74 methods for CYP2C8 and CYP3A4 in healthy volunteers 2.2.5 Agarose Gel Electrophoresis 74 2.2.5.1 Buffers and reagents for gel electrophoresis 74 2.2.5.1.1 EDTA solution (0.5M) 74 2.2.5.1.2 Tris-borate EDTA (TBE) (10x) 75 2.2.5.1.3 Loading buffer 75 2.2.5.1 .4 Ethidium bromide solution (EtBr) 75 2.2.5.1.5 DNA markers 76 2.2.5.2 Preparation of agarose gel 76 2.2.5.3 Gel electrophoresis 76 2.2.6 Genomic DNA sequencing 77 2.2.6.1 Purification of PCR products for sequencing 77 2.2.6.2 Direct DNA sequencing 78 2.2. 7 Calculation of allele frequency 78

2.3 Clinical study 80 2.3.1 Introduction 80 2.3.2 Materials and equipment 80 2.3.3 Subject sampling 80 2.3.4 Sample size calculation 82 2.3.5 Screening 83 2.3.6 Data collections 84 2.3.7 Blood sampling 85 2.3.8 Determination of repaglinide's concentration 87

vi 3.2.3.4 The effect of varying annealing temperatures 134 for CYP3A4 3.2.3.5 The effect of varying the enzyme 134 concentrations for CYP2C8 3.2.3.6 The effect of varying the enzyme 143 concentrations for CYP3A4 3.2.3.7 The effect of varying magnesium chloride 143 concentrations for CYP2C8 3.2.3.8 The effect of varying magnesium chloride 143 concentrations for CYP3A4 3.2.3.9 The final optimised PCR conditions 143 3.2.4 Interpretation of PCR products for CYP2C8 150 3.2.5 PCR-RFLP for CYP3A4 genotyping 150 3.2.5.1 PCR-RFLP for CYP3A4*4 genotyping 150 3.2.5.2 PCR-RFLP for CYP3A4*5 genotyping 150 3.2.5.3 PCR-RFLP for CYP3A4*18 genotyping 154 3.2.6 CYP2C8 and CYP3A4 genotyping in healthy volunteers 154 3.2.6.1 CYP2C8 genotypes and allelic frequencies 154 3.2.6.2 CYP3A4 genotypes and allelic frequencies 161 3.2.7 Direct DNA Sequencing 161

3.3 Clinical results 169 3.3.1 Subjects selection 169 3.3.2 Subject monitorings and side effects of repaglinide 169 3.3.3 Pharmacodynamic study 172 3.3.3.1 Effect of CYP2C8 and CYP3A4 genotypes on 172 repaglinide's pharmacodynamic

3.4 Population pharmacokinetic modeling 179 3.4.1 General 179 3.4.2 Iterative Bayesian Parametric Population Model (IT2B) 179 3.4.3 Nonparametric Adaptive Grid Population Model (NPAG) 185 3.4.4 Test statistics for mean pharmacokinetic parameter 185 values between the genotyping group 3.4.5 Effect of gender on repaglinide's pharmacokinetics 192 3.4.6 Effect of race on repaglinide's pharmacokinetics 198

CHAPTER 4 : DISCUSSIONS 200

4.1 High-performance liquid chromatography (HPLC) 200 4.2 CYP2C8 and CYP3A4 genotyping 213 4.3 Clinical study 226 4.4 Population pharmacokinetic modelling 230 4.5 Clinical relevance of study 238 4.6 Study limitations and future research 245

viii CHAPTER 5 : CONCLUSIONS 248

REFERENCES 251

APPENDICES

i Appendix A: Certification of reference standard purity ii Appendix B: Written informed consent form iii Appendix C: Data collection sheets and questionnaire iv Appendix 0: List of CYP2C8 and CYP3A4 substrates, inhibitors and inducers v Appendix E: Advertisement for subjects recruitments vi Appendix F: Published papers vii Appendix G: Awards received viii Appendix H: Abstracts from scientific conferences

ix LIST OF TABLES

Page Table 1.1 Values for serum repaglinide pharmacokinetic variables 14 following a 2 mg oral dose (single-dose regimen) Table 1.2 Some example of human P450 enzymes 20 Table 1.3 Examples of some substrates, inhibitors and inducers of 24 CYP2C8 Table 1.4 Examples of some substrates, inhibitors and inducers of 27 CYP3A4 Table 1.5 Advantages and disadvantages of population 32 pharmacokinetics Table 2.1 List of chemicals and reagents used in the HPLC 44 analysis Table 2.2 Chromatographic system and parameters for the 45 determination of repaglinide's concentrations Table 2.3 Preparation of repaglinide solutions in human plasma for 51 calibration Table 2.4 List of consumables, commercial kits and laboratory 56-57 equipment used in the genetic polymorphism study. Table 2.5 CYP2C8 primer sequences used in PCR 1 64 Table 2.6 CYP2C8 primer sequences used in PCR2 65 Table 2.7 CYP2C8*5 primer sequences used during the PCR 67 Table 2.8 Primer sequences used in PCR-RFLP of CYP3A4 68 alleles. Table 2.9 List of commercial kits and consumables used in the 81 clinical studies. Table 2.10 Inclusion and exclusion criteria 86 Table 3.1 Percentage recoveries of repaglinide and indomethacin 110 by liquid-liquid extraction method when different extracting solvents were used. Table 3.2 Recovery studies for repaglinide. 117 Table 3.3 Precision and accuracy of the HPLC method for the 119 determination of repaglinide in human plasma. Table 3.4 Drugs used for the selectivity study. 120 Table 3.5 Stability study 127 Table 3.6 The final optimised conditions for the amplification of 148 multiplex genotyping of PCR 1 and PCR2 for CYP2C8 Table 3.7 The final optimised conditions for the genotyping of 149 CYP2C8*5. Table 3.8 The final optimised conditions for the amplification of 151 CYP3A4*4, CYP3A4*5 and CYP3A4*18 alleles. Table 3.9 Allele frequency with observed and predicted genotype 159 frequencies of CYP2CB according to Hardy-Weinberg equation among Malaysians (n=121).

X Table 3.10 Allelic frequencies of CYP2C8 polymorphisms in 160 Malaysians and comparison with other ethnic populations. Table 3.11 Allele frequency with observed and predicted genotype 167 frequencies of CYP3A4 according to Hardy-Weinberg equation among Malaysians (n=121). Table 3.12 Allelic frequencies of CYP3A4 polymorphisms among 168 Malaysians and comparison with other ethnic populations. Table 3.13 Demographic data of the subjects (n=121). 170 Table 3.14 Clinical characteristics of the subjects. 171 Table 3.15 Blood glucose response to 4 mg repaglinide in healthy 174 volunteers having the CYP2C8*2 genotypes. Table 3.16 Blood glucose response to 4 mg repaglinide in healthy 175 volunteers having the CYP2C8*3 genotypes. Table 3.17 Blood glucose response to 4 mg repaglinide in healthy 176 volunteers having the CYP2C8*5 genotype. Table 3.18 Blood glucose response to 4 mg repaglinide in healthy 177 volunteers having the CYP3A4*18 genotypes. Table 3.19 Percentage adverse effect (hypoglycaemia) and the 178 differences between the five genotyping groups using Fisher's Exact test (n=121). Table 3.20 Goodness of fit of predicted repaglinide's serum 182 concentrations for IT2B programme. Table 3.21 Summary of repaglinide's pharmacokinetic parameter 184 values found with the IT2B programme. Table 3.22 Goodness of fit of predicted repaglinide's serum 188 concentrations for NPAG programme. Table 3.23 Summary of repaglinide's pharmacokinetic parameter 190 values found with the NPAG programme. Table 3.24 Mean pharmacokinetic parameters of a single oral dose 191 of repaglinide (4 mg) administered to healthy subjects (n = 121). Table 3.25 Mean pharmacokinetic parameters of a single oral dose 193 of repaglinide (4 mg) administered to healthy subjects having the CYP2C8*2 genotype. Table 3.26 Mean pharmacokinetic parameters of a single oral dose 194 of repaglinide (4 mg) administered to healthy subjects having the CYP2C8*3 genotype. Table 3.27 Mean pharmacokinetic parameters of a single oral dose 195 of repaglinide (4 mg) administered to healthy subjects having the CYP2C8*5 genotype. Table 3.28 Mean pharmacokinetic parameters of a single oral dose 196 of repaglinide (4 mg) administered to healthy subjects having the CYP3A4*18 genotype.

xi Table 3.29 Comparison of the pharmacokinetic parameters of 197 repaglinide after a single dose of 4 mg between male and female healthy subjects. Table 3.30 Comparison of the pharmacokinetic parameters of 199 repaglinide after a single oral dose of repaglinide (4 mg) in Malay and other races healthy subjects.

xii LIST OF FIGURES

Page Figure 1.1 Chemical structure of repaglinide. 9 Figure 1.2 In vitro biotransformation pathways of repaglinide. 11 Figure 1.3 Simplified workflow for the whole study. 41 Figure 2.1 Chemical structures of indomethacin (internal standard). 48 Figure 2.2 Preparation of working standard solutions of repaglinide 49 and indomethacin. Figure 2.3 Flow chart of the liquid-liquid extraction method. 53 Figure 2.4 CYP3A4*4 gene sequence from position 13887 to 14130. 69 Figure 2.5 CYP3A4*5 gene sequence from position 15620 to 16080. 70 Figure 2.6 CYP3A4*18 gene sequence from position 168869 to 71 169256. Figure 2.7 Flowchart for pharmacokinetic and pharmacodynamic 88 studies. Figure 2.8 Boxes model used for the population pharmacokinetic 93 modeling of repaglinide. Figure 3.1 Spectrophotometry of internal standard,indomethacin 97 and repaglinide. Figure 3.2 Chromatograms of standard solutions of repaglinide and 98 indomethacin ran using different percentage of acetonitrile (ACN) : ammonium formate (AF) in the mobile phase a) ACN:AF; 60%:40%, b) ACN:AF; 50%:50%, and c) ACN:AF; 40%:60%. Figure 3.3a Chromatograms of standard solution of repaglinide and 100 indomethacin using pHs of the mobile phase, a) pH 2.5, b) pH 2.7 and c) pH 2.8. Figure 3.3b Chromatograms of standard solution of repaglinide and 101 indomethacin using different pH of mobile phase, a) pHs 2.9, b) pH 3.0 and d) pH 3.5. Figure 3.4 Chromatograms of standard solution of repaglinide and 102 indomethacin ran with different column temperature a) 30°C and b) 25°C. Figure 3.5 Chromatograms of standard solution of repaglinide and 103 indomethacin ran with mobile phase flow rates, a) 1 ml/min, b) 0.8 mllmin and c) 0.6 ml/min. Figure 3.6 Chromatogram of repaglinide (8.352 min) and 105 indomethacin (5.761 min) using ethylacetate as the extraction solvent. Figure 3.7 Chromatogram of repaglinide (8.362 min) and 106 indomethacin (5.771 min) using MTBE as the extraction solvent.

xiii Figure 3.8 Chromatogram of repaglinide (8.355 min) and 107 indomethacin (5.762 min) using diethyl ether as the extraction solvent. Figure 3.9 Chromatogram of repaglinide (8.361min) and 108 indomethacin (5. 772 min) using chloroform as the extraction solvent. Figure 3.10 Chromatogram of · repaglinide (8.311min) and 109 indomethacin (5.719 min) using dichloromethane as the extraction solvent. Figure 3.11 Percentage recoveries of indomethacin and repaglinide at 112 different plasma pHs using ethylacetate as the extracting solvent. Figure 3.12 Flow chart of liquid-liquid extraction method using 113 ethylacetate as the extracting solvent. Figure 3.13 Chromatograms showing a) blank human plasma, b) 114 plasma spiked with repaglinide (30 ng/ml) (6.202 min) and indomethacin (500 ng/ml)(5.383 min) and c) plasma sample from a healthy subject 30 min post repaglinide administration (4 mg oral dose). Repaglinide plasma concentration was determined to be 71.63 ng/ml. Figure 3.14 lntraday validation: calibration curves of area ratio of 115 repaglinide to indomethacin versus repaglinide's concentrations a) on validation day 1, b) on validation day 2 and c) on validation day 3. Figure 3.15 Chromatogram of gliclazide (80 mg/10 ml)(4.187 min), 121 indomethacin (500 ng/ml)(5.413 min) and repaglinide (200 ng/ml)(6.121 min). Figure 3.16 Chromatogram of prazosin (1 mg/10 ml)(4.193 min), 122 indomethacin (500 ng/ml)(5.422 min) and repaglinide (200 ng/ml) (6.122 min). Figure 3.17 Chromatogram of atorvastatin (10 mg/10 ml)(4.380 min), 123 indomethacin (500 ng/ml)(5.434 min) and repaglinide (200 ng/ml)(6.263 min). Figure 3.18 Chromatogram of paracetamol (500 mg/10 ml)(1.665 124 min}, indomethacin (500 ng/ml)(5.311 min) and repaglinide (200 ng/ml)(6.1 01 min). Figure 3.19 PCR1 (uniplex) products for CYP2C8 for exons 3, 5 and 130 8. Figure 3.20 PCR2 (uniplex) products for variant CYP2C8*2, *3 and *4 131 alleles. Figure 3.21 The effect of varying primer concentration for CYP2C8 132 PCR1 (multiplex) showing that primer concentration of 0.1 11M is the best for exon 3, primer concentration of 0.3 11M is the best for exon 8 and primer concentration of 1 11M is the best for exon 5.

xiv Figure 3.22 The effect of varying primer concentration for CYP2C8 133 PCR2 (multiplex) showing that primer concentration of 0.2 J.!M is the best for CYP2C8*2, CYP2C8*3 (exon 3) and CYP2C8*3 (exon 8) and primer concentration of 0.3 J.!M is the best for CYP2C8*4. Figure 3.23 The effect of varying primer concentrations for CYP3A4*4 135 showing that 0.1 J.!M gave the best band. Figure 3.24 The effect of varying primer concentrations for 136 CYP3A4*18 showing that 0.3 J.!M gave the best band. Figure 3.25 The effect of varying annealing temperature for CYP2C8 137 PCR2 (multiplex) showing that 64°C gave the best band with non-specific bands. Figure 3.26 The effect of varying annealing temperature for 138 CYP2C8*5 showing that 60°C gave the best band. Figure 3.27 The effect of varying annealing temperatures for 139 CYP3A4*5 showing that 64°C gave the best band. Figure 3.28 The effect of varying annealing temperatures for 140 CYP3A4*18 showing that 58°C gave the best band. Figure 3.29 The effect of varying Taq polymerase concentrations for 141 CYP2C8 PCR1 (multiplex) showing that 1.0 U gave the best bands. Figure 3.30 The effect of varying Taq polymerase concentrations for 142 CYP2C8 PCR2 (multiplex) showing that 2.0 U gave the best bands. Figure 3.31 The effect of varying Taq polymerase concentrations for 144 CYP3A4*4 showing that 1.0 U gave the best band. Figure 3.32 The effect of varying MgCI2 concentrations for CYP2C8 145 PCR 1 (multiplex) showing that 1.5 mM MgCI2 gave the best bands. Figure 3.33 The effect of varying MgCI2 concentrations for CYP3A4*4 146 showing that 1.5 mM MgCI2 gave the best band. Figure 3.34 The effect of varying MgCI2 concentrations for CYP3A4*5 147 showing that 1.5 mM MgCI2 gave the best band. Figure 3.35 Interpretation for gel electrophoresis products for 152 CYP2C8 (PCR2). Figure 3.36 Genotyping strategy for CYP3A4*4. 153 Figure 3.37 Genotyping strategy for CYP3A4*5. 155 Figure 3.38 Genotyping strategy for CYP3A4*18. 156 Figure 3.39 a) Multiplex PCR1 products for screening of samples for 157 CYP2C8. b) PCR2 products for wild type and variant CYP2C8*2 and CYP2C8*3 alleles. Figure 3.40 Allele-specific PCR analysis of CYP2C8*5. 158 Figure 3.41 a) PCR products for amplification using CYP3A4*4 162 primers b) RFLP results for wild-type CYP3A4*11*1 after digestion with BstMA I

XV Figure 3.42 a) PCR products for amplification using CYP3A4*5 163 primers. b) RFLP results for wild-type CYP3A4*11*1 after digestion with BshV I. Figure 3.43 a) PCR products for amplification using CYP3A4*18 164 primers. b) RFLP results for CYP3A4*18 allele after digestion with Hpa II. Figure 3.44 Direct sequencing results for the CYP3A4 allele. a) A 165 trace of a sample with a CYP3A4*11*1 genotype (wild type sequence) when amplified with CYP3A4*4 primers and b) A trace of a sample from a subject with a CYP3A4*11*1 genotype (wild type sequence) when amplified with CYP3A4*5 primers. Figure 3.45 Direct sequencing results for the CYP3A4 allele. a) A 166 trace of a sample with a CYP3A4*11*1 genotype and b) A trace of a sample from a subject with a CYP3A4*11*18 genotype. Figure 3.46 Mean (n = 121 ±SO) blood glucose levels-time profiles of 173 repaglinide among subjects for the first 4 h. Figure 3.47 Convergence plots of the normalised mean values of the 180 IT2B programme for ka, kel and Vd indicating that the model was stable by the time convergence was achieved after 39 cycles. Figure 3.48 Predicted versus observed concentrations found with the 181 IT2B programme using Bayesian prediction showing a good fit for the model (r = 0.95). Figure 3.49 Three-dimensional plot of Vd versus kel for IT2B. 183 Figure 3.50 Convergence plots of the normalised mean values of the 186 NPAG programme for ka, kel and Vd indicating that the model was stable by the time convergence was achieved after 500 cycles. Figure 3.51 Predicted versus observed concentrations found with the 187 NPAG programme using Bayesian prediction showing a good fit for the model (~ = 0.96). Figure 3.52 Three-dimensional plot of Vd versus kel for NPAG 189 showing a cluster of main population and the possible presence of two subpopulations having lower (A) and higher kel (B) values respectively.

xvi IT2B Iterative Bayesian Parametric Population Model

ka Absorption rate constant kb Kilobases

KCI Potassium Chloride kel Elimination rate constant

LOD Limit of detection

LOQ Limit of quantitation

IJI microlitres mM mililitres min minutes mt mutant

MTBE methyl t-butyl ether

NONMEM Nonlinear Mixed Effect Modelling

NPAG Nonparametric Adaptive Grid

NPEM Nonparametric Expectation Maximisation

NPML Nonparametric Maximum Likelihood

OD Optical Density

PASTRX A USC*PACK programme used for entry of past therapy data, creating and storing of patient data

PCR Polymerase Chain Reaction

Pmod Each fitted Bayesian posterior parameter value in the model

Ppop Each population (mean) parameter value

QC Quality control

RFLP Restriction fragment length polymorphism xviii LIST OF ABBREVIATIONS

ACN Acetonitrile

AF Ammonium formate

AUC Area under the serum concentration-time curve

AS-PCR Allele Specific-Polymerase Chain Reaction bp Base pair

COER Centre for Drug Evaluation Research

CL Clearance

Cmax Peak concentration in serum

Cmod Concentration in the Bayesian fitted model

Cobs Observed serum concentration cv Coefficient of variation

CYP Cytochrome P450

CYP2C8 Cytochrome P450 2C8

CYP3A4 Cytochrome P450 3A4

DNA Deoxyribonucleic acid dNTP Deoxyribonucleoside triphosphate

EDTA Ethylenediaminetetraacetic acid

FDA US Food and Drug Administration

G Gauge

GIT Gastrointestinal tract h Hours

HPLC High Performance Liquid Chromatography

xvii rpm Rotation per minute

RSD Relative standard deviation

SO Standard deviation

sec Seconds

SNP Single Nucleotide Polymorphism

STS Standard Two-Stage Approach

t112 Half-life

TE Tris-EDTA

TBE Tris-borate

Tm Melting temperature

tmax time to reach Cmax

U Units

USC*PACK a PC Programme created by the University of Southern California Laboratory of Applied Pharmacokinetics

UV Ultraviolet

V Volt

Vd Volume of distribution wt Wild type

xix Population Pharmacokinetics of Repaglinide in Healthy Subjects and Genetic Polymorphisms of CYP3A4 and CYP2CB

ABSTRACT

Repaglinide is a novel prandial glucose regulator (PGR) for the treatment of type 2 diabetes mellitus. Repaglinide is mainly metabolised in the liver by CYP3A4 and CYP2C8 enzymes. The objective of the present study is to investigate the effects of the CYP3A4 and CYP2C8 genotypes on the pharmacokinetics of repaglinide in 121 healthy Malaysian subjects.

The study protocol was approved by our local Research and Ethics

Committee, School of Medical Sciences, Universiti Sains Malaysia. Initially, a new

HPLC method using a simple liquid-liquid extraction for the determination of repaglinide in human serum was developed and later validated. Then, PCR methods were optimized to detect CYP3A4 and CYP2C8 genetic polymorphisms among healthy Malaysian subjects.

Each subject received 4 mg of oral repaglinide. Six blood samples per individual were taken (0 min, 30 min, 60 min, 120 min, 180 min and 240 min) for repaglinide's serum concentration determination by using HPLC. NPAG was then used to determine population pharmacokinetic parameter values of repaglinide.

The developed HPLC method was selective and calibration curves of repaglinide were found to be linear in the concentration range of 20-200 ng/ml. The limits of detection (LOD) and quantification (LOQ) were 10 ng/ml and 20 ng/ml, respectively. The inter-day precision was from 5.21% to 11.84% while the intra-day precision ranged from 3.90% to 6.67%. The inter-day accuracy ranged between

XX 89.95% and 105.75% with the intra-day accuracy ranging from 92.37% to

104.66%. No mutations were detected for the CYP3A4*4 and CYP3A4*5 alleles.

The allele frequency of the CYP3A4*18 allele was 2.07%. All five subjects with

CYP3A4*18 mutations were found to be heterozygous. For CYP2C8, the allele frequency for both CYP2C8*2 and *3 was 0.4% while the allele frequency for

CYP2C8*5 was 4.13%. All subjects with mutations were found to be heterozygous.

No mutation was detected for the CYP2C8*4 allele. CYP2C8 and CYP3A4 genotypes were not significantly associated with changes in the blood glucose lowering effect of repaglinide. On the other hand, the CYP3A4 genotype significantly influenced repaglinide's pharmacokinetics where the mean elimination rate constant (kel) was 34% lower (p = 0.04) and the mean half-life (t112) was 133% longer (p = 0.04) in subjects having the CYP3A4*11*18 genotype compared to those having the CYP3A4*11*1 genotype.

In conclusion, CYP3A4 activity plays an important role in influencing repaglinide's pharmacokinetics.

xxi Farmakokinetik Populasi Repaglinide di dalam Subjek Sihat dan Folimorfik Genetik CYP3A4 dan CYP2CB

ABSTRAK

Repaglinide adalah sejenis ubat pengawal glukosa prandial untuk merawat penyakit kencing manis jenis 2. Repaglinide dimetaboliskan di dalam hepar oleh enzim CYP3A4 dan CYP2C8. Tujuan kajian ini adalah untuk menyelidik kesan kedua-dua genotip CYP3A4 dan CYP2C8 ke atas farmakokinetik repaglinide di dalam 121 subjek sihat.

Kajian ini telah diluluskan oleh Jawatankuasa Etika, Pusat Pengajian Sains

Perubatan, Universiti Sains Malaysia. Kaedah HPLC menggunakan pengekstrakan cecair-cecair untuk penganalisaan repaglinide di dalam serum dibangunkan dan disahkan. Kemudian, kaedah PCR diubahsuai untuk menentukan polimorfisma genetik CYP3A4 dan CYP2,C8 di dalam subjek Malaysia yang sihat. Setiap subjek menerima 4 mg repaglinide secara oral. Enam sampel darah diambil daripada setiap subjek (0 min, 30 min, 60 min, 180 min dan 240 min) untuk analisa HPLC repaglinide di dalam serum.

Kaedah HPLC yang dibangunkan adalah selektif dan keluk kalibrasinya juga adalah linear bagi julat kepekatan repaglinide di antara 20 sehingga 200 ng/ml.

Tahap pengesanan paling minimum ialah 10 ng/ml manakala tahap kuantitasi paling minimum ialah 20 ng/ml. Kejituan dalam sehari adalah di antara 5.21% hingga 11.84% manakala kejituan di antara hari mempunyai julat di antara 3.90% sehingga 6.67%. Manakala ketepatan dalam sehari berjulat di antara 89.95% dan

xxii 105.75% dan ketepatan di antara hari pula mempunyai julat di antara 92.37% sehingga 104.66%.

Tiada mutasi ditemui untuk aiel CYP3A4*4 dan CYP3A4*5. Frekuensi aiel

CYP3A4*18 di dalam populasi Malaysia ialah 2.07%. Kelima-lima subjek yang mempunyai mutasi CYP3A4*18 adalah heterozigot. Frekuensi aiel bagi CYP2C8*2 dan *3 adalah masing-masing 0.4% dan frekuensi aiel bagi CYP2C8*5 ialah

4.13%. Kesemua subjek yang mempunyai mutasi adalah heterozigot. Tiada mutasi ditemui untuk aiel CYP2C8*4. Genotip untuk CYP2C8 dan CYP3A4 tidak signifikan

untuk perubahan di dalam kesan penurunan glukosa darah repaglinide. Manakala bagi genotip CYP3A4 terdapat perbezaan yang signifikan di dalam farmakokinetik repaglinide di mana purata kadar konstan eliminasi repaglinide (kel) adalah 34% lebih rendah (p = 0.04) dan jangka masa separuh hayat (t112) pula adalah 133% lebih panjang (p = 0.04) di dalam subjek yang mempunyai genotip CYP3A4*11*18 berbanding subjek normal.

Kesimpulannya, aktiviti CYP3A4 memainkan peranan yang penting dalam mempengaruhi farmakokinetik repaglinide.

xxiii PUBLICATIONS AND PRESENTATIONS

PUBLICATIONS

Full articles

1) Ruzilawati, A. B, Suhaimi A. W., lmran, A., Ismail, Z. and Gan, S. H. (2007). Method development and validation of repaglinide in human plasma by HPLC and its application to pharmacokinetics study, Journal of Pharmaceutical and Biomedical Analysis 43(5), 1831-1835. (2007 Impact Factor- 2.761). - Received Hadiah Sanjungan USM 2007 (publication category).

2) Ruzilawati, A. B., Mohd Suhaimi A. W. and Gan, S. H. (2007). Genetic polymorphisms of CYP3A4: CYP3A4*18 allele is found in five healthy Malaysian subjects, Clinica Chimica Acta 383,158-162. (2007 Impact Factor - 2.601). Received Hadiah Sanjungan USM 2007 (publication category).

Abstracts

1) Ruzilawati, A. B., Gan, S. H., Mohd. Suhaimi, A. W. and Ismail, Z. Method development and validation of HPLC method for repaglinide in human plasma. The Malaysian Journal of Medical Sciences, Vol. 13, No. 2, July 2006.

2) Ruzilawati, A. B., Mohd. Suhaimi, A. W., lmran, A., Ismail, Z. and Gan, S. H. Validated HPLC method for determination of repaglinide in human plasma using liquid-liquid extraction. British Journal of Pharmacology- in press.

3) Ruzilawati, A. B., Mohd. Suhaimi, A. W. and Gan, S. H. Effects of CYP3A4*18 on repaglinide's pharmacokinetics. Drugs Metabolism Reviews, Vol. 40 (Supplement 1), 2008. (2006 Impact Factor- 6.238).

xxiv ORAL AND POSTER PRESENTATIONS AT SCIENTIFIC MEETINGS

1) Ruzilawati, A. B., Gan, S. H. and Ismail, Z. Method development and validation of HPLC method for repaglinide in human plasma. Presented at 1st North-South Conference and Workshops on Pharmacogenetics, Holiday Villa, Subang Jaya, Selangor, 12-13 December 2005. (poster presentation).

2) Ruzilawati, A. B., Mohd. Suhaimi, A. W., lmran, A., Ismail, Z. and Gan, S. H. Validated HPLC method for determination of repaglinide in human plasma using liquid-liquid extraction. 1 Presented at 75 h Anniversary British Pharmacological Society (BPS) Winter Meeting, University of Oxford, United Kingdom, 18-21 December 2006. (poster presentation).

3) Ruzilawati, A. B., Mohd. Suhaimi, A. W. and Gan, S. H. Genetic polymorphisms of CYP3A4 in healthy Malaysian subjects. Presented at th National Congress on Genetics, Renaissance Hotel, Kota Bharu, Kelantan, 5-7 May, 2007. (oral presentation).

4) Ruzilawati, A. B., Mohd. Suhaimi, A. W. and Gan, S. H. CYP2C8 genotyping among healthy subjects in Malaysia. Presented at th National Congress on Genetics, Renaissance Hotel, Kota Bharu, Kelantan, 5-7 May, 2007. (poster presentation).

5) Ruzilawati, A. B., Mohd. Suhaimi, A. W., and Gan, S. H. Effects of CYP3A4*18 on repaglinide's pharmacokinetics. 1 Presented at 1 0 h European Regional Meeting, International Society for the Study of Xenobiotics (ISSX), Vienna, Austria, 18-21 May 2008. (poster presentation).

6) Ruzilawati, A. B., Mohd. Suhaimi, A. W. and Gan, S. H. CY3A4 and CYP2C8 genotypes and blood glucose levels in healthy subjects administered with repaglinide. Presented at 2"d National Conference on Medical Laboratory Sciences, Grand Riverview Hotel, Kota Bharu, Kelantan, 4-6 November 2008. (poster presentation).

XXV CHAPTER 1

INTRODUCTION AND LITERATURE REVIEW

1.1 Diabetes mellitus

1.1.1 Classification of Diabetes mellitus

Diabetes means high blood sugar (glucose) or hyperglycaemia due to absolute or relative lack of insulin or insulin resistance (Tattersall, 1986, Rang &

Dale, 1993). According to Rang & Dale (1993), hyperglycaemia occurs because the liver and skeletal muscles cannot store glycogen and the tissues are unable to utilise glucose.

It is the leading cause of kidney failure (DeFronzo, 1995) and blindness

(Neely et a/.,1998). It is also a major risk factor for heart diseases and stroke

(Mafauzy, 2006a, Pertussona eta/., 2008). In Malaysia, the First National Health and Morbidity Survey (NHMS 1) conducted in 1986 reported a prevalence of diabetes of 6.3% and in the Second National Health and Morbidity Survey (NHMS

2) in 1996, the prevalence had risen to 8.2% (Zaini, 2000, Mafauzy, 2006b). In a study in Kelantan, the prevalence was reported to be higher at 10.5% (Mafauzy et a/., 1999)

Basically, there are two types of diabetes, Type 1 and Type 2 (Tattersall,

1986, Kilo & Williamson, 1987, Rang & Dale, 1993). Both have similar symptoms but their causes are different (Kilo & Williamson, 1987).

1 In Type 1 or juvenile onset diabetes, the insulin-producing 13-cells of pancreas (i.e the Islet of Langerhans) are destroyed and produce little or no insulin at all. This type of diabetes is most common in the young. It is also known as

Insulin-Dependent Diabetes Mellitus (IDDM) since the only treatment is by injection of insulin because all of the 13-cells have been destroyed.

Type 2 or maturity onset diabetes is also known as Non-Insulin-Dependent

Diabetes Mellitus. It occurs mainly in people over the age of 35 and usually in those who are fat (Kilo & Williamson, 1987). Their 13-cells of pancreas can produce some insulin but it is insufficient. NIDDM can be treated either by reducing the body's need for insulin (by losing weight or eating Jess) and/or stimulating the pancreas with one of the many medications available today for example sulphonylurea in order to produce more insulin. They usually do not require insulin injection.

The number of diabetic individuals will continue to increase worldwide.

According to estimations of the World Health Organization (WHO), in 1995 there were more than 135 million adults suffering from diabetes worldwide (King et a/.,

1995). According to WHO, it is projected that the total number of individuals with diabetes will rise to about 300 million in 2025 (King eta/., 1995).

2 1.1.2 Oral antidiabetic drugs

1.1.2.1 General aspects

The first attempts to treat human diabetes by orally-active drugs were made between 1925 and 1930 from synthalines and their derivatives. However, only in

1940's that carbutamide and tolbutamide were used for antihyperglycaemic activity

(Loubatieres, 1969). These are the first sulphonamide derivatives.

Currently, there are five groups of oral antidiabetics in clinical use

1) Sulphonylureas

2) Biguanides

3) Alpha-glucosidase inhibitor

4) Thiazolidinediones

5) Meglitinides analogue

1.1.2.2 Sulphonylureas

Oral antidiabetic drugs of the sulphonylurea family have been successfully used for the treatment of type 2 diabetes mellitus for more than four decades

(Wascher & Boes, 2003). Their popularity is based on their ease of administration, reliable effectiveness and lack of symptomatic side effects other than hypoglycaemia (Groop, 1992). They are still the most favourable treatment approach. Sulphonylurea is an oral antidiabetic drug that acts mainly by increasing endogenous insulin secretion.

3 Sulphonylureas stimulate insulin release from ~-cell of the pancreas via binding to a sulphonylurea receptor (SUR1), thus blocking KATP channel which then leads to ~-cell depolarization, influx of calcium into the cells and eventual release of insulin (Ashcroft & Gribble, 1999). All sulphonylureas lower blood glucose levels in normal and in many patients with NIDDM. The two most popular sulphonylureas used to date are glibenclamide and gliclazide (Levy, 1999). According to Berger

(1985), sulphonylureas are safe and effective drug for long-term treatment of diabetes.

1.1.2.3 Biguanides

The only biguanide drug currently in use in many countries is metformin

(Berger, 1991 ).

Biguanides do not affect glycaemia in normal individuals, but they exert a reproducible hypoglycaemic effect in hyperglycaemic patients. They only give peripheral effects (i.e does not stimulate insulin release (Levy, 1999) but they increase muscle glucose uptake and metabolism and decrease hepatic glucose production (gluconeogenesis) (Schafer, 1979, Dunn & Peters, 1995, Levy, 1999).

According to Dunn & Peters (1995), biguanide is not metabolised to a significant extent and is primarily excreted unaltered in the urine. Biguanides work synergistically with the sulphonylureas.

4 1.1.2.4 Alpha-glucosidase inhibitor

The a-glucosidase inhibitor inhibits enzymes that break down polysaccharides and sucrose in the small intestine leading to a slow down of glucose absorption from the gut (Balfour & McTavish, 1993, Levy, 1999). The first of the a-glucosidase inhibitor in clinical use was acarbose (Creuzfeldt, 1988,

Balfour & McTavish, 1993). It is eliminated through two ways. The first is via

intestinal digestive enzymes cleavage and the second is via biotransformation of the intestinal bacteria. According to Balfour & McTavish (1993), only trace amounts of unaltered acarbose are absorbed from the gastrointestinal tract into the systemic circulation.

Miglitol is a newer a-glucosidase inhibitor (Levy, 1999). It has a similar action as acarbose but it is almost completely absorbed from the gastrointestinal tract (GIT), so it has higher bioavailability. Miglitol is not metabolised and is excreted unaltered (Scott & Spencer, 2000).

1.1.2.5 Thiozolidinedione (TZD)

Thiozolidinedione (TZD) is peroxisome proliferator-activated receptor gamma (PPARy) activator which was introduced in 1997. Rosiglitazone, traglitazone and pioglitazone are three examples of a TZD. They enhance the effects of insulin on cellular glucose and lipid metabolism. They are extensively metabolised in the liver (Mudaliar & Henry, 2001 ).

5 1.1.2.6 Meglitinide analogues

Meglitinides have a mechanism of action similar to that of the sulphonylureas, but are more rapidly absorbed and eliminated (Biickie, 2006). They are taken with meals and due to their shorter duration of action, pose a smaller risk for hypoglycaemia (Dornhorst, 2001 ). Therefore, compared with sulphonylureas, meglitinides have been shown to provide a better control of postprandial hyperglycaemia and better adverse effects profile with a more favourable safety profile, especially in patients with renal failure (Scheen, 2007).

Repaglinide, a benzoic acid derivative, was the first member of the meglitinide class. It was introduced in 1998. Nateglinide is a derivative of the amino acid phenylalanine and was introduced to the market in 2001 (Levine & Burns, 2001).

Repaglinide can be used as monotherapy or in combination with metformin

(Moses, 1999) whereas nateglinide is authorised only in combination therapy with metformin (Biickie, 2006). Both are actively metabolised in the liver and are rapidly eliminated with repaglinide having a half-life (t112) of only 1 h compared to 1. 7 h for nateglinide (Culy & Jarvis, 2001, Mcleod, 2004).

1.2 Repaglinide

The long plasma half-lives and the long lasting effects of some sulphonylureas for example 4 h for glipizide and 16 h for gliclazide (Yang eta/., 2007) increase the risk of hypoglyceamia (Melander et a/., 1989, Hatorp et a/., 1999). This risk is greatest among elderly patients (Berger, 1985). In up to 20% of patients treated 6 for six months, mild hypoglycaemia develops (Jennings eta/., 1989). The incidence

of severe hypoglycaemia is approximately 0.2 per 1000 patients per year (Berger,

1985). Moreover, the use of sulphonylureas can cause weight gain (Natrass,

2000).

Therefore, the usage of new agents with shorter half-lives in order to reduce

the risk of hypoglycaemia is highly recommended. The usage of a new agent,

repaglinide which has a half-life of 1 h with less hypoglycaemic effects, especially

in elderly subjects with type 2 diabetes were recommended by the American

Diabetes Association and the European Type 2 Policy Group (Alberti & Gries,

1998).

1.2.1 Therapeutic uses

Repaglinide is a novel prandial glucose regulator (PGR) for the treatment of

type 2 diabetes mellitus (Marbury et a/., 2000, Hatorp, 2002). It reduces glucose

concentrations in patients with type 2 diabetes mellitus (Natrass, 2000) and is used

when diet, exercise and weight reduction have not been found to control blood

glucose well enough on their own. It helps to control blood sugar by increasing the

amount of insulin released by the pancreas.

7 1.2.2 Formulation, chemical properties and stability

Repaglinide is a new carbomoxylmethyl benzoic acid derivative chemically known as 2-ethoxy-4-[2-[[3-methyl-1-[2-(1-piperidinyl) phenyl] butyl] amino]-2- oxoethyl] (Figure 1.1). It is an (S)(+)-enantiomer.

Repaglinide is a white to off-white powder with shaped crystals. It is slightly soluble in aqueous acid, very soluble in aqueous phase and freely soluble in methanol and ethanol.

It is called Prandin in the United States, NovoNorm in Europe and

Gluconorm in Canada.

1.2.3 Mechanism of action

Repaglinide is a non-sulphonylurea oral hypoglycaemic agent that is rapidly absorbed. It stimulates pancreatic insulin secretion via the sulphonylurea receptor.

According to Dornhorst (2001 ), this receptor is a subunit of the ATP-sensitive potassium channel (KATP channel). It produces a hypoglycaemic effect by stimulating insulin secretion from the pancreatic p-cell (Henquin eta/., 1987, Levy,

1999). It initiates insulin secretion by closing the KATP channel (Dornhorst, 2001 ).

When the sulphonylurea binds to the p-cell it leads to depolarisation of the p-cell with influx of calcium ions and secretion of insulin from its cell.

8 0

OH

0

~CH 3

Figure 1.1 Chemical structure of repaglinide

9 1.2.4 Pharmacokinetics properties

Previous clinical trials have shown that repaglinide is rapidly absorbed from the gastrointestinal tract after oral administration. The peak plasma concentration is reached 30-60 min after administration (Guay, 1998). After reaching the peak, plasma levels decrease rapidly and the drug is eliminated within 4 to 6 h. Its absolute bioavailability is 63% but its absorption is not affected by food. The half­ life of repaglinide is about 1 h (Hatorp eta/., 1998). Repaglinide has low volume of distribution (Vd) which is about 24.4 L at steady state (Hatorp, 2002). In human, it is highly bound (more than 98%) to plasma protein albumin.

Repaglinide is mainly metabolised in the liver by an · oxidative biotransformation (Gaal eta/., 2001 ). Repaglinde is eliminated by metabolism to at least five different metabolites, as shown in vivo (van Heiningen et a/., 1999) and in vitro (Bidstrup eta/., 2003). Repaglinide is metabolised by formation of an aromatic amine (M1), opening of the piperadine ring to form a dicarboxylic acid (M2), hydroxylation of the piperadine ring (M4), de-ethylation (M5), formation of a tauride

(M6), formation of an acylglucuronide (M7) and by N-oxidation (M12) (Bidstrup et a/., 2003). M1 is formed directly from repaglinide, or by oxidative N-dealkylation from M2. In vitro, repaglinide (MO) can also be metabolised to MO-OH (Bidstrup et a/., 2003) (Figure1.2).

10 wcoo• Q t aJ \14

r(2C813A4)

COOH I (3A4) )v(X= (2C8/3A4) OH 4'11-­ H '0 6 l Rcpaglinid(' (~10) ~fti.OII (3A4'7 ~M(~ ex> ~ ---+ ~COOH M2

Figure 1.2 In vitro biotransformation pathways of repaglinide (Bidstrup eta/., 2003)

11 The most important enzymes participating in the biotransformation of repaglinide are cytochrome P450 3A4 or CYP3A4 and cytochrome P450 2C8 or

CYP2C8 (Bidstrup eta/., 2003).

In human, the main metabolites of repaglinide are (M2) (about 66% of the dose), an aromatic amine (M1) (about 4% of the dose) and M4, while other metabolites are produced only in small amounts. However, none of its metabolites contributes to its blood-glucose-lowering activity.

In vitro, both CYP3A4 and CYP2C8 have been shown to catalyse the biotransformation of repaglinide to its major metabolites, with M1 and M2 mainly formed by CYP3A4 and M4 mainly by CYP2C8. In vitro, CYP3A4 and CYP2C8 contribute similarly to the metabolism of therapeutic repaglinide concentrations, with no significant biotransformation by other CYP enzymes (Kajosaari et a/.,

2005a).

Repaglinide is excreted primarily through the bile (98%) (Owens, 1999).

Only a very small fraction (less than 8%) of the administered dose is excreted through the urine (van Heiningen eta/., 1999). In the faeces, the major metabolite was M2 (66% of administered dose) (van Heiningen eta/., 1999).

According to Marbury eta/. (2000), because repaglinide is mostly eliminated by non-renal routes, it may be an appropriate treatment for elderly subjects with renal impairment. Impaired renal function may result in greatly reduced excretion, 12 thus leading to accumulation of drug and also increasing the risk of hypoglycaemia

(Marbury et a!., 2000). If repaglinide is used in patients with severely-impaired

renal function, dose adjustments may be necessary if indicated by blood glucose

levels (Schumacher eta/., 2003). The pharmacokinetics of repaglinide are similar

in both young and elderly healthy subjects (Hatorp et a/., 1999}. The

pharmacokinetic parameters as obtained from studies done by Hatorp eta!. (1999}

and Marbury et a!. (2000) following a 2 mg oral single-dose of repaglinide are

shown in Table 1.1.

1.2.5 Dosage and administration

Repaglinide should be taken before main meals (preprandially). It is ideally

consumed 10 to 15 min before meals. According to Natrass (2000), it can be taken

up to 30 min before a meal. It affects around meal time glucose load which is

important to the treatment of type 2 diabetes mellitus. If a meal is skipped, the dose

should also be skipped. Thus, repaglinide offers a treatment which can be adjusted

to suit each individual's lifestyle (Damsbo eta/., 1999).

For na"ive patients (HbA 1c < 8%}, 0.5 mg of the dose should be taken

before each meal whereas for patients previously treated with oral hypoglycaemic

agents, the recommended dose is 2 mg before each meal (Hatorp, 2002). The

recommended maximum single dose is 4 mg. The total maximum single dose per

day should not exceed 16 mg (Novo Nordisk, 1998}.

13 Table 1.1 Values for serum repaglinide pharmacokinetic variables following a 2 mg oral dose (single-dose regimen) (Hatorp eta/., 1999, Marbury eta/., 2000).

Parameters Value Range (min- max)

AUC (ng/ml per h) 69. 0 ± 78.0 12.0-302.0

Cmax (ng/ml) 47.9 ± 32.0 18.0 - 127.0 tmax (h) 0.8 ± 0.6 0.5-2.5 t1/2 (h) 1.0 ± 0.2 0.7-1.3 kel (L/h) 0.37 0.18-0.60

Vd (L) at steady state 24.4

Vd (L) at elimination phase 28.9

CL (Lih) 33.0

Data are means ± standard error except where indicated

AUC - area under the serum concentration-time curve Cmax - peak serum concentration lmax - time to reach Cmax t112 - half-life ke,- elimination rate constant Vd - apparent volume of distribution CL - clearance

14 1.2.6 Drug interactions

The effect of CYP inhibition and induction on the pharmacokinetics of repaglinide have been studied in several cross-over studies in healthy volunteers.

The CYP3A4 inhibitors clarithromycin, itraconazole, and ketoconazole have all been shown to moderately increase repaglinide's plasma concentrations (Niemi et a/., 2001, Hatorp, eta/., 2003, Niemi eta/., 2003). Clarithromycin and itraconazole increase repaglinide's AUC by about 40% (Niemi eta/., 2001, Niemi eta/., 2003) and ketoconazole by 15% (Hatorp, et a!., 2003). Gemfibrozil, a CYP2C8 inhibitor, increases repaglinide's AUC by 8-fold, considerably prolonging and enhancing the blood glucose-lowering effect of repaglinide (Niemi eta/., 2003). Combination of gemfibrozil and itraconazole causes a nearly 20-fold increase in repaglinide's AUC, and further enhances repaglinide's blood glucose lowering effect (Niemi et a/.,

2003). In patients taking both gemfibrozil and repaglinide, serious hypoglycaemic events have been reported (Laine eta!., 2003). The CYP3A4 inducer rifampicin decreases repaglinide's plasma concentrations and similar effects are expected with other CYP3A4 inducers. In one study, when repaglinide was administered 12 h after the last rifampicin pre-treatment dose, repaglinide's AUC was reduced by

57% (Niemi et a/., 2000) whereas in another study when repaglinide was administered simultaneously with the last rifampicin dose, a 31% reduction of repaglinide's AUC was seen (Hatorp, et a/., 2003). Possible drug interactions between repaglinide and a CYP inhibitor cimetidine, CYP3A4 substrates ethinyloestradiol (also a CYP2C9 and CYP2C19 inhibitor) (Laine et a/., 2003), simvastatin and nifedipine, and drugs with narrow therapeutic indices (digoxin,

15 theophylline or warfarin) have also been investigated. However, no significant pharmacokinetic changes were observed (Hatorp, eta/., 2000).

1.2. 7 Adverse effects

Repaglinide is well tolerated when taken orally (Culy & Jarvis, 2001). A study done by Marshall et a/. (2006) in general practice in England reported that the most frequent adverse drug reactions were diarrhoea, followed by abdominal pain nausea and vomiting. Adverse events of hypoglycaemia are similar to those caused by sulphonylurea treatment with serious hypoglycaemic effects occurring more with sulphonylureas than repaglinide.

1.2. 7 Contraindications

Repaglinide is contraindicated in patients with hypersensitivity to the drug

(Novo Nordisk, 1998). Patients who suffer from diabetic ketoacidosis should be treated with insulin and should not use repaglinide. The safety of repaglinide in pregnant women has not been established and therefore it is not recommended for use during pregnancy as the potential for low blood glucose in nursing infants may exist. This drug has not been studied in children and is therefore best avoided in this group of people. Patients with hepatic disorders should also not use this drug.

16 1.3 Pharmacokinetics, drug metabolism and pharmacogenetics

1.3.1 Pharmacokinetics

Measurement of drug concentrations in the blood, serum or plasma is the most direct approach of assessing· the pharmacokinetics of drugs in the body

(Shargel & Yu, 1999). Sensitive, accurate, precise analytical methods are required for the direct measurement of drugs in biologic samples. Thus, in this study, high­ performance liquid chromatography (HPLC) was used for the determination of serum repaglinide's levels.

1.3.2 Drug metabolism and CYP enzyme system

All drugs are eliminated from the body by excretion and metabolism. Most drugs are lipid soluble compounds, which require biotransformation into more hydrophilic form before they can be excreted from the body (Sweeney & Bromilow,

2006). Drugs are most often metabolised in the liver by enzymes localised in the endoplasmic reticulum of hepatocytes. Drug metabolism can also occur in other tissues, for example the gastrointestinal tract, lungs and kidneys.

Drug metabolism can generally be divided into Phase I reactions (oxidation, reduction or hydrolysis) . and Phase II reactions (acetylation, glucuronidation, sulphation and methylation). Phase II may precede Phase I and occurs without prior oxidation, reduction or hydrolysis if there are polar compounds (Sweeney &

Bromilow, 2006). Both, most often, convert relatively lipid soluble drugs into relatively more water soluble or hydrophilic metabolites.

17 The cytochrome P450 (CYP) system is the most important xenobiotic metabolising system. Approximately 80-90% of human drug metabolism is GYP­ mediated (Wong et at., 1991, Anzenbacher & Anzenbacherova, 2001). Most of the

CYP-catalysed reactions lead to detoxification of xenobiotics.

The CYP enzymes are a superfamily of heme-containing enzymes that are found on the endoplasmic reticulum. These isoenzymes are so called because· they have a spectrophotometric absorption peak at or near 450 nm when bound and reduced by carbon monoxide (Nebert & Gonzalez, 1987). The most important property of all known P450s is their ability to bind and activate two atoms of oxygen in a drug molecule (Anzenbacher & Anzenbacherova, 2001). The CYPs constituting a family should have 40% similar sequences in their overlapping portions while a subfamily is created based on higher degree (55%) of sequence similarity (Anzenbacher & Anzenbacherova, 2001 ).

To date, a total of 57 CYP enzymes have been identified in humans

(lngelman-Sundberg et a/., 2000). The families CYP1, CYP2, and CYP3 are primarily associated with the metabolism of exogenous compounds, whereas the other CYPs have mainly endogenous roles (lngelman-Sundberg eta/., 2000).

The CYPs are found primarily in the liver and the gut mucosa and also can be found in the lungs, the kidney, the small intestines and brain in a small amount

(Zagaria, 2004). In the liver, CYP3A4 is quantitatively the most important, with

CYP2C8, CYP2C9, CYP2A6, CYP2E1 and CYP1A2 present in somewhat lower

18 quantities; CYP2C19 and CYP206 are of relatively minor quantitative importance, but their clinical importance is high (Shimada eta/., 1994). CYP3A4 is the major form of CYP expressed in enterocytes, and members of CYP2C subfamily are also significantly expressed (Zhang et a/., 1999). Table 1.2 lists some of the CYP enzymes responsible for metabolic transformation of drugs.

1.3.3 Pharmacogenetics

Drug levels in plasma may vary more than 1000-fold between two individuals having the same weight and with the same drug dosage (lngelman­

Sundberg, 2001 ). This interindividual variation is caused by several factors which can be divided into physiological and environmental (McKinnon & Evans, 2000,

Koo & Lee, 2006). Physiological factors include age, gender, ethinicity, genetic factors and body weight while environmental factors include nutritional status, concurrent drug therapy and exposure to certain chemicals.

The term "polymorphism" is used to describe allelic variant that are detected in more than 1% of a given population (Roden, 2001 ). Genetic polymorphism is a common source of interindividual difference in drug metabolism (lnaba et a/.,

1995). Much of this variation has shown to be caused by genetic polymorphisms of the CYP enzymes (Nebert & Gonzalez, 1987).

19 Table 1.2 Some example of human P450 enzymes (Anzenbacher & Anzenbacherova, 2001).

CYP Localisation

CYP 1A1 lung, liver, brain, GIT, lymphocytes, heart

CYP 1A2 liver

CYP 181 skin, brain, heart, lung, placenta, liver, kidney, GIT, spleen

CYP 2A6 liver

CYP 281/2 brain

CYP 286 liver, heart

CYP 2C8 liver, kidney, intestines, adrenal gland, brain, mammary gland, ovary

CYP 2C9/10 liver

CYP2C19 liver, heart

CYP206 liver, brain, heart

CYP2E1 liver, lung, brain, endothelium, heart, bone marrow

CYP2F lung

CYP3A4/5 liver, GIT, kidney, lung, brain, endothelium, placenta, lymphocytes

CYP3A7 fetus, placenta, liver

CYP4A9/11 kidney

CYP481 lung, placenta

CYP4F2/3 kidney

20 Depending on their metabolic status, humans are divided into poor metaboliser (PM), an intermediate metaboliser (IM), an extensive metaboliser (EM) or an ultra-rapid (ultra-extensive) metaboliser (UM). The poor metabolisers and intermediate metabolisers express dysfunctional or inactive enzymes. They possess the homozygous autosomal recessive allele (usually mutant alleles)

(lngelman-Sundberg & Evans, 2001 ). Extensive metabolisers have enzymes with normal activity. They have the heterozygous or homozygous dominant allele. At the extreme of the EM phenotype, gene amplification gives rise to the so-called ultra-rapid metabolisers. These individuals carry replicate functional copies of the genes (lngelman-Sundberg & Evans, 2001 ).

The most common types of polymorphisms are "single nucleotide polymorphisms", known as SNPs. Polymorphisms may be present in introns or exons. When they are present in exons, they may result in an amino acid change or no change at all. When they are present in introns, they may still regulate gene expression (splicing) (Aithal eta/., 1999).

Pharmacogenetics is best defined as the study of genetic variations that cause variation in drug response and includes the genetic polymorphism of drug transporter, drug metabolising enzymes and drug receptors (lngelman-Sundberg,

2001). The aim of pharmacogenetics is to aid physicians in prescribing the appropriate dose of the right medicine to a person in an attempt to obtain maximum efficacy and minimum toxicity based on genetic tests (Koo & Lee, 2006).

Individuals who inherit the deficiency in the enzyme may benefit from appropriately 21 adjusted doses of the affected drugs based on genetic tests. Pharmacogenetics is a growing discipline with great potential of improving human health-care, in terms of understanding individual drug responses, adverse drug reactions associated with genetics so that medicine could be tailored accordingly to prevent side effects and thus reducing cost of therapy. It becomes more important when the prescribed drugs have narrow therapeutic indexes and are metabolised by polymorphic enzymes as with repaglinide.

1.3.3.1 Genetic polymorphisms of CYP2CB

There are four known human CYP2C enzymes: CYP2C8, CYP2C9,

CYP2C18 and CYP2C19. These enzymes are responsible for the metabolism of about 20% of clinically described drugs (Evans & Reiling, 2004).

CYP2C8 is the major human hepatic P450, constituting about 12% of total microsomal CYP content in the liver (Rendic & Carlo, 1997) in which it conducts oxidative metabolism of at least 5% of drugs cleared by phase I metabolism. It can also be found in other tissues including the kidney, intestines, adrenal gland, brain, mammary gland, ovary and heart as well as in breast cancer tumours (Klose eta/.,

1999, Nishimura eta/., 2003, Knupfer eta/., 2004).

Drugs for which CYP2C8 contributes significantly to their biotransformation include the anticancer drug paclitaxel (Sonnichsen eta/., 1995, Dai eta/., 2001), the antidiabetic drug rosiglitazone and troglitazone (Yamazaki et a/., 1999) and

22 repaglinide (Bidstrup et at., 2003), the antimalarial amodiaquine (Dai et a/., 2001) and the hydroxymethylglutaryl co-enzyme A reductase inhibitors such as cerivastatin and fluvastatin (Muck, 2000, Wang et a/., 2002). Table 1.3 lists examples of some substrates, inhibitors and inducers of CYP2C8.

CYP2C8 is located on chromosome 1Oq24.1 and consists of nine exons

(Dai et at., 2001). The CYP2C enzymes are all genetically polymorphic with 20

SNPs identified thus far (Totah & Rettie, 2005). An updated list of allelic variant is available at (www.imm.ki.se/CYPalleles).

The most common variant alleles are CYP2C8*2 and CYP2C8*3.

CYP2C8*2 has an lle269Phe substitution in exon 5. CYP2C8*2 is expressed in black populations with an allele frequency of 18% but is very rare among white subjects (Dai et at., 2001). CYP2C8*3 includes both Arg139Lys and Lys399Arg amino acid substitutions in exons 3 and 8 and is expressed most commonly in white subjects (allele frequency, 23%). It is quite rare in black subjects (allele frequency, 2%) and appears to be absent in Japanese subjects (Dai eta/., 2001).

CYP2C8*4 represents a mutation that causes an amino acid change lle264Met in exon 5 and has a frequency of 8% in white subjects (Bahadur eta/., 2002). The

CYP2C8*5 variant has a base deletion at position 475 resulting in a frameshift at

23 Table 1.3 Examples of some substrates, inhibitors and inducers of CYP2C8

Substrates Inhibitors Inducers

Amodiaquine Gemfibrozil Rifampin

Cerivastatin Glitazones Phenobarbital

Montelukast Quercetin

Paclitaxel Trimethoprim

Repaglinide

Rosiglitazone

Troglitazone

24