Drug Bioavailability

Han van de Waterbeemd studied physical organic chemistry at the Technical University of Eindhoven, and gained his PhD in medicinal chemistry from the University of Leiden. After an academic career at the University of Lausanne with Bernard Testa, he worked for 20 years in the pharmaceutical industry for Roche, Pfizer and AstraZeneca. His research interests are in optimizing compound quality using measured and predicted physicochemical and DMPK properties. He has contributed to 145 research papers and book chapters, and (co-)edited 13 books, and was involved in organizing conferences and courses to promote medicinal chemistry, with a focus on physicochemistry and predictive approaches in drug design. Dr. van de Waterbeemd is on the editorial board of several journals and of Methods and Principles in Medicinal Chemistry.Bernard Testa is Emeritus Professor of the University of Lausanne, having served there for 25 years as a full professor and head of medicinal chemistry. He has written 5 books and edited 33 others, and (co)-authored well over 450 research and review articles in the fields of drug design and drug metabolism. Between 1994 and 1998, he was the European Editor of Pharmaceutical Research, and is now a senior editor of Chemistry and Biodiversity, as well as serving on the editorial boards of several leading journals. Professor Testa holds honorary doctorates from the universities of Milan, Montpellier and Parma, and is a recipient of the Nauta Award on Pharmacochemistry given by the European Federation for Medicinal Chemistry.

"The book covers a wide range of topics and, as such, it will serve as a valuable reference for pharmaceutical scientists, toxicologists, academicians, and the graduate students." (Doody's, May 2009)

• List of Contributors XIXPreface XXIIIA Personal Foreword XXV1 Introduction: The Why and How of Drug Bioavailability Research 1Han van de Waterbeemd and Bernard Testa1.1 Defining Bioavailability 11.1.1 The Biological Context 11.1.2 A Pharmacokinetic Overview 31.1.3 Specific Issues 31.2 Presentation and Layout of the Book 4References 6Part One Physicochemical Aspects of Drug Dissolution and Solubility 72 Aqueous Solubility in Drug Discovery Chemistry, DMPK, and Biological Assays 9Nicola Colclough, Linette Ruston, and Kin Tam2.1 Introduction 102.1.1 Definition of Aqueous Solubility 112.1.2 Aqueous Solubility in Different Phases of Drug Discovery 122.2 Aqueous Solubility in Hit Identification 122.2.1 Aqueous Solubility from DMSO Solutions 132.2.1.1 Turbidimetric Methods 142.2.1.2 UV Absorption Methods 152.2.1.3 Alternative Detection Methodology 172.2.1.4 Application of DMSO-Based Solubility Assays 182.3 Aqueous Solubility in Lead Identification and Lead Optimization 182.3.1 Dried-Down Solution Methods 202.3.2 Solubility from Solid 212.3.3 Thermodynamic Solubility Assays with Solid-State Characterization 222.3.4 Solubility by Potentiometry 242.3.5 Application of Thermodynamic Solubility Data in LI and LO 262.4 Conclusions 28References 283 Gastrointestinal Dissolution and Absorption of Class II Drugs 33Arik S. Dahan and Gordon L. Amidon3.1 Introduction 333.2 Drug Absorption and the BCS 343.3 Class II Drugs 363.4 GI Physiological Variables Affecting Class II Drug Dissolution 383.4.1 Bile Salts 383.4.2 GI pH 393.4.3 GI Transit 393.4.4 Drug Particle Size 403.4.5 Volume Available for Dissolution 413.5 In Vitro Dissolution Tests for Class II Drugs 413.5.1 Biorelevant Media 413.5.2 Dynamic Lipolysis Model 423.6 BCS-Based FDA Guidelines: Implications for Class II Drugs 433.6.1 Potential of Redefining BCS Solubility Class Boundary 433.6.2 Biowaiver Extension Potential for Class II Drugs 443.7 Conclusions 45References 454 In Silico Prediction of Solubility 53Andrew M. Davis and Pierre Bruneau4.1 Introduction 544.2 What Solubility Measures to Model? 544.3 Is the Data Set Suitable for Modeling? 564.4 Descriptors and Modeling Methods for Developing Solubility Models 584.5 Comparing Literature Solubility Models 594.6 What Is the Influence of the Domain of Applicability? 634.7 Can We Tell when Good Predictions Are Made? 654.8 Conclusions 65References 66Part Two Physicochemical and Biological Studies of Membrane Permeability and Oral Absorption 695 Physicochemical Approaches to Drug Absorption 71Han van de Waterbeemd5.1 Introduction 735.2 Physicochemical Properties and Pharmacokinetics 745.2.1 DMPK 745.2.2 Lipophilicity, Permeability, and Absorption 745.2.3 Estimation of Volume of Distribution from Physical Chemistry 765.2.4 Plasma Protein Binding and Physicochemical Properties 765.3 Dissolution and Solubility 765.3.1 Calculated Solubility 785.4 Ionization (pKa) 785.4.1 Calculated pKa 795.5 Molecular Size and Shape 795.5.1 Calculated Size Descriptors 795.6 Hydrogen Bonding 805.6.1 Calculated Hydrogen-Bonding Descriptors 805.7 Lipophilicity 815.7.1 log P and log D 815.7.2 Calculated log P and log D 835.8 Permeability 845.8.1 Artificial Membranes and PAMPA 845.8.1.1 In Silico PAMPA 855.8.2 IAM, ILC, MEKC, and BMC 855.8.3 Liposome Partitioning 865.8.4 Biosensors 865.9 Amphiphilicity 865.10 Drug-Like Properties 875.11 Computation Versus Measurement of Physicochemical Properties 885.11.1 QSAR Modeling 885.11.2 In Combo: Using the Best of Two Worlds 895.12 Outlook 89References 896 High-Throughput Measurement of Physicochemical Properties 101Barbara P. Mason6.1 Introduction 1026.2 Positioning of Physicochemical Screening in Drug Discovery 1026.3 ‘‘Fit for Purpose’’ Versus ‘‘Gold Standard’’ 1036.4 Solubility 1046.4.1 ‘‘Thermodynamic’’ Versus ‘‘Kinetic’’ 1046.4.2 Methods of Measuring High-Throughput Solubility 1066.4.3 Supernatant Concentration 1066.4.4 Measuring Solubility Across a pH Range 1076.4.5 Supernatant Concentration Methods from Solid Material 1096.4.6 Precipitate Detection 1096.4.7 Other Methods of Measuring Solubility 1106.5 Dissociation Constants, pKa 1106.5.1 Measuring pKa 1116.5.2 pKa Measurements in Cosolvent Mixtures 1126.5.3 pKa Measurements based on Separation 1136.6 Lipophilicity 1156.6.1 log P Versus log DpH 1156.6.2 Measuring Lipophilicity 1166.6.3 High-Throughput log D7.4 Measurements 1176.6.4 High-Throughput log D7.4 Versus Shake-Flask log D7.4 1176.6.5 Alternative Methods for Determining High-Throughput log DpH 1186.7 Permeability 1196.7.1 Permeability and Lipophilicity 1216.7.2 Cell-Based Assays 1216.7.3 Noncell-Based Assays: Chromatographic Methods 1226.7.4 Noncell-Based Assays: Parallel Artificial Membrane Permeability Assay 1226.7.4.1 Membrane Composition 1236.7.4.2 Suggestions for PAMPA 1236.7.4.3 Considerations in the Calculation of Permeability from PAMPA Data 1246.7.5 Sink Conditions 1256.7.6 Unstirred Water Layer 1266.7.7 Surface Properties for the Determination of Permeability 1266.8 Data Interpretation, Presentation, and Storage 1266.9 Conclusions 127References 1277 An Overview of Caco-2 and Alternatives for Prediction of Intestinal Drug Transport and Absorption 133Anna-Lena Ungell and Per Artursson7.1 Introduction 1347.2 Cell Cultures for Assessment of Intestinal Permeability 1347.2.1 Caco-2 1357.2.2 MDCK Cells 1367.2.3 2/4/A1 Cells 1377.2.4 Other Cell Lines 1397.3 Correlation to Fraction of Oral Dose Absorbed 1407.4 Cell Culture and Transport Experiments 1417.4.1 Quality Control and Standardization 1437.4.2 Optimizing Experimental Conditions: pH 1447.4.3 Optimizing Experimental Conditions: Concentration Dependence 1447.4.4 Optimizing Experimental Conditions: Solubility and BSA 1457.5 Active Transport Studies in Caco-2 Cells 1457.6 Metabolism Studies using Caco-2 Cells 1467.7 Conclusions 147References 1488 Use of Animals for the Determination of Absorption and Bioavailability 161Chris Logan8.1 Introduction 1628.1.1 ADME/PK in Drug Discovery 1628.1.2 The Need for Prediction 1638.2 Consideration of Absorption and Bioavailability 1638.3 Choice of Animal Species 1678.4 Methods 1688.4.1 Radiolabels 1698.4.2 Ex Vivo Methods for Absorption 1698.4.2.1 Static Method 1698.4.2.2 Perfusion Methods 1708.4.3 In Vivo Methods 1708.5 In Vivo Methods for Determining Bioavailability 1718.5.1 Cassette Dosing 1718.5.2 Semisimultaneous Dosing 1728.5.3 Hepatic Portal Vein Cannulation 1738.6 Inhalation 1738.7 Relevance of Animal Models 1748.7.1 Models for Prediction of Absorption 1748.7.2 Models for Prediction of Volume 1758.8 Prediction of Dose in Man 1768.8.1 Allometry 1768.8.2 Physiologically Based Pharmacokinetics 1768.8.3 Prediction of Human Dose 1778.9 Conclusions 179References 1799 In Vivo Permeability Studies in the Gastrointestinal Tract of Humans 185Niclas Petri and Hans Lennernäs9.1 Introduction 1859.2 Definitions of Intestinal Absorption, Presystemic Metabolism, and Absolute Bioavailability 1889.3 Methodological Aspects of In Vitro Intestinal Perfusion Techniques 1909.4 Paracellular Passive Diffusion 1939.5 Transcellular Passive Diffusion 1969.6 Carrier-Mediated Intestinal Absorption 1999.7 Jejunal Transport and Metabolism 2029.8 Regional Differences in Transport and Metabolism of Drugs 2089.9 Conclusions 209References 210Part Three Role of Transporters and Metabolism in Oral Absorption 22110 Transporters in the Gastrointestinal Tract 223Pascale Anderle and Carsten U. Nielsen10.1 Introduction 22310.2 Active Transport Along the Intestine and Influence on Drug Absorption 22810.2.1 Peptide Transporters 23210.2.2 Nucleoside Transporters 23310.2.3 Amino Acid Transporters 23410.2.4 Monosaccharide Transporters 23410.2.5 Organic Cation Transporters 23510.2.6 Organic Anion Transporters 23510.2.7 Monocarboxylate Transporters 23510.2.8 ABC Transporters 23510.2.9 Bile Acid Transporters 23710.3 Transporters and Genomics 23710.3.1 Introduction to Genomics Technologies 23710.3.2 Gene Expression Profiling Along the Intestine and in Caco-2 Cells 23810.3.2.1 Profiling of the Intestinal Mucosa 23810.3.2.2 Profiling of Caco-2 Cells 24010.3.3 Intestinal Transporters and the Influence of Genotypes 24210.4 Structural Requirements for Targeting Absorptive Intestinal Transporters 24510.4.1 Strategies for Increasing Drug Absorption Targeting Transporters 24510.4.2 Changing the Substrate: SAR Established for PEPT1 24710.4.3 Methods for Investigating Affinity and Translocation 24810.4.4 Quantitative Structure–Activity Relations for Binding of Drug to Transporters 24910.5 Transporters and Diseased States of the Intestine 25110.5.1 Intestinal Diseases 25110.5.2 Basic Mechanisms in Cancer and Specifically in Colon Carcinogenesis 25210.5.2.1 Basic Mechanisms 25210.5.2.2 Colon Cancer 25310.5.3 Transporters and Colon Cancer 25310.5.3.1 Transporters as Tumor Suppressor Genes 25510.5.3.2 Role of Transporters in the Tumor–Stroma Interaction 25510.5.3.3 Role of Transporters in Intestinal Stem Cells 25810.5.4 Role of PEPT1 in Inflammatory Bowel Disease 25910.6 Summary and Outlook 260References 26111 Hepatic Transport 277Kazuya Maeda, Hiroshi Suzuki, and Yuichi Sugiyama11.1 Introduction 27811.2 Hepatic Uptake 27811.2.1 NTCP (SLC10A1) 27911.2.2 OATP (SLCO) Family Transporters 27911.2.3 OAT (SLC22) Family Transporters 28111.2.4 OCT (SLC22) Family Transporters 28411.3 Biliary Excretion 28411.3.1 MDR1 (P-glycoprotein; ABCB1) 28711.3.2 MRP2 (ABCC2) 28711.3.3 BCRP (ABCG2) 28911.3.4 BSEP (ABCB11) 29011.3.5 MATE1 (SLC47A1) 29011.4 Sinusoidal Efflux 29011.4.1 MRP3 (ABCC3) 29111.4.2 MRP4 (ABCC4) 29111.4.3 Other Transporters 29311.5 Prediction of Hepatobiliary Transport of Substrates from In Vitro Data 29411.5.1 Prediction of Hepatic Uptake Process from In Vitro Data 29411.5.2 Prediction of the Contribution of Each Transporter to the Overall Hepatic Uptake 29511.5.3 Prediction of Hepatic Efflux Process from In Vitro Data 29811.5.4 Utilization of Double (Multiple) Transfected Cells for the Characterization of Hepatobiliary Transport 29911.6 Genetic Polymorphism of Transporters and Its Clinical Relevance 30111.7 Transporter-Mediated Drug–Drug Interactions 30511.7.1 Effect of Drugs on the Activity of Uptake Transporters Located on the Sinusoidal Membrane 30511.7.2 Effect of Drugs on the Activity of Efflux Transporters Located on the Bile Canalicular Membrane 30811.7.3 Prediction of Drug–Drug Interaction from In Vitro Data 30911.8 Concluding Remarks 309References 31112 The Importance of Gut Wall Metabolism in Determining Drug Bioavailability 333Christopher Kohl12.1 Introduction 33412.2 Physiology of the Intestinal Mucosa 33412.3 Drug-Metabolizing Enzymes in the Human Mucosa 33612.3.1 Cytochrome P450 33612.3.2 Glucuronyltransferase 33712.3.3 Sulfotransferase 33712.3.4 Other Enzymes 33712.4 Oral Bioavailability 34112.4.1 In Vivo Approaches to Differentiate Between Intestinal and Hepatic First-Pass Metabolism 34212.4.2 In Vitro Approaches to Estimate Intestinal Metabolism 34412.4.3 Computational Approaches to Estimate and to Predict Human Intestinal Metabolism 34512.5 Clinical Relevance of Gut Wall First-Pass Metabolism 347References 34713 Modified Cell Lines 359Guangqing Xiao and Charles L. Crespi13.1 Introduction 35913.2 Cell/Vector Systems 36013.3 Expression of Individual Metabolic Enzymes 36313.4 Expression of Transporters 36513.4.1 Efflux Transporters 36513.4.2 Uptake Transporters 36713.5 Summary and Future Perspectives 368References 368Part Four Computational Approaches to Drug Absorption and Bioavailability 37314 Calculated Molecular Properties and Multivariate Statistical Analysis 375Ulf Norinder14.1 Introduction 37714.2 Calculated Molecular Descriptors 37714.2.1 2D-Based Molecular Descriptors 37714.2.1.1 Constitutional Descriptors 37814.2.1.2 Fragment- and Functional Group-Based Descriptors 37814.2.1.3 Topological Descriptors 37914.2.2 3D Descriptors 38114.2.2.1 WHIM Descriptors 38114.2.2.2 Jurs Descriptors 38214.2.2.3 VolSurf and Almond Descriptors 38314.2.2.4 Pharmacophore Fingerprints 38414.2.3 Property-Based Descriptors 38514.2.3.1 log P 38514.2.3.2 HYBOT Descriptors 38614.2.3.3 Abraham Descriptors 38614.2.3.4 Polar Surface Area 38614.3 Statistical Methods 38714.3.1 Linear and Nonlinear Methods 38814.3.1.1 Multiple Linear Regression 38814.3.1.2 Partial Least Squares 38914.3.1.3 Artificial Neural Networks 39014.3.1.4 Bayesian Neural Networks 39014.3.1.5 Support Vector Machines 39014.3.1.6 k-Nearest Neighbor Modeling 39214.3.1.7 Linear Discriminant Analysis 39214.3.2 Partitioning Methods 39314.3.2.1 Traditional Rule-Based Methods 39314.3.2.2 Rule-Based Methods Using Genetic Programming 39414.3.3 Consensus and Ensemble Methods 39514.4 Applicability Domain 39614.5 Training and Test Set Selection and Model Validation 39814.5.1 Training and Test Set Selection 39814.5.2 Model Validation 39914.6 Future Outlook 400References 40115 Computational Absorption Prediction 409Christel A.S. Bergström, Markus Haeberlein, and Ulf Norinder15.1 Introduction 41015.2 Descriptors Influencing Absorption 41015.2.1 Solubility 41115.2.2 Membrane Permeability 41215.3 Computational Models of Oral Absorption 41315.3.1 Quantitative Predictions of Oral Absorption 41315.3.1.1 Responses: Evaluations of Measurement of Fraction Absorbed 41715.3.1.2 Model Development: Data sets, Descriptors, Technologies, and Applicability 41915.3.2 Qualitative Predictions of Oral Absorption 42015.3.2.1 Model Development: Data sets, Descriptors, Technologies, and Applicability 42015.3.2.2 An Example Using Genetic Programming-Based Rule Extraction 42615.3.3 Repeated Use of Data Sets 42715.4 Software for Absorption Prediction 42715.5 Future Outlook 428References 42916 In Silico Prediction of Human Bioavailability 433David J. Livingstone and Han van de Waterbeemd16.1 Introduction 43416.2 Concepts of Pharmacokinetics and Role of Oral Bioavailability 43716.3 In Silico QSAR Models of Oral Bioavailability 43816.3.1 Prediction of Human Bioavailability 43816.3.2 Prediction of Animal Bioavailability 44116.4 Prediction of the Components of Bioavailability 44116.5 Using Physiological Modeling to Predict Oral Bioavailability 44316.6 Conclusions 445References 44617 Simulations of Absorption, Metabolism, and Bioavailability 453Michael B. Bolger, Robert Fraczkiewicz, and Viera Lukacova17.1 Introduction 45417.2 Background 45417.3 Use of Rule-Based Computational Alerts in Early Discovery 45617.3.1 Simple Rules for Drug Absorption (Druggability) 45617.3.2 Complex Rules That Include Toxicity 47317.4 Mechanistic Simulation (ACAT Models) in Early Discovery 47417.4.1 Automatic Scaling of k’a 0 as a Function of Peff, pH, log D, and GI Surface Area 47717.4.2 Mechanistic Corrections for Active Transport and Efflux 47817.4.3 PBPK and In Silico Estimation of Distribution 48117.5 Mechanistic Simulation of Bioavailability (Drug Development) 48117.5.1 Approaches to In Silico Estimation of Metabolism 48417.6 Regulatory Aspects of Modeling and Simulation (FDA Critical Path Initiative) 48417.7 Conclusions 485References 48518 Toward Understanding P-Glycoprotein Structure–Activity Relationships 497Anna Seelig18.1 Introduction 49818.1.1 Similarity Between P-gp and Other ABC Transporters 49818.1.2 Why P-gp Is Special 50018.2 Measurement of P-gp Function 50018.2.1 P-gp ATPase Activity Assay 50018.2.1.1 Quantification of Substrate–Transporter Interactions 50318.2.1.2 Relationship between Substrate–Transporter Affinity and Rate of Transport 50418.2.2 Transport Assays 50618.2.3 Competition Assays 50818.3 Predictive In Silico Models 50818.3.1 Introduction to Structure–Activity Relationship 50918.3.2 3D-QSAR Pharmacophore Models 50918.3.3 Linear Discriminant Models 51018.3.4 Modular Binding Approach 51118.3.5 Rule-Based Approaches 51218.4 Discussion 51318.4.1 Prediction of Substrate-P-gp Interactions 51318.4.2 Prediction of ATPase Activity or Intrinsic Transport 51318.4.3 Prediction of Transport (i.e., Apparent Transport) 51318.4.4 Prediction of Competition 51418.4.5 Conclusions 514References 514Part Five Drug Development Issues 52119 Application of the Biopharmaceutics Classification System Now and in the Future 523Bertil Abrahamsson and Hans Lennernäs19.1 Introduction 52419.2 Definition of Absorption and Bioavailability of Drugs Following Oral Administration 52719.3 Dissolution and Solubility 52819.4 The Effective Intestinal Permeability (Peff) 53519.5 Luminal Degradation and Binding 53919.6 The Biopharmaceutics Classification System 54119.6.1 Regulatory Aspects 54119.6.1.1 Present Situation 54119.6.1.2 Potential Future Extensions 54319.6.2 Drug Development Aspects 54319.6.2.1 Selection of Candidate Drugs 54419.6.2.2 Choice of Formulation Principle 54519.6.2.3 In Vitro/In Vivo Correlation 54719.6.2.4 Food–Drug Interactions 54919.6.2.5 Quality by Design 55219.7 Conclusions 552References 55320 Prodrugs 559Bernard Testa20.1 Introduction 55920.2 Why Prodrugs? 56020.2.1 Pharmaceutical Objectives 56020.2.2 Pharmacokinetic Objectives 56120.2.3 Pharmacodynamic Objectives 56420.3 How Prodrugs? 56520.3.1 Types of Prodrugs 56520.3.2 Hurdles in Prodrug Research 56720.4 Conclusions 568References 56821 Modern Delivery Strategies: Physiological Considerations for Orally Administered Medications 571Clive G. Wilson and Werner Weitschies21.1 Introduction 57121.2 The Targets 57221.3 The Upper GI Tract: Mouth and Esophagus 57321.3.1 Swallowing the Bitter Pill... 57521.4 Mid-GI Tract: Stomach and Intestine 57621.4.1 Gastric Inhomogeneity 57621.4.2 Gastric Emptying 57921.4.3 Small Intestinal Transit Patterns 58121.4.4 Modulation of Transit to Prolong the Absorption Phase 58221.4.5 Absorption Enhancement 58221.5 The Lower GI Tract: The Colon 58321.5.1 Colonic Transit 58421.5.2 Time of Dosing 58521.5.3 Modulating Colonic Water 58621.6 Pathophysiological Effects on Transit 58721.7 Pathophysiological Effects on Permeability 58921.8 pH 58921.9 Conclusions 590References 59022 Nanotechnology for Improved Drug Bioavailability 597Marjo Yliperttula and Arto Urtti22.1 Introduction 59722.2 Nanotechnological Systems in Drug Delivery 59922.2.1 Classification of the Technologies 59922.2.1.1 Nanocrystals 59922.2.1.2 Self-Assembling Nanoparticulates 60022.2.1.3 Processed Nanoparticulates 60122.2.1.4 Single-Molecule-Based Nanocarriers 60122.2.2 Pharmaceutical Properties of Nanotechnological Formulations 60122.2.2.1 Drug-Loading Capacity 60122.2.2.2 Processing 60222.2.2.3 Biological Stability 60222.3 Delivery via Nanotechnologies 60322.3.1 Delivery Aspects at Cellular Level 60322.3.2 Nanosystems for Improved Oral Drug Bioavailability 60622.3.3 Nanosystems for Improved Local Drug Bioavailability 60622.4 Key Issues and Future Prospects 608References 609Index 613