Physiologically-Based Pharmacokinetic (PBPK) Modeling and Simulations. Principles, Methods, and Applications in the Pharmaceutical Industry

Preface xix

Acknowledgements xxi

About the companion xxiii

Section I. Principles, Methods, andBackground Information 1

1 A Review of Pharmacokinetic and Pharmacodynamic Principles 3

1.1 Introduction 4

1.2 Pharmacokinetic Principles 4

1.2.1 Routes of Drug Administration 4

1.2.2 Intravenous Bolus 4

1.2.3 Plasma Protein Binding and Blood–Plasma Ratio 9

1.2.4 Hepatic, Renal, and Biliary Clearances 12

1.2.5 Extravascular (Subcutaneous, Intramuscular, and Per Oral) Absorption 16

1.2.6 Absorption from Solid Dosage Forms 20

1.2.7 Role of Transporters in ADME 22

1.2.8 Linear and Non-Linear Pharmacokinetics 24

1.2.9 Intravenous Infusion, Repeated Dosing, Steady State Kinetics, and Accumulation 25

1.2.10 Active Metabolite and Prodrug Kinetics 28

1.3 Pharmacokinetic Variability 32

1.4 Pharmacokinetics Optimization in Drug Discovery 34

1.5 Pharmacodynamic Principles 34

1.5.1 Pharmacological Targets and Drug Action 35

1.5.2 Functional Adaptation Processes 39

1.5.3 Biomarkers, Surrogate Endpoints, and Clinical Endpoints 41

Keywords 47

References 48

2 A Review of Drug–Drug Interactions 51

2.1 Introduction 51

2.2 Drug Interactions Mediated by Enzymes and Transporters at Various Sites 54

2.3 Factors Affecting DDI 54

2.4 In Vitro Methods to Evaluate Drug–Drug Interactions 56

2.4.1 Candidate Drug as a Potential Perpetrator 57

2.4.2 Candidate Drug as a Potential Victim of Inhibition 58

2.5 Sources of Uncertainty 59

2.6 Therapeutic Protein–Drug Interaction 59

References 61

3 Modeling Pharmacokinetics, Pharmacodynamics, And Drug Interactions 65

3.1 Introduction 66

3.2 Modeling Pharmacokinetics 66

3.2.1 Compartmental Modeling of Linear and Nonlinear Pharmacokinetics (Enzyme and/or Transporter Capacity Limitation as Well as Target-Mediated Drug Disposition) 67

3.2.2 Population Pharmacokinetics 76

3.3 Pharmacokinetics/Pharmacodynamics and PK/Efficacy (Exposure/ Response) Modeling 80

3.3.1 PK/PD Models for Direct Effect: Sigmoid E_max Model 84

3.3.2 PK/PD Models for Direct Effect: Classical Receptor Theory 86

3.3.3 PK/PD Models Accommodating Delayed Pharmacological Response 89

3.3.4 PK/PD Models Accommodating Functional Adaptation Leading to Nonlinearity in Pharmacological Response with Respect to Time 96

3.3.5 PK/Efficacy Modeling 97

3.3.6 Translation of PK/PD and PK/Efficacy Modeling to Human 100

3.3.7 Average, Minimum, and Maximum Steady-State Concentrations 104

3.3.8 Estimation of Biologically Effective Dose in Human 107

3.3.9 Therapeutic Window 109

3.3.10 Static Models for Drug Interactions 109

3.4 Physiologically Based Pharmacokinetic (PBPK) Modeling and Its Integration with Pharmacodynamics and Efficacy Models 112

3.4.1 PK Modeling Compartmental vs PBPK 112

3.4.2 PK Variability: Population PK (popPK) Modeling vs PBPK 114

3.4.3 Integration of PBPK with PD, Quantitative Systems Pharmacology (QSP) Models or Quantitative Systems Toxicologyand Safety (QSTS) 114

3.4.4 PBPK Models to Evaluate Drug–Drug Interactions 115

3.4.5 DDI Risk Assessment with PBPK vs Static Models 118

Keywords 123

References 125

4 Physiological Model For Absorption 129

4.1 Introduction 130

4.2 Drug Absorption and Gut Bioavailability 130

4.2.1 Solubility and Dissolution Rate 130

4.2.2 Permeability: Transcellular, Paracellular, and Carrier-Mediated Pathways 136

4.2.3 Barriers to Membrane Transport – Luminal Degradation, Efflux, and Gut Metabolism 138

4.3 Factors Affecting Drug Absorption and Gut Bioavailability 140

4.3.1 Physiological Factors Affecting Oral Drug Absorption and Species Differences in Physiology 140

4.3.2 Compound-Dependent Factors 144

4.3.3 Formulation-Dependent Factors 144

4.4 In Silico Predictions of Passive Permeability and Solubility 147

4.4.1 In Silico Models for Permeability 147

4.4.2 In Silico Models for Solubility 147

4.5 Measurement of Permeability, Solubility, Luminal Stability, Efflux, Intestinal Metabolism 148

4.5.1 In Vitro, In Situ, and In Vivo Models for Effective Permeability 148

4.5.2 Measurement of Thermodynamic or Equilibrium Solubility 153

4.5.3 Luminal Stability 154

4.5.4 Efflux 154

4.5.5 In Vitro Models for Gut Metabolism and Estimation of Fraction Escaping Gut Metabolism 155

4.6 Absorption Modeling 156

Keywords 162

References 163

5 Physiological Model For Distribution 169

5.1 Introduction 170

5.2 Factors Affecting Tissue Distribution of Xenobiotics 170

5.2.1 Physiological Factors and Species Differences in Physiology 171

5.2.2 Compound-Dependent Factors 176

5.3 In Silico Models of Tissue Partition Coefficients 176

5.4 Measurement of Parameters Representing the Rate and Extent of Tissue Distribution 181

5.4.1 Assessment of Rate and Extent of Brain Penetration 181

5.5 Physiological Model for Drug Distribution 186

5.6 Drug Concentrations at the Site of Action 187

Keywords 189

References 189

6 Physiological Models For Drug Metabolism And Excretion 193

6.1 Introduction 193

6.2 Factors Affecting Drug Metabolism and Excretion of Xenobiotics 194

6.3 Models for Hepatobiliary and Renal Excretion 197

6.3.1 In Silico Models 197

6.3.2 In Vitro Models for Hepatic Metabolism 197

6.3.3 In Vitro Models for Transporters 200

6.4 Physiological Models 203

6.4.1 Hepato-Biliary Elimination of Parent Drug and Metabolites 205

6.4.2 Renal Excretion 208

References 211

7 Generic Whole-Body Physiologically Based Pharmacokinetic Modeling 217

7.1 Introduction 217

7.2 Structure of a Generic Physiologically-Based Pharmacokinetic (PBPK) Model 218

7.3 Somatic Compartments 220

7.3.1 Lungs (LU) 220

7.3.2 Arterial Blood (ART) 220

7.3.3 Venous Blood (VEN) 220

7.3.4 Stomach (ST) 220

7.3.5 Gut (GU) 220

7.4 Model Assumptions 221

7.5 PBPK Software 221

References 223

8 Pbpk Modeling Of Biotherapeutics 225

8.1 Introduction 226

8.2 Therapeutic Proteins 226

8.2.1 Peptides and Proteins 226

8.2.2 Antibodies and Antibody-Based Therapies 227

8.3 Pharmacokinetics of Therapeutic Proteins 234

8.3.1 Absorption 234

8.3.2 Renal Elimination 235

8.3.3 Immunogenicity 235

8.3.4 PEGylation 239

8.3.5 Transport by Convective and Transcytotic Extravasation 239

8.3.6 Catabolic Elimination (Proteolysis) 239

8.3.7 FcRn-Mediated Protection of IgGs Against Catabolism in FcRn-Rich Cells 241

8.3.8 Distribution and lymphatic elimination 242

8.3.9 Target-Mediated Drug Disposition and Receptor-Mediated Endocytosis 243

8.4 PBPK Modeling of Monoclonal Antibodies 244

8.4.1 Full PBPK Model for Monoclonal Antibodies 244

8.4.2 Minimal PBPK Model for Monoclonal Antibodies 253

8.5 Applications of PBPK Modeling of Monoclonal Antibodies 253

8.5.1 Pharmacokinetic Scaling 253

8.5.2 PBPK Integration with Pharmacodynamics of Monoclonal Antibodies 255

Keywords 156

References 258

9 Uncertainty And Population Variability 263

9.1 Introduction 264

9.2 Distinguishing Uncertainty and Variability 264

9.3 Sources of Uncertainty in Drug-related Parameters 264

9.4 Sources of Variability in System Parameters 266

9.5 Handling Population Variability 269

9.5.1 A POSTERIORI and A PRIORI Approaches to Handling Population Variability 269

9.5.2 Correlations Between Parameters 271

9.6 Uncertainty and Sensitivity Analysis 272

9.6.1 Local Sensitivity Analysis (One-at-a-time (OAT) and Derivative-based Methods) 272

9.6.2 Parameter Interactions and Global Sensitivity Analysis (GSA) 275

9.6.3 Global Sensitivity Analysis for Correlated Parameters (cGSA) 278

9.6.4 Applications of Sensitivity Analysis for PBPK Models 280

9.6.5 Limitations of Global Sensitivity Analysis 281

9.7 Uncertainty and Population Variability in Clinical Efficacy and Safety 282

Keywords 285

References 285

10 Nonclinical, Clinical, and Model-Informed Drug Development 293

10.1 Introduction: An Overview of Different Phases of Drug Development 294

10.2 Nonclinical Development 295

10.2.1 Preclinical Pharmacology, PK/PD Modeling, and Human Dose Prediction 297

10.2.2 Safety and Toxicology Studies 297

10.2.3 Studies with Radiolabeled Compound 298

10.3 Clinical Pharmacology Studies 302

10.3.1 First-in-Human, Single, and Multiple Ascending Dose Studies 302

10.3.2 Biopharmaceutics – Absolute Oral Bioavailability and Bioequivalence Study 304

10.3.3 Food Effect Study 304

10.3.4 Organ (Hepatic and Renal) Impairment Study 305

10.3.5 Pediatric Assessment 306

10.3.6 Mass Balance Study 307

10.3.7 Drug Interaction Study 307

10.3.8 Pharmacogenomics Study 308

10.3.9 Thorough QT (TQT) and Concentration QT (C-QT) Study 308

10.3.10 Immunogenicity Assays and Comparability Study for Biologics 309

10.3.11 Drug Labelling 309

10.4 Clinical Development in Oncology 310

10.5 Fast Track Routes to Address Unmet Medical Need in the Treatment of Serious Conditions 311

10.6 Model-Informed Drug Development 312

10.7 Physiologically Based Pharmacokinetic Models Complementing Clinical Pharmacology Studies 314

10.8 PBPK in Oncology 315

Regulatory Guidelines 316

References 319

Section II. Applications In The Pharmaceutical Industry 323

11 Overview Of Pbpk Applications 325

11.1 Introduction 325

11.2 PBPK Applications for Internal Decisions 326

11.3 PBPK Applications for Regulatory Filing 328

11.4 PBPK Modeling and Simulations Along the Value Chain 332

References 335

12 Applications Of Hypothesis Generation And Testing With Pbpk Models 337

12.1 Introduction 338

12.2 Hypothesis Generation and Testing with PBPK Models 338

12.2.1 Parameter Estimation from Intravenous Pharmacokinetic Profiles 338

12.2.2 Simulation of Oral PK Profile 341

12.2.3 Sensitivity Analysis 342

12.2.4 Verification of Hypotheses 346

12.2.5 Auto-inhibition of Drug-Metabolizing Enzymes, Uptake and Efflux Transporters 347

12.3 Hypothesis Generation and Testing Along the Value Chain 348

12.4 Conclusions 351

References 351

13 Applications of Physiologically Based Pharmacokinetic Models Integrated With Drug Effect Models (Pbpk/Pd) 353

13.1 Introduction: Integration of PBPK with Drug Effect Models 354

13.2 Dosing in Specific Populations 355

13.3 PBPK/PD for Bottom-Up Prediction of Inter-Patient Variability in Drug Response 357

13.4 PBPK/PD for Predicting the Inter-Patient Variability in Response to Prodrugs and Active Metabolites 358

13.5 PBPK/PD When Systemic Concentrations are not the Driver forDrug Response 359

13.5.1 Pre-Systemic Drug Target 359

13.5.2 Effect-Site Drug Concentration Different from Systemic Concentration 360

13.6 PBPK/PD for Monoclonal Antibodies 362

13.7 PBPK Models Linked to Quantitative Systems Pharmacology and Toxicology Models 363

13.7.1 PBPK–QST Models to Predict Drug-Induced Liver Injury 363

13.7.2 PBPK–QST Models to Predict Drug-Induced Cardiotoxicity 367

13.8 Conclusions 371

References 371

14 Pbpk Modeling and Simulations to Evaluate Clinical Drug-Drug Interactions 375

14.1 Introduction 376

14.2 Clinical DDI Studies and Modeling Approaches to Address Key Questions Related to Drug–Drug Interactions 376

14.2.1 Dedicated Clinical DDI Studies 378

14.2.2 Investigation of Phenotypic Effects for NMEs Predominantly Cleared by Polymorphic Enzyme or Transporter 379

14.2.3 Prospective Nested DDI Study 380

14.2.4 Cocktail DDI Study 381

14.2.5 PBPK Modeling and Simulations 381

14.2.6 Claims Relating to Results of DDI Studies 381

14.2.7 Impact on Label 382

14.3 PBPK Modeling of Different Types of Drug Interactions 382

14.3.1 PBPK Modeling Strategy: New Molecular Entity as Victim of CYP-Based Drug Interactions 382

14.3.2 PBPK Modeling Strategy: New Molecular Entity as Perpetrator of CYP-Based Drug Interactions 383

14.3.3 Non-CYP Based Drug Interactions 384

14.3.4 Transporter-Mediated Drug Interactions 385

14.4 DDI Predictions with PBPK Modeling and Simulations in Clinical Drug Development and Regulatory Submissions 387

14.4.1 DDI Predictions Along the Value Chain (Figure 14.5) 387

14.4.2 Possible Regulatory Outcomes, Based on the Predictions from a Verified and Validated PBPK Model 389

14.4.3 Regulatory Acceptance of PBPK Analyses Included in Regulatory Submissions 390

14.4.4 Predictive Performance of PBPK Models 391

14.5 Comparison of DDI Prediction Using Static and Dynamic Models 392

14.6 Conclusions 393

References 394

15 Dose Extrapolation Across Populations (Healthy Adult Caucasian To Pediatric, Pregnant Women, Different Ethnicities, Geriatric, Smokers And Obese Populations) 397

15.1 Introduction 398

15.2 PBPK Modeling Strategy for Dose Extrapolation to Specific Populations 398

15.3 Potential Benefits of PBPK Modeling for Dose Extrapolations to Specific Populations 399

15.4 Dose Extrapolations to Specific populations 404

15.4.1 Pediatric Starting Dose Selection 404

15.4.2 Pregnancy 406

15.4.3 Ethnicity – Japanese Population 407

15.4.4 Geriatric Population 408

15.4.5 Obese 409

15.4.6 Smokers 410

15.5 Conclusions 410

References 411

16 Dose Extrapolation Across Populations: Healthy Adult To Hepatic And Renal Impairment Populations 417

16.1 Introduction 418

16.2 Pathophysiological Changes in Organ Impairment 419

16.2.1 Hepatic Impairment 419

16.2.2 Renal Impairment 420

16.3 PBPK Modeling Strategy: Model Development, Verification, Validation, and Application 420

16.4 Benefits of Applying Validated PBPK Models to Organ-Impaired Populations 421

16.4.1 Enhancing Regulatory Confidence in the Application of PBPK Modeling for the Prediction of Exposure in the Organ-Impaired Population 421

16.4.2 Contribution of PBPK to the Totality of Evidence in Evaluating the Effect of Renal Impairment on Drug Exposure to Inform Labelling 424

16.5 Conclusions 425

References 426

17 Absorption-Related Applications Of Pbpk Modeling 429

17.1 Introduction 429

17.2 In Vitro – In Vivo Disconnect, Parameter Non-Identifiability and the Importance of Identifying Factors Limiting Absorption Through a Deconvolution of the Mechanisms Contributing to Gut Bioavailability 431

17.3 Non-Regulatory Internal Applications of PBPK Modeling and Simulations 433

17.3.1 Prediction of Fraction Absorbed 433

17.3.2 Oral Formulation Development 433

17.4 Regulatory Applications of PBPK Modeling and Simulations 438

17.4.1 Food–Drug Interactions 438

17.4.2 Interactions of a Poorly Soluble Weak Base with Acid Reducing Agents (ARAs) 444

17.4.3 In Vitro – In Vivo Correlations (IVIVCs) to Serve as Surrogate for Bioequivalence Testing (Case Study 12) 445

17.4.4 Biowaivers Based on Virtual Bioequivalence 449

17.4.5 Virtual Bioequivalence of Locally Acting Products (LAPs) 450

17.5 Conclusions 450

References 452

18 Regulatory Guidelines On The Reporting Of Physiologically Based Pharmacokinetic (Pbpk) Modeling Analysis 457

18.1 Introduction 457

18.2 Food and Drug Administration (FDA) Guidelines 458

18.3 European Medicines Agency (EMA) Guidelines 459

18.4 Comparison of FDA and EMA Guidelines 461

18.5 Risk-Informed Evidentiary Framework to Assess PBPK Model Credibility 463

18.6 Drug Model Verification of Locally Acting Products (LAPs) 464 References 466

19 Resolving The Challenges To Establishing Confidence In Pbpk Models 469

19.1 Introduction 470

19.2 Requirements for Developing Mechanistically Credible PBPK Models for the Three Broad Categories of Applications 470

19.3 Challenges to Developing Mechanistically Credible PBPK Models and Consequences 473

19.3.1 Model Building 473

19.3.2 Model Verification of Predicted Exposure and Validation of Predictive Performance 476

19.4 Resolving the Challenges to Developing Mechanistically Credible PBPK Models 476

19.5 Totality of Evidence 478

19.6 Conclusions 480

References 481

20 Epilogue 483

20.1 PBPK Modeling Successes 483

20.2 Challenges 484

20.2.1 Drug Model Parameterization 484

20.2.2 Knowledge Gaps in Physiological Parameters 485

20.2.3 Prospective Validation of Prediction Performance 485

20.3 Meeting the Challenges 485

20.4 Future Directions for PBPK Modeling 486

References 488

Section III. Case Studies Of Pbpk Applications In The Pharmaceutical Industry 491

Case Study 1 Hypothesis Testing (Solubility) 493

Case Study 2 Hypothesis Testing (Gastric Emptying) 499

Case Study 3 Hypothesis Testing (Intestinal Loss) 505

Case Study 4 Pbpk/Pd 509

Case Study 5 Drug–Drug Interaction (Inhibition) 515

Case Study 6 Drug–Drug Interaction (Induction) 521

Case Study 7 Genetic Polymorphism 527

Case Study 8 Pediatric Extrapolation 535

Case Study 9 Pregnancy 541

Case Study 10 Hepatic Impairment 547

Case Study 11 Renal Impairment 555

Case Study 12 Absorption – Ivivc 561

Appendices 567

Index 579

Now in its second edition, Physiologically Based Pharmacokinetic (PBPK) Modelling and Simulations: Principles, Methods, and Applications in the Pharma Industry remains the premier reference book throughout the rapidly growing PBPK user community. Using clear and concise language, author Sheila Annie Peters connects theory with practice as she explores the vast potential of PBPK modeling for improving drug discovery and development.

This fully updated new edition covers key developments in the field of PBPK modelling and simulations that have emerged in recent years. A brand-new section provides case studies in different application areas of PBPK modelling, including drug-drug interaction, genetic polymorphism, renal impairment, and pediatric extrapolation. Additional chapters address topics such as model-informed drug development (MIDD) and expose readers to a wide range of current applications in the field. Throughout the book, substantially revised chapters simplify complex topics and offer a balanced view of both the opportunities and challenges of PBPK modelling. Providing timely and comprehensive coverage of one of the most exciting new areas of pharmaceutical science, this book:

• Describes the principles behind physiological modeling of pharmacokinetic processes, inter-individual variability, and drug interactions for small molecule drugs and biologics
• Features a wealth of new figures and case studies of the applications of PBPK modelling along the value chain in drug discovery and development
• Reflects the latest regulatory guidelines on the reporting of PBPK modelling analysis
• Includes access to a new companion website containing code, datasets, explanations of case examples in the text, and discussion of key developments in the field
• Contains a brief overview of the field, end-of-chapter keywords for easy reference, and an extensive bibliography

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulations: Principles, Methods, and Applications in the Pharmaceutical Industry, Second Edition is an indispensable ­single-volume resource for beginning and intermediate practitioners across the pharmaceutical sciences in both industry and academia.

Sheila Annie Peters is head of Translational Quantitative Pharmacology at Merck KGaA in Darmstadt, Germany. Previously she was an Associate Principal Scientist for Discovery DMPK and Bioanalytical Chemistry at AstraZeneca and Principal Scientist at Cyprotex Discovery. She has lectured at the Regional Engineering College (Trichy, India) and University of Madras and Pondicherry University.