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List of Contributors xvii
Foreword xix
1 ADME for Therapeutic Biologics: What Can We Leverage from Great Wealth of ADME Knowledge and Research for Small Molecules 1 Weirong Wang and Thomayant Prueksaritanont
1.1 Introduction 1
1.2 SM Drug Discovery and Development: Historical Perspective 1
1.2.1 Evolving Role of DMPK: Paradigm Shift 1
1.2.2 Key Enablers to Successful DMPK Support 2
1.2.3 Regulatory Considerations 3
1.3 LM Drug Discovery and Development 3
1.3.1 Role of DMPK: Current State 3
1.3.2 SM/LM DMPK Analogy 4
1.3.3 Leveraging SM Experience: Case Examples 6
1.4 Conclusions 8
References 8
2 Protein Engineering: Applications to Therapeutic Proteins and Antibodies 13 Andrew G. Popplewell
2.1 Introduction 13
2.2 Methods of Protein Engineering 13
2.2.1 General Techniques 13
2.2.2 Introducing Specific, Directed Sequence Changes 14
2.2.3 Fragment Fusion 14
2.2.4 Gene Synthesis 14
2.2.5 Molecular "Evolution" through Display and Selection 14
2.3 Applications of Protein Engineering to Non-Antibody Therapeutic Proteins 16
2.4 Applications of Protein Engineering to Therapeutic Antibodies 16
2.4.1 Reduction of Immunogenicity 17
2.4.2 Improving Stability and Biophysical Properties 17
2.4.3 Tailoring Mechanism of Action 19
2.4.4 Influencing Distribution and PK 19
2.4.5 Improving Ligand/Receptor Interaction 20
2.5 Future Perspectives 20
References 21
3 Therapeutic Antibodies-Protein Engineering to Influence ADME, PK, and Efficacy 25 Tatsuhiko Tachibana, Kenta Haraya, Yuki Iwayanagi and Tomoyuki Igawa
3.1 Introduction 25
3.2 Relationship between pI and Pharmacokinetics 26
3.2.1 pI and Clearance 26
3.2.2 pI and Distribution 26
3.2.3 pI and SC Absorption 27
3.2.4 pI and FcRn Function 27
3.3 Nonspecific/Specific Off-Target Binding 27
3.3.1 Nonspecific Binding and Clearance 27
3.3.2 Specific Off-Target Binding and Clearance 28
3.4 pH-Dependent Antigen Binding to Reduce Target-Mediated Elimination 28
3.4.1 Concept of Recycling Antibody 28
3.4.2 pH Dependency and Target-Mediated Elimination 29
3.5 Soluble Antigen Sweeping 31
3.5.1 Concept of Sweeping Antibody 31
3.5.2 FcRn-Mediated Sweeping 31
3.5.3 Fc¿RIIb-Mediated Sweeping 33
3.6 Future Perspectives 34
References 34
4 ADME for Therapeutic Biologics: Antibody-Derived Proteins and Proteins with Novel Scaffolds 39 Chetan Rathi and Bernd Meibohm
4.1 Introduction 39
4.2 Antibody-Drug Conjugates 39
4.2.1 Components of ADCs 40
4.2.2 Types of ADC Analytes and Their PK Interpretation 41
4.2.3 PK of ADC 42
4.2.4 Immunogenicity of ADC 45
4.2.5 Exposure-Response of ADCs 45
4.2.6 Dose-Dependent PK of ADCs 45
4.3 Bispecifics 45
4.3.1 Bispecific Antibody Formats 46
4.3.2 PK of Bispecific Constructs 47
4.3.3 Immunogenicity of Bispecific Constructs 48
4.3.4 Examples of Bispecific Therapeutics-Oncology Indications 48
4.3.5 Examples of Bispecific Therapeutics-CNS Indications 49
4.3.6 Examples of Bispecific Therapeutics-Ocular Indications 49
4.4 Conclusions 50
References 50
5 Overview of ADME and PK/PD of ADCs 55 Baiteng Zhao and Tae H. Han
5.1 Introduction to ADC 55
5.2 Absorption 56
5.3 Distribution 58
5.4 Metabolism/Catabolism 58
5.5 Drug-Linker Stability 59
5.6 Elimination 60
5.7 Clinical PK 60
5.8 PK and PK/PD Modeling for ADCs 61
5.9 Summary 62
References 63
6 Role of Lymphatic System in Subcutaneous Absorption of Therapeutic Proteins 67 Jiunn H. Lin and Weirong Wang
6.1 Introduction 67
6.2 Physiology of Subcutaneous Tissue 68
6.3 Interstitial Transport from SC Injection Site 68
6.4 Relative Role of Blood and Lymphatic Systems in SC Absorption 69
6.5 Presystemic Catabolism in SC Absorption of Proteins 72
6.6 Effect of Injection Site on SC Absorption 74
6.7 Conclusions 74
References 75
7 Biodistribution of Therapeutic Biologics: Methods and Applications in Informing Target Biology, Pharmacokinetics, and Dosing Strategies 77 Sean B. Joseph, Saileta Prabhu and C. Andrew Boswell
7.1 Introduction 77
7.2 Determinants of Antibody Biodistribution 77
7.2.1 Molecular Properties 78
7.2.2 Physiological (Tissue) Properties 79
7.3 Methods of Measuring Antibody Biodistribution 81
7.3.1 In Vivo Study Design Considerations 81
7.3.2 Tissue Analysis 85
7.4 Interpretation of Biodistribution Data 85
7.4.1 Calculations and Units 86
7.4.2 Compartmental Tissue Concentrations 86
7.4.3 Blood Correction 86
7.4.4 Derivation of Interstitial Concentrations 87
7.4.5 Confirmation of Receptor Occupancy 87
7.4.6 Explaining Unexpectedly Rapid Clearance 87
7.4.7 Assisting in Clinical Dose Selection 87
7.5 Concluding Remarks 87
Acknowledgments 88
References 88
8 Prediction of Human Pharmacokinetics for Protein-Based Biologic Therapeutics 91 Chao Han and Christina Lourdes Mayer
8.1 Introduction 91
8.2 General Allometric Scaling and Interspecies Scaling Methods 92
8.3 Considerations for Interspecies Scaling of Protein-Based Biologic Therapeutics 93
8.3.1 Considerations for Interspecies Scaling of mAbs 95
8.3.2 Other Factors that may Affect PK Interspecies Scaling for Protein-Based Therapeutics 98
8.4 Physiologically Based PK Modeling 100
8.5 Perspectives Beyond the Prediction 101
8.5.1 Prediction of Human PK Serves Different Purposes at Different Stages of Drug Development 101
8.5.2 Safety Considerations When Predicting Human PK for Protein-Based Therapeutics 102
8.6 Conclusions 102
References 102
9 Fixed Dosing versus Body-Size-Based Dosing for Therapeutic Biologics-A Clinical Pharmacology Strategy 107 Diane D. Wang, Justin T. Hoffman and Kourosh Parivar
9.1 Introduction 107
9.1.1 Considerations for the Selection of a Dosing Approach 108
9.1.2 Evaluations of Fixed Dosing versus Body-Size-Based Dosing 110
9.1.3 Rationale Dosing Approach Selection Strategies Based on Stage of Clinical Development 121
9.2 Conclusions 122
References 122
10 Impact of Diseases, Comorbidity, and Target Physiology on ADME, PK, and PK/PD of Therapeutic Biologics 125 Songmao Zheng, Weirong Wang and Honghui Zhou
10.1 Introduction 125
10.1.1 ADME of Biologics 125
10.1.2 Roles of TMDD for Biologics 126
10.2 Impact of Diseases and Comorbidity on ADME and PK of Therapeutic Biologics 126
10.2.1 Disease and Comorbidity on the Subcutaneous Absorption of Biologics 126
10.2.2 Disease and Comorbidity on the Distribution of Biologics 127
10.2.3 Hepatic Impairment 128
10.2.4 Renal Impairment 128
10.2.5 Immune-Mediated Inflammatory Diseases 129
10.2.6 Diabetes 129
10.2.7 Immunogenicity 130
10.3 Impact of Disease and Target Physiology on PK and PK/PD of Therapeutic Biologics 130
10.3.1 Biologics against Membrane-Bound Targets 130
10.3.2 Biologics against Soluble Targets 133
10.3.3 When Targets Exist as Both Membrane-Bound and Soluble 133
10.4 Correlation between the PK of Therapeutic Biologics and Treatment Response 134
10.5 Other Patient Characteristics that can Impact the Treatment Response of Therapeutic Biologics 135
10.6 The Interplay between Disease, Target Physiology, and PK/PD of Therapeutic Biologics: Case Examples 136
10.7 Concluding Remarks 138
Acknowledgments 138
References 138
11 Immunogenicity: Its Impact on ADME of Therapeutic Biologics 147 Harald Kropshofer and Wolfgang F. Richter
11.1 Introduction 147
11.2 Immunogenicity of Therapeutic Biologics 147
11.2.1 The Underlying Cellular Immunology 147
11.2.2 Aspects Facilitating Immune Responses against Biologics 149
11.3 Impact of ADA on ADME 150
11.3.1 Impact of ADA on Bioanalytical Results 150
11.3.2 Formation of Immune Complexes 150
11.3.3 Clearance of Immune Complexes 151
11.3.4 Sustaining and Clearing ADAs 153
11.3.5 Impact of ADAs on Distribution 155
11.3.6 Impact of ADAs on Absorption 155
11.4 How to Deal with ADME Consequences of Immune Responses? 155
11.4.1 PK Assessment in the Presence of ADAs 155
11.4.2 In-Study Options to Overcome ADA Formation 156
11.5 Summary and Conclusions 156
References 157
12 Mechanistic Physiologically Based Pharmacokinetic Models in Development of Therapeutic Monoclonal Antibodies 159 Yanguang Cao and William J. Jusko
12.1 Background 159
12.2 History 159
12.3 Principles and Methods 162
12.4 Challenges 165
12.4.1 Physiological Parameters 165
12.4.2 Extravasation Mechanisms 165
12.4.3 FcRn Function 165
12.5 Simplified PBPK Models for mAbs 166
12.5.1 Minimal PBPK Models 166
12.5.2 Survey of mAb PK in Humans with the Minimal PBPK Model 168
12.5.3 Minimal PBPK Model with Target-Mediated Drug Disposition 169
12.6 Perspectives 171
Acknowledgments 172
References 172
13 Integrated Quantitation of Biotherapeutic Drug-Target Binding, Biomarkers, and Clinical Response to Support Rational Dose Regimen Selection 175 Philip J. Lowe, Anne Kümmel, Christina Vasalou, Soichiro Matsushima and Andrej Skerjanec
13.1 Introduction 175
13.2 Methods 176
13.2.1 Omalizumab, IgE, Itch, and Hives 176
13.2.2 QGE031 and Omalizumab, IgE, Basophil FceR1 and Surface IgE, and Allergen Skin Prick Test Response 178
13.2.3 Common Components 180
13.3 Results and Discussion 181
13.3.1 Omalizumab Capture of IgE Reducing Itch and Hives 181
13.3.2 QGE031 and Omalizumab Capture of IgE, Reducing Basophil FceR1, Surface IgE, and Allergen Skin Reactivity 185
13.4 Conclusions 191
Acknowledgments 193
References 193
14 Target-Driven Pharmacokinetics of Biotherapeutics 197 Wilhelm Huisinga, Saskia Fuhrmann, Ludivine Fronton and Ben-Fillippo Krippendorff
14.1 Introduction 197
14.2 Soluble and Membrane-Bound Targets 197
14.3 Whole-Body Target-Mediated Drug Disposition Models and Their Approximations 198
14.3.1 Generic Whole-Body TMDD Model 198
14.3.2 Characteristics of Target-Driven PK Profiles 199
14.3.3 Location of the Target: Central versus Peripheral Compartment 200
14.3.4 Parameter Identifiability and Model Reduction 200
14.3.5 Extended Michaelis-Menten Approximation with Target Turnover 201
14.3.6 Michaelis-Menten Approximation with Target Turnover 202
14.3.7 Extended Michaelis-Menten Approximation 202
14.3.8 Michaelis-Menten Approximation 203
14.3.9 Model Selection 203
14.4 Cell-Level Target-Mediated Drug Disposition Models 203
14.4.1 Cell-Level TMDD Model with a Single-Cell Type 204
14.4.2 Cell-Level TMDD Model with Normal and Tumor Cells 204
14.5 Simplified Physiologically Based Pharmacokinetic Model for mAbs 206
14.5.1 Target-Independent Pharmacokinetics 206
14.5.2 Drug-Target Interaction 208
14.6 Conclusion: Looking at Data Through Models 209
Acknowledgment 209
References 209
15 Target-Driven Pharmacokinetics of Biotherapeutics 213 Guy M.L. Meno-Tetang
15.1 Introduction 213
15.2 Peptide-FC Fusion Proteins 214
15.3 Monoclonal Antibodies (mAbs) 215
15.3.1 Antibodies Absorption 215
15.3.2 Antibodies Distribution 215
15.3.3 Mechanism of mAb Elimination 216
15.3.4 Antibody-Drug Conjugates 217
15.3.5 Recombinant Proteins 218
15.4 Parameters Controlling Target-Driven Nonlinear Pharmacokinetics of Biotherapeutics 218
15.4.1 Target Localization 218
15.4.2 Target Affinity 219
15.4.3 Target Turnover 219
15.4.4 Target Baseline and Disease Progression 219
15.4.5 Off-Target Binding 220
15.5 Impact of Target-Driven Nonlinear Pharmacokinetics of Biotherapeutics on Halometric Scaling 220
15.5.1 Ethnic Differences 220
15.6 Conclusions and Perspectives 220
References 221
16 Tumor Effect-Site Pharmacokinetics: Mechanisms and Impact on Efficacy 225 Greg M. Thurber
16.1 Introduction 225
16.2 Tumor Pharmacokinetics 225
16.2.1 Tissue Physiology, Fluid Balance, and Macromolecular Transport 225
16.2.2 Tumor Transport-An Overview 226
16.2.3 Mechanisms of Tumor Transport 227
16.2.4 Revisiting Tumor Transport Theory 229
16.2.5 Impact of Drug Targeting Parameters on Distribution 231
16.2.6 Experimental Validation and Comparison with Small Molecules 232
16.3 Impact of Tumor Pharmacokinetics on Efficacy 232
16.3.1 Overview of Cell-Killing Mechanisms 232
16.3.2 Pharmacokinetic Impact on Efficacy 233
16.4 Conclusions 235
References 236
17 Brain Effect Site Pharmacokinetics: Delivery of Biologics Across the Blood-Brain Barrier 241 Gert Fricker and Anne Mahringer
17.1 Cytotic Processes at the BBB 243
17.2 Receptors at the BBB as Targets for Biologics 243
17.2.1 Transferrin Receptor 243
17.2.2 Insulin Receptor 244
17.2.3 Insulin-Like Growth Factor Receptor 244
17.2.4 LDL Receptor 244
17.2.5 Low Density Lipoprotein Receptor-Related Protein 1 245
17.2.6 Low Density Lipoprotein Receptor-Related Protein 2 245
17.2.7 Leptin Receptor (OBR) 245
17.2.8 Receptor of Advanced Glycation Endproducts 245
17.2.9 Scavenger Receptor(SR) 246
17.3 "Trojan Horse" Approaches to Target BBB Receptors 246
17.4 Colloidal Carriers for Drug Delivery 248
17.5 Other Brain-Directed Carriers 249
17.6 Stem Cell-Mediated Drug Delivery 250
17.7 Focused Ultrasound and Microbubbles 251
17.8 Conclusions and Perspectives 251
References 251
18 Molecular Pathology Techniques in the Preclinical Development of Therapeutic Biologics 257 Thierry Flandre, Sarah Taplin, Stewart Jones and Peter Lloyd
18.1 Introduction 257
18.2 Target Expression Profiling 259
18.2.1 Detection of DNA/RNA-Based Target Expression Using Whole Tissue Extracts 259
18.2.2 Detection of Protein-Based Target Expression Using Whole Tissue Extracts 260
18.2.3 Localization of DNA/RNA and Protein-Based Target Expression at the Cellular Level Using Tissue Sections 262
18.3 Off-Target Binding of the Therapeutic Biologic Reagent 263
18.3.1 Tissue Cross-Reactivity Study 263
18.3.2 Protein Microarray 264
18.3.3 Cell Microarray Technology (Retrogenix) 264
18.3.4 Protein Pull-Down Assays 264
18.4 Biodistribution of Therapeutic Biologic Reagent 264
18.4.1 Whole-Body Autoradiography 264
18.4.2 Biodistribution: Immunohistochemistry Methods for Protein-Based Therapeutic Products 265
18.4.3 Biodistribution: Quantitative PCR Methods DNA/RNA-Based Therapeutic Products 265
18.5 Discussion 265
18.5.1 Considerations in the Interpretation of Molecular Pathology-Based Data 265
18.5.2 Examples of Molecular Pathology Methods Used in Preclinical Development 266
18.6 Conclusion 267
References 267
19 Labeling and Imaging Techniques for Quantification of Therapeutic Biologics 271 Julie K. Jang, David Canter, Peisheng Hu, Alan L. Epstein and Leslie A. Khawli
19.1 Introduction 271
19.2 New and Conventional Methods for Labeling of Biologics 272
19.2.1 Choice of Labels 272
19.2.2 Labeling Strategies of Biologics 277
19.3 Molecular Imaging for the Study of PK and Biodistribution of Biologics 285
19.3.1 SPECT Imaging 286
19.3.2 PET Imaging 286
19.3.3 Optical Imaging 288
19.4 Conclusions and Perspectives 288
References 289
20 Knowledge of ADME of Therapeutic Proteins in Adults Facilitates Pediatric Development 295 Omoniyi J Adedokun and Zhenhua Xu
20.1 Introduction 295
20.2 Comparative Evaluation of ADME of Therapeutic Proteins between Adults and Children 296
20.2.1 Absorption 296
20.2.2 Distribution 297
20.2.3 Metabolism and Elimination 297
20.3 Extrapolation of Efficacy from Adults to Pediatric Patients 298
20.3.1 No Extrapolation Approach 298
20.3.2 Partial Extrapolation Approach 298
20.3.3 Full Extrapolation Approach 299
20.4 Pediatric Dose Strategies 300
20.4.1 Body Weight-Based (Linear) Dose-Adjustment Approach 300
20.4.2 BSA-Based (Linear) Dose-Adjustment Approach 304
20.4.3 Tiered-Fixed Dose-Adjustment Approach 304
20.4.4 Hybrid Dose-Adjustment Approach 304
20.4.5 Other Dose-Adjustment Approaches 304
20.5 Sample-Size Determination for Pediatric Studies 304
20.6 Modeling and Simulation in Pediatric Drug Development Facilitated by Existing Adult Models 305
20.6.1 Modeling and Simulation Framework for Therapeutic Proteins in Pediatric Drug Development 305
20.6.2 Examples of the Application of Modeling and Simulation in the Development of Therapeutic Proteins in Pediatric Patients 307
20.7 Future Directions 309
References 309
21 LC/MS versus Immune-Based Bioanalytical Methods in Quantitation of Therapeutic Biologics in Biological Matrices 313 Bo An, Ming Zhang and Jun Qu
21.1 Introduction 313
21.2 Comparison of the Characteristics in Method Development 314
21.2.1 Method Development Time 314
21.2.2 Specificity 314
21.2.3 Characteristics of Method Development 314
21.3 Comparison of Assay Performance 316
21.3.1 Sample Preparation 316
21.3.2 Calibration Curve and Linearity Range 318
21.3.3 Applicability 318
21.3.4 Accuracy 319
21.3.5 Sensitivity 319
21.3.6 Reproducibility 321
21.4 Application of LBA and LC/MS in the Analysis of Therapeutic Proteins 323
21.4.1 Quantification of mAb in Plasma and Tissues 323
21.4.2 Application in Multiplexed Analysis 323
21.4.3 Characterization of Antibody-Drug Conjugates (ADC) 324
21.5 Summary and Future Perspective 324
References 324
22 Biosimilar Development: Nonclinical and Clinical Strategies and Challenges with a Focus on the Role of PK/PD Assessments 331 Susan Hurst and Donghua Yin
22.1 Introduction 331
22.2 Aspects of Biosimilarity 332
22.3 Biosimilars' Regulatory/Historical Perspective 333
22.3.1 European Union 333
22.3.2 EMA Nonclinical In Vivo Considerations 333
22.3.3 EMA Clinical Considerations (Related to PK/PD) 334
22.3.4 United States 334
22.3.5 FDA Nonclinical In Vivo Considerations 335
22.3.6 FDA Clinical Considerations (Related to PK/PD) 335
22.3.7 The WHO and Other Global Markets 336
22.4 Nonclinical Assessments in the Development of Biosimilars 336
22.4.1 Biosimilars Nonclinical Development 336
22.4.2 Designing the Nonclinical In Vivo Study 336
22.4.3 Designing the Nonclinical Study: Immunogenicity/Bioanalytical 337
22.4.4 Designing the Nonclinical In Vivo Study-PK and PD Focus 337
22.4.5 Designing the Nonclinical In Vivo Study-No Relevant Nonclinical Species 338
22.5 Clinical PK and PD Assessments in the Development of Biosimilars 340
22.5.1 Biosimilars Clinical Development 340
22.5.2 Bioanalytical Assays for Biosimilars PK and PD Investigations 341
22.5.3 Design Considerations for Phase I PK and PD Similarity Studies 341
22.5.4 PK Similarity Study of PF-05280014, a Proposed Biosimilar to Trastuzumab: An Example 342
22.5.5 Extrapolation of Clinical Data 342
22.6 Concluding Remarks 344
Acknowledgments 344
References 344
23 ADME Processes in Vaccines and PK/PD Approaches for Vaccination Optimization 347 José David Gómez-Mantilla, Iñaki F. Trocóniz and María J. Garrido
23.1 Introduction 347
23.1.1 Vaccine Development 347
23.1.2 Types of Vaccines 348
23.1.3 Basic Immunological Mechanism of Vaccine Development 348
23.2 Biopharmaceutic Considerations on Vaccine ADME Processes 350
23.3 Vaccines and ADME Processes 350
23.3.1 Effect of Vaccine Formulation on ADME 351
23.3.2 Effect of Route of Administration 353
23.3.3 Metabolism and Excretion 357
23.3.4 PK Considerations 357
23.4 Mathematical Modeling for Vaccine Optimization in Cancer Treatment 360
23.5 Systems Vaccinology: Application of Systems Biology in Personalized Vaccination 362
23.6 Concluding Remarks 363
References 363
24 Drug Development Strategies for Therapeutic Biologics: Industry Perspectives 369 Theresa Yuraszeck and Megan Gibbs
24.1 Introduction 369
24.1.1 Biologics Properties and Classification 370
24.1.2 Assay Development and Validation 372
24.2 Preclinical Development 372
24.2.1 FIH Starting Dose 374
24.3 Clinical Development 375
24.3.1 Intrinsic and Extrinsic Factors 375
24.3.2 Special Populations: Renal and Hepatic Impairment 376
24.3.3 Special Populations: Pediatrics 376
24.4 Biosimilars 377
24.5 Emerging Markets 377
24.6 Conclusions 378
References 379
25 Review: The Critical Role of Clinical Pharmacology in the Development of Biologics 385 Liang Zhao, Diane Wang, Ping Zhao, Elizabeth Y. Shang, Yaning Wang and Vikram Sinha
25.1 Introduction 385
25.2 PK and PD of Biologics 385
25.2.1 Structural Difference between SMDs and Biological Products 385
25.2.2 Route of Administration and Absorption 386
25.2.3 Distribution 386
25.2.4 Metabolism and Elimination 386
25.2.5 mAb Distribution 386
25.2.6 Catabolism and Elimination 387
25.2.7 Other Biologics 387
25.3 Critical Role of Clinical Pharmacology and Related Regulatory Guidance for Biologics Development 387
25.3.1 First-in-Human (FIH) Dose Determination and Study Design 387
25.3.2 Critical Considerations from a Standpoint of Clinical Pharmacology in Biologics Development 388
25.4 Model-Based Drug Development for Biologics 393
25.4.1 Fixed Dosing versus Body Size-Adjusted Dosing 394
25.4.2 Mechanism- and Physiologically Based Models for mAbs 394
25.4.3 Utility of Meta-Analysis 395
25.4.4 Utility of Case-Control Analysis in Biologics Development 396
25.5 Conclusions 397
25.6 Disclaimer 397
References 397
26 Investigating the Nonclinical ADME and PK/PD of an Antibody-Drug Conjugate: A Case Study of ADO-Trastuzumab Emtansine (T-DM1) 401 Jay Tibbitts
26.1 Introduction 401
26.2 Importance of ADME for ADCs 402
26.3 T-DM1 Bioanalytical Strategy and Methods 403
26.4 Ex Vivo Linker Stability 404
26.5 Plasma PK 404
26.6 Distribution of T-DM1 406
26.7 T-DM1 Catabolism and Elimination 406
26.8 T-DM1 Nonclinical PK/PD 408
26.9 Conclusions 409
References 409
27 Use of PK/PD Knowledge in Guiding Bispecific Biologics Research and Development 413 Andreas Baumann, Saileta Prabhu and Jitendra Kanodia
27.1 Introduction 413
27.2 Structural Formats and Generation of Bispecific Biologics 415
27.3 Biochemistry and Pharmacology of Bispecifics 416
27.3.1 Affinity 416
27.3.2 Avidity 416
27.4 Pharmacokinetics 416
27.4.1 PK Assay Strategies Employed for the Development of bsAbs 417
27.4.2 Immunogenicity Strategies Employed for the Development of bsAbs 418
27.5 Pharmacokinetic-Pharmacodynamic Model-Informed Design of bsAbs 418
27.6 Application of PK/PD in the Research and Development of Bispecific Biologics: Case Examples 419
27.6.1 Anti-TfR/BACE1 to Improve Therapeutic Antibody Transport across the Blood-Brain Barrier 419
27.6.2 PK Characterization to Optimize bsAb Molecule Design and Selection for Ophthalmology 420
27.6.3 Pharmacokinetic Studies during Development of a Bispecific T-Cell Engager 421
27.7 Outlook 421
References 422
Index 427
Weirong Wang1 and Thomayant Prueksaritanont2
1 Janssen Research and Development, LLC, Spring House, PA, USA
2 Merck Research Laboratories, West Point, PA, USA
Over the past decade, there has been increased investment to the development of biotechnologically derived drug products or biologics (including peptides, proteins, and monoclonal antibodies, mAbs, aggregately referred as large molecule (LM) drugs) in pharmaceutical companies [1, 2]. These are attributable to the reported therapeutic success of this modality thus far, together with the rapid advancement and breakthroughs in the fields of recombinant DNA biotechnology and molecular biology. However, reports on mechanistic investigation of absorption, distribution, metabolism, and excretion (ADME) processes for LMs are sparse and our current understanding of the associated mechanisms and key determinants of pharmacokinetic (PK) properties is scant [3]. Conceivably, these are related to the fact that the biopharmaceutical industry is still at an early stage, relative to the traditional pharmaceutical counterpart; the first approved LM drug product was in 1980s [4], several decades after many small molecule (SM) drugs were on the market. In addition, unlike the discovery and development of SM drugs, where the sciences and the functional role of drug metabolism and pharmacokinetics (DMPK) in studying and understanding ADME processes have been well recognized as an indispensable and integral discipline spanning from early discovery to development and postmarketing spaces [5], the function of DMPK in support of LM drug development is somewhat limited to mostly in vivo PK and/or pharmacokinetics/pharmacodynamics (PK/PD) studies, typically after candidate selection and primarily in the clinical space. Despite the intrinsic difference between SM and LM drugs, it should be of particular interest to appraise the relevance and applicability of what we have learned over the past few decades from the discovery and development of SM drugs to the same process of LMs. Thus, in this chapter, a brief historical perspective is presented on how the roles of DMPK and the key enablers for studying the ADME processes of SM drugs and their underlying mechanisms have evolved over time in order to influence internal de-risking strategy and decisions. External factors, such as changing regulatory environments and evolving LM discovery and development landscape, are briefly reviewed. Also presented is an overview of a DMPK concept analogy between SMs and LMs, as well as case examples to demonstrate the applicability of SM DMPK knowledge and experiences to LM drug discovery and development.
It has long been well recognized that the drug discovery and development process is very expensive, largely due to a high development attrition rate and prolonged development time to meet the requirement for more extensive and complex clinical trials [1, 6-8]. In 1990s, poor human PK and bioavailability were the most significant cause of attrition for SM drugs, accounting for approximately 40% of all attrition in development. This number was dramatically reduced to approximately 8% by 2000 [7]. Such a drastic difference has been attributable primarily to a Paradigm shift in the roles of DMPK from little involvement decades before 1990 to active participation in SM drug early discovery starting in late 1980s [5]. Previously, compounds were selected mainly based on in vitro potency and in vivo efficacy in animal studies, with little attention being paid to the exposure or PK as an important measure connecting pharmacodynamics (PD)/efficacy/safety profiles, or consideration to commonly observed differences in these profiles between animals and humans. The integration of DMPK support as a key component of the overall drug discovery process helped to better understand ADME properties and filled these gaps, thus enabling proper data interpretations and rationale-based predictions of DMPK-related properties in humans [9-13]. As a result, potential liabilities of new chemical entities in humans were dialed out as early as possible, leading to increased likelihood for preclinical candidates to be developed successfully as therapeutic agents.
The aforementioned successful DMPK support would not have been possible without numerous advances over the past few decades in drug metabolism sciences and technologies, which have provided powerful tools to enable DMPK scientists to shape SM drug metabolism research. Of special note are two key enablers, signifying game changers within the time period of interest (late-1980s to late-1990s): (i) rapid advancement of cytochrome P450 (CYP) science and (ii) availability of liquid chromatography-mass spectrometry (LC-MS). As will be described in later sections, these elements and associated wealth of information generated over the last few decades can be leveraged and applied to support LM drug development.
The CYP enzymes play central roles in the metabolism of SMs; it is estimated that more than 70% of marketed SM drugs were eliminated primarily by CYPs [13]. CYP enzymes were discovered in 1958, and research on their structure, function, regulation, and tissue expression levels, as well as their role in drug metabolism, was rapidly expanded in the 1980-1990s [14-16]. Such rapid advancement provided fundamental concepts and important tools that helped leverage preclinical/in vitro results as a bridge to clinical outcomes, consequently enabling one to predict, understand, and manage clinical findings, particularly with respect to human clearance and PK variability due to factors such as CYP-mediated drug-drug interaction (DDI) or CYP polymorphism [13, 16-18]. Specifically, for compounds with CYPs as the major or sole contributor to their metabolism, human metabolic clearance can be reasonably predicted based simply on in vitro metabolism studies with recombinant CYP isoforms, corrected for relative expression levels of each isoform in tissues [19]. In addition, the knowledge of CYP substrate specificity, multiplicity, and responses to factors, such as inducers and inhibitors, has provided a means to quantitatively predict, based on in vitro studies with specific CYP marker substrates or inhibitors/inducers, the magnitude of DDI, thus enabling a selection of candidates at discovery stage that do not bear considerable liability to serious clinical DDIs, either as perpetrators or victims [16-18, 20]. The DDI prediction results have also been used (and accepted by regulatory agencies) to inform inclusion and exclusion criteria for clinical programs, decide whether a clinical DDI study is needed, and inform product labeling with respect to dosage adjustment and warning/contraindication when used with other medications [21, 22]. Collectively, advances in understanding CYPs, the primary determinant for clearance mechanism of majority of SM drugs, has helped reduce drug development failure rate due to undesirable human PK properties.
In the area of tools and technologies, the successful coupling of high performance liquid chromatography with mass spectrometry (MS) has provided unprecedented sensitivity, selectivity, and high throughput that has facilitated the rapid assessment of ADME properties and the multiplicity of their governing factors for SM candidates in animals and humans [23-26]. Capitalizing on chromatographic separation and mass selectivity, the LC-MS technology enables the quantitation of coeluting or overlapping analytes, which otherwise would be constrained by chromatographic resolution. A dramatic outcome of this feature is the various in vivo and in vitro cassette studies in which more than one compounds were administered or incubated for the screening of DMPK properties, including metabolic stability, DDI liability, and plasma protein binding [23-25]. Along with the accelerated method development similarly attributed to the extraordinary selectivity and sensitivity of LC-MS, this practice has tremendously facilitated the speed and throughput of analyses of samples of low concentrations or of small volumes. Likewise, LC-MS technology has reshaped the business of metabolite characterization, allowing rapid detection and identification of major metabolites of drug candidates so that the result can be fed back into the cycle in time to influence the synthetic chemistry effort. Together, this powerful technology has enabled informed decisions to be made rapidly on a large number of candidates, each available in a small quantity, during the discovery stage. It has also enabled other in-depth mechanistic investigations into the governing factors of ADME processes, as well as detailed and accurate characterization of ADME properties of development candidates required for risk mitigation and regulatory submission [5, 10, 26]. With the recent advent of new chromatographic techniques, such as ultraperformance liquid chromatography, and more sophisticated MS, such as high resolution MS [27], this technology will continue to be the most powerful tool for drug discovery and development for SMs, and potentially for LMs alike.
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