Quantitative Pharmacology and Individualized Therapy Strategies in Development of Therapeutic Proteins for Immune-Mediated Inflammatory Diseases

HONGHUI ZHOU, PHD, FCP, FAAPS, is a Senior Director and Janssen Fellow as well as US Head of Pharmacometrics at Janssen Research & Development, LLC. DIANE R. MOULD, PHD, FCP, FAAPS, is President of Projections Research Inc., a consulting company offering pharmacokinetic and pharmacometric services, and the founder of Baysient LLC, a company that develops systems to individualize doses of drugs that are difficult to manage.

• List of Contributors xviiAbout the Editors xxiForeword xxiiiPreface xxvii1 Disease Interception in Autoimmune Diseases: From a Conceptual Framework to Practical Implementation 1Anish Suri1.1 Introduction to Disease Interception 11.2 Disease Interception in Autoimmune Diseases 31.3 Progress in Modulation of the Adaptive Immune Response in Autoimmune Inflammatory Diseases 51.4 The Complex Interplay between the Specificity of the Pathogenic Immune Repertoire and Its Sculpting by the Environment – Implications for Disease Interception 81.5 Clinical Application and Concluding Remarks 14Acknowledgments 15References 152 The Role of Biomarkers in Treatment Algorithms for Ulcerative Colitis (UC) 25Reena Khanna and Brian G. Feagan2.1 Background 252.2 Histology 322.2.1 Tissue Markers 332.3 Treatment Algorithms 342.3.1 Differentiating Inflammatory and Noninflammatory Disease 342.4 Assessing Response to Therapy 352.5 Predicting Relapse 352.6 Summary 35References 353 Mechanism and Physiologically Based PK/PD Model in Assisting Translation from Preclinical to Clinical: Understanding PK/PD of Therapeutic Proteins at Site-of-Action 43Xi Chen and Weirong Wang3.1 Introduction 433.2 Biologic Distribution to Tissue Site of Action 443.3 Target Engagement of Biologics at Site of Action 503.4 Translational Application of Mechanistic PBPK Modeling 543.5 Conclusion 59References 594 Application of Minimal Anticipated Biological Effect Level (MABEL) in Human Starting Dose Selection for Immunomodulatory Protein Therapeutics – Principles and Case Studies 65Haiqing Wang, Zheng Yang, and Rong Shi4.1 Introduction 654.2 Safety and Immune-Related Toxicities of Immunomodulatory Protein Therapeutics 664.3 Uncertainties of Toxicology Approach in FIH Safe Starting Dose Selection for Immunomodulatory Protein Therapeutics 684.4 Incorporating Mabel Approach in FIH Starting Dose Selection for High-Risk Immunomodulatory Protein Therapeutics 714.5 Case Studies of Mabel Calculation 754.6 Discussion and Conclusion 85References 875 Model-Based Meta-Analysis Use in the Development of Therapeutic Proteins 93Timothy J. Taylor, Bill Frame, and Angela D. Taylor5.1 Introduction 935.2 Types of MBMA and Database Considerations 945.3 Data Analytic Models Useful for MBMA 965.4 Example 1: MBMA in Inflammatory Bowel Disease 975.5 MBMA Literature Search 995.6 Kinetic-Pharmacodynamic Models 1005.7 MBMA Implications for Inflammatory Bowel Disease 1165.8 Example 2: MBMA in Rheumatoid Arthritis 1175.9 Conclusion 119References 1206 Utility of Joint Population Exposure–Response Modeling Approach to Assess Multiple Continuous and Categorical Endpoints in Immunology Drug Development 125Chuanpu Hu and Honghui Zhou6.1 Introduction 1256.2 Latent Variable Indirect Response Models 1266.3 Residual Correlation Modeling Between a Continuous and a Categorical Endpoint 1286.4 Structural Correlation Modeling Between a Continuous Endpoint and a Categorical Endpoint 1346.4.1 Application Example: Rheumatoid Arthritis 1346.5 Conclusion 145References 1457 Modeling Approaches to Characterize Target-Mediated Pharmacokinetics and Pharmacodynamics for Therapeutic Proteins 149Leonid Gibiansky and Ekaterina Gibiansky7.1 Introduction 1497.2 Target-Mediated Drug Disposition Model 1507.3 Data and Practical Considerations 1527.4 What to Expect from the Concentration–Time Course 1547.5 Approximations of the TMDD Model 1577.6 Identifiability of Model Parameters 1667.7 Summary 167References 1688 Tutorial: Numerical (NONMEM) Implementation of the Target-Mediated Drug Disposition Model 173Leonid Gibiansky and Ekaterina Gibiansky8.1 Introduction 1738.2 Notations and Data 1748.3 NONMEM Code for TMDD Model and Approximations 1748.4 How to Select Correct Approximation 1798.4.2 Approach Based on Biological Considerations 1808.5 Numerical Implementation 1818.5.1 Choice of ADVAN Subroutines 1818.5.2 Parallel Computing 1818.6 Summary 182References 1829 Translational Considerations in Developing Bispecific Antibodies: What Can We Learn from Quantitative Pharmacology? 187Pradeep B. Lukka, Santosh Wagh, and Bernd Meibohm9.1 Introduction 1879.2 Quantitative Pharmacokinetic Considerations of BsAbs 1879.3 Preclinical Considerations 1899.4 Translational Considerations 1969.5 Immunogenicity 1979.6 Clinical Development of BsAbs 1989.7 Conclusion 200References 20210 Application of Pharmacometrics and Systems Pharmacology to Current and Emerging Biologics in Inflammatory Bowel Diseases 209Sihem Ait-Oudhia, Yi Ting (Kayla) Lien, Sumit Basu, Lawrence Lesko, and Stephan Schmidt10.1 Introduction 20910.2 Pharmacological Approaches for the Treatment of IBD 21510.3 Mathematical Models in IBD 22410.4 Role of FDA in the Drug Development of Biologics in the Treatment of IBD 22810.5 Summary 231References 23111 Pharmacokinetics-Based Dosing for Therapeutic Monoclonal Antibodies in Inflammatory Bowel Disease 243Niels Vande Casteele and William J. Sandborn11.1 Inflammatory Bowel Disease 24311.2 Population Pharmacokinetics 24411.3 Exposure–Response 24611.4 Exposure-Based Dosing Strategies 24711.5 Discussion 249References 25112 Pharmacokinetics-Based Dosing Strategies for Therapeutic Proteins in Inflammatory Bowel Disease 255Diane R.Mould, Richard N. Upton, and Jessica Wojciechowski12.1 Introduction 25512.2 The Need for Understanding and Controlling Variability in Exposure 25612.3 History of Dose Individualization 25812.4 Bayesian Methods for Dose Individualization 26012.5 Clinical Need for Improved Dosing with mAbs 26512.6 Expectations for Bayesian Adaptive Dosing 26812.7 Summary and Conclusions 277References 27813 Quantitative Pharmacology Approach to Select Optimal Dose and Study the Important Factors in Determining Disposition of Therapeutic Monoclonal Antibody in Pediatric Subjects – Some Considerations 285Deni Hardiansyah and Chee M. Ng13.1 Introduction 28513.2 Pharmacokinetics of Therapeutic Monoclonal Antibody in Pediatric Population 28913.3 Quantitative Pharmacology Considerations to Select Optimal Pediatric Dose of mAbs Based on Adult PK Studies 29113.4 Using mPBPK Model to Study the Effects of FcRn DevelopmentalPharmacology on the PK of mAbs in Pediatric Subjects 299References 30714 Quantitative Pharmacology Assessment Strategy Therapeutic Proteins in Pediatric Subjects – Challenges and Opportunities 315Jeremiah D. Momper, Andrew Mulberg, Nitin Mehrotra, Dan Turner, William Faubion, Laurie Conklin, Karim Azer, and Marla C. Dubinsky14.1 Introduction 31514.2 Extrapolation of Efficacy 31514.3 Initiation of Pediatric Trials 32114.4 Trial Design Considerations 32214.5 Challenges in Pediatric Trials for First-in-Class vs. Follow-on Drug-in-Class 330References 33115 Case Examples of Using Quantitative Pharmacology in Developing Therapeutic Proteins for Plaque Psoriasis – Guselkumab 337Zhenling Yao, Yaowei Zhu, Chuanpu Hu, Yang Chen, Shu Li, Bruce Randazzo, Zhenhua Xu, Amarnath Sharma, and Honghui Zhou15.1 Introduction 33715.1.1 Pathogenesis of Plaque Psoriasis 33715.1.2 Current Treatment Paradigms for Psoriasis 33815.2 Understanding of Exposure–Response (ER) Relationship of Guselkumab in Psoriasis 33915.3 Dose Selection for Guselkumab in Psoriasis 34215.4 Quantitative Pharmacology in Post-submission Support 35815.5 Conclusion 359References 36016 Vedolizumab—A Case Example of Using Quantitative Pharmacology in Developing Therapeutic Biologics in Inflammatory Bowel Disease 363Maria Rosario, Nathanael L. Dirks, Diane R.Mould, Catherine Scholz, Timothy Wyant, Asit Parikh, and Irving FoxAbbreviations 36316.1 Introduction 36416.2 Dose Selection for Adult Patients in Phase 3 Trials 36516.3 Pharmacokinetic Profile of Vedolizumab 36616.4 Population Pharmacokinetics in Phase 1 and 2 Trials 36816.5 Comparison of Simulated vs. Measured Vedolizumab Trough Concentrations 37216.6 Population Pharmacokinetics in Phase 3 Trials 37216.7 Dose Selection for Pediatric Populations 37416.8 Exposure–Response Analysis 37616.9 Logistic Regression Analyses 37816.10 Exposure–Response: Causal Inferences 38116.11 Conclusion 384Disclosure 384References 38417 Case Examples of Using Quantitative Pharmacology in Developing Therapeutic Proteins in Systemic Lupus Erythematosus – Belimumab 389Herbert Struemper17.1 Introduction 38917.2 Overview of Supporting Data and Methods 39017.3 Body Size Characterizations and Impact on Switching from Weight Proportional to Fixed Dosing 39017.4 The Yin and Yang of FcRn – Opposing Effect of Albumin and IgG on mAb Clearance 39217.5 Lost in Filtration – Renal Contributions to mAb Clearance 39517.6 Conclusion 397References 39818 Case Examples of Using Quantitative Pharmacology in Developing Therapeutic Proteins in Multiple Sclerosis – Peginterferon Beta-1a, Daclizumab Beta, Natalizumab 401Xiao Hu, Yaming Hang, Lei Diao, Kumar K.Muralidharan, and Ivan Nestorov18.1 Introduction 40118.2 Application of Quantitative Clinical Pharmacology for Dosing Regimen Recommendation of Peginterferon Beta- 1a 40318.3 Population PK/PD Analyses of Daclizumab Beta and Phase 3 Dose Selection 41418.4 Model-Based Approach for the Clinical Development of Subcutaneous Natalizumab 41918.5 Summary 431References 431Index 437