Clinical Trial Simulations: Applications and Trends (AAPS Advances in the Pharmaceutical Sciences Series Book 1)

This edition presents a review of the principles and progress surrounding clinical trial simulations (CTS), along with case studies illustrating CTS in various therapeutic and application areas. In addition, the book expands on the utility of CTS for informing decisions during drug development and regulatory review. Each chapter has been written by esteemed authors who have demonstrated expertise in state-of-the-art application of CTS. The target audience for the volume includes researchers and scientists who wish to consider use of simulations in the design, analysis, regulatory review or guidance of clinical trials, and academic researchers and others working in drug development (e.g., clinicians, senior managers, project planning and regulatory affairs professionals). The focus is on the effective utilization of CTS in decision mechanisms. Readers will gain broad knowledge on how CTS can improve the efficiency, informativeness, speed and economy of model-based drug development and regulation. **Holly H.C. Kimko**, PhD is a senior pharmacometrics leader (Research Fellow) at the Department of Advanced Modeling & Simulation in Johnson & Johnson Pharmaceutical Research & Development, LLC, New Jersey, and Adjunct Professor in the faculty of the Pharmacy School of Rutgers University, New Jersey. She was previously Assistant Professor in the Center for Drug Development Science in Georgetown University Medical School, Washington DC. Trained in biochemistry and pharmacy, Dr. Kimko earned her Ph.D. degree in Pharmaceutical Science from the State University of New York, Buffalo. She has published key papers on indirect response modeling and applications of CTS, and co-edited __Simulation for Designing Clinical Trials__. **Carl C. Peck**, MD is Adjunct Professor, Center for Drug Development Science in the Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, California. He was previously Director of the FDA Center for Drug Evaluation and Research, Assistant U.S. Surgeon General, and President of the American Society for Clinical Pharmacology and Therapeutics. Dr. Peck has also held professorial appointments in the faculties of UCSF, USUHS, and Georgetown University. He is an author of more than 150 original research papers, chapters and books concerning advanced concepts and techniques of quantitative pharmacology, trial designs, and pharmaco-statistical modeling and simulation. Clinical Trial Simulations: Applications and Trends (AAPS Advances in the Pharmaceutical Sciences Series, 1)......Page 1 Front-matter......Page 2 Title page......Page 4 Copyright......Page 5 Preface......Page 6 Contents......Page 8 Contributors......Page 12 1.1 Introduction......Page 18 1.2 Encouragement by EMA and FDA......Page 20 1.3 Clinical Trial Protocol Deviations and Adherence......Page 22 1.4 CTS-Supported Strategic Decisions in Drug Development......Page 24 1.5 Conclusion......Page 25 References......Page 26 Part I: Application of M & S in Regulatory Decisions......Page 30 2.1 Introduction......Page 32 2.2.1 Available Guidelines......Page 34 2.3 Regulatory Decisions: When and Impact......Page 42 2.3.2 Clinical Trial Application......Page 43 2.3.3 Scientific Advice......Page 44 2.3.4 Approval for Marketing Authorization......Page 45 2.4.1 Keppra (levetiracetam)......Page 46 2.4.2 Celsentri (Maraviroc)......Page 48 2.5 Future Perspectives and Summary......Page 49 References......Page 51 3.1 History of Pharmacometrics at FDA......Page 54 3.2.2 Pharmacometric Reviews......Page 55 3.2.2.2 QT Study Design and Analysis......Page 56 Pediatric Trials......Page 57 3.2.2.4 Knowledge Management......Page 58 3.2.3 Research and Policy Development......Page 59 3.3.1 Summary of Regulatory Impact......Page 60 3.3.2.1 Published Case Examples......Page 61 3.3.2.2 Pediatric Dosing Regimen......Page 65 3.3.2.3 Drugs with Approved Doses Not Directly Evaluated in Phase 3 Trials......Page 67 Model-Based Primary Endpoint for Phase 3 Trials......Page 69 3.4 Future Perspectives......Page 71 References......Page 72 Part II: Strategic Applications of M&S in Drug Development......Page 75 4.1 Introduction......Page 78 4.2 Notation and Terminology......Page 80 4.3.1 Introduction to the Example......Page 83 4.3.2 Operating Characteristics for Decision Criteria Based on Point Estimates......Page 84 4.3.3 Operating Characteristics for Decision Criteria Based on Interval Estimates......Page 87 4.4.1 Introduction to the Dose-Response Example......Page 90 4.4.2 Operating Characteristics for Decisions Based on Relative Potency Alone......Page 91 4.4.3 Operating Characteristics for Decisions Based on Relative Potency and Efficacy at the Top Dose......Page 92 4.4.4 Operating Characteristics for Decisions Based on the Estimated Effect at Each Dose......Page 94 4.5 Practicalities of Simulation in Model-Based Drug Development......Page 95 4.6 Discussion......Page 97 References......Page 99 5.1 Introduction......Page 102 5.2.1 Setting the Decision Context Before CUI Creation......Page 106 5.2.2 The Clinical Utility Index: ``Nuts and Bolts ́ ́......Page 107 5.2.3 Calculating Utility: A Quick Example......Page 110 5.3 A Detailed Example of CUI......Page 113 5.4 Related Publications on CUI......Page 117 5.5 Conclusion: Putting the CUI into Practice......Page 119 Notes on Multiplicative Functions......Page 120 Link to Conjoint Analysis......Page 122 References......Page 123 6.1 Background: What are Adaptive Designs and Why Can They Be Useful?......Page 126 6.2.1 Objectives: Finding an Adequate Dose and Learning About Dose-Response......Page 128 6.2.2.1 General Adaptive Dose Allocation (GADA)......Page 130 6.2.2.3 Combined D- and C-Optimality (DcoD)......Page 131 6.2.2.6 t-Test Adaptation......Page 132 6.2.3 Remarks on ADR Methods......Page 133 6.3.1 Group Sequential Designs......Page 134 6.3.2 Adaptive Designs......Page 135 6.3.3 Sample Size Re-Estimation......Page 136 6.3.4 Applications: Treatment Selection and Enrichment Designs......Page 137 6.3.5 Practical Considerations......Page 139 6.4.1 Operating Characteristics......Page 140 6.4.2 An Illustration: Comparing ADR Approaches......Page 141 6.5 Concluding Remarks and Further Thoughts on Adaptive Designs......Page 144 References......Page 145 7.1 Introduction......Page 148 7.2 Corifollitropin Alfa Development Program......Page 151 7.3 Phase II Development: Design of a Dose-Response Study......Page 153 7.4 Phase III Development: Dose Selection......Page 157 7.5 Discussion......Page 161 References......Page 165 8.1 Introduction......Page 166 8.2 The Learn-Confirm-Learn Process......Page 168 8.3.1 Pharmacometric Knowledge Integration......Page 170 8.5 Leveraging Pharmacometrics in Early Phase Drug Development......Page 171 8.5.1 Example of Model-Based Early Development......Page 173 8.5.1.1 Translation of Nonclinical Information into Knowledge......Page 174 8.5.1.2 Pharmacometric Leveraging of Nonclinical Knowledge to Gain Insight into a Proposed FTIH Study......Page 176 Data......Page 179 Population Pharmacokinetic Analysis......Page 181 Exposure: Response Analysis......Page 184 Comparison of Performance of the FTIH Study Outcome with FTIH Clinical Trial Simulation Outcome......Page 186 8.6 Summary......Page 188 References......Page 189 Part III: Application of M&S in Selected Therapeutic Areas......Page 190 9.1 Diabetes Mellitus......Page 192 9.1.1 Treatment Option and Drug Class......Page 194 9.1.3 Experimental Techniques......Page 195 9.1.3.2 Clamp Studies......Page 196 9.2.1 Mechanistic Models of Glucose-Insulin Regulation......Page 197 9.2.2 Time-Course Models......Page 198 9.2.3 Indirect Response Models......Page 200 9.2.4 Mechanistic Linked Model of FPG-HbA1c......Page 201 9.2.6 Literature Data for Developing Drug-Disease Models......Page 202 9.3 Applications in Drug Development......Page 204 9.3.1 Discovery and Candidate Selection......Page 206 9.3.2 Proof of Concept and Time-Course of Response......Page 207 9.3.3 Dose Response of Efficacy and Safety Attributes......Page 209 9.3.4 Dose Selection......Page 210 9.4 Regulatory Considerations......Page 211 9.5 Future Directions......Page 212 References......Page 213 10.1.1 Overview of Hypercholesterolemia......Page 216 10.1.2 Overview of Pharmacology of Statins......Page 217 10.1.3 Model Based Evaluations of Cholesterol Lowering Agents......Page 218 10.2.1 Overview of Pathophysiology of Thrombus Formation......Page 221 10.2.2 Pharmacology of Anticoagulant Agents......Page 222 10.2.3 Modeling and Simulation for Dosing of Anticoagulants......Page 224 10.3.1 Overview of Stroke and Clinical Endpoints......Page 226 10.3.2 Example Stroke Disease Progression Models......Page 227 10.3.3 Longitudinal Model for Nonmonotonic Stroke Scale Data......Page 231 10.4.2 Pharmacology of Antihypertensive Agents......Page 233 10.4.3 Modeling and Simulation for Antihypertensive Agents......Page 235 10.5 Adaptive Dosing Simulation Techniques: Focus on Cardiovascular Medicines......Page 237 References......Page 240 11.1 Introduction......Page 244 11.2 Basic Viral Dynamic Model......Page 245 11.3 Viral Dynamic Modeling and Simulations in HIV......Page 247 11.3.2 Dose and Dosing Schedule......Page 251 11.3.3 Estimation of Model Parameters......Page 254 11.4 Viral Dynamic Modeling and Simulations in Hepatitis C......Page 256 11.5 Conclusions......Page 263 References......Page 264 12.1 Introduction......Page 268 12.2 Why Develop a Platform to Simultaneously Combat Infectious Diseases and Drug Resistance?......Page 269 12.3 PK/PD-Driven Clinical Trial Design for Chemotherapeutic Antimicrobial Dose-Regimen Rationalization......Page 271 12.3.1.1 Microbiological Effect Concentration......Page 274 12.3.1.2 Time-Kill Study Evaluation......Page 275 12.3.1.3 Evaluating Effect (E)-vs.-Concentration [a] Curve Symmetry/Asymmetry......Page 277 12.3.1.4 Relating the Hill Model to MICs......Page 278 12.3.1.5 Antimicrobial Drug Combinations......Page 279 12.3.1.6 In Vivo Thigh Model......Page 281 12.3.1.8 Host Defense Submodel......Page 282 12.4 Antimicrobial Chemotherapy Knowledge Integration, from Bench-to-Bedside......Page 283 12.5 Clinical Application......Page 285 References......Page 290 13.1 General Concepts and History of Model-Based Research in Oncology......Page 298 13.2 Modeling Tumor Growth and Disease Progression......Page 301 13.3 Modeling Tumor Growth and DecayUnder Treatment......Page 306 13.4 Modeling Biomarkers vs. Surrogate Endpoints......Page 307 13.5 Translational Models......Page 311 13.6 Modeling and Prediction of Adverse Events......Page 315 13.7 Clinical Trial Simulations......Page 318 13.8 Concluding Remarks......Page 321 References......Page 322 14.1 Introduction......Page 328 14.2 Extrapolating PK/PD from Preclinical to Clinical......Page 329 14.3 Predicting the Outcome of an Extended Dosing Interval Regimen......Page 332 14.4 Pediatric Study Design......Page 337 References......Page 342 15.1 Introduction......Page 346 15.2.1 Data......Page 349 15.2.2.1 Efficacy......Page 350 15.2.2.4 Model Uncertainty......Page 351 15.2.3 Dose Selection for Phase 3 Studies......Page 352 15.3.1 Efficacy......Page 353 15.3.2 Tolerability......Page 355 15.3.3 Simulation Results......Page 356 15.4 Discussion......Page 358 References......Page 360 16.1 Introduction......Page 362 16.2 Rationale......Page 363 16.3.1.1 D2-Receptor Occupancy Model......Page 364 16.3.1.3 Prediction of D2-Receptor Occupancy......Page 365 16.3.2.1 Pharmacokinetic/Pharmacodynamic (PK/PD)-Model......Page 366 16.3.2.2 PK/PD-Simulation......Page 368 16.4.1 Predicting Efficacy and Safety using D2-Receptor Occupancy as a Biomarker......Page 370 16.4.2.1 PK/PD Model for EPS-Incidence......Page 372 16.4.2.2 PK/PD Simulation for EPS-Incidence......Page 374 16.5 Discussion......Page 375 References......Page 377 Part IV: Expanded Applications of M&S......Page 380 17.1 Introduction......Page 382 17.2.1 Absorption and Bioavailability......Page 384 17.2.2 Bimolecular Interaction of Drug with Target......Page 386 17.2.3 Biodistribution......Page 387 17.2.4 Clearance......Page 389 17.2.4.1 Target-Mediated Drug Disposition......Page 391 Target-Mediated Drug Disposition Model......Page 392 Michaelis-Menten Approximation......Page 394 17.2.6 Cytokinetics......Page 396 17.2.6.1 Cell Lifespan......Page 397 17.3 Applied Modeling and Simulation from Discovery Through Clinical Development......Page 399 17.3.1 Drug Discovery: Target Evaluation and Lead Drug Optimization and Selection......Page 400 17.3.2 Preclinical Development......Page 402 17.3.3 Clinical Development......Page 403 17.3.3.2 Selection of Phase II/III Doses......Page 405 17.3.3.3 Characterization of the Dose-Concentration-Effect Relationship......Page 406 17.3.3.4 Demonstration of the Similarity of PK-PD Relationship Between Different Patient Populations......Page 407 17.3.3.5 Evaluation of Demographic or Disease Covariates to Determine the Need of Dose Modifications for Subpopulations......Page 408 17.3.3.6 Evaluation of Drug-Drug Interactions......Page 410 17.3.3.7 Comparison of Fixed Dosing vs. Body Size-Based Dosing......Page 411 17.3.3.8 Provision of Support for Switching to Alternative Route of Administration, Dosage Form, or Dosing Regimen......Page 412 17.4 Conclusions......Page 413 References......Page 414 18.1 Introduction......Page 418 18.2 Methods for Modeling and Simulation Applications......Page 422 18.2.1 Common Trial Designs for Pediatrics......Page 423 18.2.2 Converting the Developing Child into the In Silico Child......Page 425 18.3 The Pediatric CTS Model......Page 431 18.3.1 Priors for Pediatric CTS......Page 433 18.3.2 Typical Workflow......Page 436 18.4.1 Safety/PK Trial to Fulfill Regulatory Requirements - Low Molecular Weight Heparin......Page 437 18.4.2 BPCA Trial: Written Request for Actinomycin-D and Vincristine in Children with Cancer......Page 440 18.4.3 Exploratory PK/PD Trial: Topirimate Dose Finding in Post Surgical Neonates......Page 442 18.5.2 Pediatric Outcomes......Page 446 References......Page 447 Part V: Evolving Methodologies in M&S......Page 452 19.1 General Concepts......Page 454 19.2.1 Descriptive Models......Page 457 19.2.2 Mechanism-Based Models......Page 460 19.2.2.1 Turnover Models......Page 461 19.2.2.2 Cascading Turnover Models......Page 463 19.2.3 Systems Pharmacology......Page 466 19.3 Practical Challenges and Implementations......Page 468 19.4 Summary......Page 472 References......Page 473 20.1 Introduction......Page 478 20.2.2 Role of the RAS Pathway in Modulating Arterial Pressure......Page 480 20.2.4 Creating a Model of Hypertension Incorporating the RAS Pathway......Page 482 20.3.1 Model Structure......Page 483 20.3.2 Systemic RAS Model Assumptions......Page 485 20.3.3 Parameterization of a Representative Normotensive Virtual Patient (VP)......Page 487 20.4.1 Angiotensin Peptide Infusion Experiments......Page 488 20.4.2 Representation and Parameterization of Antihypertensive Therapies......Page 489 20.4.3 Validation of Antihypertensive Therapies in the Model......Page 490 20.4.4 Representation of Variability Across Different Clinical Populations......Page 491 20.4.5 Insights from Model Simulations......Page 492 20.5.2 Model Development......Page 493 20.5.3.1 Renal Vascular Compartment......Page 495 20.5.3.2 Renal Tissue Compartment......Page 496 20.6 RAS Pathway Model Application in Drug Development......Page 497 20.7 Conclusion......Page 499 References......Page 500 21.1 Introduction......Page 504 21.2.1 Prediction of Hepatic Drug Clearance......Page 507 21.2.2 Prediction of In Vivo CL from In Vitro CL......Page 508 21.2.4 Factors Influencing Hepatic Clearance......Page 509 21.3 Physiologically Based Predictions of Tissue Distribution......Page 510 21.4 Prediction Models for Oral Absorption and Bioavailability......Page 512 21.5 Applying Physiologically Based Approaches in Drug Development......Page 513 21.6 Concluding Remarks......Page 516 References......Page 517 22.1 Introduction......Page 522 22.2 Covariate Distribution Models......Page 523 22.2.1 Internal Databases......Page 526 22.2.2.1 The United States Census of Demographic Characteristics of Americans......Page 527 22.2.2.2 National Institutes of Health Databases......Page 528 22.2.2.3 The US National Health and Nutrition Examination Survey......Page 529 Generating Covariate Probability Density Functions......Page 530 Generating Laboratory Clinical Values......Page 537 22.3 Future Perspectives......Page 541 References......Page 542 Index......Page 544 This edition presents a review of the principles and progress surrounding clinical trial simulations (CTS), along with case studies illustrating CTS in various therapeutic and application areas.¡ In addition, the book expands on the utility of CTS for informing decisions during drug development and regulatory review. Each chapter has been written by esteemed authors who have demonstrated expertise in state-of-the-art application of CTS.¡ The target audience for the volume includes researchers and scientists who wish to consider use of simulations in the design, analysis, ¡regulatory review¡or guidance of clinical trials, and academic researchers and others working in drug development (e.g., clinicians, senior managers, project planning and regulatory affairs professionals). The focus is on the effective utilization¡ of CTS in decision mechanisms. Readers will gain broad knowledge on how CTS can improve the efficiency, informativeness, speed and economy of model-based drug development and regulation. Holly H.C. Kimko, PhD¡is a senior pharmacometrics leader (Research Fellow) at the Department of Advanced Modeling & Simulation in Johnson & Johnson Pharmaceutical Research & Development, LLC, New Jersey, and Adjunct Professor in the faculty of the Pharmacy School of Rutgers University, New Jersey.¡ She was previously Assistant Professor in the Center for Drug Development Science in Georgetown University Medical School, Washington DC. Trained in biochemistry and pharmacy, Dr. Kimko earned her Ph. D. degree in Pharmaceutical Science from the State University of New York, Buffalo.¡ She has published key papers on indirect response modeling and applications of CTS, and co-edited Simulation for Designing Clinical Trials. Carl C. Peck, MD¡is Adjunct Professor, Center for Drug Development Science in the Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, California.¡ He was previously Director of the FDA Center for Drug Evaluation and Research, Assistant U.S. Surgeon General, and President of the American Society for Clinical Pharmacology and Therapeutics.¡ Dr. Peck has also held professorial appointments in the faculties of UCSF, USUHS, and Georgetown University.¡ He is an author of more than 150 original research papers, chapters and books concerning advanced concepts and techniques of quantitative pharmacology, trial designs, and pharmaco-statistical modeling and simulation This edition presents a review of the principles and progress surrounding clinical trial simulations (CTS), along with case studies illustrating CTS in various therapeutic and application areas. In addition, the book expands on the utility of CTS for informing decisions during drug development and regulatory review. Each chapter has been written by esteemed authors who have demonstrated expertise in state-of-the-art application of CTS. The target audience for the volume includes researchers and scientists who wish to consider use of simulations in the design, analysis, regulatory review or guidance of clinical trials, and academic researchers and others working in drug development (e.g., clinicians, senior managers, project planning and regulatory affairs professionals). The focus is on the effective utilization of CTS in decision mechanisms. Readers will gain broad knowledge on how CTS can improve the efficiency, informativeness, speed and economy of model-based drug development and regulation. Holly H.C. Kimko, PhD is a senior pharmacometrics leader (Research Fellow) at the Department of Advanced Modeling & Simulation in Johnson & Johnson Pharmaceutical Research & Development, LLC, New Jersey, and Adjunct Professor in the faculty of the Pharmacy School of Rutgers University, New Jersey. She was previously Assistant Professor in the Center for Drug Development Science in Georgetown University Medical School, Washington DC. Trained in biochemistry and pharmacy, Dr. Kimko earned her Ph. D. degree in Pharmaceutical Science from the State University of New York, Buffalo. She has published key papers on indirect response modeling and applications of CTS, and co-edited Simulation for Designing Clinical Trials. Carl C. Peck, MD is Adjunct Professor, Center for Drug Development Science in the Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, California. He was previously Director of the FDA Center for Drug Evaluation and Research, Assistant U.S. Surgeon General, and President of the American Society for Clinical Pharmacology and Therapeutics. Dr. Peck has also held professorial appointments in the faculties of UCSF, USUHS, and Georgetown University. He is an author of more than 150 original research papers, chapters and books concerning advanced concepts and techniques of quantitative pharmacology, trial designs, and pharmaco-statistical modeling and simulation This edition includes both updates and new uses and issues concerning CTS, along with case studies of how clinical trial simulations are being applied in various therapeutic and application areas. Importantly, the book expands on the utility of CTS for informing decisions during drug development and regulatory review. Each chapter author was selected on the basis of demonstrated expertise in state-of-the-art application of CTS. The target audience for this volume includes researchers and scientists who wish to consider use of simulations in the design, analysis, or regulatory review and guidance of clinical trials. This book does not embrace all aspects of trial design, nor is it intended as a complete recipe for using computers to design trials. Rather, it is an information source that enables the reader to gain understanding of essential background and knowledge for practical applications of simulation for clinical trial design and analysis. It is assumed that the reader has a working understanding of pharmacokinetics and pharmacodynamics, modeling, pharmacometric analyses, and/or the drug development and regulatory processes. There have been tremendous advancements in application of modeling and simulation (M&S) in drug development during the last decade. The pharmaceutical companies started to pay more attention to implement simulation exercises in drug development in order to achieve cost effectiveness. The Food and Drug Administration (FDA) published a white paper titled, Critical Path Initiatives, in March 2004. This puts forward model based drug development that calls for use of quantitative M&S to facilitate informed decisions. The European Medicines Agency (EMEA) also encourages use of simulations in guiding drug development. With this much interest, Clinical Trial Simulations will serve as a reference to understand how clinical trial simulations are being used in drug development. Clinical Trial Simulations compiles the topics of recent interest and the case studies of how clinical trial simulations were used in various therapeutic areas. It is divided into parts that describe subjects that have gained interest recently; application of M&S in regulatory decisions; application of M&S in various therapeutic areas; and special use of M&S.