Incorporating Information from Completed Trials in Future Trial Planning

Abstract

This book offers a high-level treatise of evidence-based decisions in drug development. Because of the inseparable relationship between designs and decisions, a good portion of this book is devoted to the design of clinical trials. The book begins with an overview of product development and regulatory approval pathways. It then discusses how to incorporate prior knowledge into study design and decision making at different stages of drug development. The latter include selecting appropriate metrics to formulate decisions criteria, determining go/no-go decisions for progressing a drug candidate to the next stage and predicting the effectiveness of a product. Lastly, it points out common mistakes made by drug developers under the current drug-development paradigm. The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have a basic understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization. The authors provide software codes for select analytical approaches discussed in the book. The book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making themselves. Preface; Contents; Chapter 1: Clinical Testing of a New Drug; 1.1 Introduction; 1.2 Clinical Development; 1.2.1 Phase 1; 1.2.2 Phase 2; 1.2.3 Phase 3; 1.2.4 Phase 4; 1.3 Regulatory Review; 1.3.1 Accelerated Approval; 1.3.2 Breakthrough Therapy; 1.3.3 Priority Review; 1.3.4 Fast Track; 1.3.5 Orphan Drug; 1.3.6 Drug Approval in the European Union (EU); 1.4 Innovative Designs; 1.4.1 Adaptive Design; 1.4.2 Master Protocol; 1.5 Summary; References; Chapter 2: A Frequentist Decision-Making Framework; 2.1 Introduction; 2.2 Statistical Hypotheses; 2.3 Testing a Statistical Hypothesis. 2.4 Decision-Making2.5 Losses and Risks; 2.6 The Power Function of a Test; 2.7 Determining a Sample Size for an Experiment; 2.8 Multistage Tests and the Use of a No-Decision Region; 2.9 One-Sided Versus Two-Sided Tests; 2.10 P-Values; 2.11 Summary; References; Chapter 3: Characteristics of a Diagnostic Test; 3.1 Introduction; 3.2 Sensitivity and Specificity; 3.3 Positive and Negative Predictive Value; 3.4 Value of a Follow-Up Test; 3.5 When Two Tests Are Being Done Simultaneously; 3.6 Summary; References; Chapter 4: The Parallel Between Clinical Trials and Diagnostic Tests; 4.1 Introduction. 4.2 Why Replication Is Necessary4.3 Why Replication Is Hard; 4.3.1 Conditional Replication Probability; 4.3.2 Average Replication Probability; 4.3.3 When the Second Trial Has a Different Sample Size; 4.4 Differentiate Between Statistical Power and the Probability of a Successful Trial; 4.5 Summary; References; Chapter 5: Incorporating Information from Completed Trials in Future Trial Planning; 5.1 Introduction; 5.2 The Bayesian Approach to Inference; 5.3 Bayesian Average Power and Assurance; 5.4 Closed-Form Expressions for Assurance and the Simulation Approach. 5.5 PPV and NPV for a Planned Trial5.6 Forming a Prior Distribution from a Number of Similar Previous Trials; 5.7 Standard Prior Distributions; 5.8 Elicitation of a Prior Distribution from Experts; 5.9 Prior Distributions from PK/PD Modeling and Model-Based Meta-Analysis; 5.10 Discussion; References; Chapter 6: Choosing Metrics Appropriate for Different Stages of Drug Development; 6.1 Introduction; 6.2 Metrics for Proof-of-Concept Studies; 6.3 Metrics for Dose-Ranging Studies; 6.3.1 Estimating a Dose-Response Relationship; 6.3.1.1 Emax Model; 6.3.1.2 Other Dose-Response Models. 6.3.2 Testing for a Positive Dose-Response Relationship6.3.3 Calculating the Metrics; 6.4 Metrics for Confirmatory Studies; 6.5 Other Types of Success Probabilities; 6.5.1 Probability of Program Success (POPS); 6.5.2 Probability of Compound Success (POCS); 6.6 Discussion; References; Chapter 7: Designing Proof-of-Concept Trials with Desired Characteristics; 7.1 Introduction; 7.2 Five Approaches to Decision-Making; 7.2.1 The Traditional Hypothesis-Testing Approach; 7.2.2 The ESoE Approach; 7.2.3 The LPDAT Approach; 7.2.4 The TV Approach; 7.2.5 The TVMCID Approach.