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Table of Contents
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
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