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Innovative Statistics in Regulatory Science




ISBN 9780367224769
Published November 7, 2019 by Chapman and Hall/CRC
530 Pages

 
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Book Description

Statistical methods that are commonly used in the review and approval process of regulatory submissions are usually referred to as statistics in regulatory science or regulatory statistics. In a broader sense, statistics in regulatory science can be defined as valid statistics that are employed in the review and approval process of regulatory submissions of pharmaceutical products. In addition, statistics in regulatory science are involved with the development of regulatory policy, guidance, and regulatory critical clinical initiatives related research. This book is devoted to the discussion of statistics in regulatory science for pharmaceutical development. It covers practical issues that are commonly encountered in regulatory science of pharmaceutical research and development including topics related to research activities, review of regulatory submissions, recent critical clinical initiatives, and policy/guidance development in regulatory science.

  • Devoted entirely to discussing statistics in regulatory science for pharmaceutical development.
  • Reviews critical issues (e.g., endpoint/margin selection and complex innovative design such as adaptive trial design) in the pharmaceutical development and regulatory approval process.
  • Clarifies controversial statistical issues (e.g., hypothesis testing versus confidence interval approach, missing data/estimands, multiplicity, and Bayesian design and approach) in review/approval of regulatory submissions.
  • Proposes innovative thinking regarding study designs and statistical methods (e.g., n-of-1 trial design, adaptive trial design, and probability monitoring procedure for sample size) for rare disease drug development.
  • Provides insight regarding current regulatory clinical initiatives (e.g., precision/personalized medicine, biomarker-driven target clinical trials, model informed drug development, big data analytics, and real world data/evidence).

This book provides key statistical concepts, innovative designs, and analysis methods that are useful in regulatory science. Also included are some practical, challenging, and controversial issues that are commonly seen in the review and approval process of regulatory submissions.

About the author

Shein-Chung Chow, Ph.D. is currently a Professor at Duke University School of Medicine, Durham, NC. He was previously the Associate Director at the Office of Biostatistics, Center for Drug Evaluation and Research, United States Food and Drug Administration (FDA). Dr. Chow has also held various positions in the pharmaceutical industry such as Vice President at Millennium, Cambridge, MA, Executive Director at Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers

Squibb, Plainsboro, NJ. He was elected Fellow of the American Statistical Association and an elected member of the ISI (International Statistical Institute). Dr. Chow is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and Biostatistics Book Series, Chapman and Hall/CRC Press, Taylor & Francis, New York. Dr. Chow is the author or co-author of over 300 methodology papers and 30 books.

 

 

Table of Contents

Preface

1.  Introduction
    Introduction
    Key Statistical Concepts
    Complex Innovative Designs
    Practical, Challenging, and Controversial Issues
    Aim and Scope of the Book

2.  Totality-of-the-Evidence
    Introduction
    Substantial Evidence
    Totality-of-the-evidence
    Practical and Challenging Issues
    Development of Index for Totality-of-the-Evidence
    Concluding Remarks

3. Hypotheses Testing Versus Confidence Interval
    Introduction
    Hypotheses Testing
    Confidence Interval Approach
    Two One-sided Tests Procedure and Confidence Interval Approach
    A Comparison
    Sample Size Requirement
    Concluding Remarks
    Appendix of Chapter 3

4. Endpoint Selection
    Introduction
    Clinical Strategy for Endpoint Selection
    Translations Among Clinical Endpoints
    Comparison of Different Clinical Strategies
    A Numerical Study
    Development of Therapeutic Index Function
    Concluding Remarks

5. Non-inferiority Margin
    Introduction
    Non-inferiority Versus Equivalence
    Non-inferiority Hypotheses
    Methods for Selection of Non-inferiority Margin
    Strategy for Margin Selection
    Concluding Remarks

6. Missing Data
    Introduction
    Missing Data Imputation
    Marginal/Conditional Imputation for Contingency
    Test for Independence
    Recent Development
    Concluding Remarks

7.  Multiplicity
    General Concepts
    Regulatory Perspective and Controversial Issues
    Statistical Methods for Multiplicity Adjustment
    Gate-keeping Procedures
    Concluding Remarks

8. Sample Size
    Introduction
    Traditional Sample Size Calculation
    Selection of Study Endpoints
    Multiple-Stage Adaptive Designs
    Adjustment with Protocol Amendments
    Multi-Regional Clinical Trials
    Current Issues
    Concluding Remarks

9. Reproducible Research
    Introduction
    The Concept of Reproducibility Probability
    The Estimated Power Approach
    Alternative Methods for Evaluation of Reproducibility Probability
    Applications
    Future Perspectives

10. Extrapolation
    Introduction
    Shift in Target Patient Population
    Assessment of Sensitivity Index
    Statistical Inference
    An Example
    Concluding Remarks
    Appendix of Chapter 10

11. Consistency Evaluation
    Introduction
    Issues in Multi-regional Clinical Trials
    Statistical Methods
    Simulation Study
    An Example
    Other Considerations/Discussions
    Concluding Remarks

12.  Drug Products with Multiple Components
    Introduction
    Fundamental Differences
    Basic Considerations
    TCM Drug Development
    Challenging Issues
    Recent Development
    Concluding Remarks

13. Adaptive Trial Design
    Introduction
    What Is Adaptive Design
    Regulatory/Statistical Perspectives
    Impact, Challenges, and Obstacles
    Some Examples
    Strategies for Clinical Development
    Concluding Remarks

14. Selection Criteria in Adaptive Dose Finding
    Introduction
    Criteria for Dose Selection
    Practical Implementation and Example
    Clinical Trial Simulations
    Concluding Remarks

15. Generic Drugs and Biosimilars
    Introduction
    Fundamental Differences
    Quantitative Evaluation of Generic Drugs
    Quantitative Evaluation of Biosimilars
    General Approach for Assessment of Bioequivalence/Biosimilarity
    Scientific Factors and Practical Issues
    Concluding Remarks

16. Precision and Personalized Medicine
    Introduction
    The Concept of Precision Medicine
    Design and Analysis of Precision Medicine
    Alternative Enrichment Designs
    Concluding Remarks

17. Big Data Analytics
    Introduction
    Basic Considerations
    Types of Big Data Analytics
    Bias of Big Data Analytics
    Statistical Methods for Estimation of ∆ and μP - μN 
    Concluding Remarks

18. Rare Disease Drug Development
    Introduction
    Basic Considerations
    Innovative Trial Designs
    Statistical Methods for Data Analysis
    Evaluation of Rare Disease Clinical Trials
    Some Proposals for Regulatory Consideration
    Concluding Remarks

References

Subject Index

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Author(s)

Biography

Shein-Chung Chow, Ph.D. is currently a Professor at Duke University School of Medicine, Durham, NC. He was previously the Associate Director at the Office of Biostatistics, Center for Drug Evaluation and Research, United States Food and Drug Administration (FDA). Dr. Chow has also held various positions in the pharmaceutical industry such as Vice President at Millennium, Cambridge, MA, Executive Director at Covance, Princeton, NJ, and Director and Department Head at Bristol-Myers

Squibb, Plainsboro, NJ. He was elected Fellow of the American Statistical Association and an elected member of the ISI (International Statistical Institute). Dr. Chow is Editor-in-Chief of the Journal of Biopharmaceutical Statistics and Biostatistics Book Series, Chapman and Hall/CRC Press, Taylor & Francis, New York. Dr. Chow is the author or co-author of over 300 methodology papers and 30 books.