In the United States, a rare disease is defined by the Orphan Drug Act as a disorder or condition that affects fewer than 200,000 persons. For the approval of "orphan" drug products for rare diseases, the traditional approach of power analysis for sample size calculation is not feasible because there are only limited number of subjects available for clinical trials. In this case, innovative approaches are needed for providing substantial evidence meeting the same standards for statistical assurance as drugs used to treat common conditions. Innovative Methods for Rare Disease Drug Development focuses on biostatistical applications in terms of design and analysis in pharmaceutical research and development from both regulatory and scientific (statistical) perspectives.
Key Features:
- Reviews critical issues (e.g., endpoint/margin selection, sample size requirements, and complex innovative design).
- Provides better understanding of statistical concepts and methods which may be used in regulatory review and approval.
- Clarifies controversial statistical issues in regulatory review and approval accurately and reliably.
- Makes recommendations to evaluate rare diseases regulatory submissions.
- Proposes innovative study designs and statistical methods for rare diseases drug development, including n-of-1 trial design, adaptive trial design, and master protocols like platform trials.
- Provides insight regarding current regulatory guidance on rare diseases drug development like gene therapy.
Preface. 1. Introduction. 2. Basic Considerations. 3. Hypotheses Testing for Clinical Evaluation. 4. Endpoint Selection in Clinical Trials. 5. Strategy for Margin Selection. 6. Probability of Inconclusiveness. 7. Probability Monitoring Procedure for Sample Size. 8. Real-World Data and Real-World Evidence. 9. Innovative Approaches for Rare Diseases Drug Development. 10. The n-of-1 Trial Design and Its Application. 11. Two-Stage Adaptive Seamless Trial Design. 12. Master Protocol - Platform Trial Design. 13. Gene Therapy for Rare Diseases. 14. Clinical Development for NASH Program
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.
"I recommended this book not only to statisticians and physicians working on drug development but also to scientists/professionals involving in patients' access in personalized medicine. The book is directly not only useful for trial study design for rare disease for regulatory approval but also helpful on providing statistical concepts for other type of studies tackling many statistical issues such as limited numbers of research objects."
Min-Hua Jen, Eli Lilly, Bracknell UK, Journal of the Royal Statistical Society: Series A, 2022.
