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.
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