Shein-Chung Chow, Jun Shao
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Subjects -> Medicine -> Pharmacology -> Pharmacy
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Customer Reviews:
Total reviews: 2
Average rating: 5.0 of 5
great reference, a must have for pharamceutical statisticians 5 out of 5 stars.
28 of 28 people found this review helpful.
This is a very new and unique book that covers the gamut of statistical issues through all phases of drug development. Shao is a distinguished professor from Wisconsin and Chow teaches at Duke University and formerly at Temple but is known for his long career in the pharmaceutical industry.
The book is good for biostatisticians and regulatory affairs specialists as a reference source. All the key statistical issues are addressed and the reader is given the perspective of the ICH and FDA guidance documents. The underlying statistical methodology that justifies the recommendations in the guidances is presented. This is a state-of-the-art book. Shao and Pigeot produced some of the recent research in individual bioequivalence that established a bootstrap procedure as an appropriate way to construct confidence intervals for the problem. Their method is recommended in an FDA guidance document.
But more than just this one example, all the key issues that have been the subject of FDA workshops over the past several years are addressed in this book. These topics include calibration, assay and assay validation, dissolution testing, stability analysis, shelf life estimation, bioequivalence, randomization and blinding, what constitutes substantive evidence in clinical development, therapeutic equivalence and noninferiority, Bayesian approaches in clinical trials, problems involving missing and incomplete data, longitudinal methods, meta-analysis, quality of life studies and instrument validation, and medical imaging.
Other prevalent issues in clinical trials include group sequential methods, hierarchical Bayesian models and multiple testing. These issues are not covered as much in this text as the others we have mentioned. But there is some discussion of multiplicity in the context of quality of life studies. An example of sequential testing is used to illustrate model selection in Chapter 2. The important issues of design and sample size requirements are presented throughout the book.
While not all topics are covered in sufficient depth, the book is remarkable in the breadth of material covered in just 350 pages of text. The authors also provide a very authoritative list of references and regulatory guidances and other documents.
Editorial Review:
Emphasizing the role of good statistical practices (GSP) in drug research and formulation, this book outlines important statistics applications for each stage of pharmaceutical development to ensure the valid design, analysis, and assessment of drug products under investigation and establish the safety and efficacy of pharmaceutical compounds. Coverage include statistical techniques for assay validation and evaluation of drug performance characteristics, testing population/individual bioequivalence and in vitro bioequivalence according to the most recent FDA guidelines, basic considerations for the design and analysis of therapeutic equivalence and noninferiority trials.
