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  • © 2017

Quantitative Decisions in Drug Development

  • Focuses on important decision points and evidence needed for making decisions at these points during the development of a new drug
  • Takes a holistic approach towards drug development by incorporating knowledge learned from the earlier part of the development explicitly into the decisions at later stages
  • Shows the parallel between clinical trials and diagnostic tests and how this analogy is used to emphasize the importance of replication in drug development
  • Describes how to incorporate prior knowledge into study design and decision making at different stages of drug development
  • Explains metrics useful to address the objectives of the different stages of drug development and how to compare design options based on these metrics
  • Demonstrates why over-estimation is a common problem in drug development and how adjustment should be considered to correct the over-estimation

Part of the book series: Springer Series in Pharmaceutical Statistics (SSPS)

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xv
  2. Clinical Testing of a New Drug

    • Christy Chuang-Stein, Simon Kirby
    Pages 1-18
  3. A Frequentist Decision-Making Framework

    • Christy Chuang-Stein, Simon Kirby
    Pages 19-31
  4. Characteristics of a Diagnostic Test

    • Christy Chuang-Stein, Simon Kirby
    Pages 33-40
  5. The Parallel Between Clinical Trials and Diagnostic Tests

    • Christy Chuang-Stein, Simon Kirby
    Pages 41-51
  6. Incorporating Information from Completed Trials in Future Trial Planning

    • Christy Chuang-Stein, Simon Kirby
    Pages 53-67
  7. Choosing Metrics Appropriate for Different Stages of Drug Development

    • Christy Chuang-Stein, Simon Kirby
    Pages 69-84
  8. Designing Proof-of-Concept Trials with Desired Characteristics

    • Christy Chuang-Stein, Simon Kirby
    Pages 85-104
  9. Designing Dose-Response Studies with Desired Characteristics

    • Christy Chuang-Stein, Simon Kirby
    Pages 105-121
  10. Designing Confirmatory Trials with Desired Characteristics

    • Christy Chuang-Stein, Simon Kirby
    Pages 123-137
  11. Designing Phase 4 Trials

    • Christy Chuang-Stein, Simon Kirby
    Pages 139-151
  12. Discounting Prior Results to Account for Selection Bias

    • Christy Chuang-Stein, Simon Kirby
    Pages 173-190
  13. Additional Topics

    • Christy Chuang-Stein, Simon Kirby
    Pages 191-207
  14. Back Matter

    Pages 209-248

About this book

This book offers a high-level treatise of evidence-based decisions in drug development. Because of the inseparable relationship between designs and decisions, a good portion of this book is devoted to the design of clinical trials. The book begins with an overview of product development and regulatory approval pathways. It then discusses how to incorporate prior knowledge into study design and decision making at different stages of drug development. The latter include selecting appropriate metrics to formulate decisions criteria, determining go/no-go decisions for progressing a drug candidate to the next stage and predicting the effectiveness of a product. Lastly, it points out common mistakes made by drug developers under the current drug-development paradigm.

The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have a basic understanding of the drug-development processand the clinical trials conducted to support drug-marketing authorization.

The authors provide software codes for select analytical approaches discussed in the book. The book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making themselves.

Reviews

“This work offers useful algorithms, classifications, and other general points to statisticians or ‘quantitative scientists’. But, it is also really useful to regulatory affairs managers, clinicians, medical writers, and all kinds of decision-makers in the industry.” (Andrei Myslivets, ISCB News, Vol. 68, December, 2019)

“It is presented in a concise, structured, friendly, and illustrative way that allows for a good understanding of the underlying ideas … . the book from Chuang-Stein and Kirby is a valuable, interesting and easy read for statisticians and clinicians with some methodological background who are involved in clinical development or drug approval and who are looking for a structured way to make clinical development decisions.” (Norbert Benda, Biometrical Journal, Vol. 61 (4), July, 2016)

Authors and Affiliations

  • Kalamazoo, USA

    Christy Chuang-Stein

  • Pfizer Statistical Research & Consulting Center, Cambridge, United Kingdom

    Simon Kirby

About the authors

Christy Chuang-Stein was Vice President and Head of the Statistical Research and Consulting Center at Pfizer prior to retirement from the company in July 2015. She has more than 30 years of experience in the pharmaceutical industry and 160 scientific publications. She is a Fellow of the American Statistical Association (ASA) and received ASA’s Founders’ Award in 2012. She was the recipient of the Distinguished Achievement Award of the International Chinese Statistical Association in 2013.


Simon Kirby is Senior Director at the Statistical Research and Consulting Center at Pfizer. He has worked for Pfizer for more than 17 years after previously holding the position of Principal Lecturer in Statistics at Liverpool John Moores University. He has also previously worked as a Statistician at the Institute of Food Research in the UK, Rothamsted and Revlon Healthcare.


Bibliographic Information

Buy it now

Buying options

eBook USD 54.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 69.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access