Real-world evidence in drug development and evaluation

著者

    • Yang, Harry
    • Yu, Binbing

書誌事項

Real-world evidence in drug development and evaluation

edited by Harry Yang, Binbing Yu

(Chapman & Hall/CRC biostatistics series)

CRC Press, c2021

  • : hbk

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field. Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions. Features Provides the first book and a single source of information on RWE in drug development Covers a broad array of topics on outcomes- and value-based RWE assessments Demonstrates proper Bayesian application and causal inference for real-world data (RWD) Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise

目次

1 Using Real-world Evidence to Transform Drug Development: Opportunities and Challenges. 2. Evidence derived from real world data: utility, constraints and cautions. 3. Real-World Evidence from Population-Based Cancer Registry Data. 4. External Control using RWE and Historical Data in Clinical Development. 5. Bayesian method for assessing drug safety using real-world evidence. 6. Real-World Evidence for Coverage and Payment Decisions. 7. Causal Inference for Observational Studies/Real-World Data. 8. Introduction to Artificial Intelligence and Deep Learning with a Case Study in Analyzing Electronic Health Records for Drug Development.

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詳細情報

  • NII書誌ID(NCID)
    BC08644650
  • ISBN
    • 9780367026219
  • 出版国コード
    us
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Boca Raton
  • ページ数/冊数
    xii, 178 p.
  • 大きさ
    24 cm
  • 親書誌ID
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