9780367637019-0367637014-Real-World Evidence in Drug Development and Evaluation (Chapman & Hall/CRC Biostatistics Series)

Real-World Evidence in Drug Development and Evaluation (Chapman & Hall/CRC Biostatistics Series)

ISBN-13: 9780367637019
ISBN-10: 0367637014
Edition: 1
Author: Harry Yang, Binbing Yu
Publication date: 2022
Publisher: Chapman and Hall/CRC
Format: Paperback 190 pages
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Book details

ISBN-13: 9780367637019
ISBN-10: 0367637014
Edition: 1
Author: Harry Yang, Binbing Yu
Publication date: 2022
Publisher: Chapman and Hall/CRC
Format: Paperback 190 pages

Summary

Real-World Evidence in Drug Development and Evaluation (Chapman & Hall/CRC Biostatistics Series) (ISBN-13: 9780367637019 and ISBN-10: 0367637014), written by authors Harry Yang, Binbing Yu, was published by Chapman and Hall/CRC in 2022. With an overall rating of 3.7 stars, it's a notable title among other books. You can easily purchase or rent Real-World Evidence in Drug Development and Evaluation (Chapman & Hall/CRC Biostatistics Series) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.91.

Description

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

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