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[DOWNLOAD] "Bayesian Methods in Pharmaceutical Research" by Emmanuel Lesaffre, Gianluca Baio & Bruno Boulanger # Book PDF Kindle ePub Free

Bayesian Methods in Pharmaceutical Research

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eBook details

  • Title: Bayesian Methods in Pharmaceutical Research
  • Author : Emmanuel Lesaffre, Gianluca Baio & Bruno Boulanger
  • Release Date : January 15, 2020
  • Genre: Medical,Books,Professional & Technical,Pharmacology & Toxicology,
  • Pages : * pages
  • Size : 15170 KB

Description

Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients.


This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients.


The book covers:

Theory, methods, applications, and computing
Bayesian biostatistics for clinical innovative designs
Adding value with Real World Evidence
Opportunities for rare, orphan diseases, and pediatric development
Applied Bayesian biostatistics in manufacturing
Decision making and Portfolio management
Regulatory perspective and public health policies

Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.


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