Bayesian Methods in Pharmaceutical Research Bayesian Methods in Pharmaceutical Research
Chapman & Hall/CRC Biostatistics Series

Bayesian Methods in Pharmaceutical Research

Emmanuel Lesaffre and Others
    • $89.99
    • $89.99

Publisher 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.

GENRE
Professional & Technical
RELEASED
2020
April 15
LANGUAGE
EN
English
LENGTH
546
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
12.4
MB
Survival Analysis with Interval-Censored Data Survival Analysis with Interval-Censored Data
2017
Understanding Evidence-Based Rheumatology Understanding Evidence-Based Rheumatology
2014
Bayesian Biostatistics Bayesian Biostatistics
2012
Medical Risk Prediction Models Medical Risk Prediction Models
2021
Advanced Statistical Analytics for Health Data Science with SAS and R Advanced Statistical Analytics for Health Data Science with SAS and R
2025
R for Health Technology Assessment R for Health Technology Assessment
2025
Design and Analysis of Clinical Trials with Time-to-Event Endpoints Design and Analysis of Clinical Trials with Time-to-Event Endpoints
2009
Generalized Linear Models Generalized Linear Models
2000
Statistics In the Pharmaceutical Industry Statistics In the Pharmaceutical Industry
2019