Bayesian Methods in Pharmaceutical Research (eBook, ePUB)

Redaktion: Lesaffre, Emmanuel; Boulanger, Bruno; Baio, Gianluca

• Format: ePub

Produktbeschreibung

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.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 546
• Erscheinungstermin: 15. April 2020
• Englisch
• ISBN-13: 9781351718660
• Artikelnr.: 59221663

Autorenporträt

Emmanuel Lesaffre, Gianluca Baio, Bruno Boulanger

Inhaltsangabe

I Introductory part
Chapter 1: Bayesian Background
Chapter 2: FDA Regulatory Acceptance of Bayesian Statistics
Chapter 3: Bayesian Tail Probabilities for Decision Making
II Clinical development
Chapter 4: Clinical Development in the Light of Bayesian Statistics
Chapter 5: Prior Elicitation
Chapter 6: Use of Historical Data
Chapter 7: Dose Ranging Studies and Dose Determination
Chapter 8: Bayesian Adaptive Designs in Drug Development
Chapter 9: Bayesian Methods for Longitudinal Data with Missingness
Chapter 10: Survival Analysis and Censored Data
Chapter 11: Benefit of Bayesian Clustering of Longitudinal Data: Study of
Cognitive Decline for Precision Medicine
Chapter 12: Bayesian Frameworks for Rare Disease Clinical Development
Programs
Chapter 13: Bayesian Hierarchical Models for Data Extrapolation and
Analysis in Pediatric Disease Clinical Trials
III Post-marketing
Chapter 14: Bayesian Methods for Meta-Analysis
Chapter 15: Economic Evaluation and Cost-Effectiveness of Health Care
Interventions
Chapter 16: Bayesian Modeling for Economic Evaluation Using "Real World
Evidence"
Chapter 17: Bayesian Benefit-Risk Evaluation in Pharmaceutical Research
IV Product development and manufacturing
Chapter 18: Product Development and Manufacturing
Chapter 19: Process Development and Validation
Chapter 20: Analytical Method and Assay
Chapter 21: Bayesian Methods for the Design and Analysis of Stability
Studies
Chapter 22: Content Uniformity Testing
Chapter 23: Bayesian methods for in vitro dissolution drug testing and
similarity comparisons
Chapter 24: Bayesian Statistics for Manufacturing
V Additional topics
Chapter 25: Bayesian Statistical Methodology in the Medical Device Industry
Chapter 26: Program and Portfolio Decision-Making