Description

Book Synopsis

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

Trade Review

"The book is full of interesting real examples across the chapters, which not only makes the reading fun but also demonstrates the practical usefulness of Bayesian methods in pharmaceutical research. In synthesis, this is a very well written book, which can be used as self-learning material or as a main reference for experts and practitioners."

- Pablo Emilio Verde, International Society for Clinical Biostatistics, 72, 2021



Table of Contents

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

Bayesian Methods in Pharmaceutical Research

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    A Paperback by Emmanuel Lesaffre, Gianluca Baio, Bruno Boulanger

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      View other formats and editions of Bayesian Methods in Pharmaceutical Research by Emmanuel Lesaffre

      Publisher: CRC Press
      Publication Date: 12/13/2021 12:00:00 AM
      ISBN13: 9781032241524, 978-1032241524
      ISBN10: 1032241527

      Description

      Book Synopsis

      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

      Trade Review

      "The book is full of interesting real examples across the chapters, which not only makes the reading fun but also demonstrates the practical usefulness of Bayesian methods in pharmaceutical research. In synthesis, this is a very well written book, which can be used as self-learning material or as a main reference for experts and practitioners."

      - Pablo Emilio Verde, International Society for Clinical Biostatistics, 72, 2021



      Table of Contents

      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

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