Emmanuel Lesaffre, Gianluca Baio, Bruno Boulanger

"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

• I Introductory part Chapter 1: Bayesian Background Chapter 2: FDA Regulatory Acceptance of Bayesian StatisticsChapter 3: Bayesian Tail Probabilities for Decision Making II Clinical development Chapter 4: Clinical Development in the Light of Bayesian Statistics Chapter 5: Prior ElicitationChapter 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 MissingnessChapter 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-AnalysisChapter 15: Economic Evaluation and Cost-Effectiveness of Health Care InterventionsChapter 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

Emmanuel Lesaffre, Gianluca Baio, Bruno Boulanger

"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

• I Introductory part Chapter 1: Bayesian Background Chapter 2: FDA Regulatory Acceptance of Bayesian StatisticsChapter 3: Bayesian Tail Probabilities for Decision Making II Clinical development Chapter 4: Clinical Development in the Light of Bayesian Statistics Chapter 5: Prior ElicitationChapter 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 MissingnessChapter 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-AnalysisChapter 15: Economic Evaluation and Cost-Effectiveness of Health Care InterventionsChapter 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

Emmanuel Lesaffre, Gianluca Baio, Bruno Boulanger

"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

• I Introductory part Chapter 1: Bayesian Background Chapter 2: FDA Regulatory Acceptance of Bayesian StatisticsChapter 3: Bayesian Tail Probabilities for Decision Making II Clinical development Chapter 4: Clinical Development in the Light of Bayesian Statistics Chapter 5: Prior ElicitationChapter 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 MissingnessChapter 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-AnalysisChapter 15: Economic Evaluation and Cost-Effectiveness of Health Care InterventionsChapter 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