Case Studies in Bayesian Methods for Biopharmaceutical CMC

The subject of this book is applied Bayesian methods for chemistry, manufacturing, and control (CMC) studies in the biopharmaceutical industry. The book has multiple authors from industry and academia, each contributing a case study (chapter), covering a broad array of CMC topics.

Autorentext

Paul Faya (Ph.D.) is a Director in Discovery and Development Statistics with Eli Lilly and Company, USA.

Tony Pourmohamad (Ph.D.) is a Principal Statistical Scientist with Genentech, USA, and an Assistant Adjunct Professor in the Department of Statistics at the University of California, Santa Cruz.

Inhalt

1. Introduction 2. An Overview of Bayesian Computation 3. Basic Bayesian Model Checking 4. Quantitative Decision - Making, a CMC application to analytical method equivalence 5. Bayesian Dissolution Testing 6. A Non-Normal Bayesian Model for the Estimation and Comparison of Immunogenicity Screening Assay Cut-Points 7. Application of Bayesian Hierarchical Models to Experimental Design 8. Bayesian Prediction for Staged Testing Procedures 9. A Bayesian Approach to Multivariate Conditional Regression Surrogate Modeling with Application to Real Time Release Testing 10. Bayesian Approach for Demonstrating Analytical Similarity 11. Bayesian Evaluation and Monitoring of Process Comparability 12. Bayesian Alternatives to Traditional Methods for Estimating Product Shelf Life and Internal Release Limits 13. Application of Bayesian Methods for Specification Setting 14. Calculating Statistical Tolerance Intervals Using SAS 15. A Bayesian Application in Process Monitoring - Establishing Limits for Dosage Units in Early Phase Process Control