Case studies in Bayesian methods for biopharmaceutical CMC
by Faya, Paul Pourmohamad, Tony
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). The collection of case studies covers a broad array of CMC topics, including stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and com…
Read More ↓Title Statements
- Full title :Case studies in Bayesian methods for biopharmaceutical CMC / edited by Paul Faya, Tony Pourmohamad.
Summary
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). The collection of case studies covers a broad array of CMC topics, including stability analysis, analytical method development, specification setting, process development and optimization, process control, experimental design, dissolution testing, and comparability studies. The analysis of each case study includes a presentation of code and reproducible output. This book is written with an academic level aimed at practicing nonclinical biostatisticians, most of whom have graduate degrees in statistics. First book of its kind focusing strictly on CMC Bayesian case studies Case studies with code and output Representation from several companies across the industry as well as academia Authors are leading and well-known Bayesian statisticians in the CMC field Accompanying website with code for reproducibility Reflective of real-life industry applications/problems
Read More ↓Edition Statements
- Publication Date:2022.
Publication Statements
- Publisher(s):Chapman & Hall/CRC
- Place of Publication:Boca Raton
- Language:eng
- Publication Date:2022.
The Physical Object
- Description:1 online resource (1 volume)
Edition Identifiers
- ISBN:9781003255093, 1003255094, 9781000824865, 1000824861, 9781000824773, 1000824772
- DOI:10.1201/9781003255093
- oclc:on1349720087
- LC Classification:RM301.4
- Dewey Decimal:615.701519542
Table of Contents
<P>1. Introduction</P><I><P>Paul Faya and Tony Pourmohamad</P></I><P>2. An Overview of Bayesian Computation </P><I><P>David J. Kahle, John W. Seaman Jr., and James D. Stamey</P></I><P>3. Basic Bayesian Model Checking<BR><BR><I>John W. Seaman Jr., David J. Kahle, and James D. Stamey<BR></I><BR>4. Quantitative Decision -- Making, a CMC application to analytical method equivalence</P><I><P>Misbah Ahmed and Mike Denham</P></I><P>5. Bayesian Dissolution Testing</P><I><P>Tony Pourmohamad and Robert Richardson</P></I><P>6. A Non-Normal Bayesian Model for the Estimation and Comparison of Immunogenicity Screening Assay Cut-Points</P><I><P>David LeBlond and Robert Singer, Lu Xu, and Rong Zeng<BR></I><BR>7. Application of Bayesian Hierarchical Models to Experimental Design</P><I><P>Adam P. Rauk and Paul Faya</P></I><P>8. Bayesian Prediction for Staged Testing Procedures</P><I><P>Katherine E.D. Giacoletti and Tara Scherder</P></I><P>9. A Bayesian Approach to Multivariate Conditional Regression Surrogate Modeling with Application to Real Time Release Testing </P><I><P>Stan Altan, Dwaine Banton, Hans Coppenolle, Martin Kovarik and Martin Otava, and Christian Schmid</I><BR><BR>10. Bayesian Appro…
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