biostatistics for bioassay

In recent decades, there has been enormous growth in biologics research and development, with the accompanying development of biological assays for emerging products. In parallel, there have been substantial advances in statistical methodology, as well as technological advances in computer power, enabling new techniques to be implemented via statistical software. Biostatistics for Bioassay presents an overview of the statistical analysis techniques that are needed in order to report the results of biological assays. These assays are needed for testing all biological medicines, such as vaccines and cell therapies, to allow them to be released for use. Beginning with consideration of the performance characteristics required of a bioassay, including accuracy, precision, and combinations of these two attributes, the book builds a framework for statistical bioassay design.

Features:

• Explains the statistical methods needed at each stage of the lifecycle of a bioassay
• Describes the demonstration of the bioassay’s performance, known as validation
• Covers the statistical techniques for monitoring the bioassay’s performance over time
• Details how to transfer the bioassay to another laboratory or replace critical reagents
• Provides examples at every stage, to allow the reader to work through the techniques and consolidate their understanding

The book provides a resource for interested bioassay analysts, and statisticians working with bioassays. In bringing together best practices in statistics across the bioassay lifecycle into a single volume, it aims to provide a comprehensive and useful textbook for statistical analysis in bioassay.

Ann Yellowlees is Founder of Quantics Biostatistics. Ann has worked in academia, Shell Research, and the NHS in Scotland. She has been consulting in bioassay statistics since 2006. She holds degrees in both mathematics and applied statistics from the University of Oxford, and a PhD in statistics from the University of Waterloo.

Matthew Stephenson is a Director of Statistics at Quantics Biostatistics, with an undergraduate degree in human kinetics, and an MSc and PhD in statistics from the University of Guelph. He won the 2020 Canadian Journal of Statistics Award for his PhD research on leveraging graphical structure among predictors to improve outcome prediction.