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Develop Effective Immunogenicity Risk Mitigation Strategies
Immunogenicity assessment is a prerequisite for the successful
development of biopharmaceuticals, including safety and efficacy
evaluation. Using advanced statistical methods in the study design
and analysis stages is therefore essential to immunogenicity risk
assessment and mitigation strategies. Statistical Methods for
Immunogenicity Assessment provides a single source of information
on statistical concepts, principles, methods, and strategies for
detection, quantification, assessment, and control of
immunogenicity. The book first gives an overview of the impact of
immunogenicity on biopharmaceutical development, regulatory
requirements, and statistical methods and strategies used for
immunogenicity detection, quantification, and risk assessment and
mitigation. It then covers anti-drug antibody (ADA) assay
development, optimization, validation, and transfer as well as the
analysis of cut point, a key assay performance parameter in ADA
assay development and validation. The authors illustrate how to
apply statistical modeling approaches to establish associations
between ADA and clinical outcomes, predict immunogenicity risk, and
develop risk mitigation strategies. They also present various
strategies for immunogenicity risk control. The book concludes with
an explanation of the computer codes and algorithms of the
statistical methods. A critical issue in the development of
biologics, immunogenicity can cause early termination or limited
use of the products if not managed well. This book shows how to use
robust statistical methods for detecting, quantifying, assessing,
and mitigating immunogenicity risk. It is an invaluable resource
for anyone involved in immunogenicity risk assessment and control
in both non-clinical and clinical biopharmaceutical development.
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