Accurate definition of control strategies using cross validated stepwise regression and Monte Carlo simulation.

Journal of Biotechnology
Patrick Y YangCary F Opel

Abstract

Drug manufacturing processes must consistently deliver safe and effective product. A key part of achieving this is process validation utilizing Quality by Design (QbD) principles. To meet process validation requirements, process characterization (PC) studies are often performed to expand process understanding and establish an appropriate control strategy that enables the manufacturing process to consistently deliver a target product profile. Two key elements of the control strategy resulting from PC work are a list of critical process parameters (CPPs) and defined operating ranges (ORs). These are frequently derived based on mathematical models describing the relationship between process parameters and critical quality attributes (CQAs). Risk assessment and design of experiments (DOE) techniques are effectively deployed in the industry to identify parameters to study and build process understanding. However, traditional data analysis techniques do not fully utilize the data produced by these studies. In particular, stepwise regression algorithms based on p-values are prone to generate false positives and overfit data, potentially leading to unnecessarily complex control strategies. Many of the deficiencies of traditional stepwi...Continue Reading

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Citations

Apr 4, 2021·Biotechnology and Bioengineering·Tim BrantleySarwat Khattak

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