Mechanistic models are available for some unit operations, however they are not yet widely used to support biopharmaceutical development. In this case study, modeling was used to support process characterization and the development of a control strategy. As a part of late phase development, following main scoping experiments, process robustness under established conditions was evaluated. Factorial Design of Experiments (DoE) was used to examine extremes of parameters on potential critical quality attributes (pCQAs). Additionally, a mechanistic model was developed for a specific part of the process. Using process knowledge and historical batch data, a process attribute risk assessment was conducted to identify potential critical process parameters (pCPPs) to investigate during process characterization mixed design DoEs.<br/>Following process characterization, both a mechanistic model and statistical polynomial model were used to define a design space in which product quality met its expected targets when the identified CPPs were varied. Based on the results of the process characterization studies, proven acceptable ranges (PARs) for critical process parameters were demonstrated to be robust within the studied design space. This case study shows how mechanistic modeling can be used complementarily to more traditional statistical modeling approaches and bring a deeper level of process understanding.

Use of modeling to support the development of a control strategy and process characterization

Macromolecular Chemistry: The Second Century

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ACS Spring 2020 National Meeting & Expo

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