About Model Validation in Bioprocessing

• Main Authors: Vignesh Rajamanickam, Heiko Babel, Liliana Montano-Herrera, Alireza Ehsani, Fabian Stiefel, Stefan Haider, Beate Presser, Bettina Knapp
• Format: Article
• Language: English
• Published: MDPI AG 2021-05-01
• Series: Processes
• Subjects: bioprocess models; model validation; model calibration; quality by design; mechanistical and statistical models; hybrid models
• Online Access: https://www.mdpi.com/2227-9717/9/6/961

In bioprocess engineering the Qualtiy by Design (QbD) initiative encourages the use of models to define design spaces. However, clear guidelines on how models for QbD are validated are still missing. In this review we provide a comprehensive overview of the validation methods, mathematical approaches, and metrics currently applied in bioprocess modeling. The methods cover analytics for data used for modeling, model training and selection, measures for predictiveness, and model uncertainties. We point out the general issues in model validation and calibration for different types of models and put this into the context of existing health authority recommendations. This review provides a starting point for developing a guide for model validation approaches. There is no one-fits-all approach, but this review should help to identify the best fitting validation method, or combination of methods, for the specific task and the type of bioprocess model that is being developed.