Research Scientist US Food and Drug Administration
Due to the central role that cellular metabolism plays in the observed variability of a drug substance’s Critical Quality Attributes (CQA), we envision a potential novel approach for biomanufacturing processes that monitors a set of Critical Metabolic Parameters (CMP) in addition to the macroscopic process conditions used as Critical Process Parameters (CPP) today. Constraint-based systems biology models like Flux Balance Analysis (FBA) can be used to estimate metabolic reaction rates; by using metabolic rates as inputs to multivariate Batch Evolution Models (BEM), our data show that metabolic activity is reproducible among batches and can be monitored to detect a deliberately induced macroscopic process change such as a temperature shift. This new approach has the potential to increase process flexibility by defining golden batches in biomanufacturing processes from internal metabolic activity to enable Quality by Design at the cellular scale.
Learning Objectives:
Upon completion, participants will be able to construct systems biology models to predict cellular metabolic activity and use multivariate batch evolution models to monitor cellular metabolism in upstream biomanufacturing processes.
Upon completion, participants will be able to detect when a process deviation occurs from changes in cellular metabolism.
Upon completion, participants will be able to characterize metabolic behavior in their own biomanufacturing processes by implementing a similar modeling strategy.
