In biopharmaceutical production, time-based dynamic changes in cell culture have a significant impact on process performance and product quality. Conventional design of experiments (DOE) analysis mainly focuses on the final results, and has limitations in fully reflecting complex interactions over time during the culture process. On the other hand, Functional DOE can predict changes in Viable Cell Density (VCD) and metabolites by utilizing time-based data. This supports process optimization in the development phase and predicts problems caused by changes in set values in advance in the production phase, thereby ensuring stable production.
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In this presentation, we will use a typical fed-batch animal cell culture process as an example to introduce how Functional DOE can predict cell culture variability and how it can be utilized for process optimization, in comparison with existing DOE analysis techniques.
