Bioprocess Optimization: Leveraging Functional DOE With Time-Based Insights

Consistent product quality in biopharmaceutical production depends on precise control of cell culture dynamics. Traditional Design of Experiments (DOE) methods help identify critical quality attributes and process parameters, but they often focus on single-value outcomes, such as peak viable cell density or final titer, overlooking the dynamic, time-dependent nature of bioprocesses. Functional DOE addresses this limitation by utilizing time-based data to predict the evolution of key process parameters and uncover complex interactions. By analyzing how these parameters evolve over time, Functional DOE provides deeper insights for optimizing both fed-batch and continuous cell culture processes, leading to more effective decision-making in process development and manufacturing simulations.

In this webinar, we will explore the key differences between traditional DOE and Functional DOE and demonstrate how the latter enhances bioprocess optimization through a fed-batch cell culture example. We will also highlight how Samsung Biologics applies Functional DOE to improve productivity and maintain robust product quality.

Key learning objectives include understanding the limitations of traditional DOE in capturing bioprocess dynamics, exploring advanced statistical techniques used in Functional DOE, and learning how Samsung Biologics leverages this approach to optimize process control and product quality.