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Predictive Computational Modeling


Jun 29, 2022 9:08am ‐ Jun 29, 2022 9:30am



Credits: None available.

Description

Computational Fluid Dynamics (CFD) modeling has been an effective tool for bioreactor design and scale up for years. An iterative approach of computational work and empirical testing is typically required to validate a CFD model that accurately predicts bioreactor performance across scales. To support scale-up of process intensified high-density cell culture, we have used M-Star CFD without iteration to develop a bioreactor model that closely correlates with empirical testing. In this session, we will present a study comparing computational results to empirical testing results for a 4,000L single use bioreactor. Measured and calculated blend time and mass transfer coefficient (KLa) data will be presented, as well as dynamic computational models showing real-time blending, shear, and velocity profiles. We will also show that the 4,000L single use bioreactor provides significant mass transfer capability to support high-density processing.

Speaker(s):

Credits

Credits: None available.

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