Application of Mass Transfer Modeling to Improve Predictability of Scale-Down Industrial Fermentation Processes

Oxygen mass transfer is one of the largest constraints in scaling up aerobic fermentation processes. New fermentation conditions or strains that generate higher oxygen demands or broth viscosities often lead to oxygen limitations, thereby preventing implementation at industrial scale. Understanding which conditions will ultimately lead to oxygen limitation at industrial scale is of paramount importance for R&D programs that rely on scale-down models for process development. This presentation will describe a novel approach for using volumetric oxygen mass transfer coefficient (k_La) modeling to emulate large scale conditions in real-time. The construction of the k_La model will be reviewed and the utility will be demonstrated through a case study on a new strain for secondary metabolite production.