CFD-based Bayesian Optimization of Stirring Strategies in Stirred Tank Cultures of Pluripotent Stem Cell Spheroids

Abstract

The suspension culture of pluripotent stem (PS) cells in stirred bioreactors poses a delicate balance between maintaining homogeneous cell dispersion and avoiding excessive shear stress that can compromise cell viability and pluripotency. In this study, we used computational fluid dynamics (CFD) coupled with a discrete particle method (DPM) to simulate iPS cell behavior in a 5 mL delta-impeller stirred tank. Our analysis revealed that upward flow at the tank bottom and downward flow at the top are critical for maintaining a stable suspension. To optimize the stirring protocol, we applied Bayesian optimization to identify a time-dependent stirring schedule that begins with a high-speed phase for resuspension, followed by a low-speed phase for sustained suspension with minimal hydrodynamic stress. The optimized schedule demonstrated improved floating rate and reduced slip velocity, indicating lower mechanical stress on cells. These findings provide engineering insights into scalable bioreactor operation, contributing to the design of robust iPS cell manufacturing systems. HighlightsO_LICFD-DPM simulations predicted iPS spheroid motion in a stirred tank. C_LIO_LIBayesian optimization identified a two-step agitation strategy. C_LIO_LIHigh initial agitation promoted rapid particle resuspension. C_LIO_LILow subsequent agitation maintained suspension with lower downflow. C_LIO_LIParticle Reynolds number correlated with the floating rate. C_LI