Bayesian experimental design for optimizing medium composition and biomass formation of tobacco BY-2 cell suspension cultures in stirred-tank bioreactors

The results demonstrate the advantages of BED to generate new medium compositions (i.e., macronutrient concentrations) by unbiasedly varying the design space. Thereby, the discovery of new process insights (i.e., impact of individual macronutrient concentrations on the growth rate and biomass formation) is facilitated. Moreover, we show that our data-efficient and black-box BED approach represents a promising alternative to traditional design of experiments (DoE) and mechanistic white-box modeling. Established for the plant suspension cell line BY-2, our BED approach might also apply to yeast and mammalian cells.