Optimizing Feed Media Compositions
In practice, candidate production clones for scale-up often differ in metabolic phenotype resulting in different nutrient requirements during the process. Standardized feed media compositions cannot optimally support the individual nutrient demand, which can limit achievable product titers. Comprehensive metabolic characterization of the respective process not only furthers mechanistic understanding but also represents a good starting point for rational media optimization.
We computed optimized media compositions for distinct process phases based on the observed clone specific flux distributions by combining stationary and dynamic model simulations. For dynamic simulations, uniform kinetic rate laws were assigned to individual reaction steps. Additionally, feeds and sampling were accounted for. In this way, the impact of modifications in medium composition or feed rates on product synthesis, byproduct formation, and intracellular metabolism could be predicted (Figure 2).
Model parameters were determined using evolutionary strategies on high-performance computing clusters paying attention to reaction directionality where appropriate. The resulting model served to predict feed media compositions with optimized concentrations of glucose and amino acids for two sequential feeding streams.
Application of the predicted optimized feed in the cell culture process increased final product titer by more than 50% and increased the integral of viable cells already in the first iteration (Figure 3).
Moreover, a significant reduction in ammonium formation was observed. If necessary, the procedure can be repeated to further refine media compositions. Data from replicate fermentations can be included to increase the robustness of feed media proposals but is not essential.
Due its mechanistic nature, the stoichiometric network model captures forced couplings between substrate uptake and formation of byproducts. By comparison, DoE approaches entail a much larger number of experiments to extract such information, thus requiring more time and effort.