Dynamic Optimisation of Fed-Batch Bioreactors for mAbs: Sensitivity Analysis of Feed Nutrient Manipulation Profiles

Abstract

Successful cultivation of mammalian cells must consider careful formulation of culture media consisting of a variety of substrates and amino acids. A widely cited method for quantifying metabolic networks of mammalian cultures is dynamic flux balance modelling. Application of in-silico techniques allows researchers to circumvent time-consuming and costly in-vivo experimentation. Dynamic simulation and optimisation of reliable models allows for the visualization of opportunities to improve throughputs of target protein products, such as monoclonal antibodies (mAbs). This study presents a sensitivity analysis comparing dynamic optimisation results for industrial-scale fed-batch bioreactors, considering a variety of initial conditions. Optimized feeding trajectories are computed via Nonlinear Programming (NLP) model, employing the established IPOPT solver. Glucose, then glutamine, then asparagine, can lead to improved mAb yields and viable cell counts.