Development of advanced computational tools for the intensification of monoclonal antibody production

Abstract In this work we demonstrate an advanced, model-based control strategy for the maximization of the productivity of a mammalian cell culture system, using GS-NS0 cells. We consider an unstructured, differential and algebraic equation model that describes the events taking place in the bioreactor, based on glucose and four key amino acids. In particular, we monitor and maximize the accumulation of the monoclonal antibody (mAb) in the cell culture system using the feed flow rate as the control input. For the development of the controller we are following the PAROC framework and software platform, based on multi-parametric policies. The performance of the controller is also assessed in-silico against the process model. The designed optimal control policy significantly the antibody concentration within the culture and indicates a biologically significant input profile.