Metabolic flux-based modeling of mAb production during batch and fed-batch operations

Abstract

This paper proposes mathematical models that predict the physiology, growth behavior and productivity of hybridoma cells in both batch and fed-batch systems. Murine hybridoma 130-8F producing anti-F-glycoprotein monoclonal antibody was employed as a model system. A systematic approach based on metabolic flux analysis (MFA) was utilized to yield a dynamic model for predicting the concentration of significant metabolites over time. Correlation analysis was performed to formulate a Biomass Model for predicting cell concentration and viability as a function of the extracellular metabolite concentrations. The coefficients of the model equation were estimated by employing the Metropolis-Hastings algorithm. The Metabolites Model was combined with the Biomass Model to get an Integrated Model capable of predicting concentration values for substrates, extracellular metabolites, and viable and dead cell concentration by utilizing only starting concentrations as input. The prediction accuracy of the model was tested by using experimental data.