Dynamic Optimization of the Production of Monoclonal Antibodies in Semi-batch Operation

Abstract

Monoclonal antibodies (mAbs) represent the fastest growing product in the biopharmaceutical industry. mAbs are traditionally produced by the large-scale culture of mammalian cells, which suffers from low productivity. Typically, production improvements are achieved by trial and error and time-consuming costly experiments. In recent years, noticeable progress has been accomplished in modelling, opening the possibility for the more cost-effective model-based optimization and control. In this work, different strategies for optimized mAb production in mammalian cell cultures taking into account all essential amino acids depletion and the energy requirements of the cells are examined and compared, using a predictive energy-based model presented in Quiroga et al. (ESCAPE 2016). In the optimization of different objectives all production rate, cell viability and culture time are simultaneously considered. For the formulation of the optimization problem a combination of two objectives consisting of production rate and number of viable cells in the culture is additionally performed. The optimization results indicate a significant increase in productivity and an extension of the culture lifetime. In addition, they show a strong connection between culture viability and mAb production, and highlight the potential of utilizing multi-objective optimization in mammalian cell cultures.