Modeling and optimal control of integrated continuous monoclonal antibody manufacturing processes

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Drugs based on mAbs play an indispensable role in biopharmaceutical industry in aspects of therapeutic and market potentials. In therapy and diagnosis applications, mAbs are widely used for the treatment of autoimmune diseases, and cancer, etc. According to a recent publication, mAbs also show promising results in the treatment of COVID-19. Until September 22, 2020, 94 therapeutic mAbs have been approved by U.S. Food & Drug Administration (FDA) and the number of mAbs approved within 2010-2020 is three times more than those approved before 2010. In terms of its market value, it is expected to reach a value of $198.2 billion in 2023. Thus, increasing the production capacity of mAb manufacturing processes is immediately necessary due to the explosive growth in mAb market. Canada is an active and competitive contributor to the development of high capacity mAb manufacturing processes. Integrated continuous manufacturing of mAbs represents the state-of-the-art in mAb manufacturing and has attracted a lot of attention. However, there is no existing mathematical model of the integrated manufacturing process and there is no optimal control algorithm of the entire integrated process. This project will fill the knowledge gaps by first developing a mathematical model of the integrated continuous manufacturing process of mAbs. The developed model will be validated using available data in the literature as well as potential data available from our industrial partner's clients. Based on the model, the machine-learning-based optimal control algorithm will be trained, assessed, and refined to get it ready for its implementation to industrial mAb manufacturing processes. This project will (a) further enhance the competitiveness of Canada in biopharmaceutical industry, (b) train highly qualified personnel (HQP) that have interdisciplinary backgrounds in biopharmaceutical and control engineering, and (c) may create more job opportunities in the partner organization in the near future.