MANUFACTURING
Applying PAT to the Continuous Digital Biomanufacturing of Monoclonal Antibodies Biomanufacturing is moving toward digital manufacturing with increased application of process analytical technology (PAT) and continuous manufacturing. This article describes experiences in the modelling, design, control, and operation of continuous monoclonal antibody (mAb) manufacturing processes. Fully automated processes employ in-line and at-line PAT that are used to build mechanistic models to confirm process understanding and design real-time feedback control of critical quality attributes (CQAs). Moo Sun Hong, Postdoctoral Associate, Department of Chemical Engineering, Massachusetts Institute of Technology Amos E Lu, Postdoctoral Associate, Department of Chemical Engineering, Massachusetts Institute of Technology Andrew J Maloney, Graduate Student, Department of Chemical Engineering, Massachusetts Institute of Technology Rui Wen Ou, Lab Manager, Department of Biology, Massachusetts Institute of Technology Jacqueline M Wolfrum, Research Scientist, Center for Biomedical Innovation, Massachusetts Institute of Technology Stacy L Springs, Research Scientist, Center for Biomedical Innovation, Massachusetts Institute of Technology Anthony J Sinskey, Professor, Department of Biology, Massachusetts Institute of Technology Richard D Braatz, Edwin R. Gilliland Professor, Department of Chemical Engineering, Massachusetts Institute of Technology
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P H A RM A F O C U S A S I A
ISSUE 44 - 2021
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onoclonal antibodies (mAbs) are the highest selling class of biologics due to their specific action and reduced immunogenicity. As the use of mAbs promotes treating many diseases (e.g., cancer) with better targeted immunological approaches, the development of mAbs will continue to increase. Process analytical technology (PAT) is increasingly applied in biopharmaceutical manufacturing. PAT is “a system for designing, analysing, and controlling manufacturing through the timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes, with the goal of ensuring final product quality.” On-line measurements of critical quality attributes (CQAs) lead to increased process understanding and facilitate construction of process models, with most of the PAT being implemented in upstream processing. Standard sensors provide in-reactor analysis of optical density, dissolved oxygen, temperature, and pH. Moreover, online analytics of in-vessel Raman, viable cell density via capacitance, and off-gas and weight control
