Modeling and optimal control of integrated continuous monoclonal antibody manufacturing processes

集成连续单克隆抗体生产工艺的建模和优化控制

• 批准号: 558299-2020
• 负责人: Liu, Jinfeng
• 金额: $ 2.19万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=706733
• 关键词: Modeling; optimal; control; integrated; continuous

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.

基于mAB的药物在治疗和市场潜力方面在生物制药行业中起着必不可少的作用。在治疗和诊断应用中，MAB被广泛用于治疗自身免疫性疾病和癌症等。根据最近的出版物，mABS在Covid-19的治疗中也显示出令人鼓舞的结果。直到2020年9月22日，美国食品药品监督管理局（FDA）批准了94个治疗型MAB，2010 - 2020年批准的mAB数量是2010年之前批准的MAB数量。就其市场价值而言，它的价值预计将在2023年达到1982亿美元的价值。因此，将在2023年增长。加拿大是发展高容量MAB制造过程的积极竞争的贡献者。 MAB的集成连续制造代表了MAB制造中最新的，并且引起了很多关注。但是，没有集成制造过程的现有数学模型，并且没有整个集成过程的最佳控制算法。该项目将通过首先开发MAB集成连续制造过程的数学模型来填补知识空白。开发的模型将使用文献中的可用数据以及我们工业合作伙伴客户提供的潜在数据进行验证。基于该模型，将对基于机器的最佳控制算法进行培训，评估和精制，以便为其对工业MAB制造过程的实施做好准备。该项目将（a）进一步提高加拿大在生物制药行业中的竞争力，（b）培训具有生物制药和控制工程跨学科背景的高素质人员（HQP），并且（c）在不久的将来可能在合作伙伴组织中创造更多的工作机会。