期刊
TRENDS IN BIOTECHNOLOGY
卷 41, 期 4, 页码 497-510出版社
CELL PRESS
DOI: 10.1016/j.tibtech.2022.08.007
关键词
-
Artificial intelligence and machine learning have vast potential in optimizing the design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adopting these techniques include the increasing global demand for biotherapeutics and the rise of Industry 4.0, which require intelligent, automated supervision. This review summarizes the applications of artificial intelligence and machine learning in biopharmaceutical manufacturing, focusing on commonly used algorithms such as multivariate data analysis, artificial neural networks, and reinforcement learning. Perspectives on the future growth of these applications and the challenges in implementing them at manufacturing scale are also discussed.
Artificial intelligence and machine learning (AI-ML) offer vast potential in optimal design, monitoring, and control of biopharmaceutical manufacturing. The driving forces for adoption of AI-ML techniques include the growing global demand for biotherapeutics and the shift toward Industry 4.0, spurring the rise of integrated process platforms and continuous processes that require intelligent, automated supervision. This review summarizes AI-ML applications in biopharmaceutical manufacturing, with a focus on the most used AI-ML algorithms, including multivariate data analysis, artificial neural networks, and reinforcement learning. Perspectives on the future growth of AI-ML applications in the area and the challenges of implementing these techniques at manufacturing scale are also presented.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据