Artificial intelligence and machine learning applications in biopharmaceutical manufacturing

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.

Automated summary

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.