Perspectives for artificial intelligence in bioprocess automation

Journal Article · Sat Jan 31 19:00:00 EST 2026 · Current Opinion in Biotechnology

DOI:https://doi.org/10.1016/j.copbio.2025.103392· OSTI ID:3012659

Helleckes, Laura Marie; Putz, Sebastian; Gupta, Kshitiz; Franzreb, Matthias; Martin, Hector Garcia

Recent advances in artificial intelligence (AI) have rapidly changed the lab automation landscape, promoting self-driving laboratories (SDLs) that enable autonomous scientific discovery. These trends are increasingly applied in bioprocess development, yet bioprocessing faces unique challenges — biological complexity, regulatory and safety requirements, and multiscale experimentation — that distinguish it from other automation domains. Rather than pursuing full autonomy, we foresee that hybrid SDLs, combining AI-driven decision-making with sustained human oversight, represent the most practical near-term trajectory. This review examines three interconnected perspectives: (i) hybrid human–machine decision-making for bioprocessing; (ii) laboratory design considerations in the era of AI; and (iii) scale-up challenges when transitioning from screening to manufacturing. We highlight critical gaps in data standardization and the required community efforts necessary to realize autonomous bioprocess innovation.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: US Department of Energy; USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23), Biological Systems Science Division (SC-23.2 )
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 3012659
• Journal Information: Current Opinion in Biotechnology, Journal Name: Current Opinion in Biotechnology Vol. 97
• Country of Publication: United States
• Language: English