Self-Driving Development of Perfusion Processes for Monoclonal Antibody Production.

ABSTRACT: The development of autonomous agents in bioprocess development is crucial for advancing biopharma innovation. Time and resources required to develop and transfer a process for clinical material generation can be significantly decreased. While robotics and machine learning have greatly accelerated drug discovery and initial screening, the later stages of development have primarily benefited from experimental automation, lacking advanced computational tools for experimental planning and execution. For example, in the development of new monoclonal antibodies, the search for optimal upstream conditions (such as feeding strategy, pH, temperature, and media composition) is often conducted using sophisticated high-throughput (HT) mini-bioreactor systems, while the integration of machine learning

SUBMITTER: Gadiyar CJ 

PROVIDER: S-EPMC12779186 | biostudies-literature | 2026 Feb

REPOSITORIES: biostudies-literature