Genentech built a MATLAB supervisory control platform for microbial fermentations that cut algorithm rework from six months to two weeks.
Reimplementing control algorithms for fermentations took six months and errors were found in costly live runs. Genentech built ECALS in MATLAB with MathWorks Consulting, with a bioprocess simulation model for pre-deployment testing. The page reports one algorithm reimplemented in two weeks and over 800 successful fermentations under ECALS control.
MathWorks makes MATLAB and Simulink, used by pharma and medical device teams for modelling, machine learning and regulated device software development
This sits in the Ship stage of the AI use-case lifecycle: Named examples from the vendors pharma teams use to get an AI system live inside a real, regulated production workflow — validation, CRM, safety and clinical systems of record.
Published by MathWorks on its own site — read the original case study on mathworks.com ↗
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