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Optimized Machine Learning for Autonomous Enzymatic Reaction Intensification in a Self‐Driving Lab

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Observational analysis optimizes enzymatic reactions in a self-driving lab, suggesting enhanced efficiency.

The machine learning platform accelerates enzymatic reaction optimization, requiring minimal experimental effort.
Over 10,000 optimization campaigns revealed the most efficient machine learning algorithm for reaction enhancement.
The self-driving lab demonstrates effective optimization in a five-dimensional design space across various enzyme-substrate pairings.
This methodology for selecting optimization algorithms can broadly impact self-driving lab applications.

Pütz et al. (2025) studied this question.

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