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Updated: Oct 29, 2025

A Modified Lean and Release Technique to Emphasize Response Inhibition and Action Selection in Reactive Balance
Published on: March 19, 2020
Augmenting Adaptive Machine Learning with Kinetic Modeling for Reaction Optimization
A Filipa Almeida1,2, Filipe A P Ataíde1, Rui M S Loureiro1
1R&D, Process Chemistry Development, Hovione FarmaCiência S.A, Campus do Lumiar, Building S 1649-038 Lisboa, Portugal.
Abstract:
We combine random sampling and active machine learning (ML) to optimize the synthesis of isomacroin, executing only 3% of all possible Friedländer reactions. Employing kinetic modeling, we augment machine intuition by extracting mechanistic knowledge and verify that a global optimum was obtained with ML. Our study contributes evidence on the potential of multiscale approaches to expedite the access to chemical matter, further democratizing organic chemistry in a data-motivated fashion.
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