Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back.

MACHINE learning; FORECASTING; HIGH performance liquid chromatography; PARTITION coefficient (Chemistry)

The article focuses on the development of an autonomous chemical discovery platform that integrates machine learning (ML) algorithms, computer-aided synthesis planning (CASP), and automated chemical synthesis. Topics discussed include the use of ML generative algorithms to propose molecules, CASP for synthetic recipe proposals, and automated experimentation to explore and optimize chemical spaces.