To streamline drug discovery, team develops algorithmic framework to identify optimal molecular candidates

MIT researchers have created SPARROW, an algorithmic framework to optimize drug discovery by identifying the most cost-effective molecular candidates for synthesis. SPARROW balances the cost and utility of synthesizing batches of molecules, integrating data on molecular design, property prediction, and synthesis planning. This framework aims to reduce the time and expense involved in drug development and can be applied to other fields like agrichemicals and organic electronics. The algorithm leverages AI tools and expert input, ensuring efficient selection and synthesis of optimal compounds.

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