This AI has chemical expertise - and helps synthesize 35 new drugs and materials

"Now, researchers have created an artificial-intelligence system that vastly simplifies and accelerates the process of chemical synthesis. The system, which is called MOSAIC and is described in a study published in Nature on 19 January, recommended conditions that researchers were able to use to generate 35 compounds with the potential to become products like pharmaceuticals, agrochemicals or cosmetics without needing to do any further trawling or tweaking."

"Predicting the conditions of chemical reactions has been a key focus of AI use in chemistry. One of the most prominent tools is IBM's RXN for Chemistry, which is based on a large language model (LLM). It uses a system called simplified molecular-input line-entry system (SMILES). This translates chemical 3D structures into letters, numbers and punctuation, which are better suited to a system that recognizes language. By contrast, LLMs such as ChemCrow are trained for chemistry tasks using natural-language data."

Chemists seeking new drugs and materials must trawl millions of known reactions and test whether promising compounds can be synthesized. MOSAIC, an artificial-intelligence system, recommends reaction conditions and provided protocols that researchers used to generate 35 candidate compounds without additional trawling or tweaking. The system can draft complete laboratory instructions detailed enough for chemists to follow to help create molecules that have not previously existed. Removing the bottleneck of small-molecule synthesis could accelerate drug discovery and development of agrochemicals and cosmetics. AI approaches differ: SMILES-based tools like IBM's RXN encode structures as textual strings, while some large language models train on natural-language chemistry.

Read at Nature