A new type chemistry driven by Artificial Intelligence (AI) could revolutionise the way molecules are discovered, according to chemists at the University of Glasgow. In a paper published in the journal Nature, they say they have trained an organic chemical synthesis robot to automatically explore a very large number of chemical reactions.

Their ‘self-driving’ system, underpinned by machine learning algorithms, can find new reactions and molecules, allowing a digital-chemical data-driven approach to locating new molecules of interest, rather than being confined to a known database and the normal rules of organic synthesis.

The result could be a cheaper way of discovering new molecules for drugs, plus new chemical products including materials, polymers and molecules for high-tech applications like imaging. The team demonstrated the system’s potential by searching about 1,000 reactions using combinations of 18 different starting chemicals.

After exploring only around 10% of the possible reactions, the robot was able to predict (with over 80% accuracy) which combinations of starting chemicals should be explored to create new reactions and molecules.

By exploring these reactions, a range of previously unknown new molecules and reactions was discovered, with one of the reactions classed as ‘in the top 1% of the most unique reactions known’.

Lee Cronin, the University of Glasgow’s Regius Chair of Chemistry (www.gla.ac.uk), said: “This approach will allow the real-time searching of chemical space, leading to new discoveries of drugs and interesting molecules with valuable applications, while cutting cost, time and waste, improving safety and helping chemistry enter a new digital era.”