Scientists have trained an artificially-intelligent robot to automatically explore a very large number of chemical reactions, an advance that could revolutionise the way molecules are discovered.
The 'self-driving' system, underpinned by machine learning algorithms, and developed by researchers at the University of Glasgow in the UK can find new reactions and molecules.
It could allow a digital chemical data driven approach to locate new molecules of interest, rather than being confined to a known database and the normal rules of organic synthesis.
The result could be a decreased cost for discovering new molecules for drugs, new chemical products including materials, polymers, and molecules for high tech applications like imaging.
"This approach is a key step in the digitisation of chemistry, and will allow the real time searching of chemical space leading to new discoveries of drugs, interesting molecules with valuable applications, and cutting cost, time, and crucially improving safety, reducing waste, and helping chemistry enter a new digital era," said Professor Leroy Cronin from the University of Glasgow.
In a paper published in the journal Nature, the scientists demonstrated the system's potential by searching around 1,000 reactions using combinations of 18 different starting chemicals.
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After exploring only around 100, or 10 per cent, of the possible reactions, the robot was able to predict with over 80 per cent accuracy which combinations of starting chemicals should be explored to create new reactions and molecules.
By exploring these reactions, they discovered a range of previously unknown new molecules and reactions, with one of the reactions classed to within the top one per cent of the most unique reactions known.
The researchers are convinced that this result will help pave the way for the digitisation of chemistry and developing new approaches to chemistry using a digital code which drives autonomous chemical robots.
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