An MIT machine-learning model proposes new molecules for drug discovery, making sure the suggested molecules can actually be synthesized in a laboratory.
Pharmaceutical companies are using artificial intelligence to streamline the process of discovering new medicines. Machine-learning models can propose new
Machine learning-based systems hope to outperform expert-guided reaction planning technology, finds Andy Extance
When IBM’s Deep Blue supercomputer beat world chess champion Garry Kasparov in 1997, few chemists must have realised that this might signify a win for them too. But Bartosz Grzybowski did. Then a PhD student at Harvard University in the US, outside chemistry he plays the card game bridge avidly. Grzybowski’s opponents were interested in algorithms like Deep Blue’s. ‘I started thinking, why couldn’t this be done for molecules?’ he recalls. In particular, might similar algorithms help plan the strategy for making target molecules, which chemists call retrosynthesis.