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blog Mar 29, 2018

RESEARCH | Planning chemical syntheses with deep neural networks and symbolic AI

Author: Marwin Segler, Senior Machine Learning researcher at BenevolentAI

Marwin Segler, senior machine learning researcher at BenevolentAI, shows in his Nature paper how AI can transform the success rate of planning the synthesis of organic molecules – so-called retrosynthesis.

The AI technology developed by Marwin uses deep neural networks to learn from every chemical reaction ever performed (12.4 million of them). Combined with modern tree search algorithms, this allows to plan the synthesis of novel molecules. The technology augments the ability of chemists to make molecules faster, increases the success rate of synthetic chemistry and the speed and efficiency of drug development in general.


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