A new type of deep learning, known as one-shot learning, could be used to help drug development because it only requires a small number of data points, according to Stanford University researchers.
"We're trying to use machine learning, especially deep learning, for the early stage of drug design," says Stanford professor Vijay Pande.
The researchers made molecular data more compatible with the one-shot learning system by representing each molecule in terms of the connections between atoms. They note this step highlighted intrinsic properties of the chemical in a form that an algorithm could process. The team then trained an algorithm on two different datasets--one with information about the toxicity of different chemicals, and the other detailing side effects of approved medicines.
In both cases, the algorithm was better able to predict toxicity or side-effects than would have been possible by chance.
From Stanford News
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