Cutting through the noise of machine learning for drug discovery

While the topic of AI in drug discovery has received considerable attention in recent years, mature deployments of techniques such as machine learning in the industry remain rare. 

“The chemistry domain is qualitatively different from any other problem that machine learning has exhibited real success in,” said Jason Rolfe, CTO of Variational AI (Vancouver). 

For one thing, there is a relatively limited number of FDA-approved drugs. As of 2018, FDA said it had approved 19,000 prescription drugs. 

A dataset involving FDA-approved drugs that have been tested in humans would be orders of magnitude smaller than the sort of datasets that underlie Generative Pre-trained Transformer 3 (GPT-3), a language model from OpenAI, an AI research company co-founded by Elon Musk.   

Jason Rolfe

High-throughput screening can generate substantially larger datasets. The PubChem database, which NI…

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