In 2020, the CASP competition vaulted AlphaFold to prominence and a Nobel Prize. But the era of people being impressed by an artificial intelligence model correctly predicting the structure of a protein — once a challenge many experts didn’t think would be solved in their lifetime — is over. Now drug developers want AI that can solve their big problems, like discerning whether the body is going to attack a drug candidate and render it useless.
One such example is the pregnane X receptor, or PXR. When activated, PXR increases the production of an enzyme that specifically breaks down foreign organic molecules — such as drug molecules — so the body can dispose of them. The specific enzyme that PXR regulates can metabolize approximately 50% of all marketed drugs.
Most drug development campaigns only discover whether candidates trip this sensor late in the game, forcing drug developers to go back to the drawing board. But if an AI model could reliably predict whether a given drug candidate will activate the PXR receptor, it could fix a lot of problems that present hurdles for new potential drugs, including the drug exiting the body too fast or creating drug–drug interactions.
STAT+ Exclusive Story
Already have an account? Log in
This article is exclusive to STAT+ subscribers
Unlock this article — plus daily coverage and analysis of the biotech sector — by subscribing to STAT+.
Already have an account? Log in
Individual plans
Group plans
To read the rest of this story subscribe to STAT+.