PandaCommando69 t1_isqrmth wrote on October 18, 2022 at 12:27 AM

Reply to comment by Shiyayori in A new AI model can accurately predict human response to novel drug compounds by Dr_Singularity

This really does sound amazingly promising.

>Described in a newly published paper in Nature Machine Intelligence, the new model, called CODE-AE, can screen novel drug compounds to accurately predict efficacy in humans. In tests, it was also able to theoretically identify personalized drugs for over 9,000 patients that could better treat their conditions. Researchers expect the technique to significantly accelerate drug discovery and precision medicine.

I've been hearing about personalized medicine for so long, but maybe we're finally getting there?

hateboresme t1_iss058o wrote on October 18, 2022 at 7:43 AM

The AI spring is here. Get ready for an interesting ride. It's gonna get all exponential up in here.

DungeonsAndDradis t1_issjkq6 wrote on October 18, 2022 at 12:00 PM

It's the Law of Accelerating Returns in action. We're in for a very wild decade.

onyxengine t1_ist5gfr wrote on October 18, 2022 at 2:52 PM

I keep saying this too

solidwhetstone t1_isuahw4 wrote on October 18, 2022 at 7:21 PM

After a lifetime of waiting, I'm glad to finally see it.

rationalkat t1_issedrd wrote on October 18, 2022 at 11:05 AM

We are getting there!

"Our process primarily tests single drugs to identify which drugs show potential, which is where our artificial intelligence/machine learning (AI/ML) comes into play. The AI/ML platform uses the drug sensitivity data—which drugs worked, and which did not—and the patient’s genomic profile to identify multivariate mechanisms driving drug sensitivity. By understanding those critical vulnerabilities, identifying drug combinations becomes a matter of matching FDA-approved, clinically available drugs to the tumor vulnerabilities. We can then use the AI/ML to inform combination design, which, alongside physician input on combinations of interest, guides follow-up combination drug testing. The AI/ML enables us to close the feedback loop in drug combination testing for any cancer patient."