>“There are people sitting in our office in King’s Cross, London, working, and collaborating with AI to design drugs for cancer. “That’s happening right now.” https://www.htworld.co.uk/news/research-news/isomorphic-labs...
and
>...enables researchers to move seamlessly from AI-generated sequences to functional antibodies in just days https://the-decoder.com/googles-ai-drug-discovery-spinoff-is...
There may also be downsides, like skipping testing things that would enhance our fundamental understanding of something because the AI was wrong. But that’s already a problem , and having a better gauge in the early stages could be really helpful
Not making predictions that they will, just trying to give an example of a benefit that we may get out of this
It can help a little bit in the early stages of drug design, but even if it was perfect (which it's not), there's a massive gap between understanding a protein structure, and understanding how a drug will or system will interact with it.
In a broader sense, understanding the structure of a protein is only a small part of drug development. Unfortunately biology is complicated, and we're an extremely far way away from solving it.
But LLMs compute requirement is so high that it pushes the boundaries of compute, memory and memory bandwidth which is fundamental for curing diseases.
LLMs math / neural networks can and are used for medical research. Simulating a whole body with proteins, cells etc. will bring us the breakthrough we need.
Nothing in modern medicin research is withoout compute.
AlphaFold def helps researchers around the globe.