The AI angle, since many people are hyping the “AI for pancreatic cancer” line:
Yes, deep learning is used in the development of the mRNA vaccine. NetMHCpan, a small neural network, is used to help select immunogenic neoantigens (choose the most promising mutant proteins to target) for autogene cevumeran.
Most of the computational pipeline detailed in the paper consists of traditional tools, in line with what I’ve written about AI and personalized mRNA vaccines before. Deep learning is extremely useful for some things, but it should be understood as a specialized tool, not a silver bullet, for now.
I’m not sure if deep learning was used in the development of daraxonrasib. A brief glance at the paper and previous work shows plenty of references to traditional computational tools, but nothing that stands out to me as modern DL.
The company behind daraxonrasib, Revolution Medicines, is quite enthusiastic about ML. They recently made a deal with AI drug discovery platform Iambic Therapeutics. I don’t doubt Iambic’s tools will soon prove useful, but it’s fair to say “deep learning for drug discovery” is still in the early stages of development.
The AI angle, since many people are hyping the “AI for pancreatic cancer” line:
Yes, deep learning is used in the development of the mRNA vaccine. NetMHCpan, a small neural network, is used to help select immunogenic neoantigens (choose the most promising mutant proteins to target) for autogene cevumeran.
Autogene cevumeran paper https://www.nature.com/articles/s41591-024-03334-7
Most of the computational pipeline detailed in the paper consists of traditional tools, in line with what I’ve written about AI and personalized mRNA vaccines before. Deep learning is extremely useful for some things, but it should be understood as a specialized tool, not a silver bullet, for now.
AI & mRNA blog https://hedonicescalator.substack.com/p/did-paul-conyngham-really-use-ai
I’m not sure if deep learning was used in the development of daraxonrasib. A brief glance at the paper and previous work shows plenty of references to traditional computational tools, but nothing that stands out to me as modern DL.
Daraxonrasib paper https://pubs.acs.org/doi/full/10.1021/acs.jmedchem.4c02314
Previous work https://pmc.ncbi.nlm.nih.gov/articles/PMC10474815/
The company behind daraxonrasib, Revolution Medicines, is quite enthusiastic about ML. They recently made a deal with AI drug discovery platform Iambic Therapeutics. I don’t doubt Iambic’s tools will soon prove useful, but it’s fair to say “deep learning for drug discovery” is still in the early stages of development.
Iambic announcement http://iambic.ai/post/revolution-medicines-collaboration