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points by kenhwang 2 days ago | 0 comments
That's my understanding as well. Seems like they're improving a $20 part of a billion dollar process, and a part that was already heavily using state of the art AI/simulation at that. The computers already spit out more potential candidates than what can be reasonably tested in vitro.
[–] timr 2 days ago
> Seems like they're improving a $20 part of a billion dollar process, and a part that was already heavily using state of the art AI/simulation at that. The computers already spit out more potential candidates than what can be reasonably tested in vitro.

This is the fundamental problem with nearly all tech-meets-drugs startups. They almost always focus on the part of the problem where there isn't a bottleneck, because the parts where there is a bottleneck are the parts we don't understand at all.

[–] 10111001 2 days ago
> This is the fundamental problem with nearly all tech-meets-drugs startups. They almost always focus on the part of the problem where there isn't a bottleneck, because the parts where there is a bottleneck are the parts we don't understand at all.

Are they doing the thing where they develop the technology first, then hunt around for problems for it to solve and hype up potential applications?

[–] timr 2 days ago
Sort of. There’s also a big helping of intellectual arrogance, wherein the tech people think they can apply their l33t skills to biology, and get the same results (I say this as a person who has spent a non-trivial portion of my life as one of those people.)

That said, the LLM version of this is perhaps more solution-seeking-problem than past iterations. LLMs are obviously useful [1]. Scientists already use them. The labs are just desperate to find a multi-billion-dollar application outside of coding, and they’ve all decided that “drug development” is lucrative, so they're gonna apply their magic to that problem and collect profits!

[1] In the way that photocopiers are useful in drug development: as a tool. A powerful tool, but still a tool.

[–] bamboozled 2 days ago
I don’t see the issue really though, if the $20 part still produces something more likely to get through the billion dollar parts what’s the problem ?
[–] timr 2 days ago
It doesn’t. That’s what I mean when I tell you the bottleneck is somewhere else. Obviously everyone claims that they do this with new technology X, but empirically, it isn’t helpful.

Re-ranking pre-clinical leads is the scientific equivalent of that old saying about opinions.

[–] menaerus 2 days ago
Few years back many SWE people would say, including me, that the bottleneck is not in coding. We were all very wrong.
[–] timr 1 day ago
Not even close to a relevant metaphor. Compared to drug development, coding is trivial. It was always obvious that coding would be the first to fall: there’s a corpus of all the code ever written, the system is fixed in scope and relatively small, the data is text, and it’s all easily validated by machine for correctness.

There is no objective function you can optimize your way to a drug discovery machine, let alone a fundamental understanding of how the underlying system works.

[–] menaerus 1 day ago
I'd take your overly dismissive words as credible (but still wrong) only if you did the career in both disciplines which I assume you didn't. You're wrong, and your view of SWE discipline is a great example of DK effect. Not something one would expect from a PhD in computational biology, yes?