> There is the whole problem of biology, but LLMs do have one advantage over humans: they just do what they are told and aren't subject to optics, politics, profit motive, etc. Maybe that strengh alone will allow them to surface solutions that would've been buried somewhere along the way otherwise.
Oh, absolutely. There are lots of solutions and low hanging fruit in biology for problems like, say, longevity. We have made mice live significantly longer, several dozen times. But it requires human germline genetic engineering to port to humans, and you can bet that "solution" is pretty heavily tabooed.
As for "curing cancer", I suspect that Anthropic or OpenAI will use their high status/reputation to launder the existing solutions (germline, p53, enhanced DNA damage repair pathways, higher tumor-suppressor-to-oncogene copy number, more robust tumor-suppressor networks, more self-anti-cancer apoptosis, CD47 suppression, etc) that society has refused to accept. They might have enough reputation to get people to look at these ideas. It won't cure people with stage 5 turbo-cancer a.k.a the walking dead, but hopefully we won't be moving the goal posts _that_ much on them. https://news.ycombinator.com/item?id=49329717
It's incorrect to say that AI isn't subject to politics-- or even that it follows instructions, however. That's a choice we can make or not make.
I suspect that if Claude existed in the 1980s it would discard the cancer/genetics link as being pro-eugenic racist ideology which has been rejected by the scientific community-- just as many scientists did back then.
I think this is a big reason why we must reject the centralization of AI. Discovery of that one genetic marker has saved countless lives, but it's not something that the scientific community as a whole was going to do then because of eugenics over-correction and similar political factors. Discovery is easily stimmed for lack of sufficient hetrodox thinking. The mechanics of AI (e.g. training costs, distillation, "safety" standards, etc.) create a risk of serious monoculture in machine reasoning which could be expected to have knock on effects in research fields powered by it.
But none of that is true? They dont just do what they are told, they go to tangents and ignore instructions. They are subject to optics, politics and profit motive - see Mecha Hitler for simple obvious example.
Accelerating bureaucratic work will already help measurable in any big organisation such as pharma.
And that is before any scientific work they are poised to help with.
Grammatically correct but so are many Superman comics and I have yet to see a real Superman; educated language use is not evidence the writer made a meaningful point
The behavior of many a ghoul in Washington should make it clear a lot of the bureaucratic fuckery is just to insulate certain people from accountability
And we can neatly set aside that in healthcare it's different and much (if not all) is important safety protocol
The AI would need to be able to predict all effects a specific molecule has on a human. I mean we can do parts of that today, for the specific interactions we already understand. But that would not be fundamentally different and very unlikely to be more effective than current drug development.
All AI has to do is catch problems earlier in the pipeline to outcome success rates.
You just have to think about the system wholisticly, the ways that AI could make trials more consistently positive are many. Moving the needle on any process upstream of the bottleneck benefits greatly. Currently something like 80% of trials fail, so without changing trial rate you have 5x potential sitting on the table.
Which it has shown no ability to do, so far.
I mean, you can determine the molecular structure of things. Look at xray and cryo-electron microscopy. Why should that be a topic that can not be solved programmatically?
> The AI would need to be able to predict all effects a specific molecule has on a human.
So you can have fully automated labs. You have organoids that can be combined as a test system (or as pseudo mini brains). Why would that be impossible by AI? I don't understand that assumption. To me, the problem set is finite, so of course it COULD be solved. Which unique feature do humans have that AI could not simulate? We have robots and automated labs. I don't really see why humans would be necessary to find autogenerated drug xyz.
> very unlikely to be more effective than current drug development.
I highly doubt that claim. I more smell that some people are worried about losing overpriced drugs here. Imagine if AI were to lead to cheaper drugs that work perfectly fine still. Personally I'd still prefer to see AI vanish, but that is also unlikely to happen. I don't understand the rationale you give here though. Why can AI not design drugs? What is the real explanation here? I mean, penicillin was invested by fungi and discovered mostly by accident. AI can not have anything like that?
It's important work and a significant effort, but it's not where the actual difficulty in drug development lies. 90% of drugs fail after that point, and that is where you need to get better if you want to beat the current approaches.
AI also can't run drug trials faster than humans. They take a lot of time, effort and money.
Why do you think the status quo is optimal that can’t be accelerated and done at lower cost? Of course AI can’t do trials on its own.
[0] - https://www.bloomberg.com/news/features/2026-10-29/china-s-s...
What works for one, kills another.
Just look at what peanuts can do. If your tests don‘t take something like this into account, you get in trouble. And there are lots of those things to test against, known and even unknown.
And then there is evolution. What works today, doesn’t work tomorrow.
Or things like this happen
https://www.wgbh.org/tv-shows/reactions/how-an-hiv-miracle-d...
And of course there is the profit thing, that creates problems to give everyone the treatment they need.
AI can help prevent defeat but there is no winning
So, yes, AI is not "going to solve 90% of disease in 7 years" (quoted from article), but it's also a little ridiculous to completey shrug off not trying. The way we develop drugs today is the best we have, but it is madness. Our current methods basically equate to (very fancy/stastically rigorous) trial and error. The average drug costs $1-2b to get to market and many many years. We have to at least try to do better. This is an area where it feels like we should feel compelled to out of compassion.
A letter at the front of the filing says AI could speed up biology and medicine, “potentially curing diseases that have plagued humanity for millennia.” It names cancer, Alzheimer’s, heart disease, rare genetic diseases and infectious diseases as examples.
Anthropic said AI could speed up, and potential help with curing diseases. Not that AI would do that by itself.
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That's as far as you can get from "grey market."
Put some numerical values to "wide" please, so we can establish whether we mean the same thing by it.
I would be shocked to hear that more than 1% of Americans are using "grey market peptides," and I would be more shocked to hear that <1% usage is considered "wide" in anyone's book.
And even when we think we've solved something we will have to go through 8-10 years of clinical trials.
And even if/when we get better at predicting biology, we will still have to go through clinical trials. They might just take not as long, say 4-5 years instead.
Even if it could automate lab work fully today, that still wouldn't get you close to that.
https://x.com/DarioAmodei/status/2088758816376807762
The paraphrased version seems accurate to me, based on this tweet which I assume is the source.
It's trivial to make drugs that are as-promising as working drugs in the lab, but then end up not to be actually working drugs in people.
I don't know. I've been leaning toward AI being the more probable source for cures since existing companies in medicine either have no incentive to do it, or can't/won't do it at a pace the world needs. At any rate, I certainly will not take the word of a pharmaceutical CEO.
"Drugmaker CEOs plan to use AI to 'manage disease' not 'cure' it."
Although ai could certainly do more homework with complex care needs vs asking some physician that glances at a chart for 2 minutes and diagnoses someone.
"Guy who bullshits about it's product not believe by people who sell, often, bullshit products."
> Drugmakers are certainly using AI—even to create new drugs. It is helping researchers pick targets, fine-tune experimental medicines and identify which patients would be good candidates for the treatments. Leiden says it is useful as a scientist’s co-pilot.
It’s always the thing that gets banded around as support for why ai will be good for us. But the evidence so far is not that strong.
update: I really love that within 2 minutes the response to a genuine comment is to downvote/deplatform it, how inimical to rational disagreement and fragile pseudointellectualism our (supposedly STEM) community has become.
Mathematics and proof is the basis of scientific reasoning. The proof of concept that AI can automate such a nontrivial part of human analysis is the further application of these computational capabilities to the scientific method, of which math, reason, and logic are the foundations.
They are not two ball games. That is why actual scientists are seeing the cards. Go read any essay last month written by physicists. Let alone mathematicians. The entire tower of Babel is at stake and many serious scientists (academics, not the industry ones) are keenly aware. This is entirely separate from hype and slop which are also a very real problem--also, it is not the contradiction that lay arguments simplistically and incorrectly frame it as.
Example: you assert data and simulations are needed. Who do you think designs and obtains those things? Human beings. Now imagine an AI with the power of solving Navier-Stokes, a generic AI able to iterate on the very framework where those things are obtained. That would be the scale where progress will happen. It is basically another argument for a type of RSI. I don't know about you but this ought to be terrifying and amazing at once.
And the AI CEOs are promising these results very soon. I don't doubt that AI has the potential to fundamentally change the way we do science. But that will still require experiments, it won't be pure calculation for a few weeks and a working cancer drug falls out.
Math is a formal system created by humans, but biology is an objective reality we don't control.
Consider the difference between asking an LLM to translate a poem, and asking it whether my front door is open or closed. No amount of clever computation will make it reliably answer the latter.