AI doesn’t have to cure disease to move the needle.<p>Accelerating bureaucratic work will already help measurable in any big organisation such as pharma.<p>And that is before any scientific work they are poised to help with.
pton_xd posted and then deleted:<p>> 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.<p>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.<p>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. <a href="https://news.ycombinator.com/item?id=49329717">https://news.ycombinator.com/item?id=49329717</a>
On cancer, look at the history of the discovery of BRCA. The data <i>said</i> that vulnerability was extremely heritable. Mary-Claire King's view is that the development of the genetic contribution to cancer was heavily slowed by the politics of eugenics-smell.<p>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.<p>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.<p>I think this is a big reason why we must reject the centralization of AI. Discovery of that one genetic <i>marker</i> 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.
> LLMs do have one advantage over humans: they just do what they are told and aren't subject to optics, politics, profit motive, etc.<p>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.
There are so many things that digital intelligence could do to advance research and some point will maybe let us run experiments on the cloud given close enough biology simulations etc. But even until then, it could be used to better and faster diagnose people, analyze literature and data from vast sources and chart a "highest chance of curing the person" treatment just like what Gitlabs founder is doing. AI doesn't have to find a cure to disease tomorrow to save more lives.
I don't see where AI would currently get the data needed to reliably develop new drugs. Or specifically, to develop drugs with a higher success rate than what we're doing now.<p>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.
More than that, as I understand it, coming up with drugs is not the bottleneck. It’s all the testing and clinical trials that take forever. Drug companies optimize this by having multiple irons in the fire at any time, but it’s not even like AI would help there. The work is in shepherding drugs through the approval process.
To clarify, it's not <i>the approval process</i> that's challenging. It's making a safe and effective drug, then proving that it's safe and effective. If you achieve those, approval is pretty much trivial.
90% of drugs fail in the phase 1-3 trials. If AI could create drug candidates that fail less often, that would be a huge win. I doubt it can right now, and it would take years to decades and billions of dollars to figure out if the AI is actually better at that than humans.
I'm so sick of this argument.<p>All AI has to do is catch problems earlier in the pipeline to outcome success rates.<p>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.
But why not?<p>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?<p>> The AI would need to be able to predict all effects a specific molecule has on a human.<p>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.<p>> very unlikely to be more effective than current drug development.<p>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?
Solving protein structures, and specifically protein structures bound to ligands that are your potential drug candidates are very, very early phases in drug development. That is before even the phase 1 trials.<p>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.<p>AI also can't run drug trials faster than humans. They take a lot of time, effort and money.
The world isn’t deterministic and there isn’t just one human you have to test against.<p>What works for one, kills another.<p>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.<p>And then there is evolution. What works today, doesn’t work tomorrow.<p>Or things like this happen<p><a href="https://www.wgbh.org/tv-shows/reactions/how-an-hiv-miracle-drug-vanished-fawc6r" rel="nofollow">https://www.wgbh.org/tv-shows/reactions/how-an-hiv-miracle-d...</a><p>And of course there is the profit thing, that creates problems to give everyone the treatment they need.<p>AI can help prevent defeat but there is no winning
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The average drug trial is 6-7 years. In order to make better drugs, we need labeled outputs of "this worked in a trial" and (more importantly) "this did not work in a trial" (which is almost always excluded today from CROs + pharma companies). And I am using "in order to make better drugs" very loosely here. I am not saying "in order to train a model that will go from disease and person to chemistry that will work". I am saying even to have stastical helpers who can help determine if a drug should be canceled early (which is a huge help) or have its tox dose adjusted or a trial cohort segregated in a different way.<p>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.
I’ve never really understood the AI can cure disease angle. The AI/ML tools are great at managing complexity, but when it comes to treatment/cures, you have to deal with the complexity anyway. Unless you believe that drug repurposing is the universal rosetta stone for curing disease, and its just a matter of trying all these drugs we have at least run through a safety trial? However, if all these diseases/personalised medicine requires new trials of things, how can that possibly scale (up, and also down to n<10 diseases)?
Nobody promises that AI will cure diseases. This article was misleading. An earlier WSJ article wrote:<p><i>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.</i><p>Anthropic said AI could speed up, and potential help with curing diseases. Not that AI would do that by itself.
I wouldn't say current AI/ML tools are great at managing complexity, they create a lot more complexity per lines of code output than a good engineer would
Given the popularity of grey market peptides, it seems the people prefer hope over safety.
Unfortunately biology is not deterministic like math is, and won't be for a long time. Although that timeframe could accelerate dramatically if some stay focued on that.<p>And even when we <i>think</i> we've solved something we will have to go through 8-10 years of clinical trials.<p>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.
I don't see AI getting us better drugs faster until we discover how to accurately simulate organs and how molecules interact with them. Such technology seems far away to me.
I don't like AI, but ... how exactly should AI be unable to come
up with working solutions in a fully automated lab? The problem
set is finite. Either AI can solve things, or it can not, but there
really is no objective reasons why AI could not possibly solve xyz,
e. g. drugs binding to a molecular receptor - that is a finite
problem set. So there must be another explanation here. Either that
the quality is lacking, or that some people are anxious of losing
money here.
The claim by AI CEOs is that AI will cure most diseases in the next 10 years.<p>Even if it could automate lab work fully today, that still wouldn't get you close to that.
What do you mean by the problem set is finite?
Because "fully automated lab" doesn't include "put it into humans and observe them for years."<p>It's trivial to make drugs that are as-promising as working drugs <i>in the lab</i>, but then end up not to be actually working drugs in people.
articles like this annoy me a bit (even though I'm sharing it here) because everyone posts it as some kind of "AI is useless" gotcha. It doesnt help that WSJ is paywalled, so as is always the case, pharmaceutical companies are of course <i>using</i> AI fully (and IMO correctly), just not the way OpenAI et al claim it can do the work all on its own:<p>> 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.
Wouldn't this be like asking the cable company a long time ago whether they thought the internet would pose a risk to their bottom line?<p>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.
Doesn't "the cable company" sell Internet access today?<p>The hard, expensive and slow part of drug making is not the discovery part.
So you are saying they are probably right? The Internet was not a threat to the cable companies.
Translation ...<p>"Drugmaker CEOs plan to use AI to 'manage disease' not 'cure' it."
This sounds like how people were claiming that AI would never replace writers, coders or designers 3 years ago
Good luck to ai labs if they mean this stuff will cure heart disease or cancer.<p>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.
If there's one thing we have learned about the tech industry, it's that people who have never done a thing but have lots of money know all about the thing, while people with 30 years experience doing the thing obviously know nothing about it because how hard can it be really?
gosh that's a weird phrasing.<p>"Guy who bullshits about it's product not believe by people who sell, often, bullshit products."
What is the most impressive / life saving thing AI has achieved so far?<p>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.
Most diseases are environmental and/or behavioral. The idea a computer can solve all your health issues is as stupid as all the ads for supplements and miracle drugs on late night TV.
Drugmaker CEOs opinions are irrelevant, last month the mathematicians saw it and understood it, what AI is for better and worse, and now scientists are just waiting for the other shoe to drop. It will be a mix of hype and revolution, dismissing the former does not mean being blind to the latter.<p>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.