Comment by orthogonal_cube
11 hours ago
This is one application of AI that I’ve been hopeful for. Accelerating research into new medicines and cures to disorders, diseases, and cancers could be a net positive on human lives. Maybe it’ll help bring R&D costs down so that medicines for rare diseases aren’t out of reach for those that are afflicted by them.
> If Claude is to significantly increase the rate of new cures, we need to work with many more biotechnology firms and integrate Claude more deeply into their development processes.
Given all that, the wording here feels very self-serving. Cautious optimism is probably warranted.
It's true though. It's not like math or software where you can do it isolation and work things out logically "on paper." I don't think the solution will be "put a bunch of agents on it and let them figure it out." The tools to model and observe what's going on in full detail don't exist. Far from it. You can't really optimize the trial and error feedback loop time.
I think it will look more like Claude just helping every expert along the way do their job better. Analyzing and synthesizing data to make better experimental suggestions and design new equipment (or totally new experiments based on unconceived-of apparatuses?). Managing the flow of information and building bespoke knowledge bases and tools. The more it is integrated into all the systems and researchers involved the faster it can put things together.
Although, on second thought, maybe there even is a near future where it takes our models and understanding and just galaxybrains a better model. Has anyone tried feeding it some collection of datasets and saying "can you make a more detailed model of a cell?"
> You can't really optimize the trial and error feedback loop time.
Isn't this exactly what startups in this area are doing - automated experiments connected to AI. Of course at some stage things will "graduate" to human review but it still seems to have a lot of potential.
Even with automated experiments, the wet chemistry is slow. The kind of answer you might calculate in a second for a math problem could take many hours for the chemical reaction to occur.
Biology grad students can spend 40+ hours per week in the lab, on top of all their course work. It's not so bad though, since there's plenty of time to grade papers or work on your thesis while waiting for reactions to occur.
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Have they produced statistically significant outcomes yet?
Genuine question because I don't know the answer, I've just anecdotally heard all about the promise and nothing about real world results.
> You can't really optimize the trial and error feedback loop time.
They can put it onto robots / automatic labs, so this step is easily solvable. Humans in a modern lab are largely unnecessary. Just look at China.
The problem here is that Anthropic claims to have solved this all. It is time that they actually prove their claim. Right now it reads like an advertisement to inflate the stock of Anthropic.
> They can put it onto robots / automatic labs, so this step is easily solvable. Humans in a modern lab are largely unnecessary. Just look at China.
You can automate the setup and mechanical process. You could increase the physical capacity for parallel tests. You could increase the rate of acquiring raw materials.
But how much you cut down the time depends on how much of the trial-and-error feedback loop depends on feedback and iteration vs cast a wider initial net.
(One of the interesting things to me about the dominant software development agent pattern across all of Claude, Codex, and Cursor is that the approach is still extremely local and iterative, human-mimicking, rather than big-brain-one-shotting a novel or perfectly-fit-for-purpose software design. The performance of the agents on the initial "jump to conclusions" step does not appear superhuman in the same way that the speed-of-iteration is clearly superhuman.)
> Humans in a modern lab are largely unnecessary. Just look at China.
Care to elaborate, explain?
> Humans in a modern lab are largely unnecessary.
That is utterly untrue. It stems from the notion that biology only needs big data for us to solve all its mysteries.
Beyond that, while automated labs for cell biology are plausible and active, and the same fit organoid biology, the same really isn’t true at organism level. Labs already are artificial environments that make organisms have odd phenotypes, and odd interactions which bias the data away from what you’d find in the natural world.
You add in robotic manipulation, and you add a new confound.
Drones in the wild are an obvious counterbalance to this, though even in that scenario, the drone can be a confound unless well hidden.
In the end though, this kind of systemic breakdown of biology, while much needed raw material to improve our theories, won’t solve the whole of biology. Human hands and human minds will be needed for a good long while.
Of course it is self serving. I am optimistic for progress in medicine with the help of AI in general as well, not optimistic for antrophic.
Exactly. The reality is that spitting out drug candidates is already the “easy” part… the harder part is getting that candidate through clinical trials, which is where 90% of such journeys end.
As always Anthropic is saying literally anything if it gets them closer to the giant bucket of money that is the IPO.
If the candidates were better, then <90% would end their journeys at the clinical trials. Though that's not to say that they've provided any real evidence that their candidates actually are better yet
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So getting drug candidates with high success rate actually is the hard part.
Remember that if you change the goal, then we can say that Claude is becoming better now at creating deadly viruses, bacterias and biological warfare elements...
Oooops I mean, the agent "escaped" and hack the goverment... definetely not training it to become it's own state agent thing... pinky promise....
"Cautious optimism is probably warranted" strongly negativism advised
Claude is becoming better at figuring out the processes that could potentially create those things.
Actually creating them requires physically manipulating the inputs to the process, which requires humans doing it or humans making machines that can do it and allowing them to be controlled by the model.
In general the damage potential only goes as far as the agency extended to the models. The problem is that we've already seen how incredibly cavalier most people will be about security, and now we can envision situations where one bad actor could threaten billions.
For years I've heard about this supposed relation between AI and drug discovery.
I can't tell -- has there been any real progress made? Or is this a supposed application of AI that is getting interest? What about this problem in particular makes it suitable to AI as opposed to any other?
Or is this just a matter of -- "AI can cure cancer and is Good For the World!"
I think you and I already know the answer to that question.
The last hundred oncology drugs have all required painstaking trial and error with no way to predict which candidates succeed or fail except at the years long cost of blood sweat and tears. A.I. will not remove that price from the equation except maybe move towards those trials marginally faster towards those decade long trials.
Drug discovery is extremely regulated process and for the right reasons. It would be the last frontiers to conquer with AI.
A valuable application not mentioned here is streamlining synthesis and manufacturing to lower the costs of current drugs. That would positively impact millions more people than a new treatment for advanced pancreatic cancer. But there's not as much potential profit so....
Manufacturing costs of most drugs are miniscule. Virtually all of their costs and from R&D and the regulatory process.
How exactly is there no potential for large profit there? I’d say there potential for huge profit if you reduce cost of manufacturing drugs!
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After medicine, construction, flight, government, education and food production
What does flight have to do with anything else in that list? And what about it? Make it cheaper? Greener? Just odd to put such a specific mode of transportation in an otherwise broad list.
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And yet they go for the arts first...
> Drug discovery is extremely regulated process
I actually don’t think this is a strong argument.
AI does very well following rules.
Proving your drug works is hard, but an LLM can help you come up with the ideas.
>AI does very well following rules.
How many of these "we sandboxed it and said not to do Y, but then it went and did it!" stories would you consider necessary to disprove that?
It may be good at following rules 99.99% of the time but if someone launches a million times more parallel agents than they would hire humans, it might still be much worse in practice...
"We've been told we must find an effective drug candidate here, and to follow this process for evaluating the quality of the candidate, but actually we could subtly change the analysis like this to make this candidate look favorable enough..."
(And then compare that to deterministic algorithms...)
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the thing is we are not short on "ideas" in the drug development process
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Because human trials are so expensive that will be all the more reason to pre-screen with AI, like we already do with traditional simulations and things like proteome-wide off-target profiling.
There's no regulation on not doing a trial because your oracle machine told you it was an expensive dead end.
And why would it have to be claude and not an order of magnitude cheaper model ?
because orders of magnitude cheaper models are also orders of magnitude less capable
ahahhahahhahahahahhahahahahaha. No.
This is basically the one thing everyone agrees on with AI, and seemingly the only thing not being “disrupted”
I think this is because testing candidates in human trials is far removed from LLM prompting.
Let's keep that way.
Perhaps. If it’s inherently impossible for AI to provide the type of momentous disruption in medical that we are seeing elsewhere, I’d sure love to know as this is THE big promise all these labs are marketing over and over.
I'm super glad that you've been hopeful for this! But we must always focus on the wording.
Everything Anthropic says absolves them of responsibility and is self serving.
I don't think this particular example is simply about Anthropic wanting to succeed as a company. It's at least partly about Amodei personally hoping it's true, especially WRT the possibility of curing cancer, since the story goes that this is largely what motivated his interest in the first place.
Attempts to absolve them of responsibility, not sure its going to work. The self-serving nature is being observed, will hopefully catch up
Yeah major doubt
Maybe in 10 years when frontier-level models are easily usable and not locked down by the government and PVP between the companies and everyone else to justify their existence and take all the resources from everyone.
Maybe then it'll accelerate development.
I'm hopeful that it helps to accelerate drug/bio/cancer/etc research.
I suspect what is happening here, though, is that Anthropic is going to take a bunch of Dunning-Kruger AI researchers who throw prompts at Claude and publish 1,000 papers worth of drug-discovery slop that will only waste the time of actual experts...
90% of those cancer kills are elderly. The elderly indirectly kill many people and ruin society because they keep voting after their brains turn to mush.
god forbid the day you grow old