James van Geelen Of Citrini research brought up a good point on a podcast this week, that designing the molecules is perhaps 10-20% of the effort in bringing a drug to market. We have more possible drug designs than ever get developed.

Whilst AI drugs might be more likely to pass phase 2 tests than others and AI might be applied to the rest of the process there are still big bottlenecks in the way of AI creating a radical change.

https://podcasts.apple.com/gb/podcast/monetary-matters-with-...

My money is on Eli Lilly leveraging AI to develop drugs vs Anthropic becoming Eli Lilly. Obviously teaching drillers to be astronauts is the better movie though.

> 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.

This has been one of the target AI applications since the 1960s.

(Former drug developer who will never touch the life sciences again)

>> 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

Sounds invasive.

The problem is that biology is like trying to reverse engineer alien technology to understand how it works. Math/engineering is more like building up complexity through well defined parts. Math/engineering is a heck of a lot more deterministic than biology. The ultimate bottleneck in biology in context of AI is well curated and breadth of data, not necessarily intelligence.

If that's the bottleneck maybe we need to rethink all the bureaucracy around the process instead of using AI to fill a document and then using AI to read it. That's just plain stupid.

“Generate scientist” … is that a real job like “prompt engineer”

Seems kind of stupid, because AI companies aren't cuddly benevolent family members, they want to eat everyone's lunch.

Unfortunately, the feedback cycle in drug development is measured in years (and millions of dollars). I've seen cases where a drug works better than competitors but has a worse safety profile. The solution was to alter the drug to remove the side-effects, but that required a new trial (meaning, two more years plus ten million dollars more).

That said, I do think there is some low-hanging fruit. There are lots of datasets from past trials and it's likely that there are some patterns there that AI could mine. I don't think it will be like software engineering ("we build a Photoshop-clone in 2 hours") or math, but we might see announcements about a new drug candidate being found. Verifying it, however, will take a long time.

If the work by Cody Trangbarger pays off and some how helps find a cure or at least halt the muscle wasting of GNE patients, then I will start to believe that AI is truly revolutionary and not a hyped up normal technology.

Rare disease research have always suffered from lack of funding as pharma companies don't have incentive to find a cure for small numer of patients when there are easier ways to make money from diseases which affect larger populations.

Interestingly AI companies seem to be desperate to prove the usefulness of their product and so for the first time rare diseases are getting the spotlight, I hope this works as I live with a rare disease myself.

Same applies to construction projects, BTW.

Other large companies and foundations have copied this model and I would presume have given much more latitude in coloring outside the lines without red tape. Beyond that I am curious what will be innovative about this (sure, claude is amazing, but there's nothing stopping another grant making organization from saying here's a bunch of money and compute - hire great people and go wild)

So dear AI labs, here's a drug-related challenge for you that might actually help: streamline the production of the top 100 generic drugs. Make them higher quality, lower variance and then race against each other to drive down the price to candy level. Show us how to build mini factories for cheap that we can build anywhere in the world.

That's where an LLM and robots can come into play potentially. If we can just scan everyone every year at their physical we could prevent potentially millions of deaths. Yea there are downsides but the downsides are all the extra tests afterwards which we would then have to make faster. Then you add extra blood work at the physical too, not just the default panel.

The equivalent of a GPU but for bio lab experiments. It should be able to do all the basic lab operations of mixing chemicals, heating, cooling, various tests etc tens of thousands of times per second.

Then you hook many AI's up to the automated lab and watch science happen far faster.

(No one please propose automated mice testing or the EAs will have an aneurysm, haha.)

This is complete nonsense. There is already plenty of ML in drug research, the bottleneck is not coming up with experiments its the testing and implementation of that testing (capital!!) Llms cannot contribute anything to this process that traditional ML hasn't already.

Automating or streamlining human/animal trials with 24/7 monitoring and AI check-ins would be huge.

Also Anthropic: “we’ve given AI a biological lab to develop chemicals that impact humans!”

And what we need is not simply more biological phenotypical data (such as genomics, biomarkers, etc.) that we can plug into a model. We actually need that AND labeled trial outcomes, which is a challenge in and of itself because pharma companies will often hide negative trial results (which are advantageous for training the model layer) in order to exacerbate the perception of drugs that make it to market (search for "missing data phenomenon pharma"). The clinical trials are an extremely costly (and necessary) market inefficiency that leads to a bunch of bad behavior that is unfortunately self-reinforcing. I spoke on the phone with a biotech entrepreneur who told me to think of the Gavin Belson (from Silicon Valley the TV show) quote where he says "I don't know about you, but I don't want to live in a world where someone other than me makes the world a better place better than me", and to just remember that's how many people think in pharma and biotech + pharma.

Augmenting how pharma companies work is a great first step. Augmenting how candidate drugs are engineered is a good first step. But that does not change the fact that we simply do not have deterministic governing laws (as we do in physics) to understand the complete pharmacokinetics/dynamics of a drug across a large patient population. You just have to run the test. It is true that AI will help, but only as much as we have a reasonable way to predict that candidate drugs will lead to positive trial outcomes and a large market.

Note that I am not a doomer here. I think AI will have a profoundly disruptive and positive impact on the pharma industry. I'm just not sure starting with drug design alone leads to hope unless there are things happening in the background between pharma + the labs (very possible) that could lead to better trial outcomes.

I don't believe there's any shortage of _potential_ new medicines being developed, but very few get to the stage where they are proven to be both safe and effective.

If anything Claude might just increase the downstream bottlenecks.

I won't judge which way, but I am getting tired of the repetitive nature here. Quite frankly, science works in large parts by others (independent) folks investigating any findings. Low quality or fake had been retracted in the past - see https://www.thelancet.com/journals/lancet/article/PIIS0140-6... from 2016.

It is time for others to do a more systematic research of anything coming out from Anthropic here.

I know Anthropic are brilliant at knowing when to focus where, but I genuinely expected them to be talking about 3-5x more serious scaled up drug discovery plays at this stage.

Is this not a focus, or did the big plays not want to be part of a roundup post?

- Publicly funded researchers are on the verge of a breakthrough on some type of very important medicine. Cure for diabetes let's say.

- These researchers use Claude for some stuff. Maybe cleaning up the wording in their paper, finding relevant work to cite, whatever.

- Anthropic notices their work, and puts an army of agents on scooping them. These agents are able to make use of the researchers as yet unpublished work.

- Anthropic scoops the publicly funded researchers and patents the diabetes cure.

- Rather than being available at low prices, the cure for diabetes is put behind a paywall.

Here the stakes are much higher than the ones in the mathematical scenario we've already seen play out. We're talking life or death shit, rather than some ethical or philosophical questions about what is math really or whatever.

Don't tell me a for-profit company would never do this. We've all seen worse.

The reason that Phase 3 trials are any sort of bottleneck instead of just checking boxes is that drugs that make it to that point are still extremely likely to fail and not be productized. The phase 3 trial is hard, expensive, and slow because it's the only strong filter we have! After phase 3 trials is the only point at which you become confident that this chemical doesn't do crazy unknown things to humans.

This is because the previous trials are not sufficient enough and high fidelity enough analogues of real human biology to be able to prevent that outcome!

Literal living human cells in a petri dish are not sufficient to tell you if a drug will work or not because the entire human system is extremely chaotic and interconnected. Even animals "99%" similar to humans are not similar enough to prevent unpredicted catastrophic outcomes in that full blown human trial.

We do not have enough knowledge anywhere about any of this for an LLM to be useful at all, because we have simply never collected the data necessary to be able to predict outcomes of novel interactions in the full scale system.

We haven't quantified the human system nearly enough.

You want to fix this? Don't go buy tokens, spend $2 trillion on grad bioscience students quantifying literally every protein and gene and structure and behavior and interaction in the human body. You literally have to brute force this problem.

You can't use "simulators" because there's no data for the sim to be evaluated and verified against in the first place. Our knowledge is too sparse.

LLMs cannot magic new information from limited data. Even magic "Superintelligent" AI wouldn't be able to fix fundamental deficiencies in what we know about the human body. There's this extremely silly and weird belief that it will be able to figure everything out "from first principles" and it's driving me up a wall.

Atom level simulations of anything in our reality are computationally infeasible at scales larger than "One cell", and you should expect that to not change since there's not expected to be a magic machine that can somehow undo computational complexity. Well, there is, in that our reality is that machine, but it's not very amenable to isolation for experimentation.

Fundamentally, there seems to be a serious fault among "AI" boosters of deeply believing the "Great man" theory of reality, that everything just needs a magically "smart" enough person to solve, as if someone clever enough could somehow trick physics itself. It's extremely ignorant of reality. There are problems in the current world that no amount of "intelligence" can solve, because the problem is not constrained by reasoning ability in the first place. A lot of bioscience fits that.

    > We’ve also created the Life Sciences Verification Program to allow trusted organizations to use our most powerful models with more permissive versions of our safeguards, which are necessary to prevent misuse but which can impede legitimate biological research

You also can't get verified as a student, let alone as an independent learner or someone seeking to change careers, or heck just an entrepreneur with scientific interests.

Somewhere around March, Anthropic disabled their sales@ account as well. So you can't even email their sales.

I work a lot with younger scientists and people interested in science, and watching them navigate this ridiculous gatekeeping genuinely makes me sad. You can't use Claude to write grants without special dispensation from Anthropic, which is great if you're in California, but less so if you're in Tanzinia, Kazakhistan, Nepal, Bangladesh, India, South Africa, Brazil, Chile...

It's next to impossible for them to get support.

But at the same time, Anthropic can and does have a disproportionate impact on their lives. You can see that in what they brag about. Anthropic has actively bragged about blocking real research to make better painkillers and study a neglected tropical disease.

This is from their "Detecting and countering misuse of AI: September 2026" report. https://news.ycombinator.com/item?id=49647300

Here's one case study they cited, this one was called, "Case study 3: Covert frontier model access for orthopoxvirus research"

    > In May 2026, our biological safety classifier blocked a request for Claude’s assistance in authoring a grant application for scientific funding. The work discussed in the application involved gain-of-function research (that is, research that genetically alters an organism to create a new or enhanced biological property) on the chikungunya virus. This gain of function research was aimed at the virus’ transmissibility and immune evasion properties.

"blocked a request for Claude’s assistance in authoring a grant application"

    > Chikungunya virus is a mosquito-borne virus that causes debilitating symptoms (such as severe pain and fever) that can last for weeks or months, and has no licensed therapeutic. And because chikungunya circulates naturally, a deliberate release (as part of a bioweapon) would be difficult to distinguish from a natural outbreak. The grant sought to identify enhancing mutations in the chikungunya virus, engineer them into infectious clones, and select for virulence in vivo. In other words, the virus would become progressively more harmful as it repeatedly infected live animals, with researchers keeping the most disease-causing variants in each round. Similar research could certainly be used in the development of better vaccines and therapeutics for the virus—but it could also be used to make the pathogen more dangerous.

Note, "The grant sought to identify enhancing mutations in the chikungunya virus, engineer them into infectious clones, and select for virulence in vivo" [..] and then, "Similar research could certainly be used in the development of better vaccines and therapeutics"

It was most likely vaccine development. They stopped the study of a neglected tropical disease and vaccine development.

No Claude for the developing world, I guess.

For maximum charitability, they emphasize that they can't be sure because,

    > One of the reasons we were inclined to think this research was less innocuous was that the institutional affiliation associated with the grant was also a cause of concern. Although information within the application suggested that the research was pursued by civilian researchers, it was intended to be performed at a military research institute.

In most parts of the world, there's either strict military control over BSL-4 labs, or a mixed military-civilian hybrid model.

I doubt that researchers working in the military side of these labs looking to weaponize things are writing grants with Claude.

I really want to be charitable here, but in general, it seems that they stopped people writing grants and reports for vaccine and therapeutics research and are claiming it as "possible efforts to build biological weapons."

Because – and this is the most charitable read here – are you claiming that you stopped a nation state - one with a large military - that has an institutional BSL-4 lab staffed with biologists from making bioweapons by blocking a scientist from using Claude to do grammar checks?

It's somewhat insulting that they termed a working scientist using their chatbot to write a grant as "uplift."

Because what is Anthropic saying here? Are they saying that the only thing stopping a military from a country like India, Russia, China, Iran, South Africa etc from making bioweapons --- a technology that's more than a century old, btw --- is whether or not they can use a Claude account to write grants?

I would be more than OK with their right to create such restrictions if they weren't lobbying the US Government and other Governmetns to restrict others, thereby ensuring that they control humanity's intellectual commons well into the future.

Because who are they to say what I can learn or can't learn? Who are they to control what I can or can't do with these tools?

Who are they to say who can use Claude to generate drug discovery targets or not?

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edit - I encourage you to paste the URL to this thread into a Claude Fable session. You will be blocked for "safety."