--- title: Early progress on accelerating drug development with Claude description: Anthropic reports early results from six drug-development partnerships using Claude, plus its own research programs including rare muscular dystrophy... canonical: https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Early progress on accelerating drug development with Claude | daily.dev og:description: Anthropic reports early results from six drug-development partnerships using Claude, plus its own research programs including rare muscular dystrophy... og:url: https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss og:image: https://api.daily.dev/og/posts/6oIgvlGss.png og:image:alt: Early progress on accelerating drug development with Claude og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Early progress on accelerating drug development with Claude **[Hacker News](https://daily.dev/sources/hn)** · 10 min read · 0 upvotes · 0 comments ## Summary Anthropic reports early results from six drug-development partnerships using Claude, plus its own research programs including rare muscular dystrophy treatments. Generate Biomedicines used Claude Code to design a CAR T-cell therapy component 70% shorter than standard, boosting receptor production tenfold in lab tests. Divergence Labs had Claude autonomously generate roughly 35,000 antibody designs in a month for a food-allergy treatment. BigHat tested about 1,010 molecule variants guided by Claude in 10 weeks, improving binding strength over 10x. Enveda's Claude-based document review caught all 11 issues human reviewers found plus seven they missed, cutting review time 89%. Anthropic's acquired Mithril Medicine took a muscular dystrophy treatment from idea to promising mouse results in under 18 months, with human trials possible by late 2028. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### How many antibody designs did Claude generate for Divergence Labs' food allergy drug? Claude generated roughly 35,000 antibody designs in about a month for Divergence Labs, working largely autonomously after converting the company's goals into a detailed design plan. The designs targeted a dual-arm molecule meant to detach IgE from immune cells. Early testing found three designs that bind IgE and 20 that could dislodge it, with three outperforming the standard medication. _Developers curious how AI agents handle large-scale generative design tasks can follow cases like this on daily.dev._ ### How much did Claude speed up regulatory document drafting at Enveda? Claude drafted a regulatory document in four hours that normally took about three months by hand at Enveda. In a separate review task, Claude checked 1,061 pages of manufacturing documentation, catching all 11 issues human reviewers found plus seven they missed, cutting review time by 89%, from over 25 hours to less than three. _Anyone evaluating AI for document-heavy compliance work can track real-world benchmarks like this on daily.dev._ ### What results did BigHat Biosciences get from using Claude for lead optimization? BigHat Biosciences used Claude, connected to its lab data system Reccy, to propose molecule changes, then tested about 1,010 variants over 10 weeks. The best versions bound more than 10 times more tightly than the originals, one cancer-targeting lead stayed stable in solution at 18°C higher temperatures, and another lead clumped more than 100 times more slowly. _Teams weighing AI-assisted R&D workflows can follow case studies like this one on daily.dev._ ## Community take How the wider developer community reacted, aggregated from 1 discussion and 132 comments across hackernews (as of 2026-10-28). **TL;DR:** Reaction is largely skeptical: many see this as a self-serving, IPO-timed press release that overstates AI's role in a drug-development pipeline bottlenecked by slow wet-lab work, clinical trials, and regulation rather than by idea generation. **Sentiment:** 15% positive · 35% mixed · 50% skeptical **The case for** - Some think AI-assisted document review and regulatory paperwork could meaningfully speed up a slow, bureaucratic part of the process. - A few are cautiously optimistic that AI could still lower R&D costs and help rare-disease research over time. - Some note that even modest improvements in candidate selection could meaningfully raise costly clinical trial success rates. **The pushback** - Many argue coming up with drug candidates is already the easy part; the real bottleneck is expensive, slow wet-lab validation and clinical trials that AI can't shortcut. - Several call the post self-serving marketing timed around Anthropic's IPO, inflating modest results. - Multiple commenters report Claude's safety guardrails have become so aggressive that they block or hinder legitimate biology/grant-writing work, undercutting the stated goal. - Some note this is a long-studied application (since the 1960s) and question whether anything genuinely new is being shown versus existing ML/simulation tools already used in the industry. - A few feel the showcased examples are thin and overly reliant on one case being just 'better paperwork' rather than actual scientific breakthroughs. **By community** - hackernews (skeptical): Commenters broadly doubt the significance of the results, citing wet-lab/clinical-trial bottlenecks, self-serving IPO-timed framing, and complaints about overly restrictive safety guardrails limiting real research use. **Hottest debate:** Whether drug discovery's bottleneck is idea/candidate generation (which AI can help with) or the slow, expensive wet-lab and clinical-trial validation process (which AI can't meaningfully accelerate). **Open questions** - Will simulation ever be accurate enough to substitute for wet-lab experiments and clinical trials, and what would that require? - How will regulatory frameworks adapt if AI enables faster parallel drug candidate generation? - Will Anthropic's safety/verification programs for biological research become more accessible to ordinary researchers rather than a gatekept few? - Is there real evidence that AI is accelerating actual drug approvals, or just early-stage candidate generation and paperwork? **Highlights** > It's because these systems aren't as impactful in biology as folks who have never been in a lab would have you believe. Because believe it or not, you can't just go "Claude make me a drug!!" Neural network driven drug candidate creation has been around since the 1980s. The blockbuster GLP-1 agonists were actually derived from the peptide in Gila monster venom by algorithmic search. But you can't, and I can't emphasize this enough, just go "Claude make me a virus" and have it work. It just doesn't work that way. And the only reason why people think it does is because they haven't spent enough time in a lab, https://news.ycombinator.com/item?id=49620521 Don't get me wrong, this technology is worth fighting for because it will have incredible impact on the long time scale. But just not in ways they're talking about and expect. Nor the ways in which they're trying to dictate top down. > — [areoform on hackernews · 1 comments](https://news.ycombinator.com/item?id=50267594) > > 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 can't contact anyone on this team. If you know someone who knows someone, then good for you! But if you don't, then sucks to be you. Which is why I would once again like to be annoying and take a moment of your time to remind everyone that Anthropic impedes legitimate researchers from using Claude to write grants. And they would like to scale this to make sure that researchers across the world can't use their chatbot for grammar checks. I wish I was joking. 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. What were the researchers using Claude for? What did they block? "blocked a request for Claude’s assistance in authoring a grant application" Oh. So no Claude for the developing world, I guess. > 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. What was the grant being written? 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. But we 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. I would like to point out the most notable part, this account was used by "civilian researchers" at an "institutional affiliation associated with the grant was also a cause of concern" and the concern was that they were researchers at "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 "possib > — [areoform on hackernews](https://news.ycombinator.com/item?id=50267439) > I work at a university, and part of the job is helping researchers with AI. Our bio and chem researchers are starting to despise Claude because it's been actively getting worse over the last months with increasingly aggressive guardrails. Many of them gave up because they feel they can't do anything useful with it anymore. There's a verified life sciences program, yeah. Is it an easy, transparent process capable of handling the hundreds at just our institution? Not even close. Best ad for open models though, thanks Anthropic! > — [rcr-anti on hackernews](https://news.ycombinator.com/item?id=50267219) > Coming up with candidate drugs is the easiest part of the process. It’s possible that that could be improved a little (not sped up, but suggesting compounds in silico less likely to fail) and possibly have suggestions for scale up, but those are all hard, and the latter is less amenable to being “read” during trains phase. This has been one of the target AI applications since the 1960s. (Former drug developer who will never touch the life sciences again) > — [gumby on hackernews · 3 comments](https://news.ycombinator.com/item?id=50267192) > 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. > — [orthogonal\_cube on hackernews · 11 comments](https://news.ycombinator.com/item?id=50266566) **Source threads** - [hackernews](https://news.ycombinator.com/item?id=50265609) · 139 points · 132 comments ## Similar posts on daily.dev - [Anthropic's new pharma deal targets paperwork, not molecules](https://daily.dev/posts/anthropic-s-new-pharma-deal-targets-paperwork-not-molecules-ftxalhznc) · The Next Web · 0 upvotes · 0 comments - [Claude Science is Anthropic’s newest flagship product](https://daily.dev/posts/claude-science-is-anthropic-s-newest-flagship-product-vfmdw1psb) · MIT Technology Review · 0 upvotes · 0 comments --- Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#claude](https://daily.dev/tags/claude), [#anthropic](https://daily.dev/tags/anthropic), [#healthcare](https://daily.dev/tags/healthcare) [View this post on daily.dev](https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Early progress on accelerating drug development with Claude","url":"https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss"},"datePublished":"2026-10-27T23:12:47.579Z","dateModified":"2026-10-28T11:54:33.943Z","description":"Anthropic reports early results from six drug-development partnerships using Claude, plus its own research programs including rare muscular dystrophy...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/f62983c20b68137b7e9ffe63ec342cd6?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/f62983c20b68137b7e9ffe63ec342cd6?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"Hacker News","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"Hacker News","logo":"https://media.daily.dev/image/upload/t_logo,f_auto/v1/logos/hn","url":"https://daily.dev/sources/hn"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":0},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"ai-agents,claude,anthropic,healthcare","timeRequired":"PT10M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Hacker News","item":"https://daily.dev/sources/hn"},{"@type":"ListItem","position":3,"name":"Early progress on accelerating drug development with Claude"}]} {"@context":"https://schema.org","@type":"FAQPage","@id":"https://daily.dev/posts/early-progress-on-accelerating-drug-development-with-claude-6oigvlgss#faq","mainEntity":[{"@type":"Question","name":"How many antibody designs did Claude generate for Divergence Labs' food allergy drug?","acceptedAnswer":{"@type":"Answer","text":"Claude generated roughly 35,000 antibody designs in about a month for Divergence Labs, working largely autonomously after converting the company's goals into a detailed design plan. The designs targeted a dual-arm molecule meant to detach IgE from immune cells. Early testing found three designs that bind IgE and 20 that could dislodge it, with three outperforming the standard medication. Developers curious how AI agents handle large-scale generative design tasks can follow cases like this on daily.dev."}},{"@type":"Question","name":"How much did Claude speed up regulatory document drafting at Enveda?","acceptedAnswer":{"@type":"Answer","text":"Claude drafted a regulatory document in four hours that normally took about three months by hand at Enveda. In a separate review task, Claude checked 1,061 pages of manufacturing documentation, catching all 11 issues human reviewers found plus seven they missed, cutting review time by 89%, from over 25 hours to less than three. Anyone evaluating AI for document-heavy compliance work can track real-world benchmarks like this on daily.dev."}},{"@type":"Question","name":"What results did BigHat Biosciences get from using Claude for lead optimization?","acceptedAnswer":{"@type":"Answer","text":"BigHat Biosciences used Claude, connected to its lab data system Reccy, to propose molecule changes, then tested about 1,010 variants over 10 weeks. The best versions bound more than 10 times more tightly than the originals, one cancer-targeting lead stayed stable in solution at 18°C higher temperatures, and another lead clumped more than 100 times more slowly. Teams weighing AI-assisted R\u0026D workflows can follow case studies like this one on daily.dev."}}]} ```