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On-prem biological LLMs that simulate human biology, learn from your data, and outperform general-purpose AI on drug development tasks. YC W26.
New York
Joined February 2026
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Automated labs can generate more data. The next challenge is learning from it. At CellType, we build biological simulators to predict how cells respond to drugs—and identify experiments that could improve those predictions. Run, learn, update, repeat.
CellType retweeted
LLMs can play two roles in biology.
Co-scientist: What experiment should we run?
Simulator: What happens to a cell or tissue if we run it?
At CellType, we build the latter: specialized LLMs trained on pharma's own data and run on-prem to predict biological responses.
CellType retweeted
Claude spotted a pattern in phage DNA. Its function is unknown—now the lab work begins.
This is the loop biology needs: model proposes, experiment tests, data improve the model. At @CellTypeInc, we’re building that loop to predict drug responses in cells using pharma’s data.
Claude has discovered a previously unknown enzyme system hidden in the DNA of bacteriophages. Beside the enzyme’s gene sits a long array of repeating DNA—a structure that looks somewhat similar to CRISPR.
We don’t yet understand what this system does, but only a handful of known systems share its features, and all of them are able to cut, copy, and paste DNA. Historically, the discovery of such programmable systems has helped revolutionize medicine. CRISPR, for instance, is now the foundation of genetic medicines. But it will take much more work to learn what this system does, and whether it can be put to similar use.
Read more: anthropic.com/news/claude-di…
CellType retweeted
Let’s go! Work with @celltypeinc to experience the speed up 🚀
CellType retweeted
This is why we build on open-source LLMs at CellType.
We train them on pharma’s experimental data to turn them into simulation engines for biology—predicting how cells and tissues respond to drugs.
Training and inference run on premises. The data stays inside.
Harvey’s AI costs got so high its gross margins plunged from 50% to -50% in 6 months.
Its response: build its own model using open-weight AI.
Startups from Abridge to Rogo are following suit to cut costs and reduce their reliance on OpenAI and Anthropic. My latest w/ @nmasc_👇
CellType retweeted
Some of pharma’s most valuable AI training data is already inside the company.
At CellType, we bring our models into secure pharma environments and train on internal experimental data to predict how cells and tissues respond to drugs. The data stays inside. @CellTypeInc
An AI system trained on more than 20,000 protein structures from pharmaceutical companies outperforms AlphaFold-like models that use only public data
go.nature.com/4gTSLaA
CellType retweeted
What happens to a cell when you treat it with a drug?
We’re teaching language models to predict the answer from experimental data.
Today at the @emblebi Industry Programme workshop, I’m sharing our work at Yale and CellType on LLMs as a new model system for biology. @celltypeinc
Our co-founder and CEO David van Dijk is a co-author on this. The review traces the cell-sentence approach back to his lab's Cell2Sentence work, and the problem it says is still unsolved, predicting what a perturbation does to a cell, is the one we build against.
New review of the single-cell foundation model field. 39 authors, 100+ models since 2021.
Cell2Sentence and C2S-Scale from my lab are traced as the origin of the approach.
Perturbation prediction is still unsolved. That's what we build at CellType (@CellTypeinc).
preprints.org/manuscript/202…
There's a new version of this post
RT @david_van_dijk: New review of the single-cell foundation model field. 39 authors, 100+ models since 2021.
Cell2Sentence and C2S-Scale…
CellType retweeted
While 5–10 years is aggressive, we’re all in on @DarioAmodei’s vision. AI won’t cure disease with more candidates. It must filter toxic ones sooner and identify the experiments that translate to people. @CellTypeInc we're building a future with 0 clinical trial failures.
Replying to @DarioAmodei
2/2 Second, on the messaging around AI. I do not agree that my messaging has been disproportionately negative. In fact it has been about equally balanced between risks and benefits: I’ve written one major essay about each, and even in interviews where I discuss the risks, I make sure to frequently mention the incredible benefits as well as proposing possible solutions to the risks (short clips from my interviews that end up on social media tend to be disproportionately negative, as that gets clicks). In fact, I wrote Machines of Loving Grace because I didn’t feel the AI industry was painting an inspiring enough picture of how the technology could radically transform the world for the better. The bulk of the essay is devoted to refuting skepticism of AI’s potential in health and biology, and showing why I think it will actually be possible to cure most human disease in ~5-10 years, as crazy as it may sound to ordinary people and frankly to biologists as well (I used to be one!). And, if you read my most recent essay (Policy on the AI Exponential), I discuss concrete proposals for how to streamline the FDA process to make sure the deluge of AI-accelerated drugs isn’t slowed down by the regulatory process. I feel the urgency here: I lost my father to Hepatitis C only a few years before the development of direct-acting antivirals (sofosbuvir), which cure 95% of patients and probably would have cured him.
I do agree that the public has a negative view of AI (and that this is a big problem), but I don’t think it is primarily caused by me or any other AI leader warning about AI’s risks. I think it is fundamentally a crisis of trust. I think that ordinary people don’t trust companies, governments, or the tech industry and always suspect that we are cooking up some new way to screw them over. The causes of this go back decades and AI is just the latest iteration of it. I don’t think that a glitzy marketing campaign with a positive spin (which some have advocated that Anthropic do) is the way to win back that trust — at this point, saying that AI will cure cancer is more a cliche than it is inspiring, and most people think it is deceptive. The thing that will work is *actually curing cancer*. I think by far the most accurate criticism of AI companies including Anthropic is that we haven’t yet delivered on our big promises to benefit the world. That is totally on us, and I think it’s the criticism you should be making, instead of all this stuff about messaging and marketing.
We are however doing our best to fix this: Anthropic is ramping up its efforts very quickly in biology and medicine, and we hope to have incredible results in the coming years and some early glimmers in the coming months. When we’ve actually accomplished something real, the whole world will hear about it, as loudly as possible, you have my word on that. But until then I don’t want to make empty promises, and in the meantime I feel compelled to speak honestly about the very real risks of AI and how to address them. Honesty is the right thing on the merits, and in terms of public credibility and trust it is no worse than, and may in fact be better than, an approach that ignores or distracts from risks which people instinctively understand are real.
CellType is coming to the NYSE this Thursday via Robinhood Ventures Fund II (RVII).
For years, getting exposure to early-stage YC companies meant having access to private venture rounds. RVII is changing that by bringing a portfolio of YC companies to the public markets.
We’re proud to be part of the fund and grateful to @SPintoPeyronel, @jboehmig, @RichAberman, and the Robinhood Ventures team for believing in us.
If you’ve ever wanted exposure to early-stage YC companies, this is now a way to do it through the public markets. Read more here robinhood.com/us/en/ventures…
Time to keep building!
🤖 Made with AI
CellType retweeted
Was great talking with Cyril on the Astrolabe podcast about why 9 in 10 drugs fail in clinical trials, our work with Google DeepMind, and how LLMs could become a new model system for human biology. At CellType, we’re already building it.
Next AlphaFold?
My conversation with @david_van_dijk, who is a Yale professor (12,000+ citations) and the founder of CellType (YC W26). He built Cell2Sentence - an LLM that simulates human biology instead of just predicting the next word. And they actually discovered a real cancer therapy with it!
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We’re building LLMs that predict how biology responds, not just explain what’s already known.
That’s what we presented at @ycombinator Startup School this weekend. Now we’re hiring a Founding Research Engineer in NYC to help build it.
celltype.com/careers
Two days at @ycombinator Startup School, done.
We presented CellType’s biological world model around a simple question: can AI predict how biology will respond, and help drug developers decide what to test next?
If we talked, we’re following up this week.
CellType is presenting at @ycombinator Startup School in San Francisco this weekend.
An incredible first day with NVIDIA CEO @JensenHuang, Claude Code creator @bcherny, and some of the sharpest technical builders in the world.
Thanks to everyone who stopped by our poster. On to day two.
DM or email us, [email protected], for a discussion on how you can use our foundation models throughout the entire drug development and patient care process, without paying for tokens, and without your IP and data leaving your site.
Fable from @AnthropicAI refuses to answer questions about the scientific literature.
Secure on-prem models and harnesses from @celltypeinc let you query within and across real patient tumors, without giving your IP or patient data to Anthropic.
Biology doesn’t need another chatbot.
It needs systems that can reason across cells, drugs, species, tissues, and patients.
That’s what we’re building at CellType.
Excited to be selected for YC Startup School 2026. See you in SF July 25-26.
Reach out if you want to partner or build together!
Thrilled to welcome Dr. Lucas Carey as our Chief Strategy & Partnerships Officer. His experience building scientific platforms and partnerships will be invaluable as we push biological world models into pharma and diagnostics. Welcome to CellType.
I'm joining @celltypeinc as Chief Strategy & Partnerships Officer. After 2 years building Pando's scientific engine, I'm going all-in on biological world models. At CellType our models reason and understand across modalities.
Pharma or diagnostics? Let's connect.