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GPT-Rosalind surfaced a new lead for drug discovery: could restoring cholesterol transport protect neurons from degeneration? DCTN1 is a gene linked to Perry syndrome, a rare neurodegenerative disorder. In mouse-brain data, disrupting it increased expression of genes involved in making cholesterol. GPT-Rosalind suggested a possible explanation: cholesterol may not be reaching where neurons need it. That gives scientists a specific mechanism to test and, if confirmed, a direction for developing new treatments for neurodegenerative disorders. With @perturbai_tx and @scrippsresearch, a team of thousands of GPT-Rosalind agents worked in parallel, connecting gene-expression results from millions of mouse brain cells with scientific literature in just 32 minutes. We’re now expanding this collaboration to identify new drug targets. openai.com/index/scaling-ai-…

Using thousands of AI agents to uncover new leads in biological data

See how OpenAI, PerturbAI, and Scripps Research used distributed AI agents to uncover promising research leads in data from millions of brain cells.

openai.com

Oct 21, 2026 · 1:32 PM UTC

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OpenAI
@OpenAIOct 21
In the same mouse-brain dataset, GPT-Rosalind found a possible clue to why TSC2 mutations tend to cause more severe tuberous sclerosis than TSC1 mutations. The two genes work together to regulate mTOR. Yet in one group of cerebellar neurons, disrupting TSC2 changed the expression of dozens of genes, including genes involved in neuronal communication. Disrupting TSC1 had little effect on gene expression in the same cell type. Existing treatments already target mTOR. Do they reverse these changes, or is there more to TSC2’s role in these neurons?
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Coinbase Predict
@CoinbasePredictOct 21
@OpenAI
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Would love to get our access to Rosalind! We have some massive insights on neurons grown on a chip @sama @gdb 😃
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Doctors: we didn't ask for this🤣
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xitter.cf/EricTopol/status/21129…
Eric Topol
@EricTopolOct 21
My @scrippsresearch colleague @xinjin and her team are doing amazing brain biology discovery work with 2,000 agents, PerturbAI, in collaboration with @OpenAI prnewswire.com/news-releases…
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This why you need to flood your system with cholesterol. I eat a stick of butter and a can of cod liver every day
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This will prove to show that statins cause neuro degeneration
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The interesting part isn’t that AI “discovered a drug target in 32 minutes.” It found a mechanistic thread worth testing: DCTN1 disruption → ↑ cholesterol synthesis genes → possible cholesterol transport failure → could restoring distribution protect neurons? That’s where AI-assisted science gets interesting: not replacing the experiment, but finding the experiment worth running next.
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Why don’t you tell us which model is Rosalind based on? 🤡 because it’s the same one 4-b micro is based on?
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If AI can "discover" this in 32 minutes from mouse data, why aren't we already curing Parkinson's and Alzheimer's instead of still watching people die while pharma protects patents?
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Cholesterol not reaching the neurons is at least a testable call. Who's running the wet lab follow-up?
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I wouldn’t be surprised if GPT-Rosalind is actually GPT-4o, or at least built on top of it.
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Once AI can improve health the negative public perception goes out the window and everyone will become positive toward AI.
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as a longevity guy this is the ai news i actually care about. the brain is the one thing i cant really track at home, leads like this give hope
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Alzheimer’s is related to cholesterol transport as well (apoe e4 especially) Would be a good one to solve
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Generating hypotheses was never the bottleneck in biology. Testing them is. The interesting metric isn't how many leads Rosalind surfaces, it's how many survive the wet lab. Will you publish the hit rate once these are tested?
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Who should a neurodegeneration researcher contact about getting involved as this expands? My partner works on exactly this at a leading research institute in Italy @perturbai_tx @scrippsresearch
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The pace of scientific advancement in the years to come will be hard to imagine
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LOL. Something is not getting where its needed. GIVE THEM THEIR NOBEL!!! ALL DISEASES ARE NOW DECLARED SOLVED!!!
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The bottleneck here isn't the predictive accuracy anymore — it's the orchestration layer. How are you handling the latency and consensus communication protocols when thousands of agents are querying biological datasets simultaneously?
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This is where AI could truly transform medicine. Discovering previously unrecognized cellular pathways, identifying new therapeutic targets, and uncovering mechanisms of disease at a speed that was unimaginable just a few years ago. AI is not just accelerating drug discovery. It is expanding the boundaries of what we can potentially treat. For millions of patients living with diseases we still cannot cure, this represents extraordinary hope.
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Now do Multiple Sclerosis. 🧠🔬 Could disrupted cholesterol trafficking be a missing link in failed remyelination? Investigate oligodendrocyte maturation, microglial lipid recycling, and axonal repair. Let's move beyond slowing MS progression toward restoring myelin. @OpenAI
🤖 Made with AI
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Thousands of agents connected millions of cells to the literature in 32 minutes. The science bottleneck just moved. It's no longer generating the hypothesis — it's testing it. Labs that verify fastest win the next decade of drug discovery.
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5 years out, why wouldnt frontier labs eat the entire economy?
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in just 32 minutes wow Google is pushing Gemini deeper into scientific research too the AI race is getting way bigger than just chatbots 💀
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god now you'll be fucking people's physical health after fucking their mental health with reroutes and model deprecations? 😑
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no idea about the neuroscience but love that you put a question at the end instead of a victory lap. curious what the scientists make of it
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Thousands of agents plus millions of cells in 32 minutes is a fast way to generate hypotheses. The checkable part is the funnel: how many leads did it produce, how many survived expert review, and how many have been tested in the lab? One lead is a hypothesis, not yet a result.
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A hypothesis from mouse-brain data is still an R&D funnel problem. The commercial question is whether Rosalind shortens the path from lead to a trial protocol someone will fund—not another pretty association.
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This is why we pay openai >$1000 for startup idea implementation
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XYO
@OfficialXYOOct 21
Families living with Perry syndrome deserve every new lead they can get, and we’re cheering for the team testing this one 🧠
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parallel agent swarms extracting viable biological hypotheses in minutes is where model scaling actually delivers utility
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Julian C
@JulianUnlockedOct 21
Neurodegeneration often hides in plain sight: sometimes, restoring a basic function like cholesterol transport does more for neurons than the latest molecular tweak. It’s a reminder that repair can beat reinvention.
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32 minutes to a hypothesis is cool but the hard part starts now. I mean, has anyone actually tested cholesterol transport in DCTN1 knockdown neurons yet or is that the next step?
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