The AI Biology Company

London/San Francisco
Joined March 2025
Congratulations to @thernabio on the launch of RNA-Logix™ and BioReason-RNA today. We are proud to support Therna and their customers in turning biological questions into testable hypotheses.
Meet RNA-Logix™, our AI RNA Biologist. It proposes why an RNA behaves as it does, then checks the answer against tens of millions of our measurements. Its reasoning model, BioReason-RNA, was developed in collaboration with @NVIDIAHealth . Thank you to @PrimaMente and @tamarindbio for hosting BioReason-RNA exclusively for our customers businesswire.com/news/home/2… #RNA #AIinBiotech
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We are excited to announce that @nvidia has committed to an investment in @PrimaMente. Built upon years of close collaboration, this investment deepens our partnership and strengthens our ambition to tackle complex diseases. Neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and ALS remain among medicine’s greatest unmet needs. Making real progress requires global coordination around data, foundation models, and experimental and clinical validation. We are grateful to @nvidia for their commitment and look forward to deepening our partnership as we pursue breakthrough discoveries for these diseases, and beyond.
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Today we're launching the Alzheimer's Translation Challenge, a global AI competition to discover new therapeutic hypotheses for Alzheimer's disease. At its core is a new 150M cell atlas of neurons, astrocytes, and microglia across different genetic backgrounds under combinatorial perturbations, with multi-modal readouts. The data will be made available through the AD workbench, Hugging Face and Prima Mente's modeling platform. The challenge is led by @PrimaMente and @AlzData in collaboration with @nvidia, @huggingface, @nebiusai, Talisman Therapeutics, @UltimaGenomics, @cellanome, @PrimeIntellect, @GoodfireAI, and @boltz_bio. In 1906, Alois Alzheimer described a new disease of the brain. After 120 years of progress, we still don't fully understand what drives this disease. We want to change that. Participants will use the dataset to build AI models, assessed through a series of evals from general benchmarks to more complex tasks. Top teams will be shortlisted, and their experimental hypotheses tested in Prima Mente's wet lab. Teams win when their hypotheses demonstrate the predicted molecular and functional effect.
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Registration is now open and free to enter, the competition starts in spring 2027. More details on prizes, community and competition milestones will be shared in the coming months. More details on prizes, community and competition milestones will be shared in the coming months. Register here: primamente.com/challenges
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Each dataset becomes a source of evals for model development and testing. These three gave us six new tasks for prima-bench, our soon-to-be-released suite of evals. These included isoform prediction, splicing change in disease, cancer detection from plasma, and chromatin accessibility from DNA sequence.
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How long did this take? 5, 9 and 6 days. Against modelled one-person manual schedules that's up to 10x faster and an estimated 89% cheaper, showing how efficient and affordable well-designed AI workflows in the sciences can be. Directing AI tools with no framework around them can end up slower and pricier than doing it by hand.
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We'll open-source Prima Daedalus very soon! Read the full technical piece here: primamente.com/daedalus Work by @GanbatJay and @fmmartinz, with thanks to @union_ai, @SeqeraLabs and @nebiusai for the infrastructure behind it. This is the first of several deep dives into how we build at @PrimaMente. More soon.
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Case 2: plasma cell-free RNA for cancer detection. Default pipeline settings would have discarded the microbial reads for modelling, so the agents changed them. Cancer vs healthy AUROC 0.89 (paper ~0.9), and five-cancer mean recall of 63.8% vs the published best of 60.4%.
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Case 3: qDA-seq, a rare assay that measures how chromatin opens up over time. No pipeline existed, so Daedalus ported the authors' method. Daedalus reproduced the biological finding that even "closed" heterochromatin becomes accessible over the course of a few days.
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Published biology can take weeks or months to turn into usable training data and new evals. Our Prima Daedalus agents do it up to 10× faster, and 89% lower estimated cost. They reproduce papers, beat published results, and find previously overlooked biology.
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Case 1: long-read single-cell RNA from brains from individuals with frontotemporal dementia (FTD). Daedalus matched all 79 comparable splicing calls in direction (ρ = 0.89), then found 14 events the paper didn't report, incl. SLC12A2 in neurons and CAMK2B and CHL1 in glia.
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In the past 6 months alone, approximately 900k papers have been published and 4PB of sequence data alone has been uploaded to the NIH. The bottleneck is onboarding this: learning each assay's chemistry, building the pipeline, validating the output. Daedalus takes a paper and its raw data through 3 stages: interpret the study, build the pipeline, check the results against the authors'. Out comes an evaluated dataset that feeds model training and evals. 3 examples below.
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Prima Mente retweeted
We recently started scaling experiments for our next-generation model, pre-training up to 68B parameter models on a diverse single-base corpus spanning methylated DNA, chromatin accessibility, 3D DNA conformation, and RNA.
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Prima Mente retweeted
Congratulations to the awardees of the Data & AI Fueling R&D of Tomorrow QuickFire Challenge: Singapore & Beyond! @PrimaMente @waypointbio These innovators will receive grant funding and mentorship to help advance their AI/ML innovations aimed at transforming drug discovery and research. jji.jnj/DataAISingapore
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Prima Mente retweeted
At @PrimaMente, speed matters. Every failed experiment, delayed training, or lost week delays delivering Alzheimers prevention, treatment, or cure to patients. That’s why they turned to Nebius to speed up training cycles for their foundation models. Full story → nebius.com/customer-stories/…
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Thrilled to share that we are one of the 20 Discovery Award winners of the @longitude_prize on ALS. With this award, we gain access to the largest and most comprehensive ALS patient datasets ever assembled, supplemented by our own internal data generation efforts. By combining whole genome sequencing, multi-omic patient data, and high-throughput cellular models, we are bringing together a highly vetted ALS data corpus with a level of scale and quality that has not previously existed in one place.
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At Prima Mente, we believe that combining clinically informed patient data, frontier biological models, and experimental validation can unlock biological insights and therapeutic opportunities that were previously out of reach. Paired with lab autonomy, this enables us to validate insights from models at scale and accelerate discovery toward patient impact.
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Excited to share that Prima Mente is part of the founding portfolio of the @UKSovereignAI Fund. We are one of the first companies selected to receive backing and access to the UK’s leading AI supercomputers. Thank you for backing AI companies building in Britain Joséphine Kant, @KanishkaNarayan, Andrew Crawford and the entire @UKSovereignAI team.
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