04/02/2026
Clinical Study: Our AI Predicts Response Across 7 Biologics
In a leading-hospital study, Alphabiome’s AI predicted response across seven biologic drugs, showing up to 3x higher accuracy than state-of-the-art models.
See drug response
before the trial does
Alphabiome transforms raw cohort sequencing and clinical outcomes into predictive patient stratification, novel biological signatures and interpretable mechanisms of response and non-response.
From cohort to answer
- INPUT. Raw sequencing data, treatment outcomes and clinical labels.
- REPRESENTATION. Projected into Alphabiome’s global reference-free biological vocabulary.
- PREDICTION. Models identify responder and non-responder structure.
- EXPLANATION. High-value signals are traced to protein sequences and interpretable mechanisms.
- VALIDATION. Performance is evaluated on held-out data and, where available, prospectively collected patients.
Validated across seven IBD therapies
Across seven human therapies, predictive performance exceeded AUC 0.85. Alphabiome outperformed every genomic and microbiome representation tested in the same evaluation framework and produced up to threefold responder enrichment compared with established clinical markers.
One representation. Multiple strategic uses
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Patient stratification
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Clinical-trial enrichment
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Drug rescue and repositioning
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Mechanism discovery
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Biomarker definition and deployment
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Portfolio-level biological intelligence
Designed to compound
The vocabulary is periodically refreshed as new data is added, similar to how large AI models are expanded and retrained. More than 100 trillion genetic bases have already contributed to the platform’s growing view of biological structure.
Built to become harder to replicate over time
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Proprietary reference-free algorithms and accumulated token relationships.
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Outcome-linked data and a global biological vocabulary.
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Patented and patent-pending technology across 12 patent filings.
Bring us a biological dataset that existing AI cannot read.
Science & News
16/04/2026
Our Representation Layer Extends to a New Domain: 8 Therapies
Alphabiome extends its reference-free intelligence layer to a new domain, turning raw genetic signal into response prediction across three indications and 8 therapies.
21/11/2025
Peer-Reviewed: Reference-Free AI Validated at Scale
A peer-reviewed study validated Alphabiome’s reference-free AI across 10 farms and 339 animals, predicting response directly from raw DNA signal.
25/11/2025
Predicting Response Straight from Raw DNA Signal
Alphabiome’s reference-free AI now reaches human disease. Our tokenization engine reads raw DNA the rest of biology AI can’t, then predicts response.
06/05/2025
Alphabiome Unveils Revolutionary AI for Reference-Free Decoding
Alphabiome tokenizes raw genetic sequence that today’s biology AI can’t read, to accurately predict response.
07/05/2025
Alphabiome Raises $8M to Build the Biological AI Layer
Finsmes.com- Alphabiome secures seed funding to expand R&D and build the representation layer between raw genetic signal and biological AI.
06/05/2025
AI That Predicts Drug Response from Raw Genetic Signal
Health Technology Net- Alphabiome’s engine reads raw, unannotated DNA beyond reference genomes, delivering unmatched signal for AI drug-response prediction.
25/09/2025
Independent Validation: Our Reference-Free AI Predicts Again
A controlled trial validated Alphabiome’s reference-free AI on a second compound- an independent test of the same engine on new raw sequence.
10/04/2025
Peer-Reviewed Validation: Cross-Farm Prediction Across 13 Herds
A peer-reviewed study validated Alphabiome’s reference-free AI across 13 commercial dairy herds, predicting additive response directly from raw genetic signal alone.
08/09/2024
From Swarm Math to Biology: Predicting Response from Raw Sequence
Our R&D team carries decentralized swarm mathematics into genomics, predicting feed additive efficacy from rumen sequencing, in CRC Press’s Applied Swarm Intelligence
