Strand AI
ActiveMultimodal foundation models to predict uncollected patient biology
About
Strand AI develops foundation models to generate missing bio-data about patients. With this imputed data, pharmaceutical companies can select better patients for their drug trials and shave months from their drug launch timelines. We’ve already trained a multimodal foundation model that integrates spatial biology modalities, beating SOTA at a fraction of the cost.
Founders · 2
Cofounder & CEO at Strand AI ex-Pathos AI, Enable Medicine, Microsoft Research, Element AI. Trained foundation models for biology on the largest patient dataset in existence.
Cofounder & CTO at Strand AI Ex-Enable Medicine Building foundation models to enrich biology data and improve patient outcomes. Oded Falik, CTO, was the Tech Lead for Enable Medicine's spatial biology platform, scaling to 12B+ single-cell annotations and petabyte-scale pipelines. Programming since 8 years old, published first app on iOS app store at 11 years old.
Launch
Strand AI builds foundation models to turn sparse clinical trial datasets into complete multimodal profiles.
Strand AI builds foundation models that impute missing multimodal patient data (genomics, imaging, proteomics, etc.) to help pharma and biotech companies select better trial participants and reduce time to launch. They trained a multimodal model predicting spatial proteomics from H&E slides and plan to deploy it at scale for enriching patient data in trials.
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