Tissue-language foundation model
Pathology AI for toxicology and clinical trial teams.
TileBio Precedent finds prior cases, triages slides and measures treatment effects across your toxicology archive. TileBio Motif finds the tissue patterns that separate responders from non-responders in your trials. Both run on a patented model that learns from unlabelled slides.
- Setup
- No labelsYour slides are indexed as they stand, with no annotation
- Method
- PatentedAnd published in Nature Communications
- Whole-slide images
- 2M+Available for model training and validation
- Deployment
- On siteOn your own hardware in Docker, or hosted in the TileBio cloud
Products
For toxicology, clinical trials and bespoke research
For toxicology and safety assessment teams
Morphology search, slide triage and treatment-effect analysis for toxicology archives and studies.
ExploreFor clinical trial and translational teams
Exploratory biomarker discovery for clinical trials: the tissue phenotypes linked to response, with example tiles for each.
ExploreFor pharma, biotech and academic groups
Bespoke computational pathology research: scoped studies on your own cohort, run by our scientific team.
Explore
Approach
A model that learns tissue structure without labels
Most pathology AI can only find the categories it was trained on. Our model learns a vocabulary of tissue phenotypes from unlabelled slides and reads each slide as a spatial composition of them.
Partners
Clinical data partnerships with the NHS
TileBio holds a data partnership with NHS Greater Glasgow & Clyde and the NHS West of Scotland Innovation Hub. The method is patented and published in Nature Communications.
- NHS Greater Glasgow & Clyde
- NHS West of Scotland Innovation Hub
We have an announced collaboration with Terrain Life Science and are engaging with global pharmaceutical companies on toxicology and discovery pilots.
Discuss a study
Tell us about your cohort and the question you want to answer, and we will advise whether our model is a good fit.