# Paige AI

Source: https://onco.cc/companies/paige/  
OnCo record `paige` (Company). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

MSK spin-out with the first FDA-cleared AI pathology product and the Virchow foundation model.

## Summary

Paige AI, based in New York, is the Memorial Sloan Kettering spin-out with the first FDA-cleared AI pathology product, Paige Prostate Detect, cleared in 2021, and the Virchow and Virchow2 foundation models built with Microsoft. Its work extends to pan-cancer detection, and OnCo links it to digital pathology, pathology foundation models and the AI in the oncology clinic roadmap. It bears on bottlenecks about unvalidated AI and biomarkers and the shortage of pathologists, and on ideas including a standard evaluation pathway for AI pathology, AI-first reading for high-volume diagnoses and one digital PD-L1 scale across assays. Whether a foundation model trained on one institution's slides generalises everywhere is the open question. Paige Prostate Detect has its own page.

## Fields

- Kind: Company
- Last checked: 2026-09-04
- HQ: New York, NY
- Type: ai-software
- Website: https://paige.ai

## Sources

- Official website: https://paige.ai

## Connected records

- fronts: [AI & Computation](https://onco.cc/fronts/ai-computation/)
- technologies: [Digital pathology & AI](https://onco.cc/technologies/digital-pathology-ai/), [Pathology & radiology foundation models](https://onco.cc/technologies/pathology-foundation-model/), [Virchow / Virchow2 (Paige, MSK)](https://onco.cc/technologies/virchow/)
- institutions: [Memorial Sloan Kettering Cancer Center](https://onco.cc/institutions/mskcc/)
- bottlenecks: [AI that is built but not validated or deployed](https://onco.cc/bottlenecks/b-ai-validation/), [Biomarkers are not validated or standardised](https://onco.cc/bottlenecks/b-biomarker-validation/), [No one can predict who responds to immunotherapy](https://onco.cc/bottlenecks/b-immunotherapy-response/), [Not enough oncologists, nurses, pathologists, physicists](https://onco.cc/bottlenecks/b-workforce/)
- ideas: [A pre-competitive consortium to train a shared multimodal cancer foundation model](https://onco.cc/ideas/idea-data-precompetitive-cancer-foundation-model/), [A standard evaluation pathway for AI-assisted pathology, from reader study to deployment](https://onco.cc/ideas/idea-data-ai-pathology-evaluation-standard/), [AI second reads to stop borderline lesions being upgraded to cancer](https://onco.cc/ideas/idea-prev-pathology-ai-borderline-anchor/), [AI-first reading for high-volume common cancer diagnoses, pathologist for the exceptions](https://onco.cc/ideas/idea-acc-ai-first-pathology-common-cases/), [One digital PD-L1 scale that maps across all the competing assays](https://onco.cc/ideas/idea-tr2-pdl1-digital-calibration/), [Turn the map of immune cells inside a tumour into a standardised test](https://onco.cc/ideas/idea-bio2-spatial-signature-cdx/), [Version control and locked reference sets for AI algorithms used as companion diagnostics](https://onco.cc/ideas/idea-tr2-ai-cdx-change-control/)
- companies: [Microsoft (Research and Health AI)](https://onco.cc/companies/microsoft-research/)
- roadmaps: [AI in oncology roadmap: pattern readers → foundation models → agents in the workflow](https://onco.cc/roadmaps/ai-oncology-roadmap/), [AI in the oncology clinic: from narrow cleared tools to multimodal decision support](https://onco.cc/roadmaps/ai-oncology-clinic/)
- drugs: [Paige Prostate Detect](https://onco.cc/drugs/paige-prostate/)
- terms: [Pathology foundation models: UNI, UNI2, Virchow2, CTransPath, CONCH, TITAN](https://onco.cc/terms/pathology-foundation-models/)

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