# Virchow / Virchow2 (Paige, MSK)

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

## TL;DR

A pathology foundation model trained on millions of slides that can detect cancer and predict biomarkers from an ordinary H&E slide.

## Summary

Virchow (2024, 632M parameters, 1.5M slides) and Virchow2/2G (2024, up to 1.9B parameters, 3.1M slides from MSK and global sites, mixed magnification) are the largest proprietary pathology foundation models; they underpin Paige's pan-cancer detection and biomarker products and were trained with Microsoft compute.

## Fields

- Kind: Technology
- Status: emerging
- Last checked: 2026-09-08
- Tags: foundation-model; pathology
- Principle: Self-supervised DINOv2 vision transformer pretraining on tissue tiles at several magnifications; frozen encoder plus small task heads.
- Since: 2024
- Strengths: Scale and data diversity; Strong biomarker prediction from H&E
- Limitations: Proprietary weights; Scanner and stain shift

## Sources

- Virchow2 (arXiv 2024): https://arxiv.org/abs/2408.00738
- Virchow, Nature Medicine 2024: https://doi.org/10.1038/s41591-024-03141-0

## 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/)
- companies: [Microsoft (Research and Health AI)](https://onco.cc/companies/microsoft-research/), [Paige AI](https://onco.cc/companies/paige/)
- institutions: [Memorial Sloan Kettering Cancer Center](https://onco.cc/institutions/mskcc/)
- key papers: [A foundation model for clinical-grade computational pathology and rare cancers detection](https://onco.cc/key-papers/paper-vorontsov-nat-med/)
- 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/), [Diagnostics roadmap: stains → gene panels → blood tests that decide treatment](https://onco.cc/roadmaps/diagnostics-roadmap/)

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