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Paige AI
MSK spin-out with the first FDA-cleared AI pathology product and the Virchow foundation model.
Overview
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.
Headquarters
New York, NY, US
Scorecard
All companies#364of 1244 companies, score 10
- approved products +6
- modalities +2
- regions +2
1 approved, 0 in phase 3, 0 earlier, 0 targets, 0 registry studies. Formula on the scorecards page.
Type
Website
ApprovedAI digital pathology detection software (prostate biopsy)
Paige Prostate Detect · Paige Prostate
The first AI for reading biopsy slides authorised by the FDA, which points pathologists to prostate cancer they might otherwise miss.
Similar pages
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- IdeaAI quantification of HER2-low and HER2-ultralow
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fronts
technologies
drugs
ApprovedAI digital pathology detection software (prostate biopsy)
Paige Prostate Detect · Paige Prostate
companies
institutions
terms
roadmaps
ideas
A pre-competitive consortium to train a shared multimodal cancer foundation modelA standard evaluation pathway for AI-assisted pathology, from reader study to deploymentAI second reads to stop borderline lesions being upgraded to cancerAI-first reading for high-volume common cancer diagnoses, pathologist for the exceptionsOne digital PD-L1 scale that maps across all the competing assaysTurn the map of immune cells inside a tumour into a standardised testVersion control and locked reference sets for AI algorithms used as companion diagnostics
bottlenecks
Open-source projects
All open source in oncology →Open-source projects that this organisation maintains, from OnCo's own catalogue: licence and last activity as the repository reported them on the day of the fetch. Listing is not endorsement; check the licence before reuse and the validation before clinical use.
Paige's pathology foundation model trained on 1.5 million slides; the model card releases the model and code under Apache-2.0.
Software in use
The software of oncology →Commercial and regulated products that this organisation sells. Each card says what is behind it: a regulator's database, the literature, a public body's list, or only the company's own words. Listing is not endorsement, and a clearance is a regulatory fact, not a clinical one.
An algorithm that flags areas suspicious for prostate cancer on a scanned biopsy slide, the first such pathology algorithm authorised in the United States.