PathAI runs the AISight AI pathology platform and quantifies biomarkers for pharma trials.
PathAI, based in Boston, runs the AISight AI pathology platform and quantifies biomarkers for pharmaceutical trials. Its products include AISight image management, the AIM-PD-L1 and AIM-HER2 quantification algorithms and TumorDetect, backed by large pharma partnerships, and its PLUTO foundation model has its own OnCo record. OnCo links it to digital pathology and to bottlenecks on unvalidated AI, unstandardised biomarkers and the shortage of pathologists, and to ideas including a standard evaluation pathway for AI pathology and one digital PD-L1 scale that maps across competing assays. Whether AI biomarker scoring becomes the regulatory standard for trial enrolment is the open question. The digital pathology page carries the wider picture.
Shares A standard evaluation pathway for AI-assisted pathology, from reader study to deployment, AI second reads to stop borderline lesions being upgraded to cancer, Version control and locked reference sets for AI algorithms used as companion diagnostics, A pre-competitive consortium to train a shared multimodal cancer foundation model.
Shares Version control and locked reference sets for AI algorithms used as companion diagnostics, One digital PD-L1 scale that maps across all the competing assays, AI that is built but not validated or deployed, Digital pathology & AI.
Shares AI-first reading for high-volume common cancer diagnoses, pathologist for the exceptions, AI that is built but not validated or deployed, Not enough oncologists, nurses, pathologists, physicists, Digital pathology & AI.
Shares A standard evaluation pathway for AI-assisted pathology, from reader study to deployment, Version control and locked reference sets for AI algorithms used as companion diagnostics, AI-first reading for high-volume common cancer diagnoses, pathologist for the exceptions, AI that is built but not validated or deployed.
Shares A pre-competitive consortium to train a shared multimodal cancer foundation model, AI-first reading for high-volume common cancer diagnoses, pathologist for the exceptions, AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI that is built but not validated or deployed.
Shares A pre-competitive consortium to train a shared multimodal cancer foundation model, AI that is built but not validated or deployed, Digital pathology & AI.
Shares AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI that is built but not validated or deployed, Digital pathology & AI.
Shares AI in oncology roadmap: pattern readers → foundation models → agents in the workflow, AI that is built but not validated or deployed, Digital pathology & AI.
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.
PathAI's image management system for diagnostic laboratories, the platform its algorithms are meant to run inside.