{"id":"ai-oncology-clinic","name":"AI in the oncology clinic: from narrow cleared tools to multimodal decision support","route":"/roadmaps/ai-oncology-clinic/","eras":[{"era":"2017-2021","title":"Narrow detection tools cleared","description":"FDA clears the first AI detection aids: mammography CAD successors, Paige Prostate (2021), radiology triage for haemorrhage and embolism. Evidence is mostly reader studies.","status":"historic","refs":[{"id":"digital-pathology-ai","kind":"technology","name":"Digital pathology & AI","route":"/technologies/digital-pathology-ai/","status":"established","tldr":"Scanning microscope slides and letting software measure things a pathologist cannot see, including predictions of who will benefit from a treatment."},{"id":"radiology-ai-screening","kind":"technology","name":"AI in radiology","route":"/technologies/radiology-ai-screening/","status":"established","tldr":"Software that reads scans alongside radiologists, catching cancers earlier and predicting who is at risk."},{"id":"paige","kind":"company","name":"Paige AI","route":"/companies/paige/","tldr":"MSK spin-out with the first FDA-cleared AI pathology product and the Virchow foundation model."}],"trials":[],"papers":[]},{"era":"2022-2024","title":"Screening at scale and risk models","description":"MASAI (Sweden) shows AI-supported mammography reading finds more cancers with less workload; Sybil and Mirai predict future cancer from today's scan; whole-slide imaging becomes routine, enabling slide-level AI.","status":"current","refs":[{"id":"mammography","kind":"technology","name":"Mammography & tomosynthesis","route":"/technologies/mammography/","status":"standard-of-care","tldr":"Low-dose breast X-ray used for screening. Newer 3D versions find more cancers with fewer false alarms."},{"id":"sybil","kind":"technology","name":"Sybil (MIT/MGH lung cancer risk from CT)","route":"/technologies/sybil/","status":"emerging","tldr":"Predicts a person's six-year lung cancer risk from one low-dose CT, even when no nodule is visible."},{"id":"mirai","kind":"technology","name":"Mirai (MIT breast cancer risk from mammograms)","route":"/technologies/mirai/","status":"emerging","tldr":"Reads a mammogram to estimate five-year breast cancer risk, consistently across races and devices."},{"id":"digital-pathology-ai","kind":"technology","name":"Digital pathology & AI","route":"/technologies/digital-pathology-ai/","status":"established","tldr":"Scanning microscope slides and letting software measure things a pathologist cannot see, including predictions of who will benefit from a treatment."}],"trials":[],"papers":[]},{"era":"2025-2026","title":"First predictive AI and foundation models in products","description":"ArteraAI Prostate (de novo 2025) predicts treatment benefit; ArteraAI Breast cleared 2026. Pathology foundation models (Virchow2, Prov-GigaPath, TITAN, Atlas) move into commercial biomarker products; multimodal models (MUSK) predict immunotherapy response retrospectively.","status":"current","refs":[{"id":"artera-ai-prostate","kind":"drug","name":"ArteraAI Prostate","route":"/drugs/artera-ai-prostate/","status":"approved","tldr":"The first AI tool cleared by the FDA to predict both prognosis and treatment benefit from a routine biopsy slide, in prostate cancer."},{"id":"artera-ai-breast","kind":"drug","name":"ArteraAI Breast","route":"/drugs/artera-ai-breast/","status":"approved","tldr":"An FDA-cleared AI test (May 2026) that reads breast cancer slides to estimate recurrence risk in early hormone-positive disease."},{"id":"virchow","kind":"technology","name":"Virchow / Virchow2 (Paige, MSK)","route":"/technologies/virchow/","status":"emerging","tldr":"A pathology foundation model trained on millions of slides that can detect cancer and predict biomarkers from an ordinary H&E slide."},{"id":"prov-gigapath","kind":"technology","name":"Prov-GigaPath (Microsoft, Providence)","route":"/technologies/prov-gigapath/","status":"emerging","tldr":"An open pathology model trained on 1.3 billion image tiles from a US health system, modelling whole slides at gigapixel scale."},{"id":"titan","kind":"technology","name":"TITAN (whole-slide multimodal model)","route":"/technologies/titan/","status":"emerging","tldr":"TITAN is a model that summarises a whole slide, not just tiles, and can write a draft pathology report."},{"id":"atlas-aignostics","kind":"technology","name":"Atlas (Aignostics, Mayo Clinic, Charité)","route":"/technologies/atlas-aignostics/","status":"emerging","tldr":"Atlas is a pathology foundation model trained on 1.2 million slides from two of the world's largest hospitals."},{"id":"musk","kind":"technology","name":"MUSK (Stanford, vision-language pathology)","route":"/technologies/musk/","status":"emerging","tldr":"A model that reads slides and clinical text together to predict who will respond to immunotherapy."}],"trials":[],"papers":[]},{"era":"2026-2028","title":"Prospective evidence and regulatory frameworks","description":"Randomised or pragmatic trials of AI-guided decisions (screening intervals, treatment selection); FDA predetermined change control plans for model updates; EU AI Act high-risk obligations; payment codes for AI-derived biomarkers. LLM assistants (Med-Gemini class) enter tumour boards for documentation and trial matching under human review.","status":"emerging","refs":[{"id":"med-gemini","kind":"technology","name":"Med-Gemini and MedLM (Google)","route":"/technologies/med-gemini/","status":"emerging","tldr":"Google's medical versions of its Gemini models, able to reason over text, images, and long records."},{"id":"ai-trial-matching","kind":"technology","name":"AI trial matching & clinical decision support","route":"/technologies/ai-trial-matching/","status":"established","tldr":"Software, increasingly LLM-based, that reads a patient's record and finds trials or guideline options they qualify for."},{"id":"tempus-multimodal","kind":"technology","name":"Tempus multimodal models","route":"/technologies/tempus-multimodal/","status":"emerging","tldr":"Models trained on Tempus's paired genomic, pathology, imaging and outcome data to predict response and prognosis."},{"id":"foresight-ehr","kind":"technology","name":"Foresight (generative EHR model)","route":"/technologies/foresight-ehr/","status":"emerging","tldr":"A model trained on millions of hospital records that forecasts a patient's next diagnoses."}],"trials":[],"papers":[]},{"era":"2029+","title":"Speculative: multimodal decision support as standard of care","description":"A single model reads slides, scans, genomics and records to recommend and monitor therapy, audited against outcomes and updated continuously. Depends on data-sharing, liability and validation questions that are open today.","status":"speculative","refs":[{"id":"idea-multimodal-foundation-model","kind":"idea","name":"Patient-level multimodal foundation models for treatment selection","route":"/ideas/idea-multimodal-foundation-model/","tldr":"Train one AI on scans, pathology slides, genomics and treatment outcomes pooled across patients, including completed phase 3 trials, so it can predict which treatment will work for a new patient. Pathology and radiology models already exist separately; combining them with genomic and trial outcome data is the untested step."},{"id":"flatiron-foundation-cgdb","kind":"collection","name":"Flatiron Health and Foundation Medicine Clinico-Genomic Database","route":"/collections/flatiron-foundation-cgdb/","tldr":"Real-world evidence at scale: what happened to patients with a given genomic profile on a given treatment."},{"id":"imaging-data-commons","kind":"collection","name":"NCI Imaging Data Commons (IDC)","route":"/collections/imaging-data-commons/","tldr":"The Imaging Data Commons is TCIA in the cloud, ready for large-scale model training."}],"trials":[],"papers":[]}],"watch":[]}