Digital twins for treatment selection, validated by predicting before observing
Build a computer model of each patient's cancer that forecasts how it will respond to each treatment option, and prove it by writing the forecast down before the real result is known.
Patient digital twins (mechanistic, statistical or hybrid models of a patient's tumour and physiology) are proposed for treatment selection, but validation is almost entirely retrospective. The proposal is a validation programme with a strict protocol: for each enrolled patient, the twin's prediction (response, progression time, toxicity) for the chosen treatment is locked before treatment; predictions are compared with observed outcomes; calibration and discrimination are published. Only twins that pass proceed to trials where predictions inform choices.
- AI that is built but not validated or deployed · Thousands of cancer AI models are published; a handful are in clinical use, and fewer have shown they help patients.
- Tumour heterogeneity and clonal evolution · A tumour is many tumours. Treatments that kill most cells leave the rest to grow back, changed.
Pages like this
not linked directly; found by shared links- IdeaWhole-patient digital twins validated in prospective randomised trials
Shares Patient-level multimodal foundation models for treatment selection, AI that is built but not validated or deployed.
- IdeaA registry of external validation datasets for cancer AI models, with mandatory reporting
Shares Patient-level multimodal foundation models for treatment selection, AI that is built but not validated or deployed.
- IdeaAn open foundation model of the cancer cell trained on perturbation data
Shares In silico trials to prioritise combinations, scored against later real trials, AI that is built but not validated or deployed.
- IdeaA bone marrow niche on a chip to study human dormancy
Shares Functional (ex vivo) drug testing, Patient-derived organoids.
- IdeaTest drugs on freshly cut slices of the patient's own tumour
Shares Functional (ex vivo) drug testing, Patient-derived organoids.
- InstitutionAtrium Health Wake Forest Baptist Comprehensive Cancer Center
Shares Functional (ex vivo) drug testing, Patient-derived organoids.
- ProductArteraAI Breast
Shares Patient-level multimodal foundation models for treatment selection, AI that is built but not validated or deployed.
- IdeaBarcode patient-derived tumours to watch which clones win under each drug
Shares Patient-derived organoids, Tumour heterogeneity and clonal evolution.