{"entity":{"id":"idea-moon-validated-digital-twins","kind":"idea","name":"Whole-patient digital twins validated in prospective randomised trials","aka":[],"tldr":"Build a computer model of each patient's cancer and body that simulates how different treatments would go, and prove in a proper trial that choosing treatment with the model helps.","summary":"Multimodal models combining genomics, pathology, imaging, pharmacokinetics and clinical history increasingly predict outcomes, but no digital twin has been validated as a decision tool in a randomised trial. The proposal is an open framework: standardised inputs, mechanistic plus learned components, calibration on federated real-world and trial data, and a series of randomised trials in which treatment selection assisted by the twin is compared with standard multidisciplinary decision-making, with regulators engaged on the evidence standard.","asOf":"2026-09-08","links":[{"label":"Bottleneck evidence (AI that is built but not validated or deployed): Wu et al., How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals (Nature Medicine 2021)","url":"https://doi.org/10.1038/s41591-021-01312-x"}],"tags":[],"related":["idea-multimodal-foundation-model"],"cancers":[],"sections":[],"technologies":["pathology-foundation-model","digital-pathology-ai"],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":["b-ai-validation","b-combination-space","b-preclinical-models"],"keyPapers":["paper-wu-nat-med"],"journals":[],"dependsOn":[],"notes":[],"hypothesis":"Twin-assisted selection improves progression-free survival or reduces toxicity in at least one common indication in a randomised trial, establishing an evidence standard for oncology decision AI.","rationale":"Retrospective accuracy has not translated into clinical benefit for most oncology AI; only prospective randomised evaluation can establish whether models change outcomes, and doing it once creates the pathway.","test":"Randomised trial in second-line lung or colorectal cancer of twin-assisted versus standard treatment choice; primary endpoint progression-free survival, secondary toxicity and cost.","maturity":"speculative","actor":"research","cost":"large","horizonYears":8},"route":"/ideas/idea-moon-validated-digital-twins/","neighbours":{"idea":[{"id":"idea-multimodal-foundation-model","kind":"idea","name":"Patient-level multimodal foundation models for treatment selection","route":"/ideas/idea-multimodal-foundation-model/"}],"technology":[{"id":"digital-pathology-ai","kind":"technology","name":"Digital pathology & AI","route":"/technologies/digital-pathology-ai/"},{"id":"pathology-foundation-model","kind":"technology","name":"Pathology & radiology foundation models","route":"/technologies/pathology-foundation-model/"}],"bottleneck":[{"id":"b-ai-validation","kind":"bottleneck","name":"AI that is built but not validated or deployed","route":"/bottlenecks/b-ai-validation/"},{"id":"b-preclinical-models","kind":"bottleneck","name":"Lab models that fail to predict what happens in patients","route":"/bottlenecks/b-preclinical-models/"},{"id":"b-combination-space","kind":"bottleneck","name":"Too many combinations to test","route":"/bottlenecks/b-combination-space/"}],"paper":[{"id":"paper-wu-nat-med","kind":"paper","name":"How medical AI devices are evaluated: limitations and recommendations from an analysis of FDA approvals","route":"/key-papers/paper-wu-nat-med/"}]}}