{"entity":{"id":"idea-tr2-model-report-cards","kind":"idea","name":"Score every preclinical model by how often it predicted the clinical result","aka":[],"tldr":"For each type of laboratory model, keep a public record of how often its predictions came true in patients, so that researchers know which models to trust for which question.","summary":"Model predictivity is asserted, not measured. Linking preclinical efficacy claims (from publications and investigational new drug packages) to subsequent clinical outcomes would yield per-model, per-indication predictive values: for instance how often cell-line xenograft regression preceded objective responses in the same indication. Failures are essential to this calculation, which is why they must be recorded.","asOf":"2026-09-08","links":[{"label":"Bottleneck evidence (Failures are hidden): Anderson et al., Compliance with results reporting at ClinicalTrials.gov (NEJM 2015)","url":"https://doi.org/10.1056/NEJMsa1409364"}],"tags":[],"related":["cancer-models","idea-tr2-failure-taxonomy"],"cancers":[],"sections":[],"technologies":["pdx-models","organoids"],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":[],"trials":[],"people":[],"bottlenecks":["b-negative-results","b-preclinical-models"],"keyPapers":["paper-anderson-n-engl-j-med"],"journals":[],"dependsOn":[],"notes":[],"hypothesis":"Report cards will show at least two-fold differences in positive predictive value between model classes within the same indication, and this information will change model choice in subsequent grant applications.","rationale":"Systematic reviews in stroke and neuroscience showed that animal model results predicted clinical results poorly; oncology has never computed the equivalent at scale despite having the most trials.","test":"Link 300 drug-indication pairs with published preclinical data to trial outcomes; compute predictive values by model class; publish and update annually.","maturity":"speculative","actor":"data","cost":"small","horizonYears":3},"route":"/ideas/idea-tr2-model-report-cards/","neighbours":{"collection":[{"id":"cancer-models","kind":"collection","name":"Cancer Models (PDCM Finder) & HCMI","route":"/collections/cancer-models/"}],"idea":[{"id":"idea-tr2-failure-taxonomy","kind":"idea","name":"A machine-readable taxonomy of why cancer drugs fail","route":"/ideas/idea-tr2-failure-taxonomy/"},{"id":"idea-tr2-preclinical-living-reviews","kind":"idea","name":"Living systematic reviews of animal and organoid evidence before every new trial","route":"/ideas/idea-tr2-preclinical-living-reviews/"}],"technology":[{"id":"organoids","kind":"technology","name":"Patient-derived organoids","route":"/technologies/organoids/"},{"id":"pdx-models","kind":"technology","name":"Patient-derived xenografts","route":"/technologies/pdx-models/"}],"bottleneck":[{"id":"b-negative-results","kind":"bottleneck","name":"Failures are hidden","route":"/bottlenecks/b-negative-results/"},{"id":"b-preclinical-models","kind":"bottleneck","name":"Lab models that fail to predict what happens in patients","route":"/bottlenecks/b-preclinical-models/"}],"paper":[{"id":"paper-anderson-n-engl-j-med","kind":"paper","name":"Compliance with results reporting at ClinicalTrials.gov","route":"/key-papers/paper-anderson-n-engl-j-med/"}]}}