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No one keeps score of which laboratory models actually predicted what happened in patients. A public scoreboard would show which models to trust.
Protein structure prediction improved rapidly once CASP created a blinded, periodic benchmark. An oncology equivalent would take drugs with known but embargoed clinical outcomes, ask model owners (organoids, PDX, chips, in silico) to submit blinded predictions of response rate or ranking, and publish accuracy by model class. Over time this creates evidence for which systems merit regulatory and investment weight.
Shares Estimation of clinical trial success rates and related parameters, Preclinical results do not reproduce, AI-driven drug & target discovery, Patient-derived organoids.
Shares Estimation of clinical trial success rates and related parameters, Patient-derived xenografts, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares Estimation of clinical trial success rates and related parameters, Patient-derived xenografts, Preclinical results do not reproduce, Lab models that fail to predict what happens in patients.
Shares Broad Institute of MIT and Harvard, Patient-derived xenografts, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares Estimation of clinical trial success rates and related parameters, Patient-derived xenografts, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares Patient-derived xenografts, Preclinical results do not reproduce, Patient-derived organoids.
Shares Estimation of clinical trial success rates and related parameters, Patient-derived xenografts, Patient-derived organoids, Lab models that fail to predict what happens in patients.
Shares Estimation of clinical trial success rates and related parameters, Patient-derived xenografts, Lab models that fail to predict what happens in patients.