OnCo
ideasIdea

Pick the laboratory model that matches the patient, not the one to hand

Labs usually use whichever tumour models they already have. A searchable index that finds the model closest to a specific patient's tumour would make experiments more relevant.

Thousands of characterised models exist across DepMap, the Human Cancer Models Initiative, PDX repositories and institutional banks, but selection is driven by availability and habit. A matching engine indexing molecular profiles, ancestry, treatment history and microenvironment features would return the closest available models for a given tumour profile, and quantify how much of the clinical population has any representative model at all.

Hypothesis
Formal matching shows that a substantial share of common tumour molecular subtypes and non-European ancestries have no closely matched model, and directs derivation effort toward those gaps.
Rationale
Model collections over-represent easily grown, historically sampled tumours from a narrow population, which is a plausible and testable contributor to translational failure and to inequitable drug performance.
What would test it
Build the index across public repositories, compute coverage of clinical genomic cohorts by subtype and ancestry, and publish the gap map as a derivation priority list.
Maturity
speculative
Who has to act
data
Cost to try
Small (under $1M)
Years to first evidence
2
Bottlenecks it attacks

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