OnCo
ideasIdea

A target de-risking index that counts failures as well as successes

For each drug target, show how many programmes have been tried against it and how many failed, so new teams know what they are up against.

Target prioritisation platforms (Open Targets) weight positive evidence. A complementary index that aggregates discontinued programmes, failed trials and deposited negative preclinical results per target and indication, with reasons where known, would give a Bayesian prior: a target with eight failed programmes and no success should require a stronger hypothesis than one never tried. Publicly available pipeline data makes a first version feasible now.

Hypothesis
Targets in the highest-failure decile will continue to attract new programmes at the same rate as others unless the index is visible; where visible, new programme starts against them will fall by at least a quarter unless accompanied by a new mechanistic rationale.
Rationale
Herding on a few targets (IDO1, CD47, TIGIT) with repeated failure is a documented pattern. Making the failure count visible changes the decision calculus.
What would test it
Build the index for 300 oncology targets from public pipeline and trial data; publish; track new programme initiations by index decile over three years.
Maturity
speculative
Who has to act
data
Cost to try
Small (under $1M)
Years to first evidence
2
Bottlenecks it attacks
  • Failures are hidden · Negative trials, failed drugs and abandoned programmes are rarely published, so the same mistakes are repeated.
  • The undruggable drivers · The proteins that drive most cancers, such as MYC, mutant p53 and most RAS variants, still have no good drug.

Connected

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