Contraview Research
What really predicts biotech success
Every signal is tested against what happened next, using only what was known at the time.
Selected signals
Outcomes within 36 months · private company-years and 9,313 Phase 2 programmes
Specialist biotech fund on the cap table
2.0xAny exit95% CI 1.8 to 2.3 · p <0.001Single variable
Two or more specialist funds
2.9xTakeout of $100M+95% CI 2.1 to 3.9 · p <0.001Single variable
Pharma investor on the cap table
2.2xTakeout of $100M+95% CI 1.5 to 3.0 · p <0.001Single variable
Trial stopped in the prior 3 years
0.37xAny acquisition95% CI 0.16 to 0.61 · p 0.004Single variable
12+ rivals entered Phase 2 on its target in the last 3 years
0.54xAny acquisition95% CI 0.24 to 0.96 · p 0.04Single variable
A rival drug on the same target is already in the clinic for the same disease
2.4xPhase 2 to Phase 395% CI 1.9 to 2.9 · p <0.001Full model
Risk ratio vs. no signal, adj. for year and data depth · 95% CI, clustered bootstrap · Single: signal alone · Full: with controls · Associations, not causes.
Every variable is audited
1,396 variables tested · 62% pass
Leak: the variable encodes the outcome or was recorded after it. Circular: it is built from the outcome. Model output: another model's score, not a measurement.
See what the data says.
Short research notes for biotech investors and founders, each measured before the outcome was known.