Why Preclinical Studies Fail Investors Before They Fail Science
The most common reasons a preclinical package dies in diligence — and how to design around them.
Most preclinical programs that stall in diligence don’t stall because the science is wrong. They stall because the study can’t answer the question an investor is actually asking: will this result hold up when someone else runs it? That’s a different bar than “did we see an effect” — and it’s the bar that decides funding.
Here are the failure modes I see most often when I pressure-test a preclinical package, and how to avoid them before you’re in the room.
1. The endpoint doesn’t match the claim. A team claims a disease-modifying effect but measured a proxy only loosely linked to the clinical outcome. The data may be real; the inference is a stretch. Fix: define the decision the data must support first, then choose endpoints that defend that specific claim — not the easiest thing to measure.
2. Underpowered, or powered after the fact. Small n, no pre-specified power analysis, and a p-value that arrived after a few animals were excluded. Reviewers can smell post-hoc power. Fix: pre-register the sample size and the analysis plan; state the effect size you powered for and why.
3. No blinding, no randomization, no control for batch. Effects that vanish under blinding are the single most common diligence casualty. Fix: blind scoring, randomize allocation, and treat cage, cohort, scanner, and operator as real sources of variance — not footnotes.
4. One site, one operator, one run. A result that exists only in your hands, once, is a hypothesis wearing the costume of a finding. Fix: build in a replication — a second operator or a second cohort — before you raise on it.
5. A hand-wavy reference standard. When ground truth is “an expert looked at it,” reviewers want to know which expert, how many, how they agreed, and how disagreements were resolved. Fix: document the standard, the qualifications, and the inter-rater agreement.
None of these are exotic. They’re the difference between a package that survives scrutiny and one that quietly dies in committee. The teams that get funded design for the diligence conversation from day one — they treat “would this convince a skeptical outside expert” as a study-design constraint, not an afterthought.
If you’re heading into a raise and want a clear-eyed read on where your preclinical story is strong and where it’s exposed, that’s what a program audit is for.