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Trial Pre-Mortem

A clinical-trial pre-mortem agent: it tells a drug developer whether a trial is worth running and where it will die - then says "run this" or "do not run." - potentially saving hundreds of millions of dollars and letting

Core trick

LLM reasons over a trial protocol against past failed mechanisms to flag design risks and output a run or do-not-run verdict.

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Description

A clinical-trial pre-mortem agent: it tells a drug developer whether a trial is worth running and where it will die - then says "run this" or "do not run." - potentially saving hundreds of millions of dollars and letting clinical trial developers focus on better designs or repurposing efforts.
shawndimantha/trial-prioritizer★ 10 forksPythonCreated Jun 13, 2026 · last push Jun 13, 2026

README excerpt

# Trial Pre-Mortem (PSP)

## The problem

In rare neurodegeneration, a single clinical trial costs years and nine figures —
and program after program has died re-running a mechanism that **already failed**,
sometimes despite demonstrably hitting its molecular target. Progressive
Supranuclear Palsy (PSP), a 4-repeat tauopathy with no disease-modifying therapy,
is the clearest example: a string of anti-tau antibody trials engaged the target
and produced **zero clinical benefit**. The most valuable thing a tool can tell a
drug developer is often *"do not run this trial as designed"* — before the spend,
not after.

This is a **pre-mortem**, not a dashboard. Given a protocol synopsis (population,
mechanism, endpoints, powering, design), it doesn't score-and-display — it
**reasons**: it proposes findings about where the trial will die, critiques them
against public ground truth, and **kills any finding it cannot substantiate from a
retrievable source.** The output is a ranked kill-list plus either a defensible
redesign or a reasoned "do not run."

## Who it's for

Clinical-development strategists and biotech execs in rare neurodegeneration
deciding whether to greenlight a program, and translational investors sizing the
risk — the people about to commit years and capital to a mechanism that may have
already failed in disguise.

## How it works

A **builder** (Opus 4.8) retrieves public data (ClinicalTrials.gov v2 +
web search/fetch) and drafts per-axis findings. An **independent ver

Team