About
Why this exists
Trial Run shows a method: point agents at a large public dataset and hours of primary source, and turn them into structured, sourced, decision-ready intelligence, fast. It is here to show the digging, not to teach anyone their market.
A decade in venture and operating roles, though not in clinical trials, so rather than claim the domain I computed it from public ClinicalTrials.gov data. Every figure carries its sample, every limit is stated, nothing is imputed, and what public data cannot support, like which CRO ran a trial, is named as a blind spot.
The method, made visible
Built for a Strategy Manager in a CEO office. What that desk runs on, and where it shows up here.
| What a CEO office runs on | Where it shows up here |
|---|---|
| Ingest a large dataset into a usable view | The interactive map: pain by disease area and phase, every figure with its sample |
| Turn it into a ranked, actionable list | The ranked accounts: exposure and concentration as separate lists, terminated trials as evidence |
| Show the working, so it can be trusted | The methodology: deterministic, refreshable from the registry, limits declared |
None of this required private data. It required deciding what question to ask, and pointing the right tools at it.