What this stage does
Estimate whether the protocol can enroll on time and on budget across the intended geographies.
Where AI applies
Enrollment forecasting from claims and EHR-derived cohorts, and I/E criteria simulation on real-world data.
Under the Hood · 5
5 capability-angle deep-dives generalizing this essay's pattern for AI and software engineers.
A fluent, citation-studded yes has no tether to the truth unless something outside the model enforces one.
Precision that presents a distribution as a single measured fact isn't rigor. It's the uncertainty, deleted.
A private calibration adjustment fixes the next forecast. A published one fixes the next submission.
Averaging three forecasts into one number destroys the one thing worth knowing: which source to trust.
A forecast without an interval, a date, and a name isn't a bet. It's a slide nobody can be held to.