QIS is a clinical-data-first offering with pulmonary fibrosis as its beachhead and a data-agnostic methodology underneath. Three speaking tracks bring the thesis to the audiences that need to hear it: rare disease researchers, data and AI practitioners, and federal policy leaders.
Each track carries a distinct pitch and evidence base. Tracks can be combined within a single talk when the audience demands it. The choice belongs to the engagement.
Clinical trials capture what happens at scheduled visits. They miss what happens between them. In rare disease, that gap is not incidental. It is predictive of dropout, non-adherence, and patient loss. Anchored in six Session 1 interviews and the Margaret composite case.
Recursive Triangulation. Multi-model AI with independent analytical lenses. Human review at defined gates. Single-model AI is insufficient for consequential decisions. This track is data-agnostic. The beachhead is clinical data. The architecture applies anywhere triangulation is required.
Federal biotechnology investment has no architectural category for qualitative patient intelligence. The gap is an infrastructure problem, not a funding problem. Qualitative patient intelligence must become named federal infrastructure. The way electronic health records did twenty years ago.