T−minus

Blueprint

Every tool in the lab is documented the same way, from the operational problem to the MLR questions a reviewer will ask.

1. 1

   Operational problem

   Medical Affairs plans congress coverage, publication timing, advisory boards and launch readiness around when competitor and class data will land. That timing is scattered across hundreds of ClinicalTrials.gov records, analyst notes and people's memory.

   Building a readout calendar for one therapeutic area takes hours of registry searches and produces a spreadsheet that is out of date the day it is finished.

2. 2

   Hypothesis

   If every interventional trial's primary completion date in a therapeutic area is visible on one screen, refreshed on demand from the public registry, teams will see data waves months earlier and prepare scientific responses, field medical priorities and congress plans ahead of them.

   A free, transparent first pass should cover most day-to-day questions before anyone opens a paid competitive intelligence database.

3. 3

   Solution architecture

   • One HTML file (about 0.5 MB with embedded fonts), no framework and no build step to deploy.
   • Registry relay: a 70-line PHP script whitelists query parameters and calls the ClinicalTrials.gov API v2 from the server, so visitor IP addresses never reach a third party.
   • Deterministic parsing of phase, sponsor class, enrollment, countries, interventions and primary endpoints.
   • Views: a canvas radar (centre is the past year, edge is 36 months ahead) with a time machine, readouts per quarter, sponsors reading out next, EU enrollment, and a sortable study list with CSV export.
   • Hardening: a Content Security Policy pinned by SHA-256 script hash blocks any other script or connection. Installable as a PWA with an offline app shell.
4. 4

   HCP and patient impact

   HCPs: earlier awareness of upcoming readouts helps medical teams prepare balanced, timely scientific exchange when clinicians ask about new data.

   Patients: indirect. Seeing where late-stage trials enroll, with EU sites flagged, supports conversations about trial availability and investigator site planning.

   No patient-level data is processed at any point.

5. 5

   Regulatory and MLR considerations

   • Public registry data only. No personal data, no HCP data, no confidential input.
   • Built for internal scientific landscape monitoring, not promotion. Anything used externally goes through Medical, Legal and Regulatory review.
   • No generative AI: outputs are reproducible and auditable, and every number traces back to a registry record.
   • Data source attribution: ClinicalTrials.gov, U.S. National Library of Medicine. T−minus is independent and not endorsed by NLM.