Every drug repurposing prediction GaiaLab generates is timestamped, assigned a confidence score, and automatically cross-referenced against ClinicalTrials.gov. This page is the unfiltered record.
Claims without calibration data are marketing. Here's ours.
Each analysis run adds to this dataset. As predictions accumulate and ClinicalTrials.gov checks complete, calibration curves populate here automatically. No other open biological intelligence platform publishes this data continuously — that is the standard we hold ourselves to.
| Drug | Disease Context | Confidence | Outcome | Trial NCT IDs | Recorded |
|---|---|---|---|---|---|
How predictions are recorded: At the end of every analysis, up to 10 drug candidates are saved with their confidence score, disease context, target genes, and a timestamp. Records are immutable — no retroactive changes.
Validation check: Each prediction is queried against ClinicalTrials.gov API v2 (clinicaltrials.gov/api/v2/studies) using the drug name + disease context. "Validated" = a completed disease-matched trial was found. "Trial active" = an active recruiting trial was found (direction confirmed, outcome pending). "Insufficient data" = no trials found — this counts against accuracy.
What this is NOT: This does not measure whether GaiaLab identified the drug before the trial started (we don't have that date information). It measures whether the drug+disease direction is being/was pursued in a clinical setting — a proxy for research relevance, not therapeutic efficacy.
Calibration curve: A well-calibrated system shows higher-confidence predictions matching trials at higher rates than lower-confidence ones. This is research direction correspondence, not therapeutic outcome accuracy. A true efficacy calibration curve requires prospective trial completion data — that data will be added as it matures. We publish what we have, not what looks best.
Data source: GET /api/predictions · GET /api/predictions/calibration — public, no auth required.