RegTrace v1 — FDA Regulatory Trajectory Dataset for Reinforcement Learning

This page on Zenodo hosts a free sample only (50 trajectories) — not the full dataset. The complete RegTrace v1 dataset — 29,395 trajectories, 457 SFT traces with full CRL letter text, and 795 forecasting records — is available at sentineldata.com.ua/dataset/regtrace-v1 . This sample is a true, unmodified subset of the full dataset (the first 50 rich episodes) and contains: regtrace_v1_sample.parquet — 50 rows × 14 columns, flat tabular view with deficiency counts and outcomes regtrace_v1_sample_episodes.jsonl — 50 full RL episodes with decision-point turns, rewards, and CRL observations Dataset Architecture & Specifications RegTrace v1 is a fully real, non-synthetic dataset of FDA drug-application regulatory trajectories, built entirely from public openFDA sources (Drugs@FDA bulk data, the CRL Transparency archive, and the openFDA API) and restructured into reinforcement-learning episodes with verifiable rewards. There are no simulated patients, no modeled physiology, and no estimated parameters: every application number, CRL letter, and outcome is a real government record, and 100% of the underlying source counts were confirmed by direct download in the current build session (full provenance in the included audit file, regtrace_v1_audit.parquet). Metric Value Total Trajectories 29,395 (336 rich / 459 semi-rich / 28,600 thin skeletons) CRL Letters (full text, SFT-ready) 457 ... Full description with all tables is on the Wiki page of this project. Full dataset and purchase: https://sentineldata.com.ua/dataset/regtrace-v1 . Zenodo copy: https://doi.org/10.5281/zenodo.22944132