Build verifiable regulatory evidence bundles with end-to-end lineage across plans, tool calls, models, datasets, and generated artifacts. Designed for audit readiness and compliance workflows.
Refua Regulatory helps teams follow drug regulation processes by turning campaign decisions and execution outputs into verifiable evidence bundles with end-to-end lineage across plans, tool calls, models, datasets, and generated artifacts.
Every decision in a Refua campaign is extracted, given a deterministic ID, and linked to its model provenance and data manifests. The result is a complete audit trail that supports internal regulatory readiness reviews before agency submission.
A structured manifest.json with bundle ID, creation timestamp,
source campaign, and included artifact references.
Structured decisions.jsonl with deterministic decision IDs, rationale,
model/data provenance, and execution context.
A lineage.json connecting plans to tool calls to artifacts, enabling
full traceability of every campaign output.
SHA-256 checksums for every artifact in the bundle, enabling tamper-detection and verification for audit handoff.
Automated checklist evaluation against drug discovery comprehensive and FDA/CDER AI-ML templates with strict and manual-review gates.
Campaign run files, data manifests, and extra artifacts organized in a standardized directory structure for handoff.
pip install refua-regulatoryrefua-regulatory build \
--campaign-run artifacts/kras_campaign_run.json \
--output-dir artifacts/evidence/kras_run_001refua-regulatory verify --bundle-dir artifacts/evidence/kras_run_001refua-regulatory checklist \
--bundle-dir artifacts/evidence/kras_run_001 \
--template fda_cder_ai_ml \
--strictRefua Regulatory ensures every campaign decision has a verifiable chain of evidence, making regulatory readiness a natural outcome of the discovery process.