Astraea provides a standards‑aware, multi‑agent AI platform that automates clinical trial data workflows from protocol design through FDA submission. By reusing structured metadata and generating regulator‑ready outputs, it cuts biometrics‑to‑reporting cycles by 30–50% while maintaining CDISC compliance, 21 CFR Part 11 auditability, and HIPAA alignment. The system augments biostatisticians, programmers, and medical writers with a traceable execution layer that reduces handoffs and lowers trial costs.
Funding
Funding not disclosed
Founders
Product
Problem
Clinical trial teams face lengthy, error‑prone workflows when transforming raw study data into regulator‑ready submissions, requiring manual handoffs, extensive metadata mapping, and strict adherence to standards such as CDISC, HIPAA, and 21 CFR Part 11. These complexities increase cycle times, costs, and audit risk, slowing the delivery of new therapies.
Solution
Astraea offers a standards‑aware AI platform that orchestrates the entire biometrics and submission lifecycle—from protocol design and SAP definition through SDTM/ADaM mapping, TLF generation, and FDA‑ready eCRT packages. Its multi‑agent architecture automates data transformation, annotation, validation, and evidence synthesis while preserving human‑in‑the‑loop checkpoints for biostatisticians, programmers, and medical writers. Every action is versioned, logged, and compliant with CDISC, HIPAA, GDPR, and 21 CFR Part 11, providing an auditable, traceable execution layer. By reusing structured metadata across stages, the system reduces biometrics cycle times by 30–50% and cuts associated costs. The platform delivers regulator‑ready outputs—including Define‑XML, Pinnacle 21‑validated datasets, and CSR drafts—directly to a unified control plane for review and submission.
Target Audience
Primary customers are pharmaceutical sponsors, biotech innovators, and contract research organizations that conduct biometrics, statistical programming, and regulatory submission activities.
Features
- Multi‑agent AI engine that automates SDTM, ADaM, and Define‑XML transformations from raw study data
- CDISC‑compliant aCRF annotation generated from protocol artifacts and metadata
- Automated TLF creation directly from the Statistical Analysis Plan with built‑in Pinnacle 21 validation
- HIPAA and GDPR‑aligned data desensitization preserving analytical utility
- Evidence synthesis module that extracts protocol‑aware information from SAPs, CSRs, and regulatory filings
- Governed orchestration with role‑based access, versioning, and approval gates for full auditability
- 21 CFR Part 11‑aligned audit logs capturing who performed each action, when, and on which dataset
- Unified control plane providing end‑to‑end visibility of workflow status, lineage, and review checkpoints