Nxtcure Labs operates Galen, a full-stack AI-driven clinical research organization where thirteen purpose-built agents run oncology studies end to end. Every action with clinical, safety, regulatory, or financial consequence requires human approval in a single review queue, with a certified board of oncologists making final calls. Galen currently runs on CDISC SDTM data, including a synthetic Phase 3 NSCLC study with 450 subjects across 13 countries.
Funding
Funding not disclosed
Founders
Product
Problem
Clinical trials are complex, document-heavy operations that require coordination across feasibility, protocol design, site activation, monitoring, data management, safety surveillance, and regulatory documentation. Traditional CRO workflows are slow, error-prone, and burden investigators with repetitive administrative tasks, while automation in clinical settings raises concerns about accountability and patient safety.
Solution
Nxtcure Labs provides Galen, a full-stack AI-driven CRO that runs clinical studies end to end using thirteen purpose-built agents operating in lifecycle order. Each agent handles a discrete phase—from feasibility and protocol drafting to biostatistics, medical writing, and Trial Master File management—while every action with clinical, safety, regulatory, or financial consequence stops in one human review queue until a qualified professional approves or rejects it. Galen includes a certified board of oncologists who make medical, safety, and regulatory decisions, ensuring that serious adverse events are never closed by software, causality is never decided by software, and patient contact remains non-autonomous. The system runs on CDISC SDTM data and provides plain-language reasoning for every action, supporting transparent, auditable decision-making across the trial lifecycle.
Target Audience
Primary customers are pharmaceutical companies, biotechnology firms, academic medical centers, and clinical research organizations conducting oncology trials who need AI-driven efficiencies without compromising human oversight and regulatory compliance.
Features
- Thirteen specialized AI agents covering the full trial lifecycle: feasibility, protocol, activation, recruitment, monitoring, data, safety, retention, termination watch, supply, biostatistics, medical writing, and TMF
- Single human review queue with mandated approval for any action having clinical, safety, regulatory, or financial impact
- Protocol drafting with amendment-risk scoring against the SPIRIT checklist and activation readiness tracked against a 77-day benchmark
- Risk-based monitoring with KRI scorecards per site, drug-supply forecasting with 15% buffer, and dropout prediction with termination-risk watch
- Pharmacovigilance triage that always escalates serious adverse events, with causality decisions reserved for humans
- Query generation and auto-resolution on a 14-day SLA, and TLFs generated behind a double-programming validation gate
- Self-auditing Trial Master File with PubMed evidence links for every review and print-ready PDF output for regulatory submission
- Designed to align with FDA and EMA January 2026 guiding principles for AI in drug development