AI for Clinical Research & Regulatory Affairs
Synthesise evidence across thousands of studies. Track adverse events. Accelerate regulatory submissions to FDA, EMA, and MHRA, with every claim cited.
Built for
Why Healthcare teams struggle today
The problems we see in every healthcare workflow.
- Regulatory submissions to FDA/EMA require meticulous documentation across thousands of pages
- Adverse event reports buried across multiple systems delay safety signals
- Clinical trial data extraction is manual and inconsistent across studies
- Systematic reviews take 6-12 months of researcher time
- Medical literature monitoring at scale is impossible manually
How DataStruct AI solves it
Purpose-built capabilities for healthcare workflows.
- Clinical trial data extraction (endpoints, sample sizes, outcomes, adverse events)
- Adverse event detection and tracking across studies
- Regulatory submission compliance checks against ICH, FDA, EMA standards
- Cross-study evidence synthesis with source-grounded summaries
- Real-time medical literature monitoring with custom alerts
Healthcare use cases
The most impactful workflows DataStruct AI powers for healthcare teams.
Systematic Reviews
Problem: Cochrane-grade systematic reviews take 6-12 months and require teams of researchers.
Solution: AI screens thousands of papers, extracts study data, and synthesises evidence with PRISMA-compliant outputs.
Impact: Faster reviews with reproducible methodology and a full audit trail.
Regulatory Submissions
Problem: FDA and EMA submissions require precise cross-referencing across thousands of pages.
Solution: Automated cross-reference checking, citation validation, and compliance gap detection.
Impact: Fewer agency questions. Faster approval timelines.
Adverse Event Detection
Problem: Safety signals hide in narrative text across thousands of case reports.
Solution: NLP extraction of adverse events with severity classification and aggregation.
Impact: Detect signals earlier. Improve patient safety.
Medical Literature Monitoring
Problem: Staying current with publications in a therapeutic area is impossible manually.
Solution: Custom alerts on PubMed, journals, and conference abstracts with AI-generated summaries.
Impact: Medical affairs teams stay ahead of competitors and regulators.
Document types we handle
Questions you can ask
- ›“What was the primary endpoint result?”
- ›“Compare efficacy across studies in this evidence set”
- ›“What adverse events were reported in Phase III?”
- ›“Summarise safety signals across all trials”
- ›“Which inclusion/exclusion criteria are most common?”
Why Healthcare teams choose DataStruct AI
Evidence-cited AI
Every answer linked to source. Designed to reduce hallucinations through citation validation and abstention. Audit-ready by design.
Built to scale
Multi-tenant architecture with SSO, RBAC, and audit logs. Scales to thousands of users without losing tenant isolation.
12 domain packs
Pre-configured terminology, document types, and rule packs for your vertical.
See DataStruct AI in action
Tell us about your team, document volumes, and integrations. We'll put together a tailored package and walk you through the platform.