For Healthcare & Life Sciences
AI for Clinical Research & Regulatory Affairs
Who it is for
- Pharma companies
- CROs
- Academic medical centres
- Hospital research teams
- Regulatory consultants
Evidence synthesis for research-driven decisions
Problem and approach
Where healthcare teams lose time today
- 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
- Evidence for a submission is scattered across protocols, reports and correspondence
What DataStruct does
- Clinical trial data extraction (endpoints, sample sizes, outcomes, adverse events)
- Adverse event extraction across studies, linked to source
- Rule packs you define for ICH, FDA and EMA submission requirements
- Cross-study evidence synthesis with source-grounded summaries
- Source-linked extraction from published literature
Use cases
Healthcare use cases
Systematic Reviews
Cochrane-grade systematic reviews take 6-12 months and require teams of researchers.
Extract study data across the paper set with source links; screening and synthesis decisions stay with the review team.
Regulatory Submissions
FDA and EMA submissions require precise cross-referencing across thousands of pages.
Rule packs you define for required sections, with source-linked extraction across the dossier for reviewer checking.
Adverse Event Detection
Safety signals hide in narrative text across thousands of case reports.
Extraction of reported adverse events with source links; severity is assigned by rules you define.
Literature Data Extraction
Pulling study design, populations and outcomes from hundreds of papers by hand is slow and inconsistent.
Define the fields once and extract them across the paper set, each value linked to its source passage.
Documents and questions
What healthcare teams bring, and ask
Documents it reads
- Clinical Trial Reports
- Research Papers
- Regulatory Submissions
- Adverse Event Reports
- FDA/EMA Filings
- Study Protocols
- Literature Reviews
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?”
How findings read
The same evidence model in every sector
Answers cite the sources they rely on. Records DataStruct could not confirm are shown separately for a reviewer to check, related material is kept apart from evidence, and a finding with no support says so. Access is controlled by workspace roles, and sensitive actions are audit logged.