Case study
From vendor-dependent reporting to automated daily data access.
Anonymized pharmaceutical client • 4 clinical studies • 2 external EDC vendors
4
Clinical studies
2
EDC vendors
3 weeks
Before
2–4 hrs
After
A slow and costly reporting process across multiple external EDC environments
Four clinical studies were hosted across two external EDC vendors. Custom reports and exports across multiple domains required vendor tickets, with development and validation typically taking around three weeks.
New reporting requirements could trigger Change Orders of up to €7,500 per report, and urgent Data Management requests were constrained by vendor timelines. Manual Excel-based extraction and downstream processing added further operational effort.
~3 weeks
€7,500
Core issue: reporting capability depended on external vendor capacity rather than internal Data Management needs.
Automated clinical data integration with a controlled reporting layer for the Clinical Data Management Team
2 vendors / 4 studies
Study-specific extraction
Nightly run at 02:00
Centralized processing
Queries & custom reports
over DTM SQL Query Reporter
02:00 automated extraction → processing, import & reconciliation → updated data available within 2–4 hours
Controls embedded across the automated downstream reporting pipeline
EDC remained the system of record; Azure SQL served as the controlled downstream reporting and analytics layer.
Faster access, lower external reporting dependency and controlled self-service for Clinical Data Management
Clinical data access became an automated, controlled and scalable internal capability for the Clinical Data Management Team.
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Let’s discuss how automated data integration, validation and reporting can support your clinical studies.