Case Study
Scaling Clinical Research with an Automated Duplicate-Prevention Registry and Data Quality Workflows


Industry
- Healthcare Technology / Clinical Research (GxP & 21 CFR Part 11 Compliant)
Overview
CenExel, a leading clinical research organization operating across multiple regions, faced serious risks caused by duplicate and professional subjects entering multiple studies under different identities. This led to compromised data integrity, regulatory concerns, and delays in study timelines. They also needed reliable Study/Protocol-wise visit tracking and a controlled process ensuring that only trained and certified site users could enter participant data.
To address these challenges, Vivasoft Ltd. delivered two integrated, high-security solutions.
Vivasoft Ltd. engineered CTSdatabase to serve as a centralized clinical trial subject registry. They designed it specifically to detect and prevent duplicate subjects without exposing private or identifiable information.
- Anonymity by Design: Vivasoft Ltd. ensured the system maintains complete subject anonymity while identifying attempts by professional subjects to alter their presentation.
- Investigative Insights: They provided investigators with a full history of a subject’s past study participation. They delivered actionable match insights that enable confident enrollment decisions.
- Access Control: Vivasoft Ltd. enforced site-user training and certification requirements before any subject data can be entered.
Technologies Used
C#
Dot Net
Power Apps
DataBricks
Power Automate
EF Core
JWT Authentication
xUnit
Next.js
React
Azure Web App
React Query
Azure SQL
Redis Cache
Azure Application Insights
Azure Firewall
Azure DevOps
Power BI
NextAuth
.NET 8
MediatR
FluentValidation
IQVIA
Challenges & Solutions
Challenges Faced by the Client
- High risk of duplicate and professional subjects enrolling across different clinical trial sites, threatening study integrity.
- Need a secure, privacy-preserving identity verification mechanism without collecting or exposing personal information.
- Complex multi-step workflows for rater surveillance, quality monitoring, and Study/Protocol-wise visit management.
- Lack of real-time insights, making it difficult for site users, sponsors, and analysts to track operational KPIs.
- Inconsistent or outdated data across systems, leading to reporting gaps and compliance risks.
- Scalability limitations as the number of studies, sponsors, and trial sites continued to grow.
- Need to ensure site-user training and certification compliance before allowing any study data entry.
Solutions provided by Vivasoft Ltd.
- Vivasoft implemented CTSdatabase, a centralized subject registry with advanced duplication-prevention logic to block repeat or professional subjects—while maintaining complete anonymity.
- They enabled the management of Sponsor-wise and Study/Protocol-wise operations across all trial sites.
- Developed secure authentication & authorization flows for Site Users, System Admins, and Sponsors with role-based access control.
- Built a Clean Architecture + CQRS–based backend, ensuring long-term maintainability, modularity, and scalability.
- Integrated Azure Application Insights for comprehensive logging, monitoring, and performance metrics.
- Automated scientific and operational workflows through Azure DataBricks ETL pipelines and Power Platform integration.
- Delivered dynamic Power BI dashboards for operational, analytical, and regulatory reporting across all stakeholder groups.
- Implemented robust global error handling, structured logging, and complete API documentation for seamless operations.
- Added compliance workflows ensuring site-user training and certification before data entry, reducing human-error risks.
Measurable Results
Increased efficiency
Cost savings
Growth metrics
Time saved
Team Involvement
| Resources | Count |
|---|---|
| Solution Architect | 1 |
| Backend Developers | 2 |
| Frontend Developers | 2 |
| Power Platform Developer | 1 |
| Project Manager | 1 |
| SQA | 2 |
Core Features of CTSdatabase V4
Advanced duplicate-subject prevention with high-accuracy identity-matching logic.
Sponsor-wise Study/Protocol management and site-level subject visibility to enforce protocol rules per sponsor and study.
Site User management (provisioning, role assignment, training/certification status, and access controls)
Secure, privacy-preserving multi-role authentication & authorization for Site Users, Sponsors, and Admins.
Built-in training and certification enforcement ensuring only authorized, certified site users can enter study data.
Real-time screening insights with actionable match reports for faster, safer enrollment decisions.
Custom Power BI dashboards for operational, sponsor-specific, and regulatory reporting
Modern, integration-ready REST API architecture supporting multi-site interoperability and sponsor integrations.
Features of CenExel Data Quality Program
Comprehensive rater surveillance, performance tracking, and compliance monitoring
Automated Study/Protocol-wise data quality workflows that reduce manual effort and errors
User-friendly Power Apps web interface for site-level and sponsor-level operations
Scalable Azure DataBricks ETL pipelines for scientific, statistical, and operational data processing
Advanced analytical dashboards for real-time decision making and study oversight
Module: Sponsor Portal Dashboard
1. Protocol Violation Monitoring
- Visualizes total flag counts categorized by violation type (e.g., Age/BMI, Active in Another Study).
- Includes interactive tooltips that display the specific flag name, count, and severity level.
- Updates the dataset automatically whenever a different study is selected from the dashboard.
2. Cross-Therapeutic Indication Analysis
- Visualizes the percentage distribution of matched indications (e.g., Schizophrenia, Depression, Migraine).
- Labels each chart segment clearly with the specific indication name and its calculated percentage.
- Updates the dataset automatically whenever a different study is selected from the dashboard.
Development Timeline
Future Prospects
- Planned integration with Azure ML: They are building predictive models to identify professional subject behavior.
- Predictive Analytics: They are developing modules for predictive data quality scoring.
- Cloud Optimization: They provide ongoing maintenance and cloud cost optimization.
- Long-term Collaboration: They provide continued enhancements to the platform through an ongoing strategic partnership.










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