RISKVIEW 2.0:
FROM CRISIS TO COMPLIANCE
A global pharmaceutical sponsor needed to rebuild their critical RBQM risk dashboard after discovering significant validation gaps and technical debt. We led the complete redesign, development, and validation—delivering a compliant, scalable solution in 6 months.
CLIENT CONTEXT
A Top 15 global pharmaceutical company with an established RBQM program supporting 30+ active clinical trials across oncology, rare disease, and neurology therapeutic areas.
The organization had invested heavily in a custom-built risk dashboard ("RiskView 1.0") three years prior. The platform integrated data from Medidata Rave, Oracle Argus, and internal CTMS systems to provide real-time risk monitoring across their global trial portfolio.
However, as the platform scaled and regulatory expectations evolved (particularly with ICH E6(R3) on the horizon), critical issues emerged that threatened both compliance and operational effectiveness.
THE CHALLENGE
Validation Gaps
An internal audit revealed that RiskView 1.0 lacked critical validation documentation (URS, IQ/OQ/PQ, traceability matrices). The platform was technically "unvalidated" and at risk of regulatory findings.
Technical Debt
The original development team had left the organization, leaving behind poorly documented code, hard-coded logic, and fragile data pipelines that broke frequently. Maintenance was becoming unsustainable.
Scalability Constraints
The platform was built for 10-15 studies but now supported 30+. Performance degraded significantly, with dashboard load times exceeding 2 minutes and frequent timeouts during peak usage.
Business Continuity Risk
With 12 active Phase III studies relying on RiskView for centralized monitoring, any extended downtime could delay critical quality decisions and jeopardize regulatory submissions.
The Bottom Line:
The organization faced a binary choice: invest in a complete rebuild with proper validation and modern architecture, or abandon the platform entirely and revert to manual monitoring—a regression that would undermine years of RBQM maturity.
OUR APPROACH
We led a structured, risk-based approach to rebuild RiskView from the ground up while maintaining business continuity for ongoing studies.
Discovery & Requirements (Weeks 1-3)
Stakeholder Interviews: Conducted 25+ interviews with Clinical Ops, Data Management, QA, and IT to understand current workflows, pain points, and future requirements.
Technical Assessment: Performed comprehensive code review and architecture analysis of RiskView 1.0, documenting technical debt and identifying reusable components.
User Requirements Specification (URS): Developed detailed URS covering functional requirements, data flows, KRI logic, user roles, and compliance requirements (GAMP5 Category 4).
Architecture & Design (Weeks 4-6)
Modern Tech Stack: Migrated from legacy R-Shiny to Power BI with Azure Data Factory for ETL, ensuring enterprise scalability and Microsoft ecosystem integration.
Modular Architecture: Designed loosely-coupled data pipelines with clear separation between ingestion, transformation, and visualization layers to enable independent testing and maintenance.
Validation Strategy: Developed risk-based Computer System Assurance (CSA) approach aligned with GAMP5, focusing validation efforts on custom logic and critical data transformations.
Development & Testing (Weeks 7-18)
Agile Sprints: Delivered functionality in 2-week sprints with continuous stakeholder feedback, ensuring alignment with operational needs and minimizing rework.
Parallel Operations: Ran RiskView 2.0 in parallel with 1.0 for 8 weeks, allowing users to validate outputs and build confidence before cutover.
Performance Optimization: Implemented incremental refresh, query folding, and aggregation strategies—reducing dashboard load times from 120+ seconds to under 5 seconds.
Validation & Deployment (Weeks 19-24)
Comprehensive Validation: Executed 180+ test scripts covering IQ (installation), OQ (operational), and PQ (performance) qualification, with 100% pass rate on first execution.
Traceability: Maintained full Requirements Traceability Matrix (RTM) linking URS → Functional Specs → Test Scripts → Test Results, ensuring regulatory audit readiness.
Phased Rollout: Deployed to 3 pilot studies first (2 weeks), then remaining 9 studies (4 weeks), with dedicated support during transition period.
RESULTS & IMPACT
Regulatory Compliance
Achieved full GAMP5 Category 4 validation with complete documentation package (VP, URS, FS, IQ/OQ/PQ, VSR, RTM). Platform passed FDA inspection with zero findings.
Performance Gains
Reduced dashboard load times by 96% (from 120s to <5s). Eliminated timeout errors entirely. System now supports 50+ concurrent users without degradation.
Technical Excellence
Modular architecture reduced maintenance effort by 70%. Comprehensive documentation enables internal team to manage updates independently.
Business Continuity
Zero downtime during migration. All 12 studies transitioned seamlessly with no disruption to centralized monitoring activities or quality decisions.
Long-Term Value
Scalability: Platform now supports 50+ studies (vs. 30 at launch) with no performance degradation, enabling continued portfolio growth.
Extensibility: Modular design allows rapid addition of new KRIs, data sources, and visualizations without re-validation of core platform.
Knowledge Transfer: Comprehensive training and documentation enabled internal team to assume full ownership within 3 months post-launch.
TECHNOLOGIES & PLATFORMS
Data Sources
- • Medidata Rave (EDC)
- • Oracle Argus (Safety)
- • Internal CTMS
- • ePRO platforms
ETL & Data Engineering
- • Azure Data Factory
- • Azure SQL Database
- • Power Query (M language)
- • DAX for calculations
Visualization & BI
- • Power BI Premium
- • Row-Level Security (RLS)
- • Incremental Refresh
- • Custom visuals
Validation & Compliance
- • GAMP5 Category 4 approach
- • Computer System Assurance (CSA)
- • Azure DevOps for change control
- • Automated test scripts
KEY TAKEAWAYS
Validation Cannot Be Retrofitted
Attempting to validate an existing system is exponentially harder than building validation into the development lifecycle from day one. The cost of RiskView 2.0 was 3x the original build—but the alternative (regulatory findings) was unacceptable.
Parallel Operations Reduce Risk
Running old and new systems in parallel for 8 weeks allowed users to validate outputs, build confidence, and identify edge cases before cutover—eliminating the "big bang" risk that often derails platform migrations.
Invest in Architecture, Not Just Features
RiskView 1.0 prioritized feature velocity over architectural soundness. The rebuild invested heavily in modular design, documentation, and performance optimization—ensuring long-term sustainability and extensibility.
FACING A SIMILAR CHALLENGE?
Whether you need to rescue a failing platform, build a new RBQM system from scratch, or validate an existing tool—we've been there. Let's discuss your specific situation.