Clinical Trials Consortium
Global Clinical Research Network
Optimizing Patient Matching with AI
Learn how Clinical Trials Consortium enhanced clinical trial efficiency through intelligent patient-protocol matching and semantic data models, achieving 60% faster enrollment and 85% protocol accuracy.
The Challenge
Clinical Trials Consortium faced significant challenges in patient recruitment and protocol matching across their global network of 200+ trial sites. Traditional manual matching processes created bottlenecks and reduced trial efficiency.
- Manual patient screening taking weeks per candidate
- Inconsistent eligibility criteria interpretation across sites
- Poor visibility into patient populations across sites
- High screen failure rates due to mismatched criteria
- Limited ability to predict enrollment timelines
The GraphFlux Solution
AI-Powered Patient Matching
Intelligent algorithms for precise patient-protocol matching using clinical ontologies
Standardized Clinical Data
Unified patient data model with HL7 FHIR and ICD-10 integration
Real-Time Site Visibility
Live dashboard for patient availability and enrollment progress across all sites
Predictive Analytics
Machine learning models for enrollment timeline and success rate prediction
Results & Impact
Enrollment Efficiency
- • 60% faster patient enrollment
- • 85% improvement in protocol accuracy
- • 40% reduction in screen failures
Operational Excellence
- • $1.2M annual cost savings
- • 95% site coordinator satisfaction
- • 25% faster trial completion
"GraphFlux's clinical trial intelligence platform has transformed our patient recruitment process. The AI-powered matching capabilities have dramatically improved our enrollment rates while reducing operational overhead across our entire network."
Ready to Optimize Your Clinical Trials?
Discover how GraphFlux can accelerate patient enrollment and improve trial efficiency.
Request a Demo