Clinical Trials & Research Intelligence
Transforming care delivery data into feasibility insight, cohort discovery, recruitment support, and real-world evidence.
A Parallel Research Data Layer Built on Real Care Delivery
SUJA's model does not bolt on a disconnected trials application. It extends the operational EMR into a parallel research intelligence layer supporting retrospective analysis, protocol matching, feasibility assessment, patient discovery, and AI-assisted exploration.
Operational EMR
System of record for care delivery.
- CareAxes workflows
- Live clinical encounters
- IVF / OB-GYN data
- Transactional care delivery
Analytics & Reporting Layer
Structured insight for operational visibility.
- Dashboards
- Trend analysis
- Structured reporting
- Practice-level insights
Research Data Layer
AI-ready research intelligence.
- Clinical replica
- AI-enriched data
- Slice and explore
- LLM-ready workflows
A Proven EMR-Driven Workflow for Clinical Trials
Grounded in real-world execution thinking shaped by prior work for a major global pharmaceutical environment, this model combines retrospective clinical analysis with proactive point-of-care recruitment support.
Site Identification
Identify high-volume practices and relevant patient populations.
Feasibility Assessment
Use historical data and trend analysis to estimate protocol support.
Cohort Discovery
Match inclusion and exclusion criteria against available data.
Point-of-Care Alerting
Trigger workflow prompts during live encounters.
Coordinator Referral
Route potentially eligible patients into structured review.
Enrollment Support
Track referrals, outcomes, and recruitment performance.
Why Fertility and OB-GYN Are Ideal for Research Intelligence
Fertility, IVF, and women's health generate some of the richest longitudinal journeys in healthcare. That makes them especially well suited for feasibility, trial recruitment, outcomes analysis, and real-world evidence.
Longitudinal Journeys
IVF cycles, protocols, embryo development, outcomes, and repeat follow-up create strong research continuity.
Rich Clinical Data
Structured records, narrative notes, labs, and outcomes create deep research value.
High Patient Engagement
Frequent touchpoints improve continuity and support ongoing evidence generation.
Strong RWE Potential
Supports protocol comparison, treatment effectiveness, and maternal-neonatal insights.
Intelligence
A Continuous Learning Engine for Fertility Care
We are not simply building a trials module. We are building a continuous learning engine where care delivery and research intelligence strengthen one another over time.
Every IVF cycle, protocol variation, patient interaction, and clinical outcome contributes to a research-ready environment that can improve recruitment, generate evidence, and support future clinical decisions.
AI That Makes Clinical Research More Actionable
AI should not remain a disconnected reporting layer. In SUJA's model, AI helps transform clinical information into research intelligence that is searchable, usable, and operationally relevant.
AI Data Enrichment
Normalize and structure clinical content for research workflows.
Cohort Reasoning
Use LLM-driven exploration and protocol logic to accelerate candidate discovery.
Predictive Feasibility
Estimate likely patient availability and protocol fit before launch.
Real-Time Matching
Support identification of eligible patients during live encounters.
Outcome Intelligence
Enable research analysis and real-world evidence across longitudinal data.