Intelligent Clinical Trial Matching Digital Worker
This digital worker deploys a coordinated multi-agent system that performs federated search across 175M+ patient records, automatically evaluates 47+ eligibility criteria per patient, predicts treatment response using ML models, optimizes site selection, monitors diversity metrics, and generates real-time enrollment tracking..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Clinical trial configuration interface for defining trial parameters, molecular criteria, and eligibility requirements for intelligent patient matching
AI-powered eligibility assessment evaluating 1124 patient candidates against 47 eligibility criteria with real-time genomic profile matching
Enrollment tracking dashboard displaying trial progress, site performance metrics, and AI-generated insights for optimization
Comprehensive results summary showing 196 qualified patients, 79% response prediction, diversity metrics, and $12.6M cost savings
AI Agents
Specialized autonomous agents working in coordination
Workflow Coordinator Agent
Complex multi-stage trial matching requires orchestration of parallel workflows, agent handoffs, and synthesis of recommendations from multiple specialized systems.
Core Logic
Orchestrates the entire clinical trial matching workflow by initiating searches, coordinating agent handoffs, synthesizing recommendations from specialized agents, monitoring overall progress, and making final enrollment strategy decisions based on aggregated inputs.
Federated Search Agent
Patient data is siloed across hundreds of healthcare institutions, making comprehensive patient discovery impossible without data movement that violates privacy regulations.
Core Logic
Executes privacy-preserving federated queries across distributed healthcare networks. Connects to 175M+ patient records across multiple institutions, applies search criteria locally at each node, and aggregates de-identified candidate counts without exposing protected health information.
Eligibility Assessment Agent
Manual evaluation of 47+ inclusion/exclusion criteria per patient is time-consuming and inconsistent, with different coordinators interpreting criteria differently.
Core Logic
Systematically evaluates each candidate patient against all trial criteria using rule-based logic and NLP extraction. Documents evidence for each criterion evaluation, calculates confidence scores, categorizes patients as pass/fail/needs-review, and provides detailed audit trails for regulatory compliance.
Response Prediction Agent
Identifying which eligible patients are most likely to respond to treatment is critical for trial success but requires analysis of complex genomic and clinical factors.
Core Logic
Analyzes patient genomic profiles, clinical history, and biomarkers using ML models trained on real-world evidence from 50K+ similar patients. Computes response probability with confidence intervals, identifies favorable and risk factors, and ranks patients by predicted treatment benefit.
Enrollment Strategy Agent
Developing optimal enrollment strategies requires balancing multiple factors including site capacity, geographic distribution, timeline constraints, and budget limitations.
Core Logic
Synthesizes inputs from all agents to generate optimized enrollment recommendations. Performs Monte Carlo simulations for timeline projection, calculates cost-benefit analysis vs. traditional recruitment, identifies risk mitigation strategies, and produces actionable site-prioritized enrollment plans.
Diversity Monitoring Agent
Clinical trials historically underrepresent minority populations, leading to treatments that may not be effective or safe across all demographic groups.
Core Logic
Continuously monitors demographic composition of the enrolled cohort against diversity targets. Identifies gaps in representation by race, gender, and age groups, recommends specific sites and patients to address gaps, and provides real-time diversity trend analysis throughout enrollment.
Site Selection Agent
Choosing optimal trial sites from hundreds of possibilities requires evaluation of historical performance, patient proximity, capacity, and infrastructure factors.
Core Logic
Evaluates and ranks potential trial sites using historical enrollment success rates, qualified patient proximity analysis, site capacity assessment, and geographic diversity optimization. Produces prioritized site recommendations with projected enrollment rates and capacity utilization forecasts.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
7 technologies
Architecture Diagram
System flow visualization