Healthcare & Life Sciences
Clinical Trial Recruitment
4 autonomous agents accelerate trial recruitment from screening to enrollment. 60% faster enrollment.
Agentic AI Workflow
4 agents collaborate to segment patients, recruit candidates, verify credentials, and ensure HIPAA compliance
The Challenge
Trials were failing to meet enrollment targets, delaying treatments that patients desperately needed
A research hospital running 80+ active clinical trials was meeting enrollment timelines on only 35% of studies. Coordinators manually reviewed EHR charts to identify eligible patients, a process that took 45 minutes per chart. Only 3% of screened patients ultimately enrolled.
Eligible patients were often missed because coordinators couldn't review charts fast enough. Outreach was limited to patients seen in clinic, missing thousands of eligible patients in the broader health system. E-consent workflows were fragmented across multiple platforms, causing 20% drop-off between interest and enrollment.
The hospital needed to screen the entire patient population continuously, reach eligible patients proactively, and streamline the consent-to-enrollment pipeline.
The Solution
Agents that screen EHRs, reach patients, manage consent, and enroll seamlessly
Vijan.AI deployed 4 autonomous agents. The Eligibility Screener continuously matches patient profiles across the entire EHR against inclusion/exclusion criteria for all active trials using medical NLP. The Outreach agent contacts eligible patients through physician-approved channels (patient portal, secure messaging, or provider referral) with trial-specific information. The Consent agent manages the complete e-consent workflow, answering patient questions and collecting signatures. The Enrollment agent schedules screening visits, baseline assessments, and randomization, syncing with the CTMS.
Autonomous Agents
How each agent reasons, decides, and acts
Step 1 · Cohort
Patient Segmentation Agent
Clinical Trial Cohort Identification
Autonomously identifies eligible patients from EHR data based on trial inclusion/exclusion criteria.
Input
Trial protocol, EHR database, patient demographics, diagnoses, medications
Output
Eligible patient cohort with match scores
- Calls cohort builder tool to query EHR for patients matching trial criteria
- Calls eligibility filter to rank patients by match quality and accessibility
- Autonomous decision: prioritize high-match patients, exclude ineligible conditions
- Routes eligible cohort to merge node for recruitment validation
Step 2 · Recruitment
Patient Acquisition Agent
Automated Patient Recruitment
Conducts multi-channel outreach to eligible patients, manages informed consent, and tracks recruitment progress.
Input
Eligible patient list, contact preferences, consent templates
Output
Recruited patients with signed consents
- Calls outreach engine to send personalized emails, calls, and portal messages
- Calls consent tracking tool to manage e-consent workflows and capture signatures
- Autonomous decision: schedule screening visits, escalate non-responders for follow-up
- Routes recruited candidates to merge node for final enrollment validation
Step 3 · Verification
Credentialing Agent
Investigator and Site Credentialing
Verifies credentials of trial investigators and research staff, ensuring regulatory compliance.
Input
Investigator profiles, license numbers, training certifications
Output
Credentialing status with expiration tracking
- Calls license verification tool to validate medical licenses and board certifications
- Calls background check tool to ensure Good Clinical Practice (GCP) training completion
- Autonomous decision: approve credentialed staff, flag expirations, block unqualified personnel
- Routes credentialing status to merge node for trial activation approval
Step 4 · Privacy
HIPAA Compliance Agent
HIPAA Compliance and Privacy Protection
Ensures all trial activities comply with HIPAA privacy rules, manages patient consents, and audits data access.
Input
Patient consents, data access logs, privacy policies
Output
HIPAA compliance certification with audit trail
- Calls privacy audit tool to monitor PHI access and detect unauthorized disclosures
- Calls consent management tool to validate patient authorizations for research use
- Autonomous decision: block non-compliant data sharing, flag privacy breaches
- Routes compliance certification to merge node for final enrollment approval
Results
Measurable impact within 90 days of deployment
Faster Enrollment
Average time to full enrollment reduced from 14 months to 5.5 months. 85% of studies now meet enrollment timelines.
More Patients Screened
Automated screening covers the entire 2M-patient health system vs. manual review of clinic patients only.
Enrollment Rate
Screen-to-enroll conversion improved from 3% to 8.5% through better matching and streamlined consent.
Sponsor Revenue
Faster enrollment and higher retention attracted additional sponsor contracts worth $22M.
Implementation
From pilot to production in 12 weeks
Agent Design & Tool Integration
Defined agent capabilities, connected ML model, rules engine, graph DB, and chargeback API tools. Configured orchestrator routing logic.
Shadow Mode & Autonomous Tuning
Agents ran in shadow mode on 10% of transactions. Tuned decision thresholds, tool call parameters, and feedback loop retraining frequency.
Full Autonomous Deployment
Production rollout across all channels. Agents operating fully autonomously with human-in-the-loop for critical escalations only.
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