AI-Driven, Consent-Based Patient Eligibility Assessment for Clinical Trials

Problem Statement

Clinical trial recruitment in the US and UK is constrained by strict consent, governance, and protocol requirements. Eligibility screening is largely manual, time-consuming, and dependent on specialist review, leading to delayed enrolment, high screening failure rates, and increased trial costs.

AI Implementation Approach

Deploy an AI system that ingests approved clinical trial protocols into a controlled knowledge base and performs eligibility assessment only on consented patient cohorts. The system supports protocol-driven screening workflows, assisting research teams by identifying potentially eligible patients while preserving clinician oversight and regulatory compliance.

Input

Industry

• Hospitals

• academic medical centres

• clinical research organizations

• NHS trusts

Output

Pre-Screened Patient Candidate Lists

• List of potentially eligible patients

• Match confidence indicators

• Clear flags for manual clinical validation

• No automated patient contact or enrolment actions

Protocol-to-Patient Traceability View

• IRB-approved (US) or REC-approved (UK) trial protocols

• Inclusion and exclusion criteria

• Study phase, endpoints, and eligibility logic

Research and Clinician Dashboards

• Enrolment funnel visibility

• Screening and exclusion reasons

• Alerts for newly eligible consented patients

• pharmaceutical sponsors

Clinical Trial Protocols

Consented Patient Data Sources

• EHR data from SQL and NoSQL databases

• Clinical notes, lab values, medication history

• Data accessed only after documented patient consent

• On-prem or cloud-hosted hospital systems

• Criterion-level mapping showing how patient data aligns with protocol requirements

• Transparent explanations suitable for audit and regulatory review

Key Parameters and Impact

• Faster trial start-up and recruitment timelines

• Better utilization of research coordinator time

• Lower screening failure rates

• Improved compliance with protocol and governance standards

• Reduction in manual pre-screening effort

Security and Governance

Integration and Deployment

• HIPAA-compliant processing for US healthcare systems

• Alignment with UK GDPR and NHS data governance policies

• Consent-driven data access and usage

• Role-based access controls and audit trails

• Human-in-the-loop review for all eligibility decisions

• Integration with US EHR systems and UK NHS data platforms

• API-based connectors for SQL, NoSQL, and cloud data stores

• Deployable within hospital or research-controlled environments

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