Recrutement Essais Cliniques IA

Par Delos Intelligence — 2026-08-24

How biopharma sponsors use AI to automate EHR screening and patient matching.

Over 80% of clinical trials miss enrollment deadlines costing 600K-8M USD per day. AI agents transform patient screening and cohort matching.

The Bottlenecks

Unstructured EHR data (80% in narrative notes), physician screening fatigue, and lack of demographic diversity create structural recruitment failures.

AI-Powered Patient Matching

1. Protocol Ingestion

AI ingests study protocols and transforms I/E criteria into computable ontologies using SNOMED-CT, RxNorm, LOINC, and ICD-10/11.

!Clinical Trial Recruitment Pipeline

2. Multimodal EHR Screening

Federated learning and NLP models extract surgical histories, genomic mutations (EGFR, KRAS, HER2), and longitudinal biomarker trends from institutional EHRs.

3. Principal Investigator Assist

AI compiles pre-screening briefings showing exactly how each patient satisfies protocol criteria, with personalized informed-consent materials.

!Clinical Trial Enrollment Impact

Proven ROI

  • 300% faster pre-screening speed
  • 50% reduction in time to first patient in
  • 45% drop in pre-screening dropout rates
  • 35% increase in underrepresented demographic cohorts

Privacy and Compliance

HIPAA Safe Harbor, GDPR Article 9, FDA 21 CFR Part 11 auditability. AI acts exclusively as decision-support; all enrollment decisions remain with qualified investigators.