AI for Patient Recruitment & Retention — AI for Clinical Trial Design

# AI for Patient Recruitment & Retention

Patient enrollment is the single largest bottleneck in clinical development. The average Phase 3 trial takes 12-18 months to fully enroll, and 80% of trials fail to meet their initial enrollment timelines. This adds an estimated $600K-$8M in costs per day of delay for a blockbuster drug.

The Patient Matching Challenge

Clinical trial eligibility criteria define a narrow patient population. Matching real patients to these criteria requires screening medical records, lab results, imaging reports, concomitant medications, and medical histories — a process that is overwhelmingly manual at most sites.

AI can transform this by analyzing Electronic Health Record (EHR) data at scale:

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What you'll learn:

Apply AI to identify and match patients to clinical trials using EHR and claims data
Use AI-driven predictive models to forecast enrollment rates and identify bottlenecks early
Build AI-powered retention strategies that predict and prevent patient dropout

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