Lesson 113 of 1550
Clinical Trial Patient Matching: AI-Assisted Eligibility Screening
Clinical trials enroll only 3-5% of eligible patients, partly because eligibility screening is time-intensive. AI can assist in matching patients to trials by comparing patient profiles to eligibility criteria — expanding research participation and patient access to cutting-edge treatments.
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What this lesson covers
Learning path
The main moves in order
- 1The enrollment gap in clinical research
- 2clinical trial matching
- 3eligibility criteria
- 4research participation
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Section 1
The enrollment gap in clinical research
The US runs over 400,000 registered clinical trials, but fewer than 5% of eligible patients enroll. Screening patients against complex inclusion/exclusion criteria is labor-intensive, and many oncologists and specialists simply don't have time to review the full trial landscape for each patient. AI can match de-identified patient profiles to trial eligibility criteria in seconds — surfacing options that might never have been identified manually.
Trial matching prompt
- 1De-identify all inputs before using any non-BAA-covered AI tool
- 2AI matching is a first-pass screen — a clinical research coordinator or PI must confirm eligibility
- 3Exclusion criteria are as important as inclusion — a single exclusion can disqualify a patient
- 4Phase matters: Phase 1 trials prioritize safety; Phase 3 trials most closely approximate standard care
- 5Underrepresented populations (minorities, elderly, pediatric) are systematically under-enrolled — AI matching can help address this by proactively surfacing trials with equity-focused eligibility criteria
Equity in clinical trial enrollment
Historical clinical trial populations have underrepresented women, racial and ethnic minorities, and elderly patients — producing drugs and treatments whose efficacy and safety profiles are less well-characterized in these groups. AI-assisted matching programs that actively flag under-enrollment by demographic subgroup and route eligible patients to trials seeking to address this gap are a tool for both research integrity and health equity.
Key terms in this lesson
The big idea: AI screens thousands of trials against a patient profile in seconds. The clinician and research team confirm eligibility and obtain informed consent.
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