How AI Is Matching Patients to Clinical Trials in Days

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How AI Is Matching Patients to Clinical Trials in Days

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Clinical trial enrollment is notoriously slow — 80 percent of trials fail to meet enrollment targets on time, and patients often wait months to find out if they qualify. In this episode, Lucas and Luna look at how AI-powered matching platforms are compressing that timeline from months to days. They examine the case of Triall, a startup using natural language processing to scan electronic health records against trial eligibility criteria in real time. When a patient in a partner hospital system gets a new diagnosis, the AI cross-references their full medical history with thousands of active trials within 24 hours. Lucas walks through the specific technical challenge: unstructured clinical notes written in free text, which traditional keyword searches miss entirely. Luna flags the ethical tension — hospitals sharing data with a third-party AI — and the workaround using de-identified queries. They close on the economics: a single trial day costs drug companies an estimated $8 million in lost revenue, so even a modest speedup delivers billions in value. #ClinicalTrials #AI #Triall #PatientMatching #NaturalLanguageProcessing #HealthTech #DigitalHealth #DrugDevelopment #ElectronicHealthRecords #TrialEnrollment #Pharmaceutical #Biotech #Business #Technology #FexingoBusiness #BusinessPodcast #LucasAndLuna #HealthAI Keep every episode free: buymeacoffee.com/fexingo

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