Accelerate Enrollment And Reduce Site Burden

Citeline PatientMatch is an AI- and real-world data–powered solution designed to help sponsors identify highly qualified, protocol-matched patients earlier in their clinical journey — when enrollment decisions have the greatest impact on trial timelines and outcomes. By proactively surfacing eligible candidates before or at the point of care, the platform supports faster, more efficient recruitment while preserving protocol integrity.

The solution integrates diverse, longitudinal data sources, including medical and pharmacy claims, laboratory results, electronic health records (EHRs), and provider-dictated clinical notes. Using advanced natural language processing (NLP) and machine learning, it extracts both structured and unstructured insights to match patients against complex inclusion and exclusion criteria with high precision. This multimodal data approach enables deeper phenotyping, identification of nuanced clinical characteristics, and more accurate cohort targeting.

For sponsors, Citeline PatientMatch improves enrollment forecasting, enhances site performance, and reduces costly recruitment delays. For investigative sites, it minimizes manual chart reviews and administrative burden by delivering prioritized lists of likely eligible patients, allowing research teams to focus on engagement rather than data mining.

By combining AI-driven analytics with real-world data at scale, Citeline PatientMatch accelerates enrollment timelines, improves patient access to clinical trials, and ultimately helps bring therapies to market more efficiently.