Inovalon has launched a new clinical trial eligibility screener aimed at addressing one of the most persistent bottlenecks in clinical research: patient recruitment. The service is designed to help sponsors, clinical research organisations, sites and recruitment vendors assess patient eligibility against study inclusion and exclusion criteria in near real time, with the goal of reducing manual pre-screening and accelerating trial enrolment.

Clinical trial recruitment remains a major challenge across the industry. More than two-thirds of trial sites fail to meet enrolment targets, while up to half enrol one or no patients at all. Traditional pre-screening approaches, such as phone interviews and questionnaires, are often slow, resource intensive and poorly aligned with increasingly complex trial protocols. As a result, significant time and cost can be spent engaging patients who ultimately do not qualify for a study.

Inovalon’s eligibility screener is built to integrate directly into existing recruitment platforms and site workflows. It evaluates patient eligibility using longitudinal, primary source medical data, returning near-instant insights that indicate whether a patient passes, fails or requires further review for each eligibility criterion. By reducing reliance on manual review, the company aims to help sites prioritise likely eligible participants earlier in the recruitment process.

Ed Chidsey, president of Inovalon’s insights business unit, said: “Patient recruitment continues to be one of the most persistent challenges in clinical research, often delaying trials and slowing access to new therapies. Our eligibility screener empowers sponsors, CROs, sites, and recruitment organizations with real-time, actionable insights to overcome data fragmentation, set a new standard for accurate patient identification, and improve trial enrollment and execution at scale.”

The application programming interface applies natural language processing to interpret free-text eligibility criteria contained in trial protocols. Rather than relying solely on structured fields, the system parses narrative inclusion and exclusion requirements and matches them against available clinical data. This approach is intended to support scalable eligibility assessments across multiple studies while helping teams corroborate patient-reported medical histories earlier in the recruitment pathway.

By flagging ineligible patients sooner, the tool is designed to reduce unnecessary site visits and administrative workload, particularly for complex studies with narrow eligibility windows. Faster identification of suitable participants may also support more timely study start-up and reduce delays that can cascade into later phases of clinical development.

The launch reflects broader efforts across the clinical research ecosystem to apply data-driven approaches to trial feasibility, site performance and patient centricity. As protocols become more complex and competition for patients increases, technologies that streamline recruitment and eligibility assessment are increasingly viewed as critical to maintaining trial timelines.

While the screener is positioned as an operational support tool rather than a replacement for clinical judgement, its use of real-time data and automated assessment highlights the growing role of advanced analytics and AI-enabled technologies in trial execution. Whether such approaches can meaningfully improve enrolment outcomes at scale will be closely watched by sponsors and CROs under continued pressure to deliver studies faster and more efficiently.