Element / Life Sciences - Clinical Trials Recruitment
Clinical Trials Recruitment
Problem :
Recruiting eligible patients for clinical trials remains one of the most resource-intensive and time-consuming aspects of drug development. Traditional recruitment methods-such as manual outreach, physician referrals, and static eligibility screening-often result in low enrollment rates, delayed study timelines, and high dropout rates. Patient records are scattered across disconnected EHR systems, and trial coordinators struggle to identify candidates who meet complex inclusion/exclusion criteria. Additionally, outreach efforts are generic and lack personalization, leading to poor engagement and low response rates, especially in underserved or geographically dispersed populations.
Solution :
Element’s AI-powered recruitment platform, originally built for enterprise talent acquisition, has been repurposed for clinical trial enrollment. The system ingests structured and unstructured patient data (e.g., EHRs, medical histories, demographics) and applies semantic screening algorithms to match patients to trial protocols based on eligibility criteria. The platform includes an AI-conducted interview module that can engage patients in natural language, assess willingness to participate, answer FAQs, and capture additional context-such as travel limitations or preferences-before referring candidates to coordinators. It also supports automated outreach via SMS, email, and web portals, ensuring personalized and timely engagement with potential participants.
Outcome :
Trial sponsors and research organizations benefit from significantly reduced time-to-enrollment and increased participant diversity. AI-driven screening improves match precision, eliminating the manual burden of sifting through patient databases. Coordinators receive pre-qualified, context-rich profiles, allowing them to prioritize outreach efforts and reduce time spent on unviable candidates. Patients receive clear, accessible communication about trial opportunities tailored to their medical background and personal preferences. Ultimately, this results in higher enrollment rates, fewer dropouts, and faster trial initiation-accelerating the path to regulatory submission and market access.