WILMINGTON, DE — Trialbee has added an artificial intelligence pre-screening agent to its Honey Platform to identify ineligible clinical trial candidates earlier and move qualified referrals to research sites faster, targeting a recruitment process in which the company reports that about 78% of candidates who pass an initial self-assessment are later disqualified.
The AI Pre-Screening Agent allows patients to complete secondary screening immediately or request a call with a Trialbee nurse. The company is positioning the technology as an alternative to a process in which patients submit information and wait for follow-up before progressing toward enrollment.
The system also answers general clinical research questions and study-specific questions involving locations, visit requirements, participation expectations and next steps.
Each deployment is configured for an individual study or program and uses approved study content and protocol criteria, according to Trialbee. Questions outside the system’s defined scope are escalated rather than answered by the agent.
The product is intended to address a costly operational bottleneck for clinical trial sites and sponsors by filtering candidates before referral. Trialbee states that approximately 78% of candidates completing an initial self-assessment across therapeutic areas are subsequently disqualified during secondary screening.
Completing that screening before a referral can reduce follow-up with candidates who do not meet study criteria while shortening the interval between initial interest and the next step for those who may qualify.
“Our conversational AI Pre-Screening Agent is the latest example of technology built in-house and informed by decades of hands-on recruitment expertise to solve a real enrollment bottleneck,” Trialbee Chief Executive Officer Matt Walz stated.
The technology runs within Trialbee’s Honey Platform and was developed with input from the company’s patient recruitment specialists as well as sponsors, contract research organizations, research sites, nurses, customers and other platform users.
Patients using the AI option can move from initial interest through secondary screening in the same digital process while retaining the ability to request a nurse at any point.
The pre-screening system expands a group of AI functions already available through Honey. Those include Scout, a conversational tool for recruitment data; Candidate Summaries that consolidate eligibility information, nurse notes, assessments, and patient activity; duplicate-patient and spam detection; automatic masking of personally identifiable information in free-text fields; and Global Patient Access checks designed to identify potential language and time-zone barriers.
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