Trialbee Added AI Agent to Accelerate Patient Screening
The new digital tool aims to reduce clinical trial recruitment delays by automating the secondary candidate vetting process.
Updated on Sept. 27, 2026 in Artificial Intelligence
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Trialbee has integrated an artificial intelligence pre-screening agent into its Honey Platform. The system enables prospective clinical trial candidates to complete secondary assessments immediately, addressing a significant recruitment bottleneck.
Why it matters
Late-stage candidate disqualification is a major hurdle in clinical research, causing significant trial delays. By automating initial filtering, this tool shifts the screening process earlier in the patient engagement lifecycle.
Approximately 78% of candidates who pass an initial self-assessment are typically disqualified during secondary screening. The new agent automates these secondary checks to streamline the transition to research sites.
The players
Trialbee
A Wilmington-based technology firm that specializes in digital platforms for clinical trial patient recruitment and retention.
The details
The AI agent operates within the Honey Platform by using approved study content and protocol criteria to verify candidate eligibility. Patients can complete their secondary screening digitally or request a live call with a nurse. The system is designed to provide information on study locations, visit requirements, and participation expectations, with built-in logic to escalate complex questions outside its defined scope to human operators.
Timeline
September 27, 2026: Trialbee announced the addition of the AI pre-screening agent.
The Tech Race
The clinical trial recruitment industry is currently racing to minimize drop-off rates through digital automation. Trialbee is positioning its Honey Platform against manual, site-led screening processes that have historically slowed trial initiation.
Prospective clinical trial participants using the Honey Platform can now expect faster eligibility determinations. The agent provides immediate answers to logistical questions about study requirements without requiring manual intervention.
The takeaway
This integration signals a move toward higher-throughput digital enrollment for research sites. Industry participants should watch for future reports on the tool's performance in reducing overall site-referral wait times.
Further reading
For more developments in clinical research automation, visit the Artificial Intelligence section.
Source note: This article includes information reported by MyChesCo.
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