Development and Evaluation of a Human-in-the-Loop Data Curation Training Program to Support a Digital Clinical Trial Platform: Descriptive Feasibility Study

Background: LookUpTrials is a clinician-facing digital platform designed to support point-of-care navigation of institution-specific oncology clinical trials, incorporating artificial intelligence-assisted summarization and search functionalities. While embedding curated trial knowledge tools in community oncology workflows is feasible, the human infrastructure required to sustain high-quality, up-to-date trial data over time remains underexplored. Objective: This study aimed to evaluate the feasibility of a structured training program embedding trainees within a supervised human-in-the-loop workflow for oncology clinical trial data curation in support of the LookUpTrials digital platform. Methods: We conducted a descriptive feasibility evaluation of a cohort-based training and workflow model. A total of 10 undergraduate trainees curated publicly available trial information from institutional portals and ClinicalTrials.gov across 5 academic medical centers. Trial throughput and participant experiences were summarized descriptively. Results: Over 10 months, trainees curated 2503 oncology clinical trial entries across 5 institutions, with processing rates increasing over time. Participants reported that structured onboarding and peer support facilitated engagement with data curation workflows. Conclusions: Standardized human-in-the-loop workflows for clinical trial data stewardship can be implemented with individuals without prior clinical trials or informatics experience when supported by structured training and quality assurance. This study complements prior feasibility work on embedding trial knowledge tools in community oncology settings by focusing on the sustainability of the underlying content pipeline. Further evaluation is needed to assess scalability across institutions and durability over longer periods of platform maturation.