Clinical Research Directory

Development of a Mobile Terminal-Based Intelligent Detection System for Multiple Anterior Segment Diseases of the Eye

This is a multi-center, cross-sectional study evaluating a smartphone-based artificial intelligence (AI) system for anterior segment eye disease screening. The system is designed to identify 16 clinically important anterior segment conditions from images captured using a standard Android smartphone. A core design feature of the system is that all image analysis is performed entirely on the smartphone itself, without requiring internet connectivity or cloud-based server infrastructure. The study is motivated by a structural challenge in the deployment of medical AI: systems that depend on cloud infrastructure for inference are non-functional in settings without reliable internet access, which disproportionately excludes populations in low-resource regions where the burden of preventable eye disease is highest. This study evaluates whether an on-device AI system, designed with operational constraints as a primary engineering objective, can deliver clinically acceptable diagnostic performance while remaining operable under real-world connectivity limitations. The study comprises five evaluation components. First, the diagnostic performance of the AI system is benchmarked against board-certified ophthalmologists of varying seniority on a standardized set of smartphone-captured anterior segment images. Second, the usability of the system is evaluated among non-medical users who perform self-administered screening with minimal instruction, with per-screening time recorded across consecutive attempts to characterize the learning curve. Third, a head-to-head field trial directly compares the on-device AI system against a functionally equivalent cloud-based deployment of the same model architecture across key operational dimensions including screening duration, diagnostic performance, and user acceptability. Fourth, population-level screening is conducted among consecutively enrolled community residents at two low-resource sites, with per-disease sensitivity and specificity calculated against reference-standard slit-lamp examinations. Fifth, pre-specified health-economic and environmental analyses compare the two deployment modalities in terms of per-person screening cost, cost-effectiveness, per-inference electricity consumption, and projected carbon emissions at scale. The reference standard for all diagnostic comparisons is slit-lamp biomicroscopic examination performed by board-certified ophthalmologists. The study is designed and reported in accordance with the DECIDE-AI reporting guideline for early-stage clinical evaluation of AI-driven decision-support systems.

Extension Study of Two Doses of Linsitinib in Subjects With Active, Moderate to Severe Thyroid Eye Disease (TED)

The overall study objective is to continue to assess the efficacy, safety, pharmacokinetics, and pharmacodynamics of linsitinib in subjects who were enrolled in the prior VGN-TED-301 through Week 24. These subjects include VGN-TED-301 Week 24 proptosis non-responders or subjects who relapse during the Follow-Up Period of VGN-TED-301.

A Phase 2b, Study of Linsitinib in Subjects With Active, Moderate to Severe Thyroid Eye Disease (TED)

The overall objective is to study the safety, pharmacokinetics and efficacy of linsitinib (a small molecule IGF-1R inhibitor) administered orally twice daily (BID) vs. placebo, at 24 weeks in the treatment of subjects with active, moderate to severe thyroid eye disease (TED).