Clinical trials

This prospective observational study evaluates the feasibility and clinical utility of a smartphone-based artificial intelligence (AI) self-monitoring system in adults with thyroid eye disease (TED) undergoing non-surgical treatment. Eligible participants will use their own smartphones and the study application (Glandy) to perform at least weekly home monitoring consisting of a symptom questionnaire (diplopia, pain on visual analog scale) and a standardized frontal facial photograph. AI-derived outputs (Glandy CAS, Glandy EXO, Glandy LID) obtained at routine clinic visits will be compared with standard clinician assessments (CAS total score, Hertel exophthalmometry, MRD1/MRD2). AI outputs will not be used for real-time clinical decision-making during the study.

This prospective, multicenter, multinational observational study evaluates the clinical validity of an AI-based quantitative eye movement analysis system (Glandy EOM) that analyzes smartphone-recorded 9-gaze videos. Approximately 200 adults per site with suspected or confirmed ocular motility abnormalities will undergo a single study visit consisting of a standard clinical 9-gaze examination, an assistant-aided smartphone video recording, and a patient self-recorded video acquisition using a mobile application. Because the study population is defined by clinical suspicion or diagnosis of ocular motility abnormality rather than confirmed disease at enrollment, some participants may be clinically judged to have no abnormality on formal evaluation; such subjects remain part of the study population and are not considered healthy volunteers. AI-derived quantitative eye movement metrics (corneal center displacement in millimeters and angular deviation) will be compared with rater-derived measurements obtained from the same videos using a calibrated reference approach, and with clinician-assessed 9-gaze grading. The investigational device is used solely for video acquisition and analysis and does not influence clinical decision-making.

This observational study aims to evaluate the performance of a software-based medical device, Glandy HYPER, in detecting the thyrotoxic state in patients with hyperthyroidism. The device utilizes heart rate data collected from commercially available wearable devices and compares it with thyroid function test results. The study will enroll patients diagnosed with Graves' disease, monitoring their heart rate during sleep and correlating these measurements with free T4 levels obtained through serial blood testing. No investigational device output will be disclosed to participants, and the study will not alter standard clinical care.