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Multimodal Glucose Prediction in Type 2 Diabetes

NCT07633171 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 36

Last updated 2026-06-09

No results posted yet for this study

Summary

The primary objective of this research, funded by Samsung Strategic Alliance for Research and Technology, is to develop multi-modal foundation models that integrate Continuous Glucose Monitoring (CGM) data with patient behavior data (food intake, medication, and physical activity) to improve real-time glucose prediction and personalized diabetes management for patients with Type 2 diabetes (T2D), delivered via mobile apps and digital health tools.

Conditions

Interventions

DEVICE

Digital Health Data Collection System

Participants will use a digital health data collection system that includes the Welldoc app, a Samsung smartwatch, and the participant's existing continuous glucose monitor. The system will collect CGM data, smartwatch-derived activity, sleep, and vital sign data, and app-based behavioral information such as meals, physical activity, and medication use. Participants will continue usual diabetes care and will not receive treatment recommendations from the study team. Data will be used to develop and validate glucose prediction models and Artificial Intelligence (AI)-generated research outputs that will be reviewed by the study team and not delivered to participants.

Sponsors & Collaborators

Principal Investigators

  • Nestoras Mathioudakis, MD, MHS · Johns Hopkins University

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-06-15
Primary Completion
2027-01-15
Completion
2027-02-26

Countries

  • United States

Study Locations

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Entities

Diseases
Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07633171 on ClinicalTrials.gov