NCT07533604

SnapDandCGMinType2Diabetes

The Effectiveness of an AI-powered Thai Food Analysis (SnapD) and Continuous Glucose Monitoring on Glycemic Control in Patients With Type 2 Diabetes and Overweight or Obesity: A Randomized Controlled Pilot Study

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 45 (estimated)
• Sponsor: Ramathibodi Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 65 Years
• Healthy volunteers: Not accepted

Summary

Study Title: The Effectiveness of an AI-powered Thai food analysis (SnapD) and Continuous Glucose Monitoring on Glycemic Control in Patients with Type 2 Diabetes and Overweight or Obesity: A Randomized Controlled Pilot Study Rationale: Effective dietary management is the cornerstone of treating Type 2 Diabetes (T2DM) and obesity. However, traditional manual food logging is often inaccurate and burdensome. While digital tools and Continuous Glucose Monitoring (CGM) have shown promise internationally, there is a lack of validated AI-powered tools specifically designed for Thai cuisine. This study introduces SnapD, an AI-powered platform (utilizing Gemini 2.5 Flash) designed to recognize Thai food, estimate nutritional values, and integrate with CGM data to provide personalized feedback. The primary goal of this pilot study is to evaluate the efficacy of the SnapD application, both as a standalone tool and in combination with CGM, compared to Standard of Care in improving glycemic control (HbA1c) over 8 weeks. Additionally, the study aims to assess the feasibility, participant adherence, and safety of these digital interventions to inform a future, fully powered randomized controlled trial. Study Design: This is an 8-week, randomized, open-label, parallel-group, superiority pilot study with a 1:1:1 allocation ratio. A total of 45 participants will be enrolled and assigned to one of three arms: 1. Intervention Arm 1: SnapD application + Real-time CGM + Diabetes Self-Management Education and Support (DSMES) 2. Intervention Arm 2: SnapD application standalone + DSMES 3. Control Arm: DSMES alone Inclusion Criteria Highlights: Adults (18-65 years) diagnosed with T2D with BMI \> 23 kg/m² (overweight/obesity) with HbA1c between 6.5% and 9.0% with Must possess a compatible smartphone/tablet Procedures: Baseline (Visit 1): All participants receive 20-30 minutes of DSMES. Intervention groups receive training on SnapD. Arm 1 receives a 15-day CGM sensor.During Study: Intervention arms log meals via SnapD (at least twice daily). Nutritionists conduct bi-weekly follow-up calls to address technical issues and provide support. End-of-Study (Week 8): Assessment of HbA1c, body weight, waist circumference, lipid profile, and patient-reported outcomes (self-care activities and user satisfaction) Primary Outcome: Mean change in HbA1c from baseline to 8 weeks Secondary Outcomes: Changes in Fasting Plasma Glucose (FPG), body weight, waist circumference, and lipid profiles, Diabetes self-management scores (SDSCA questionnaire), User satisfaction with the SnapD application, Incidence of adverse events (hypoglycemia/hyperglycemia). Significance: This study will provide preliminary evidence on the synergistic benefits of AI-driven nutritional feedback and CGM in a Thai-specific context, supporting the development of scalable, culturally adapted digital health technologies for diabetes management.

Conditions

• Type2 Diabetes Mellitus

Interventions

Type	Name	Description
DEVICE	SnapD	SnapD, developed by the Division of Endocrinology and Metabolism, Department of Medicine, Ramathibodi Hospital, is a Progressive Web App. It is built using React 18.3.1, TypeScript, and Vite for responsive performance on both mobile and desktop platforms. The application utilizes Supabase for database management, which operates on a PostgreSQL backend.
DEVICE	Linx CGM	The Linx CGM system, manufactured by Connect Diagnostics, is a real-time device that measures glucose concentrations in the interstitial fluid. It is an all-in-one device, integrating the glucose sensor, applicator, and transmitter into a single unit. The device has a diameter not exceeding 22 mm and a weight not exceeding 2.2 g. The sensor has a maximum operational life (wear time) of 15 days. It demonstrates a Mean Absolute Relative Difference (MARD) not exceeding 8.67%, which meets the standard accuracy requirement of \<10%. This device was registered as a medical device by the Thai Food and Drug Administration (Thai FDA), Ministry of Public Health, in January 2025, for the indication of management of diabetes in adults age 18 and older (as shown in the attached document) .
OTHER	Diabetes Self-Management Education (DSMES)	Participants will receive 1 single session of DSMES, 20-30 minutes/session. This single session will be delivered at the baseline visit only. All personnel providing DSMES are Certified Dietitians (CD) and/or have passed the Certified Diabetes Educator (Thai CDE) examination

Timeline

• Start date: 2026-01-20
• Primary completion: 2026-07-01
• Completion: 2026-09-01
• First posted: 2026-04-16
• Last updated: 2026-04-16

Locations

1 site across 1 country: Thailand