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NCT Number: NCT07533604

SnapDandCGMinType2Diabetes

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.

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Key information

Conditions

Type2 Diabetes Mellitus Body Weight Nutrition Disorders Nutritional and Metabolic Diseases Obesity Overnutrition Overweight Pathological Conditions, Signs and Symptoms Signs and Symptoms

Age range

18 year–65 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Department of Medicine, Ramathibodi Hospital,

Bangkok, 10400, Thailand

Location status: Recruiting

Location contact

Supasuta Wongdama, Doctor of Medicine

CONTACT

[email protected]

+6690-575-4190

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Aged 18 to 65 years, male or female at birth
  • Diagnosed with type 2 Diabetes Mellitus with overweight or obesity (BMI>23 kg/m²)
  • Hemoglobin A1c (HbA1c) 6.5-9% measured within 3 months prior to the screening date
  • Willing to maintain their current antidiabetic medication regimen without dose adjustment for the entire 8-week study duration
  • Must possess an internet-enabled devices e.g. smartphone, tablet compatible with the SnapD application
  • Able and willing to adhere intervention, including using snapD and CGM

Exclusion criteria

  • Currently pregnant, plan pregnancy or breastfeeding during the 8-week study period
  • Current participation in another interventional clinical trial
  • Current use of insulin or incretin-based therapies (e.g., GLP-1 Receptor Agonists, GIP/GLP-1 Receptor Agonists)
  • Presence of severe hearing or visual impairment that, in the investigator's judgment, would preclude the participant from safely and effectively using the SnapD application or the CGM device
  • known contraindication to CGM usage e.g., a history of severe hypersensitivity to the device's materials or adhesive, planing to go on CT-contrasted imaging etc.

Treatment and study plan

SnapD

Device

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.

Linx CGM

Device

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) .

Diabetes Self-Management Education (DSMES)

Other

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

Primary outcomes

  1. To evaluate the efficacy of two intervention arms on glycemic control

    Time frame: baseline, 8 weeks

    HbA1c level(%)

Secondary outcomes

  1. To assess changes in other glycemic parameter

    Time frame: baseline, 8 weeks

    Fasting plasma glucose(mg/dL)

  2. To assess changes in anthropometric measurements

    Time frame: baseline, 8 weeks

    Body Mass Index(Kg/m2)

  3. To evaluate changes in metabolic parameters

    Time frame: baseline, 8 weeks

    • change in systolic and diastolic blood pressure (mmHg)

  4. To evaluate changes in diabetic self-management activities via questionnaire

    Time frame: Baseline, 8 weeks

    A modified version of the SDSCA tool, developed by Rattanaporn Jeerawattana, encompassing domains of diet, exercise, self-monitoring, foot care, and medication. The total score ranges from 0 to 133, where higher scores indicate better diabetes self-care activities.

  5. • To evaluate user satisfaction scores for the SnapD application

    Time frame: 8 weeks

    Name of the questionnaire is User satisfaction with the SnapD and CGM application. It was an a self-developed questionnaire validated by experts. The total score ranges from 7 to 35, where higher scores indicate better user satisfaction.

  6. • To assess adverse events about glycemic control

    Time frame: up to 8 weeks

    • Incidence of hypoglycemia and/or hyperglycemia

  7. To assess changes in anthropometric measurements

    Time frame: baseline, 8 weeks

    change in waist circumference(cm)

  8. Change in metabolic parameters

    Time frame: baseline, 8 weeks

    change in lipid profile including serum Total Cholesterol, Triglyceride-Cholesterol, HDL-Cholesterol, LDL-Cholesterol

Study contacts

Contact information is provided by the study sponsor or research team.

Supasuta Wongdama, MD

CONTACT

[email protected]

+6690-575-4190

Sponsors and collaborators

Lead sponsor

Ramathibodi Hospital

Other

Registry information

Official 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

Acronym: SnapD in T2DM

Important dates

Study start
2026
Primary completion
2026
Study completion
2026
First posted
Apr 16, 2026
Registry last updated
Apr 16, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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