NCT07533604

Brief 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. 1.Intervention Arm 1: SnapD application + Real-time CGM + Diabetes Self-Management Education and Support (DSMES)
  2. 2.Intervention Arm 2: SnapD application standalone + DSMES
  3. 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.

Trial Health

77
On Track

Trial Health Score

Automated assessment based on enrollment pace, timeline, and geographic reach

Enrollment
45

participants targeted

Target at P25-P50 for not_applicable

Timeline
4mo left

Started Jan 2026

Shorter than P25 for not_applicable

Geographic Reach
1 country

1 active site

Status
recruiting

Health score is calculated from publicly available data and should be used for screening purposes only.

Trial Relationships

Click on a node to explore related trials.

Study Timeline

Key milestones and dates

Study Progress39%
Jan 2026Sep 2026

Study Start

First participant enrolled

January 20, 2026

Completed
1 month until next milestone

First Submitted

Initial submission to the registry

February 26, 2026

Completed
2 months until next milestone

First Posted

Study publicly available on registry

April 16, 2026

Completed
3 months until next milestone

Primary Completion

Last participant's last visit for primary outcome

July 1, 2026

Expected
2 months until next milestone

Study Completion

Last participant's last visit for all outcomes

September 1, 2026

Last Updated

April 16, 2026

Status Verified

April 1, 2026

Enrollment Period

5 months

First QC Date

February 26, 2026

Last Update Submit

April 9, 2026

Conditions

Keywords

AI-powered Thai food analysisContinuous Glucose MonitoringGlycemic ControlObesity

Outcome Measures

Primary Outcomes (1)

  • To evaluate the efficacy of two intervention arms on glycemic control

    HbA1c level(%)

    baseline, 8 weeks

Secondary Outcomes (8)

  • To assess changes in other glycemic parameter

    baseline, 8 weeks

  • To assess changes in anthropometric measurements

    baseline, 8 weeks

  • To evaluate changes in metabolic parameters

    baseline, 8 weeks

  • To evaluate changes in diabetic self-management activities via questionnaire

    Baseline, 8 weeks

  • • To evaluate user satisfaction scores for the SnapD application

    8 weeks

  • +3 more secondary outcomes

Study Arms (3)

SnapD + CGM

EXPERIMENTAL

Use of the AI-powered SnapD application to log meals (at least 2 times/day) combined with a 15-day real-time CGM session. Participants also receive one session of Diabetes Self-Management Education and Support (DSMES).

Device: SnapDDevice: Linx CGMOther: Diabetes Self-Management Education (DSMES)

SnapD Application only

EXPERIMENTAL

Use of the SnapD application as a standalone digital food diary to log meals (at least 2 times/day) throughout the 8-week study. Participants receive one session of DSMES.

Device: SnapDOther: Diabetes Self-Management Education (DSMES)

Standard Care (DSMES)

PLACEBO COMPARATOR

Standard of care including one session of DSMES (20-30 minutes) and self-directed behavioral changes.

Other: Diabetes Self-Management Education (DSMES)

Interventions

SnapDDEVICE

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.

SnapD + CGMSnapD Application only
Linx CGMDEVICE

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) .

SnapD + CGM

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

SnapD + CGMSnapD Application onlyStandard Care (DSMES)

Eligibility Criteria

Age18 Years - 65 Years
Sexall
Healthy VolunteersNo
Age GroupsAdult (18-64), Older Adult (65+)

You may qualify if:

  • 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

You may not qualify if:

  • 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.

Contact the study team to confirm eligibility.

Sponsors & Collaborators

Study Sites (1)

Department of Medicine, Ramathibodi Hospital,

Bangkok, Bangkok, 10400, Thailand

RECRUITING

MeSH Terms

Conditions

Obesity

Condition Hierarchy (Ancestors)

OverweightOvernutritionNutrition DisordersNutritional and Metabolic DiseasesBody WeightSigns and SymptomsPathological Conditions, Signs and Symptoms

Study Officials

  • Supasuta Wongdama

    Ramathibodi Hospital

    PRINCIPAL INVESTIGATOR

Central Study Contacts

Supasuta Wongdama, MD

CONTACT

Study Design

Study Type
interventional
Phase
not applicable
Allocation
RANDOMIZED
Masking
NONE
Masking Details
This is an open-label study. Blinding of participants and investigators is not feasible due to the distinct procedural nature of the assigned interventions (e.g., the visible use of a wearable CGM device and a specific mobile application). However, to minimize bias in the assignment, allocation concealment is ensured by using sequentially numbered, opaque, sealed envelopes prepared by a non-investigator.
Purpose
TREATMENT
Intervention Model
PARALLEL
Model Details: This is a randomized, open-label, parallel-group, superiority pilot study designed with a 1:1:1 allocation ratio. The study compares two digital intervention arms against a standard of care control group over an 8-week period. Arm 1 (SnapD + CGM): Participants use the SnapD AI-powered application for food logging combined with a 15-day session of real-time Continuous Glucose Monitoring (CGM). Arm 2 (SnapD only): Participants use the SnapD application as a standalone digital food diary. Control Arm: Participants receive standard Diabetes Self-Management Education and Support (DSMES) only. The randomization uses a permuted variable block size design to ensure balanced allocation. Allocation concealment is maintained using sequentially numbered, opaque, sealed envelopes. The study aims to evaluate the feasibility and preliminary efficacy of these tools in patients with type 2 diabetes and overweight or obesity.
Sponsor Type
OTHER
Responsible Party
PRINCIPAL INVESTIGATOR
PI Title
Principal investigator

Study Record Dates

First Submitted

February 26, 2026

First Posted

April 16, 2026

Study Start

January 20, 2026

Primary Completion (Estimated)

July 1, 2026

Study Completion (Estimated)

September 1, 2026

Last Updated

April 16, 2026

Record last verified: 2026-04

Data Sharing

IPD Sharing
Will not share

Locations