Testing a non-invasive smartphone application to predict sugar levels in the blood
| ISRCTN | ISRCTN15977623 |
|---|---|
| DOI | https://doi.org/10.1186/ISRCTN15977623 |
| ClinicalTrials.gov (NCT) | Nil known |
| Clinical Trials Information System (CTIS) | Nil known |
| Integrated Research Application System (IRAS) | 296787 |
| Protocol serial number | BIOAPP1010, IRAS 296787 |
| Sponsor | Bioepic Ltd |
| Funder | Bioepic Ltd |
- Submission date
- 31/05/2022
- Registration date
- 27/06/2022
- Last edited
- 20/06/2022
- Recruitment status
- No longer recruiting
- Overall study status
- Completed
- Condition category
- Nutritional, Metabolic, Endocrine
Plain English summary of protocol
Background and study aims
The key to managing and living well with diabetes involves early diagnosis and monitoring of glucose (blood sugar) control. Traditional self-monitoring of blood glucose (SMBG) via finger-prick testing can help patients to maintain their glucose levels within the appropriate range. However, we know each SMBG test requires a single-use test strip and lancet, conferring a significant economic burden on healthcare systems and patients. Additionally, the discomfort of SMBG can result in reduced compliance with monitoring. A non-invasive glucose monitoring device (NIGMD) has the potential to achieve efficiency savings and can reduce physical and psychological barriers to testing. The Bioepic Glucose Monitoring System is a NIGDM that utilises a video trace of blood flow in the user’s fingertip (recorded by a smartphone camera) to quantify certain aspects of the user’s pulse and uses artificial intelligence (AI) to predict the blood glucose level. This AI has been trained using SMBG measurements from individuals with and without diabetes.
Who can participate?
Adults with type 2 diabetes
What does the study involve?
The purpose of this study is to test the AI-predicted blood glucose level derived from the Bioepic system in individuals with non-insulin-treated Type 2 Diabetes and compare the readings with those from SMBG. The Bioepic system glucose reading is recorded via a pre-downloaded App on a smartphone, by placing a fingertip over the smartphone camera lens for 30 seconds. An SMBG reading is also recorded to create a ‘matched pair’. Participants will not have access to the glucose value recorded by the App. The study would be undertaken in two parts. One part would involve participants recording matched pairs at home over a 30-day period. The other part of the study would involve participants taking matched pair samples at a study site before and after a set carbohydrate meal. These matched pairs will be compared to assess the accuracy of the Bioepic system against accepted standards.
What are the possible benefits and risks of participating?
The study benefits are that this is a non-invasive method to measure glucose levels
There are no known risks to participants
Where is the study run from?
Southern Diabetes Medical Services
When is the study starting and how long is it expected to run for?
August 2020 to December 2022
Who is funding the study?
Bioepic Ltd (UK)
Who is the main contact?
Dr Richard Wood (scientific)
richard@ennehealth.com
Contact information
Scientific
Bioepic Ltd
8 Wye Street
Hereford
HR2 7RB
United Kingdom
| Phone | +44 (0)1544 318 411 |
|---|---|
| richard@ennehealth.com |
Study information
| Primary study design | Observational |
|---|---|
| Study design | Observational methodological comparison study |
| Secondary study design | Observational methodological comparison study |
| Study type | Participant information sheet |
| Scientific title | Intermediate type 2 diabetes trial |
| Study acronym | IT2DT |
| Study objectives | The aim of this study is to compare the predicted blood glucose levels derived from the Bioepic non-invasive Smartphone application compared with the glucose values measured using a blood glucometer from the blood drawn from a finger prick test. This aim will test the hypothesis that the percentage of individual glucose values measured by the Bioepic Smartphone Application compared with capillary glucometer readings falling within zones A and B of the Consensus error grid will meet the minimum criteria for acceptable system accuracy |
| Ethics approval(s) | Approved 23/07/2021, South West - Frenchay Research Ethics Committee (Ground Floor, Temple Quay House, 2 The Square, Bristol, BS1 6PN, United Kingdom; +44 (0)207 104 8379; frenchay.rec@hra.nhs.uk), ref: 1/SW/0030 |
| Health condition(s) or problem(s) studied | Type 2 diabetes |
| Intervention | The Bioepic system is a non-invasive technology that is designed to predict blood glucose levels, using artificial intelligence, from a 30-second fingertip video recorded by the camera of a smartphone with Bioepic’s proprietary App. The aim of this study is to compare the blood glucose levels derived from the Bioepic App with the glucose values measured by a standard blood glucometer via a finger-prick test to demonstrate the accuracy of the Bioepic system. |
| Intervention type | Device |
| Phase | Not Applicable |
| Drug / device / biological / vaccine name(s) | |
| Primary outcome measure(s) |
Estimated blood glucose levels measured using the Bioepic System, a pre-loaded smartphone App (Enne Health) that characterises an approximation of blood glucose by taking a Photoplethysmography (PPG) video of the fingertip, falling within zones A and B of the Consensus error grid and therefore meeting the minimum criteria for acceptable system accuracy in 100 paired glucose readings taken at home over a 30 day period (3-6 readings per day) plus 6 readings on the active study day, 15 minutes apart. |
| Key secondary outcome measure(s) |
The percentage of predicted glucose levels from the Bioepic App System meeting the minimum criteria for acceptable system accuracy when grouped by certain criteria: |
| Completion date | 31/12/2022 |
Eligibility
| Participant type(s) | Patient |
|---|---|
| Age group | Adult |
| Sex | All |
| Target sample size at registration | 72 |
| Key inclusion criteria | Type 2 diabetes |
| Key exclusion criteria | 1. Body mass index < 18.5 kg/m2 2. Pregnancy or lactating 3. Participation in any clinical study during the previous 2 months 4. Any other condition that in the opinion of the investigator would interfere with the evaluation of the study results or constitute a health risk for the participant 5. Any medication that in the opinion of the investigator would interfere with the evaluation of the study results 6. Recreational or illicit drug intake 7. Individuals who fail to utilise the Smartphone App appropriately 8. Aversion to the sight of blood 9. Severe coronary heart disease 10. Participants with known uncontrolled hypertension (i.e. >160mmHg systolic or >95 mmHg diastolic) 11. Severe renal impairment (eGFR<15ml/min) |
| Date of first enrolment | 20/04/2022 |
| Date of final enrolment | 20/10/2022 |
Locations
Countries of recruitment
- United Kingdom
- England
Study participating centre
Cams Hall Estate
Fareham
PO16 8UY
United Kingdom
Results and Publications
| Individual participant data (IPD) Intention to share | Yes |
|---|---|
| IPD sharing plan summary | Stored in non-publicly available repository |
| IPD sharing plan | Stored in a non-publicly available repository, which is a cloud-based storage platform. The repository stores the neural network-based glucose estimates from pulse plethysmography that are incorporated directly into a diabetes log with paired glucometer readings and also allows the individual to record activities, meals etc., and all other collated data that are stored anonymously. |
Study outputs
| Output type | Details | Date created | Date added | Peer reviewed? | Patient-facing? |
|---|---|---|---|---|---|
| Participant information sheet | Participant information sheet | 11/11/2025 | 11/11/2025 | No | Yes |
Editorial Notes
LH 20/06/2022: Trial's existence confirmed by MHRA.
