Translating Biometric Data Into Blood Glucose Levels

NCT04946188 | Completed

• 1 other identifier: 2020-02-099
• Study Type: interventional
• Target: 14
• Locations: 1 country
• Sites: 1

Brief Summary

This study is designed to assist with the development of a first, truly non-invasive technology for blood glucose monitoring, which will have the potential to eliminate the need for painful finger pricking or expensive continuous blood glucose monitor use. The purpose of this study is to collect biometric data, such as bioimpedance (how well the body impedes electric current flow), from participants who are living with type 2 diabetes. A proof-of-concept prototype (non-invasive continuous glucose monitor; NI-CGM) will be used to collect this biometric data. The data will then be used to develop and refine a computer model that can be used to predict blood glucose levels (BGLs). Individuals with diabetes experience a great range of blood BGLs throughout their daily life and activities, therefore it is essential to gather biometric data corresponding to this large range to build a computer model, to ensure model reliability.

Conditions

Diabetes Type 2

Keywords

Non-invasive; Blood Glucose Levels; Monitoring

Outcome Measures

Primary Outcomes (2)

• Generation of a predictive models for determining blood glucose levels

  Performance of computer models for blood glucose level estimation using collected bioimpedance spectroscopy data.

  at 14 days post introduction of intervention

• Validation of predictive model for determining blood glucose levels

  Performance of predictive models will be evaluated using the consensus error grid. Mean Absolute Relative Difference (MARD) and Consensus Error Grid (CEG) distribution.

  at 14 days post introduction of intervention

Study Arms (1)

Opuz NICGM

EXPERIMENTAL

Participants will be provided with one non-invasive, custom-built prototype device (study device), which they will use throughout their day-to-day life/activities over the study period.

Device: Opuz NICGM

Interventions

Opuz NICGM DEVICE

A wearable and non-invasive prototype device that allows for measurement of bioimpedance data with the aim to help develop a mathematical model to predict blood glucose levels.

Also known as: Opuz Device, Opuz Ring

Opuz NICGM

Eligibility Criteria

• Age: 18 Years - 70 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Aged 18 - 70 years
• Physician diagnosis of Type 2 diabetes
• Haemoglobin A1c (HbA1c) range between 7 - 10%
• Body mass index between 20 - 40
• Regularly eats 3 meals per day (breakfast, lunch, and dinner)
• Technologically literate (e.g. able to use Apps, smart phones)
• Able to commit to attending the Sponsor site
• Able to commit to wearing a non-invasive, custom-built device through most daily activities
• Currently self-monitoring their BGL and able to commit to taking measurements at least 6 times per day
• Proficiency in reading and writing in English

You may not qualify if:

• Currently on insulin therapy (other than long-acting insulin therapy)
• Currently pregnant, pregnant in the last 6 months, or planning a pregnancy
• Currently breastfeeding
• Current smoker
• Any other confounding major disease or condition as deemed appropriate by investigator, determined by review of medical history and/or patient reported medical history
• Clinically unstable or rapidly progressing diabetic retinopathy, neuropathy, and/or frequent nausea, bloating or vomiting, sever gastroesophageal reflux, or early satiety.
• Currently on active curative treatments for cancer
• Currently receiving systemic glucocorticoid therapy
• Using lipid-lowering medication at a dose that has not been stable for the past 3 months
• History of reactions to alcohol wipes, antiseptics, or adhesives (isobornyl acrylate which is the adhesive used for attachment of Freestyle Libre sensors and may cause contact dermatitis)
• Using an insulin pump
• Pacemaker fitted
• Fasting C-peptide levels below 0.5 ng/mL or above 2.0 ng/mL
• Has had an episode of diabetic ketoacidosis in the past 6 months
• Has had an episode of severe hypoglycemia within the past 6 months

Sponsors & Collaborators

• Scimita Operations Pty Ltd.: lead

Study Sites (1)

Scimita Operations

Sydney, New South Wales, 2044, Australia

Location

Related Publications (9)

• Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, Malanda B. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018 Apr;138:271-281. doi: 10.1016/j.diabres.2018.02.023. Epub 2018 Feb 26.

  PMID: 29496507 BACKGROUND

• Villena Gonzales W, Mobashsher AT, Abbosh A. The Progress of Glucose Monitoring-A Review of Invasive to Minimally and Non-Invasive Techniques, Devices and Sensors. Sensors (Basel). 2019 Feb 15;19(4):800. doi: 10.3390/s19040800.

  PMID: 30781431 BACKGROUND

• D. K. Kamat, D. Bagul, and P. M. Patil, "Blood Glucose Measurement Using Bioimpedance Technique," Adv. Electron., vol. 2014, pp. 1-5, 2014, doi: 10.1155/2014/406257

  BACKGROUND

• Tura A. Noninvasive glycaemia monitoring: background, traditional findings, and novelties in the recent clinical trials. Curr Opin Clin Nutr Metab Care. 2008 Sep;11(5):607-12. doi: 10.1097/MCO.0b013e328309ec3a.

  PMID: 18685457 BACKGROUND

• P. Daarani & A.Kavithamani, "Blood glucose level monitoring by noninvasive method using near infra red sensor," Int. J. Latest Trends Eng. Technol., vol. IRES, no. 1, 2017, doi: 10.21172/1.ires.19

  BACKGROUND

• N. D. Nanayakkara, S. C. Munasingha, and G. P. Ruwanpathirana, "Non-invasive blood glucose monitoring using a hybrid technique," in MERCon 2018 - 4th International Multidisciplinary Moratuwa Engineering Research Conference, pp. 7-12, 2018, doi: 10.1109/MERCon.2018.8421885

  BACKGROUND

• Ding S, Schumacher M. Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review. Sensors (Basel). 2016 Apr 23;16(4):589. doi: 10.3390/s16040589.

  PMID: 27120602 BACKGROUND

• Valensi P, Extramiana F, Lange C, Cailleau M, Haggui A, Maison Blanche P, Tichet J, Balkau B; DESIR Study Group. Influence of blood glucose on heart rate and cardiac autonomic function. The DESIR study. Diabet Med. 2011 Apr;28(4):440-9. doi: 10.1111/j.1464-5491.2010.03222.x.

  PMID: 21204961 BACKGROUND

• Mueller M, Talary MS, Falco L, De Feo O, Stahel WA, Caduff A. Data processing for noninvasive continuous glucose monitoring with a multisensor device. J Diabetes Sci Technol. 2011 May 1;5(3):694-702. doi: 10.1177/193229681100500324.

  PMID: 21722585 BACKGROUND

Related Links

• World Health Organisation. (2018, Oct. 30). Diabetes

MeSH Terms

Conditions

Diabetes Mellitus, Type 2

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Study Officials

• Thomas Telfer, PhD (Med)

  Scimita Operations

  PRINCIPAL INVESTIGATOR

• Farid Sanai, PhD (Med)

  Scimita Operations

  STUDY CHAIR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: OTHER
• Intervention Model: SINGLE GROUP
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 22, 2021
• First Posted: June 30, 2021
• Study Start: July 21, 2020
• Primary Completion: December 14, 2020
• Study Completion: December 14, 2020
• Last Updated: July 22, 2021

Record last verified: 2021-07

Data Sharing

• IPD Sharing: Will share
• Time Frame: De-identified data is expected to be available after study completion and following publication of results, with no determined end date.
• Access Criteria: Data obtained from this study will be made available after approval from PI Dr Thomas Telfer. Scimita ventures t.telfer@scimitaventures.com +61 481848190

Locations

AU (1)