Clinical trial NCT05386849: Closed Loop Glucose Control in Patients With Type 2 Diabetes
Official title: Demonstration of an Artificial Intelligence Based Closed Loop Glucose Control System as a Therapeutic Modality in Type 2 Diabetic Patients
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Diabetes Mellitus, Type 2
Keywords: Closed Loop Glucose Control
Artificial Pancreas
Artificial Intelligence
Glucose
Intensive Care Unit
Lead sponsor: Ideal Medical Technologies
Sponsor class: INDUSTRY
Collaborators: name: Emory University
First posted: 2022-05-23
Enrollment: 2
Sex: ALL
Minimum age (years): 18
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NA
Intervention model: SINGLE_GROUP
Intervention model description: Early Feasibility Safety Study
Primary purpose: DEVICE_FEASIBILITY

Brief summary: This is a proof of concept safety study of an artificial intelligence based closed loop glucose control system designed for use in the intensive care unit setting.

The type 2 diabetic subjects in this study will have their glucose controlled to a range of 100-140 mg/dL by a novel artificial intelligence based closed loop glucose control system for a period of 24 hours. The subjects will consume three standardized meals during the 24 hour study period.

Detailed description: Tight glucose control in the intensive care unit (ICU) setting is difficult to achieve. The investigators hypothesize that a closed loop glucose control system based on artificial intelligence (AI) will improve upon the glucose control currently achieved by the current open loop manual methods, and that this improved glucose control may improve the outcomes of critically ill patients, including those with COVID-19.

This Earl Feasibility Study will test the ability of a prototype artificial intelligence based closed loop glucose control system named FUSION, to provide safe and effective glucose control in subjects with type 2 diabetes in a clinical research center (CRC) setting. Subjects with type 2 diabetes have been chosen as they are insulin resistant, which makes their insulin resistance profile similar to that of ICU patients. As this is the first in human study of a new medical device, the controlled environment of the CRC is preferable to the less controlled environment of an ICU setting.

The prototype FUSION system to be used in this study will consist to two Dexcom G6 continuous glucose monitors (CGM), the AI-based glucose control software run on an all-in-one medical computer, and two syringe pumps. The prototype system is housed on a medical cart. Based on the average glucose value of the two Dexcom G6 CGM's, and the rules of the FUSION systems AI-based glucose control software, the FUSION system will make rate adjustments every 5-10 minutes to the intravenous infusion rates of short acting insulin (NovoLog) and dextrose (D10NS) under its control, in an attempt to keep the subjects glucose in the range of 100-140 mg/dL. The FUSION system only requires entry of the subjects study identification number and weight in kilograms to initiate the system.

For safety reasons, the subjects will have their blood glucose independently measured every 10-60 minutes on a YSI 2900 glucose analyzer and the point of care Nova StatStrip system, throughout the 24 hour study period.

The study has halting criteria to avoid recurrent instances of severe hypoglycemia (\< 54 mg/dL).

The average of the two CGM's, that is used by the FUSION system for glucose control, will be used for statistical analysis. In addition, both the average glucose value used by the FUSION system and each individual CGM system will be compared to the YSI glucose analyzer for correlation between systems using the Surveillance Error grid.

Eligibility criteria: Inclusion Criteria:

1. Are 18-70 years of age, inclusive.
2. Can understand and sign an informed consent, communicate with the investigator, and understand and comply with the protocol requirements.
3. Have had a diagnosis of type 2 diabetes for a period of at least 3 months.
4. Use insulin injections at home for glucose control.
5. Have a hemoglobin A1c (HbA1c) in the range of 7.0 - 10.0%.
6. Have a hemoglobin in the normal range for sex:

   1. Females: 12-15.5 grams/dL.
   2. Males: 13.5-17.5 grams/dl.
7. Have adequate venous access sites in upper extremities.
8. Body weight between 40 - 150 kg.

Exclusion Criteria:

1. Have participated in an interventional medical, surgical, or pharmaceutical study within 30 days of screening.
2. Have a known hypersensitivity to any of the components of study treatment.
3. Have skin disease/injury at Dexcom G6 CGM insertion site(s) that would prevent insertion of the CGM.
4. Currently abuses drugs or alcohol or has a history of abuse that in the investigator's opinion would cause the individual to be noncompliant.
5. Have a medical condition that in the opinion of the investigator could affect study participation and/or personal well-being.
6. Have a clinically significant history or presence of any of the following conditions:

   1. Hepatic failure or has alanine aminotransferase (ALT) greater than 3 times the upper limit of normal.
   2. Has an estimated GFR \<30 ml/min/1.73 m2 or End Stage Kidney Disease on renal replacement therapy.
   3. Have congestive heart failure greater than class 1 on the NYHA classification system.
   4. Have a history of seizures.
   5. Have a history of cerebrovascular accident.
   6. Have a history of ischemic heart disease.
7. For female subjects of potential childbearing age (age 18 to 55) they will be excluded if:

   1. Pregnant.
   2. Refuse to agree to a pregnancy test at the time of enrollment.
   3. Have a positive urine pregnancy test at the time of enrollment.
8. Have a positive COVID-19 test within 14 days of visit 3.
9. Have any COVID-19 related symptoms in the 14-day period prior to visit 3.
10. Have a known unprotected COVID-19 exposure in the 14-day period prior to visit 3.

Primary outcomes:
measure: Primary Safety Outcome
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
measure: Primary Efficacy Outcome
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
Secondary outcomes:
measure: Severe hypoglycemia
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
measure: Hyperglycemia
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
measure: Glucose dispersion
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
measure: Time in desired control range
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
Other outcomes:
measure: Average glucose value used by FUSION system versus from blood
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
measure: Glucose readings from CGM's versus from blood
timeFrame: From beginning of use of the FUSION system to end of use of the FUSION system, which will be a period of time of up to 24 hours
Locations:
city: Atlanta
country: United States
facility: Emory University
state: Georgia
Study officials:
affiliation: Ideal Medical Technologies
name: Leon DeJournett, MD
role: STUDY_DIRECTOR
affiliation: Emory University
name: Francisco Pasquel, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: DeJournett L, DeJournett J. In Silico Testing of an Artificial-Intelligence-Based Artificial Pancreas Designed for Use in the Intensive Care Unit Setting. J Diabetes Sci Technol. 2016 Nov 1;10(6):1360-1371. doi: 10.1177/1932296816653967. Print 2016 Nov.
citation: DeJournett J, DeJournett L. Comparative Simulation Study of Glucose Control Methods Designed for Use in the Intensive Care Unit Setting via a Novel Controller Scoring Metric. J Diabetes Sci Technol. 2017 Nov;11(6):1207-1217. doi: 10.1177/1932296817711297. Epub 2017 Jun 22.
citation: DeJournett J, Nekludov M, DeJournett L, Wallin M. Performance of a closed-loop glucose control system, comprising a continuous glucose monitoring system and an AI-based controller in swine during severe hypo- and hyperglycemic provocations. J Clin Monit Comput. 2021 Apr;35(2):317-325. doi: 10.1007/s10877-020-00474-2. Epub 2020 Jan 31.
citation: DeJournett L. Essential elements of the native glucoregulatory system, which, if appreciated, may help improve the function of glucose controllers in the intensive care unit setting. J Diabetes Sci Technol. 2010 Jan 1;4(1):190-8. doi: 10.1177/193229681000400124.
citation: Sardu C, D'Onofrio N, Balestrieri ML, Barbieri M, Rizzo MR, Messina V, Maggi P, Coppola N, Paolisso G, Marfella R. Outcomes in Patients With Hyperglycemia Affected by COVID-19: Can We Do More on Glycemic Control? Diabetes Care. 2020 Jul;43(7):1408-1415. doi: 10.2337/dc20-0723. Epub 2020 May 19.