Feasibility Evaluation of an Artificial Pancreas With Glucose Prediction Trust Index

NCT03092310 | Completed FDA Device

• 1 other identifier: Pro00020556
• Study Type: interventional
• Target: 15
• Locations: 1 country
• Sites: 1

Brief Summary

The purpose of this pilot study is to establish that closed-loop insulin delivery with a target enchanted model predictive control (eMPC)/Health Monitoring System (HMS) algorithms with a trust index of the predicted glucose value is safe and effective, to analyze and learn to improve upon the accuracy of the predicted glucose values, and to collect efficacy data to inform a future larger study.

Conditions

Type 1 Diabetes Mellitus

Keywords

Artificial Pancreas

Outcome Measures

Primary Outcomes (1)

• Percent time within the target glucose range of 70-180 mg/dl overall as assessed by continuous glucose monitoring (CGM).

  The primary endpoint for this pilot study will be time within the target glucose range of 70-180 mg/dl overall as assessed by continuous glucose monitoring (CGM), during closed-loop use, determining if the combination of eMPC and the assessment of trust index can provide safe and effective glucose control.

  48 hours

Secondary Outcomes (11)

• Assessment of the trust index predictions vs. standard eMPC glucose predictions.

  48 hours

• Frequency of hypoglycemia during closed-loop use.

  48 hours

• Frequency of hyperglycemia during closed-loop use.

  48 hours

• Percent time within the target glucose range of 70-140 mg/dl during closed-loop use.

  48 hours

• Percent time glucose is within range 70-150 mg/dl postprandial within 5 hours following meals, during closed-loop use.

  48 hours

Study Arms (1)

Artificial Pancreas

EXPERIMENTAL

The artificial pancreas device will employ its enhanced Model Predictive Control (MPC) algorithm with a target glucose level of 110 mg/dL with a trust index for MPC-predicted glucose values, weighing future glucose predictions and only acting on predictions with higher weight in the trust index. The Health Monitoring System algorithm uses the same CGM data as the MPC control algorithm but utilizes a separate algorithm for trending and predictions of future glucose values. Using a redundant and independent algorithm is an important safety feature of the overall AP device.

Device: Artificial Pancreas Device

Interventions

Artificial Pancreas Device DEVICE

Artificial Pancreas Device

Artificial Pancreas

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Age ≥ 18 and ≤ 75 years at the time of screening.
• Clinical diagnosis of type 1 diabetes for at least one year.
• Has been using an insulin pump for at least 6 months at the time of screening.
• HbA1c \< 10%, as performed by point of care or central laboratory testing. A1c will be assessed at the screening visit, or if already completed within 2 months of the screening visit, the prior lab value may be used in lieu of repeating this assessment.
• Serum creatinine of \< 2.0 mg/dL. Serum creatinine will be assessed at the screening visit, or if already completed within 2 months of the screening visit, the prior lab value may be used in lieu of repeating this assessment.
• Bolus for all meals and snacks that contain ≥ 5 grams of carbohydrate.
• Willing to perform at least 7 fingerstick blood glucose tests a day.
• Willing to refrain from taking acetaminophen products for the duration of the clinical trial. If acetaminophen is taken, subject is to avoid making any insulin dosing decisions based on CGM for at least 12 hours.
• Willing to abide by the study protocol and use study-provided devices, including the Omnipod, Dexcom CGM, glucometer, ketone meter and pAPS tablet.

You may not qualify if:

• Pregnancy
• One or more episodes of hypoglycemia requiring an emergency room visit or hospitalization in the past 6 months.
• One or more episodes of hyperglycemia requiring an emergency room visit or hospitalization in the past 6 months.
• Known unstable cardiac disease or untreated cardiac disease, as revealed by history or physical examination.
• Dermatological conditions that would preclude wearing a CGM sensor or Pod.
• One or more seizures in the past year.
• Screening A1c ≥ 10% or serum creatinine ≥ 2.0 mg/dL.
• Any condition that could interfere with participating in the trial, based on investigator judgment.
• Concurrent use of any non-insulin glucose-lowering agent (including GLP-1 agonists, Symlin, DPP-4 inhibitors, SGLT-2 inhibitors, biguanides, sulfonylureas and naturaceuticals), defined as using any of these medications within 30 days of the screening visit or during the study.
• Participation in another pharmaceutical or device trial at the time of enrollment or during the study.

Sponsors & Collaborators

• Sansum Diabetes Research Institute: lead
• Harvard University: collaborator

Study Sites (1)

William Sansum Diabetes Center

Santa Barbara, California, 93105, United States

Location

Related Publications (1)

• Pinsker JE, Laguna Sanz AJ, Lee JB, Church MM, Andre C, Lindsey LE, Doyle FJ 3rd, Dassau E. Evaluation of an Artificial Pancreas with Enhanced Model Predictive Control and a Glucose Prediction Trust Index with Unannounced Exercise. Diabetes Technol Ther. 2018 Jul;20(7):455-464. doi: 10.1089/dia.2018.0031.

  PMID: 29958023 RESULT

MeSH Terms

Conditions

Diabetes Mellitus, Type 1

Interventions

Pancreas, Artificial

Condition Hierarchy (Ancestors)

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

Intervention Hierarchy (Ancestors)

Artificial Organs; Surgical Equipment; Equipment and Supplies

Study Officials

• Jordan E Pinsker, MD

  Sansum Diabetes Research Institute

  PRINCIPAL INVESTIGATOR

• Eyal Dassau, PhD

  Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University

  PRINCIPAL INVESTIGATOR

• Francis J Doyle III, PhD

  Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University

  PRINCIPAL INVESTIGATOR

• Alejandro Leguna, PhD

  Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Research Physician

Study Record Dates

• First Submitted: March 15, 2017
• First Posted: March 27, 2017
• Study Start: March 20, 2017
• Primary Completion: December 20, 2017
• Study Completion: December 20, 2017
• Last Updated: July 12, 2018

Record last verified: 2018-07

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)