AIDANET for Type 1 Diabetes

(MiniNET Trial)

Overseen By Sara Prince, RN

Age: 18 - 65

Sex: Any

Trial Phase: Academic

Sponsor: Marc Breton

Must be taking: Insulin

Must not be taking: SGLT-2 inhibitors, Steroids

Disqualifiers: Seizure disorder, Heart condition, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 3

What You Need to Know Before You Apply

What is the purpose of this trial?

This trial tests a new system called AIDANET (Automated Insulin Delivery as Adaptive NETwork), designed to help adults with type 1 diabetes better manage their insulin levels. The study examines whether this system is safe and easy to use in a fully automated way. Participants will use the AIDANET system both at home and in a supervised setting. This trial suits those who have had type 1 diabetes for at least a year, use an insulin pump, and a Dexcom G6 or G7 continuous glucose monitor. As an unphased trial, it offers a unique opportunity to contribute to innovative diabetes management solutions.

Do I have to stop taking my current medications for the trial?

The trial protocol does not specify if you must stop taking your current medications. However, you cannot start any new non-insulin glucose-lowering agents during the trial, and you cannot use SGLT-2 or SGLT-1/2 inhibitors. If you are on a stable dose of a non-insulin glucose-lowering agent, you may continue it.

What prior data suggests that the AIDANET system is safe for adults with type 1 diabetes?

Research has shown that automated insulin delivery (AID) systems, such as AIDANET, are generally safe for people with type 1 diabetes. Studies have demonstrated that these systems effectively manage blood sugar levels without causing major problems. For instance, a review found that AID systems improve blood sugar control and are safe to use.

The AIDANET system employs smart technology to automatically adjust insulin doses, eliminating the need for users to announce meals. This feature aims to simplify life for users while ensuring their safety.

Although specific safety data for AIDANET may not be available, AID systems overall have a strong safety record, making them a promising option for managing type 1 diabetes. ^{1 2 3 4 5}

Why are researchers excited about this trial?

Researchers are excited about the AIDANET system for Type 1 Diabetes because it offers a novel approach to managing blood sugar levels. Unlike traditional insulin therapy with manual monitoring, AIDANET integrates advanced technology to automate insulin delivery, potentially improving convenience and precision. This system allows users to transition seamlessly between their home and controlled settings, providing flexibility while maintaining consistent treatment. The potential to enhance quality of life by reducing the burden of constant monitoring and adjustment makes AIDANET a promising advancement in diabetes care.

What evidence suggests that the AIDANET system is effective for type 1 diabetes?

Research has shown that automated insulin delivery systems, such as AIDANET, can help people with diabetes manage their blood sugar levels. In this trial, participants will experience both usual care and the AIDANET system. Studies indicate that systems like AIDANET increase the time blood sugar remains within the healthy range of 70-180 mg/dl. This is crucial because maintaining this range helps prevent diabetes-related health issues. Other trials have found a reduction in hemoglobin A1c levels, indicating better long-term blood sugar control. These findings suggest that AIDANET could effectively manage type 1 diabetes by automatically adjusting insulin based on real-time blood sugar readings. ^{2 4 6 7 8}

Who Is on the Research Team?

Sue Brown, MD

Principal Investigator

University of Virginia Center for Diabetes Technology

Are You a Good Fit for This Trial?

This trial is for adults with type 1 diabetes interested in a new automated insulin delivery system. Specific eligibility criteria are not provided, but typically participants must meet certain health standards and may be excluded based on factors that could impact the study or their safety.

Inclusion Criteria

I have been using an insulin pump for at least three months.

Willingness not to start any new non-insulin glucose-lowering agent during the trial

Proficient in reading and writing English

Exclusion Criteria

Participation in another interventional trial at enrollment

I have had a severe low blood sugar episode with seizure or unconsciousness in the past year.

I have a history of adrenal insufficiency.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

1 week

Control Period

Participants complete a 7 days/6 nights at-home usual care period using their personal equipment

1 week

Remote monitoring

AIDANET System Use

Participants use the AIDANET system during a 3 days/2 nights hotel admission and continue at home for 7 days/6 nights

10 days

3 days/2 nights in-person, 7 days/6 nights remote

Follow-up

Participants are monitored for safety and effectiveness after treatment

1 week

What Are the Treatments Tested in This Trial?

Interventions

• AIDANET

Trial Overview The trial is testing AIDANET, an Automated Insulin Delivery as Adaptive NETwork system in a smaller network version. It's designed to manage insulin levels automatically and will be compared using a crossover method where participants switch between treatments.

How Is the Trial Designed?

Group I: Usual Care→AIDANET Active Control 1 Intervention

Participants will complete 7 days/6 nights at home usual care period using their personal equipment. Participants will then use the AIDANET system during a 3 days/2 nights hotel admission. Participants will continue to use the AIDANET system at home for 7 days/6 nights.

Group II: AIDANET→Usual Care Active Control 1 Intervention

Participants will use AIDANET system during a 3 days/2 nights hotel admission. Participants will continue to use the AIDANET system at home for 7 days/6 nights and then will complete 7 days/6 nights at home usual care period using their personal equipment.

Who Is Running the Clinical Trial?

Marc Breton

Lead Sponsor

Trials

6

Recruited

200+

Tandem Diabetes Care, Inc.

Industry Sponsor

Trials

43

Recruited

5,800+

DexCom, Inc.

Industry Sponsor

Trials

151

Recruited

35,700+

Kevin Sayer

DexCom, Inc.

Chief Executive Officer since 2015

Bachelor’s and Master’s degrees in Accounting and Information Systems from Brigham Young University

Dr. Shelly Lane

DexCom, Inc.

Chief Medical Officer since 2023

MD from University of California, San Diego

Published Research Related to This Trial

The study developed a model predictive control (MPC) algorithm for an automated insulin delivery system that significantly improves blood glucose control in Type 1 diabetes by incorporating an insulin on board (IOB) safety constraint.

Simulations showed that using the IOB constraint reduced the risk of hypoglycemic events from 50% to 10%, highlighting its importance in ensuring both safety and efficacy in insulin therapy.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Safety constraints in an artificial pancreatic beta cell: an implementation of model predictive control with insulin on board. Ellingsen, C., Dassau, E., Zisser, H., et al.[2021]

The use of the AndroidAPS automated insulin delivery system significantly improved glycemic control in young children with type 1 diabetes, with time in range increasing and HbA1c levels decreasing after switching from a sensor-augmented pump.

No severe hypoglycemia or diabetic ketoacidosis (DKA) events were reported during the use of AndroidAPS, indicating a safe profile, along with reported improvements in quality of life for users.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Pre-school and school-aged children benefit from the switch from a sensor-augmented pump to an AndroidAPS hybrid closed loop: A retrospective analysis. Petruzelkova, L., Jiranova, P., Soupal, J., et al.[2022]

Automated insulin delivery systems (AID) have significantly improved the management of Type 1 diabetes (T1D) by reducing the daily burden and risk of hypoglycemia, although their use is still limited by factors like acceptance and availability.

Intraperitoneal (IP) insulin delivery has shown promise in improving glycemic control without the need for meal announcements, as it mimics natural insulin secretion more closely, and a new control algorithm has been developed to optimize this delivery method in a fully closed-loop system.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

In silico design and validation of a time-varying PID controller for an artificial pancreas with intraperitoneal insulin delivery and glucose sensing. Dalla Libera, A., Toffanin, C., Drecogna, M., et al.[2023]

The multi-level supervision and controller modification (ML-SCM) module enhances the performance of artificial pancreas systems by continuously monitoring and adjusting insulin delivery based on real-time glucose data, leading to safer blood glucose concentration levels.

In a study involving 30 subjects using a metabolic simulator, the AP system with the ML-SCM module demonstrated improved insulin infusion rates and better glucose control compared to systems without this module, indicating its efficacy in managing type 1 diabetes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Multi-level Supervision and Modification of Artificial Pancreas Control System. Feng, J., Hajizadeh, I., Yu, X., et al.[2020]

In a 6-month trial with 168 patients, a closed-loop insulin delivery system significantly increased the percentage of time blood glucose levels were within the target range (70-180 mg/dL) by 11 percentage points compared to a sensor-augmented pump, demonstrating improved glycemic control.

The closed-loop system also resulted in a lower mean glycated hemoglobin level and reduced time spent with low blood glucose levels, with no serious hypoglycemic events reported, indicating a safe and effective option for managing type 1 diabetes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes. Brown, SA., Kovatchev, BP., Raghinaru, D., et al.[2022]

Hybrid closed-loop insulin delivery systems, known as artificial pancreas (AP), significantly improve glucose control in children and adolescents with type 1 diabetes, increasing the time spent in the target glucose range without raising the risk of hypoglycemia.

Despite the effectiveness of these systems for overnight glycemic control, daytime management remains challenging, highlighting the need for careful meal planning and bolusing, as fully automated systems are still under investigation.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Artificial Pancreas Technology Offers Hope for Childhood Diabetes. Schoelwer, MJ., DeBoer, MD.[2022]

Automated insulin delivery systems, or 'artificial pancreas' systems, are significantly improving the management of type 1 diabetes by automatically adjusting insulin delivery based on real-time glucose levels.

Clinical trials and real-world evidence show that these systems not only enhance glycemic control but also provide psychosocial benefits for users, indicating a positive impact on overall quality of life.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

The changing landscape of automated insulin delivery in the management of type 1 diabetes. Lakshman, R., Boughton, C., Hovorka, R.[2023]

The Diabeloop Generation 1 (DBLG1) hybrid closed-loop artificial pancreas system significantly improved glycemic control in 25 patients with type 1 diabetes over 6 months, reducing HbA1c from 7.9% to 7.1% (P < 0.001) and increasing time in range (TIR) from 53% to 69.7% (P < 0.0001).

The system was safe to use, with no serious adverse events reported, and it also reduced the time spent in hypoglycemia (TIR <70 mg/dL decreased from 2.4% to 1.3%, P = 0.03).

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Diabeloop DBLG1 Closed-Loop System Enables Patients With Type 1 Diabetes to Significantly Improve Their Glycemic Control in Real-Life Situations Without Serious Adverse Events: 6-Month Follow-up. Amadou, C., Franc, S., Benhamou, PY., et al.[2021]

A fully automated multihormone artificial pancreas, which combines insulin and pramlintide, showed comparable glycemic control to an insulin-only system in adults with type 1 diabetes, achieving similar time in target glucose range (81% vs 83%).

The iterative enhancements to the system, including adjustments to dosing algorithms and meal detection, indicate that while the multihormone approach can maintain glycemic control, further optimization is needed before proceeding to larger randomized controlled trials.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Fully Automated Artificial Pancreas for Adults With Type 1 Diabetes Using Multiple Hormones: Exploratory Experiments. Majdpour, D., Tsoukas, MA., Yale, JF., et al.[2022]

The Artificial Endocrine Pancreas (AEP) uses advanced technology to automatically regulate insulin delivery in people with Type 1 Diabetes Mellitus, aiming to mimic the natural insulin secretion of a healthy pancreas.

The H(infinity) control algorithm effectively manages insulin infusion rates during various metabolic conditions, such as hyperglycemia and exercise, demonstrating good performance in maintaining stable blood glucose levels and reducing the risk of glycemic disturbances.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Theoretical blood glucose control in hyper- and hypoglycemic and exercise scenarios by means of an H(infinity) algorithm. Quiroz, G., Femat, R.[2013]

Citations

1. clinicaltrials.gov clinicaltrials.gov/study/NCT07039617

Study Details | NCT07039617 | AIDANET At Home Study A randomized cross-over trial assessing glycemic control on Automated insulin delivery as Adaptive Network (AIDANET) algorithm when used in three modes: ...

2. pmc.ncbi.nlm.nih.gov pmc.ncbi.nlm.nih.gov/articles/PMC12017971/

Efficacy of automated insulin delivery systems in people with ... The results showed that AID systems were beneficial to varying degrees with respect to the percentage of time in the range of 70–180 mg/dl and ...

3. datascience.virginia.edu datascience.virginia.edu/news/new-uva-clinical-trial-explores-ai-powered-insulin-delivery-better-diabetes-care

New UVA Clinical Trial Explores AI-Powered Insulin Delivery ... A new clinical trial at UVA is aiming to simplify diabetes management by testing an innovative AI-powered device designed to improve automated insulin delivery.

4. jamanetwork.com jamanetwork.com/journals/jamanetworkopen/fullarticle/2830238

Automated Insulin Delivery in Adults With Type 2 Diabetes In this nonrandomized clinical trial including 305 adults with type 2 diabetes, there was a significant decrease in hemoglobin A 1c (HbA 1c ) levels from 8.2% ...

5. endocrinolrespract.org endocrinolrespract.org/Content/files/sayilar/69/ERP_20240618_nlm_new_indd.pdf

Early Stage Effectiveness of the Automated Insulin Delivery ... The 2-week period after AID initiation was divided into 3 periods of 5 days each, and the median values of HbA1c, sensor glucose levels, Q1, Q3, ...

6. diabetesjournals.org diabetesjournals.org/diabetes/article/74/Supplement_1/962-P/159109/962-P-Evaluating-Type-1-Diabetes-T1D-Care-across

962-P: Evaluating Type 1 Diabetes (T1D) Care across All ... The AIDANET system uses an adaptive algorithm that removes the need for meal announcement. This may help address age-specific obstacles in T1D.

7. clinicaltrials.gov clinicaltrials.gov/ct2/show/NCT06728059

Safety and Feasibility of a Machine-Learning Bolus Priming ... This is a research study about the UVA Automated Insulin Delivery System known as Adaptive NETwork (AIDANET). This system consists of a Reinforcement Learning ...

8. sciencedirect.com sciencedirect.com/science/article/pii/S2468451121000520

Review of automated insulin delivery systems for ... Automated insulin delivery (AID) systems have proven safe and effective in improving glycemic outcomes in individuals with type 1 diabetes.