# Translation of the UVA Advanced Automated Insulin Delivery Systems to Clinical Care in Young Children: Glycemic Control, Regulatory Acceptance and Optimization of Day to Day Use

> **NIH NIH U01** · UNIVERSITY OF VIRGINIA · 2021 · $1,437,367

## Abstract

In 2011 we put forward the idea that Artificial Pancreas (AP) systems is a digital treatment ecosystem that can
offer different treatment modalities tailored to patient/families' preferences and signal availability. After extensive
testing around the world, our CLC algorithm and AP components were implemented in commercial systems
(Dexcom, formerly TypeZero, InControl and Tandem t:slim X2 with ControlIQ) available to patients since the end
of 2019 following more than 30 clinical trials and 1.2 million hours of use. We propose now, in collaboration with
Tandem Diabetes Care and Dexcom, to introduce the next generation of algorithm technology insulin pump, and
continuous glucose sensors. Making the system smaller, easy to use, and with a user interface perfectly suitable
for children 2-6 years old and their parents/caregivers. At this point we can confirm that reliable technology has
been developed and sufficient data have been accumulated to warrant a large-scale study aiming to establish
this new state-of-the-art technology as a clinically accepted treatment for children (2-6 years old) with type 1
diabetes (T1D) and their families. We propose a large-scale multi-center clinical trial at 3 research sites around
the United States that will enroll 102 2-6 years old children with T1D and at least 1 of their parents/caregivers,
to use the system for 3 months in a 2:1 randomized, control parallel study comparing AP vs. Standard of Care
(SoC). In addition, the study will conclude with a 3-month extension in which the SoC group will transition to use
AP and the experimental group will continue with more relaxing follow up visits. All study sites are pediatric
centers with extensive expertise in clinical trials in children and AP track record. We will show:
(1) that glycemic control achieved by CLC will be superior to SoC therapy in terms of: (i) Reduced incidence of
hypoglycemia without deterioration in HbA1c; (ii) Improved time within the target ranges of 70-180 mg/dl during
the day and 70-140 mg/dl overnight; (iii) Improved HbA1c without increased risk of hypoglycemia, notably for
those with HbA1c 7.5% at the baseline, and (iv) Reduced extreme glycemic events below 54 mg/dl and above
300 mg/dl, and fewer episodes of severe hypoglycemia, episodes of DKA, or other serious adverse events.
(2) and that use of AP with real-time monitoring and cloud features will reduce diabetes distress and will result
in: (i) Reduced fear of hypoglycemia, in both parent and child and better quality of life among parents/caregivers
and children as compared to SoC; (ii) System acceptance and positive evaluation of the AP user interface and
of the real-time remote monitoring/automated notification system; the latter will be particularly useful for parents
when children are at pre-school/day care, and (iii) System reliability and usability meeting regulatory acceptance
criteria.
We therefore expect to test and validate an AP system that includes interacting Local (AP, near th...

## Key facts

- **NIH application ID:** 10265602
- **Project number:** 5U01DK127551-02
- **Recipient organization:** UNIVERSITY OF VIRGINIA
- **Principal Investigator:** MARC D BRETON
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $1,437,367
- **Award type:** 5
- **Project period:** 2020-09-17 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10265602

## Citation

> US National Institutes of Health, RePORTER application 10265602, Translation of the UVA Advanced Automated Insulin Delivery Systems to Clinical Care in Young Children: Glycemic Control, Regulatory Acceptance and Optimization of Day to Day Use (5U01DK127551-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10265602. Licensed CC0.

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