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

UVA 先进自动胰岛素输送系统在幼儿临床护理中的应用：血糖控制、监管接受和日常使用优化

• 批准号: 10265602
• 负责人: MARC D BRETON
• 金额: $ 143.74万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-17 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10265602
• 关键词: 6 year old; Acute; Adolescent; Adult; Affect; Age; Algorithms; American; Artificial Pancreas; Autoimmune Diseases; Caregivers; Caring; Cellular Phone; Charge; Child; Child Welfare; Childhood; Chronic; Clinical; Clinical Trials; Collaborations; Complex; Complications of Diabetes Mellitus; Consensus; Consumption; Data; Day Care; Deterioration; Development; Diabetes Mellitus; Ecosystem; Enrollment; Equilibrium; European; Evaluation; Event; Excess Mortality; Exposure to; FDA approved; Family; Family dynamics; Focus Groups; Fright; General Population; Generations; Glucose; Glycosylated hemoglobin A; Goals; Guidelines; Hour; Hyperglycemia; Hypoglycemia; Incidence; Insulin; Insulin Infusion Systems; Insulin deficiency; Insulin-Dependent Diabetes Mellitus; Intervention; Life; Measurement; Medical; Metabolic Control; Methods; Mind; Modality; Modernization; Multi-Institutional Clinical Trial; Neurocognitive; Notification; Nursery Schools; Outcome; Parents; Participant; Pathway interactions; Patients; Pattern; Psychometrics; Psychosocial Factor; Pump; Quality of life; Randomized; Randomized Clinical Trials; Regimen; Research; Risk; Safety; Serious Adverse Event; Signal Transduction; Site; Sports; System; Technology; Testing; Time; Translations; United States; United States National Institutes of Health; Universities; Variant; Virginia; Visit; Vulnerable Populations; analog; base; blood glucose regulation; clinical care; clinically significant; design; diabetes distress; diabetes management; diabetes risk; digital treatment; early childhood; expectation; experimental group; follow-up; glucose monitor; glucose sensor; glycemic control; improved; international center; meetings; next generation; novel; peace; pediatric patients; peer; preference; prevent; prototype; psychologic; psychosocial; real time monitoring; remote monitoring; simulation; standard of care; success; usability

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 the child) and Global (Cloud/Real-time remote monitoring, available to parents) components, which in concert provide both optimal glucose control for 2-6 years old children with type 1 diabetes and peace of mind for their families.

2011年，我们提出了人工胰腺（AP）系统是一个数字治疗生态系统，可以