ADAPTIVE MOTIF-BASED CONTROL (AMBC): A FUNDAMENTALLY NEW APPROACH TO AUTOMATED TREATMENT OPTIMIZATION FOR TYPE 1 DIABETES

自适应基序控制 (AMBC)：1 型糖尿病自动优化治疗的全新方法

• 批准号: 10684819
• 负责人: SUE A BROWN
• 金额: $ 68.56万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-17 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684819
• 关键词: Address; Adult; Algorithms; Area Under Curve; Artificial Intelligence; Artificial Pancreas; Cellular Phone; Child; Classification; Clinical; Clinical Trials; Code; Color; Continuous Glucose Monitor; Cross-Over Trials; Crossover Design; Data; Data Science; Databases; Development; Diabetes Mellitus; Enrollment; Europe; European; Exercise; Glucose; Goals; Health; Health Personnel; Hour; Hybrids; Hyperglycemia; Hypoglycemia; Incidence; Individual; Inferior; Injections; Insulin; Insulin Infusion Systems; Insulin-Dependent Diabetes Mellitus; Learning; Libraries; Measures; Medicine; Metabolic; Methods; Modality; Monitor; New England; Non-Insulin-Dependent Diabetes Mellitus; Outcome; Participant; Patient Education; Pattern; Pattern Recognition; Persons; Physical activity; Pilot Projects; Population; Population Database; Process; Proliferating; Property; Protocols documentation; Publishing; Randomized; Recording of previous events; Running; Structure; System; Technology; Testing; Text; Time; advanced system; clinical practice; clinical translation; control trial; data library; data space; deep neural network; design; efficacy evaluation; experience; glycemic control; improved; innovation; new technology; next generation; novel; novel strategies; process optimization; subcutaneous; tool; treatment optimization; trial comparing; trial enrollment; virtual

PROJECT SUMMARY Adaptive Motif-Based Control (AMBC): A Fundamentally New Approach to Automated Treatment Optimization for Type 1 Diabetes Automated Insulin Delivery (AID) has transitioned to the clinical practice and one of the most advanced systems to date –Control-IQ (Tandem, Inc.)– is based on the UVA-AID, developed and tested by our team. Following two pivotal trial in adults and children with type 1 diabetes (T1D), both published in the New England J of Medicine, the system was cleared by the FDA and European regulatory agencies, and is now in use worldwide. With this clinical translation now accomplished, our academic objective is to design and test next-generation AID solutions. The key innovative concept behind the new Adaptive Motif-Based Control (AMBC) class of AID algorithms proposed here, is the ability to learn from a user’s past glycemic-control patterns and from population patterns, and optimize this user’s treatment in real time; thus, unlike any other AID system, the AMBC will utilize both a person’s own history and the history of others, to forecast glycemic changes and adapt AID action accordingly. To achieve its goals, the AMBC will employ: (i) a newly discovered fundamental structure underlying the multitude of possible daily continuous glucose monitoring (CGM) profiles in diabetes, which allows classification of these profiles into a finite number of basic “motifs”, and (ii) a new Adaptation-to-Profile treatment optimization process. To test the AMBC, we propose a pilot study, followed by a randomized cross-over trial enrolling 90 participants with T1D and Control-IQ experience, to compare the UVA-AID (as built in Control-IQ) to 3 treatment modalities: AMBC with meal and exercise announcements; AMBC-A without meal or exercise announcements, i.e. a “full closed-loop,” and an intermediate AMBC-EA which will have meal but no exercise announcement. Participants will be randomized to two groups following different sequences of treatment modalities: UVA-AID-->AMBC- A-->AMBC-EA-->AMBC and AMBC-->AMBC-EA-->AMBC-A-->UVA-AID. Each treatment modality will continue for 5 weeks. This time-tested design enables four crossover comparisons, which will test the following hypotheses: (1) AMBC with meal/exercise announcements will be superior to UVA-AID in terms of time in the range 70- 180mg/dl and reduced incidence of hypoglycemia (measured by CGM), and technology acceptance; (2) AMBC-A without meal/exercise announcements will be non-inferior to UVA-AID in terms of time >180mg/dL during the day, incidence of hypoglycemia during and after exercise, and postprandial glucose variability; (3) Deescalating AMBC-->AMBC-EA-->AMBC-A vs escalating AMBC-A-->AMBC-EA-->AMBC deployment of meal and exercise announcements will have no influence on the outcome within each treatment modality. Overall, we affirm that reliable technology has been developed and sufficient data accumulated to warrant the development of a new class of AID algorithms – AMBC – which is expected to become the first AID system learning from a user’s own historical metabolic patterns and from the patterns of others structured in a new relational data library. We view the AMBC as a paradigm for transition from hybrid to full (no announcements) AID, but do not claim that the AMBC is a full closed-loop system.

项目摘要 自适应基序控制（AMBC）：一种全新的自动化治疗方法 1型糖尿病的治疗 自动胰岛素输注系统（AID）已进入临床实践，是目前最先进的系统之一 迄今为止-Control-IQ（Tandem，Inc.）- 基于我们团队开发和测试的UVA-AID。以下两 在成人和儿童1型糖尿病（T1 D）中进行的关键试验，均发表在新英格兰医学杂志上， 该系统已获得FDA和欧洲监管机构的批准，目前已在全球范围内使用。与此 临床翻译现已完成，我们的学术目标是设计和测试下一代AID解决方案。 新的基于自适应基序的控制（AMBC）类AID算法背后的关键创新概念 这里提出的是从用户过去的血糖控制模式和群体模式中学习的能力， 并在真实的时间内优化该用户的治疗;因此，与任何其他AID系统不同，AMBC将利用 患者自身的病史和其他人的病史，以预测血糖变化并相应地调整AID行动。 为了实现其目标，AMBC将采用：（i）一个新发现的基础结构， 糖尿病患者可能的每日连续葡萄糖监测（CGM）曲线，可对这些 配置文件成有限数量的基本“图案”，以及（ii）一个新的适应配置文件处理优化过程。 为了测试AMBC，我们提出了一个试点研究，然后是一个随机交叉试验，招募了90名参与者 具有T1 D和Control-IQ经验，比较UVA-AID（Control-IQ内置）与3种治疗方式： AMBC-A，不带用餐或锻炼通知，即“全 闭环”，和一个中间的AMBC-EA，将有膳食，但没有运动公告。参与者 将按照不同的治疗方式顺序随机分为两组：UVA-AID->AMBC- A-->AMBC-EA-->AMBC和AMBC-->AMBC-EA-->AMBC-A-->UVA-AID。每种治疗方式将持续 五周。这种经过时间考验的设计可以进行四次交叉比较，这将测试以下假设： (1)在70- 100秒的时间范围内，带有进餐/运动通知的AMBC将优于UVA-AID上级。 180 mg/dl和低血糖发生率降低（通过CGM测量），以及技术接受; (2)在时间> 180 mg/dL方面，不带进餐/运动通知的AMBC-A不劣于UVA-AID 白天，运动期间和运动后低血糖的发生率，以及餐后血糖变异性; (3)降级AMBC-->AMBC-EA-->AMBC-A vs升级AMBC-A-->AMBC-EA-->AMBC部署 膳食和运动通知将不会对每种治疗方式的结果产生影响。 总的来说，我们确认已经开发了可靠的技术，并积累了足够的数据，以保证 开发了一种新的AID算法- AMBC，有望成为第一个AID系统 从用户自己的历史代谢模式和从在新的代谢模式中构造的其他人的模式中学习， 关系数据库我们将AMBC视为从混合型向全面型过渡的典范（无公告） AID，但不要声称AMBC是一个完整的闭环系统。