MODULAR BIO-BEHAVIORAL CLOSED-LOOP CONTROL OF TYPE 1 DIABETES

1型糖尿病的模块化生物行为闭环控制 项目总结/摘要 从本质上讲，控制血糖的闭环系统（称为人工胰腺）的发展 (BG)糖尿病是一个涉及生理学、行为科学和工程学的跨学科项目。 因此，该项目代表了医生，心理学家， 来自美国、意大利和法国的数学家和工程师致力于了解 1型糖尿病（T1 DM）的个体定制闭环控制的行为和生物先决条件。 提出的研究的主要思想是：为了成功，闭环控制必须适应 个人的生理特征和每个人的行为特征。这种适应的关键是 生物系统（患者）观察和模块化控制。因此，我们建议为模块化奠定基础 系统由患者行为和代谢状态的算法观察器和控制模块组成 负责胰岛素输送和低血糖预防。建立这个系统，我们将利用我们广泛的 在人体代谢的计算机建模和模拟方面的专业知识，以及我们最近的经验 闭环控制研究。该系统的开发和测试将分四个阶段完成： 第1阶段将研究与T1 DM控制相关的行为事件模式。实地研究将记录膳食， 胰岛素注射，运动与持续血糖监测平行，旨在培养学习能力， 算法-行为观察器-将随着时间的推移跟踪一个人的日常生活的关键重复元素。 第2阶段将研究胰岛素敏感性和受损的反调节与BG变异性的关系， 旨在开发算法生理学观察器，其将跟踪葡萄糖变异性的特定参数 和反复发生的低血糖作为一个人的胰岛素敏感性和反调节能力变化的标志。 第3阶段将在现场测试一个咨询系统，为T1 DM患者提供个性化反馈。的 该系统将由行为和生理观察员提供信息，并将包括三个咨询模块： 提前24小时评估低血糖的风险;（ii）建议餐前胰岛素剂量的推注计算器，以及 (iii)基础输注率顾问建议未来24小时的基础输注率曲线。 第4阶段将侧重于自动闭环控制，进行一系列研究（门诊和住院） 依次测试三个控制模块，负责：（i）检测和预防低血糖1-2 提前数小时，（ii）控制餐前胰岛素推注，以及（iii）控制基础速率和过夜稳态。 我们设想，根据患者或医生的选择，每个观察者或咨询/控制模块可以 可以单独使用，也可以在集成的开环或闭环控制系统中使用。模块化方法将允许 逐步测试和部署系统功能，这将构成和促进系统开发。

MODULAR BIO-BEHAVIORAL CLOSED-LOOP CONTROL OF TYPE 1 DIABETES PROJECT SUMMARY / ABSTRACT By nature, the development of a closed-loop system (known as artificial pancreas) controlling blood glucose (BG) in diabetes is an interdisciplinary project involving physiology, behavioral science, and engineering. Consequently, this project represents an interdisciplinary and international effort of physicians, psychologists, mathematicians, and engineers from the United States, Italy, and France dedicated to the understanding of behavioral and biological prerequisites to individually-tailored closed-loop control of type 1 diabetes (T1DM). The principal idea of the proposed research is: in order to be successful, closed-loop control must adapt to individual physiologic characteristics and to the behavioral profile of each person. The keys to this adaptation are biosystem (patient) observation and modular control. Thus, we propose to lay the foundation for a modular system comprised of algorithmic observers of patients' behavior and metabolic state, and control modules responsible for insulin delivery and hypoglycemia prevention. Building this system, we will utilize our extensive expertise with in silico modeling and simulation of the human metabolism, and the experience from our recent closed-loop control studies. The development and testing of this system will be accomplished in four phases: Phase 1 will investigate patterns of behavioral events relevant to T1DM control. A field study will record meals, insulin injections, and exercise in parallel with continuous glucose monitoring, aiming to develop a learning algorithm - behavioral observer - which will track over time key recurrent elements of a person's routine. Phase 2 will investigate relationships of insulin sensitivity and impaired counterregulation with BG variability, aiming to develop algorithmic physiology observers, which will track specific parameters of glucose variability and recurrent hypoglycemia as markers of change in a person's insulin sensitivity and counterregulatory ability. Phase 3 will test in the field an advisory system providing personalized feedback to people with T1DM. The system will be informed by behavioral and physiology observers and will consist of three advisory modules: (i) evaluation of risk for hypoglycemia 24 hours ahead; (ii) bolus calculator suggesting pre-meal insulin doses, and (iii) basal rate advisor suggesting basal rate profiles for the next 24 hours. Phase 4 will focus on automated closed-loop control conducting a series of studies (outpatient & inpatient) testing sequentially three control modules responsible for: (i) detection and prevention of hypoglycemia 1-2 hours ahead, (ii) control of pre-meal insulin boluses, and (iii) control of basal rate and overnight steady state. We envision that, depending on patients' or physicians' choice, each observer or advisory/control module could be used separately, or within integrated open- or closed-loop control systems. A modular approach will permit incremental testing and deployment of system features, which will structure and facilitate system development.