Global Sensitivity Analysis enabled Uncertainty Domain Reduction for Euglycemic Control of Type 1 Diabetics

糖尿病的祸害困扰着超过百分之十的美国人口。2017年，糖尿病护理费用估计超过3000亿美元。被诊断为1型糖尿病的人中有5%到10%是1型糖尿病患者，他们不断监测血糖，用胰岛素调节血糖以维持生存。在过去的几十年里，连续葡萄糖监测仪和胰岛素泵有了很大的改进，现在可以部署人工胰腺。该设备旨在模拟健康胰腺的功能，从而减轻糖尿病患者管理疾病的负担。糖尿病患者在身体对胰岛素的反应方面存在巨大的差异，以及对极低血糖的恐惧（这可能是致命的）要求开发强大的控制器来应对这种差异。这项资助支持基础研究，以模拟公认的胰岛素反应特征的日常变化，并合成自动膳食检测算法。这与全面的全球敏感性分析相结合，将使可部署的实时控制器的血糖调节的发展。这项研究的结果将有助于降低数百万糖尿病患者的医疗保健成本，提高患者的生产力，帮助美国经济和社会福祉。为了实现人工胰腺的全部潜力，这项研究将模拟昼夜胰岛素敏感性，包括黎明和黄昏现象，并开发一种膳食检测算法来应对未宣布的膳食，或者纠正公布的膳食中错误计算的碳水化合物。这两个目标将增强现有的葡萄糖-胰岛素模型。然而，所提出的模型的复杂性的增加将负担的不确定参数的维数增加。 这要求开发一个框架，非时刻为基础的全球敏感性指标，排名顺序参数，最有助于预测血糖浓度的不确定性。由此产生的不确定空间的维数降低，将允许准确的不确定性量化，并有助于开发鲁棒控制器，最大限度地提高血糖调节的时间范围内的性能指标。 美国食品和药物管理局批准的用于验证开发的控制器和300名患者数据集的软件将支持研究结果。虽然该研究的直接受益者是1型糖尿病患者，但一旦成熟，该研究也有可能使2型糖尿病患者受益。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The scourge of diabetes afflicts over ten percent of the US population. In 2017, the cost of diabetes care was estimated to be over $300 billion. Five to ten percent of those diagnosed are Type 1 diabetic who constantly monitor their blood glucose to regulate it with insulin for survival. There have been profound improvements over the past few decades in continuous glucose monitors and insulin pumps, which now make it feasible to deploy an artificial pancreas. This device aims to emulate the function of a healthy pancreas and thus reduce the burden of managing the ailment for diabetics. The tremendous variability across diabetics in how the body responds to insulin and the fear of extremely low blood glucose (which can be fatal) mandates the development of robust controllers to account for this variability. This grant supports fundamental research to model well-recognized daily variation in insulin response characteristics and synthesize automated meal detection algorithms. This, in conjunction with comprehensive global sensitivity analysis, will enable the development of deployable real-time controllers for blood-glucose regulation. Results from this research will help reduce the cost of health care for millions of diabetics and improve the patient’s productivity, helping the US economy and well-being of society.To realize the full potential of an artificial pancreas, the research supported by this grant will model diurnal insulin sensitivity, which includes the dawn and dusk phenomena, and develop a meal detection algorithm to respond to unannounced meals, or rectify incorrectly counted carbohydrates in announced meals. These two goals will enhance the existing glucose-insulin models. However, the increased complexity of the proposed model will be burdened with increase in the dimension of the uncertain parameters. This mandates the development of a framework for non-moment based global sensitivity metrics to rank order parameters contributing the most to uncertainty in forecasting blood-glucose concentration. The resulting reduced dimension of the uncertain space will permit accurate uncertainty quantification and aid the development of robust controllers that maximize the time-in-range performance metric for blood-glucose regulation. A Food and Drug Administration approved software for validating the developed controllers and a 300-patient dataset will buttress the research outcomes. Although the immediate beneficiaries of the research are Type 1 diabetics, once matured, the research has the potential to also benefit people with Type 2 diabetes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.