Development of a personalized infusion failure detection algorithm combining tissue counter pressure and blood glucose data for closed-loop diabetes management

开发结合组织反压和血糖数据的个性化输注失败检测算法，用于闭环糖尿病管理

• 批准号: 10296116
• 负责人: John Clark Gray
• 金额: $ 30万
• 依托单位: DIATECH DIABETES, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10296116
• 关键词: 3-Dimensional; Address; Adhesions; Affect; Algorithms; Angiography; Artificial Pancreas; Blood Circulation; Blood Glucose; Bolus Infusion; Cannulas; Caring; Cessation of life; Characteristics; Clinical Data; Collection; Complex; Computer software; Data; Databases; Deposition; Detection; Development; Diabetes Mellitus; Diabetic Ketoacidosis; Diagnostic radiologic examination; Diffusion; Ensure; Equipment; Exercise; Failure; Family suidae; Glucose; Goals; Health; Hospital Costs; Hour; Hyperglycemia; Image; Immobilization; Infection; Infusion Pumps; Infusion procedures; Injury; Insulin; Insulin Infusion Systems; Insulin-Dependent Diabetes Mellitus; Label; Lead; Life; Life Style; Liquid substance; Machine Learning; Measures; Medical Care Costs; Medical Device; Methods; Microfluidics; Miniature Swine; Modeling; Modernization; Monitor; Noise; Patients; Performance; Pharmaceutical Preparations; Phase; Physiology; Prevention; Pump; Quality of life; Recommendation; Reporting; Research; Resistance; Risk; Safety; Skin; Small Business Innovation Research Grant; Source; Specimen; Symptoms; System; Technology; Testing; Time; Tissues; Training; Update; Vision; Work; base; cost; design; diabetes management; diabetic; experience; field study; fluid flow; glucose monitor; glycemic control; improved; in vivo; irritation; machine learning method; novel; pre-clinical; pressure; prevent; prototype; sensor; subcutaneous

PROJECT SUMMARY/ABSTRACT Advances in diabetes care technology over the past several decades, including improvements in continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM), have led to more streamlined treatments and reduced burden for patients with type 1 diabetes (T1D). As the field moves toward increasingly autonomous, closed-loop systems for management of T1D, infusion set failure (ISF) remains a health risk to patients and a barrier to the development of artificial pancreas systems. ISF, the disruption of fluid flow from insulin pump to patient causing loss of glycemic control, affects an estimated 50% of pump wearers, placing them at risk for hyperglycemia and life-threatening complications such as diabetic ketoacidosis. Because modern insulin pumps are not equipped with a mechanism for monitoring infusion performance, patients may not know an ISF has occurred until experiencing symptoms of hyperglycemia. There is no existing technology capable of accurately identifying ISF in real-time, before dysregulation of blood glucose (BG). Diatech Diabetes is addressing this unmet need with SmartFusion, an AI-based platform to monitor infusion performance, immediately alert patients when ISF occurs, and help users infuse confidently and safely. Diatech’s novel algorithm leverages tissue counter pressure (TCP) and CGM data to offer a superior method for ISF detection. The company’s long-term vision is that by detecting ISF in real time, SmartFusion will improve patients’ glycemic control, prevent complications of hyperglycemia, and reduce excess medical costs. Diatech has already collected preliminary data to show that TCP waveforms can feasibly be leveraged to differentiate healthy and malfunctioned infusions. The goal of this Phase I SBIR proposal is to collect increasingly complex and representative preclinical data to train and optimize the TCP-CGM algorithm and demonstrate proof-of-concept that it can accurately detect ISF. Diatech will pursue this goal through the following aims: 1) collect and characterize labeled in vivo TCP and x-ray imaging data of typical and malfunctioned infusions, 2) collect and characterize labeled in vivo TCP and BG/CGM data of failure modes consistent with ISF in immobilized diabetic swine, and 3) collect 3-day TCP and BG/CGM data from ambulatory diabetic swine with failure modes consistent with ISF. Successful completion of the project will result in a novel TCP-CGM algorithm to accurately detect ISF in closed- loop systems. The algorithm will be further optimized through collection and integration of clinical data in Phase II. SmartFusion will ultimately be integrated into insulin pumps and diabetes management platforms to provide real-time ISF detection and personalized recommendations for ISF prevention. Further, by enabling new avenues for control of closed-loop systems, SmartFusion can offer a significant leap forward for implementation of artificial pancreas technology, leading to improved health and quality of life for patients living with T1D.

项目总结/摘要 在过去的几十年里，糖尿病护理技术的进步，包括持续的 皮下胰岛素输注（CSII）和连续葡萄糖监测（CGM），已导致更精简的 1型糖尿病（T1 D）的治疗和减轻负担。随着该领域越来越多地 用于管理T1 D的自主闭环系统，输注管路故障（ISF）仍然是一种健康风险， 病人和人工胰腺系统的发展障碍。ISF，液体流动的中断， 胰岛素泵对患者造成血糖控制丧失，影响估计50%的泵佩戴者， 他们有高血糖症和危及生命的并发症如糖尿病酮症酸中毒的风险。因为现代 胰岛素泵未配备监测输注性能的机制，患者可能不知道 发生ISF，直至出现高血糖症状。没有任何现有技术能够 在血糖（BG）失调之前，实时准确识别ISF。 Diatech Diabetes正在通过SmartFusion解决这一未满足的需求，SmartFusion是一种基于AI的输液监测平台 这款产品具有高性能，在发生ISF时立即提醒患者，并帮助用户放心、安全地进行输液。Diatech's 新算法利用组织反压（TCP）和CGM数据为ISF提供了一种上级方法 侦测该公司的长期愿景是，通过真实的时间检测ISF，SmartFusion将改善患者的 血糖控制，预防高血糖并发症，降低多余的医疗费用。Diatech已经 收集的初步数据表明，TCP波形可以可行地用于区分健康和 输液故障第一阶段SBIR提案的目标是收集日益复杂和 具有代表性的临床前数据，用于训练和优化TCP-CGM算法，并证明概念验证 它能准确地探测到ISF Diatech将通过以下目标实现这一目标：1）收集和 表征典型和故障输注的标记的体内TCP和X射线成像数据，2）收集和 表征固定糖尿病患者中与ISF一致的失效模式的标记体内TCP和BG/CGM数据 猪，以及3）从具有一致失效模式的非卧床糖尿病猪收集3天TCP和BG/CGM数据 与ISF一起。 该项目的成功完成将产生一种新的TCP-CGM算法，可准确检测闭合血管中的ISF。 回路系统该算法将通过阶段中临床数据的收集和整合进一步优化 二. SmartFusion最终将集成到胰岛素泵和糖尿病管理平台中， 实时ISF检测和针对ISF预防的个性化建议。此外，通过使新 作为闭环系统控制的途径，SmartFusion可以为实施提供一个重大的飞跃 人工胰腺技术，改善T1 D患者的健康和生活质量。