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.

项目概要/摘要 过去几十年糖尿病护理技术的进步，包括持续改进 皮下胰岛素输注 (CSII) 和连续血糖监测 (CGM) 已导致更加简化 治疗并减轻 1 型糖尿病 (T1D) 患者的负担。随着该领域越来越走向 用于管理 T1D 的自主闭环系统，输液器故障 (ISF) 仍然是一个健康风险 患者和人工胰腺系统发展的障碍。 ISF，流体流动中断 向患者泵胰岛素会导致血糖失控，影响估计 50% 的泵佩戴者， 他们面临高血糖和糖尿病酮症酸中毒等危及生命的并发症的风险。因为现代 胰岛素泵没有配备监测输注性能的机制，患者可能不知道 出现 ISF 直至出现高血糖症状。现有技术尚无能力 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 是一个基于人工智能的输液监测平台 性能，当 ISF 发生时立即提醒患者，帮助用户自信、安全地输液。迪亚泰克的 新颖的算法利用组织反压 (TCP) 和 CGM 数据为 ISF 提供卓越的方法 检测。该公司的长期愿景是，通过实时检测 ISF，SmartFusion 将改善患者的健康状况 控制血糖，预防高血糖并发症，减少多余的医疗费用。迪亚泰克已经 收集的初步数据表明 TCP 波形可以切实用于区分健康和 输液故障。第一阶段 SBIR 提案的目标是收集日益复杂和 用于训练和优化 TCP-CGM 算法并演示概念验证的代表性临床前数据 它可以准确地检测ISF。 Diatech 将通过以下目标来实现这一目标：1) 收集和 表征典型和故障输注的标记体内 TCP 和 X 射线成像数据，2) 收集和 表征与固定糖尿病患者 ISF 一致的失效模式标记体内 TCP 和 BG/CGM 数据 猪，以及 3) 从动态糖尿病猪那里收集 3 天的 TCP 和 BG/CGM 数据，其故障模式一致 与国际安全基金会。 该项目的成功完成将产生一种新颖的 TCP-CGM 算法，可以在封闭环境中准确检测 ISF。 循环系统。算法将通过阶段性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，以提供 实时 ISF 检测和 ISF 预防的个性化建议。此外，通过启用新的 SmartFusion 可以为闭环系统的控制提供重大飞跃 人工胰腺技术，改善 T1D 患者的健康和生活质量。