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.

项目摘要/摘要 过去几十年糖尿病护理技术的进步，包括持续不断的改进 皮下胰岛素输注(CSII)和持续血糖监测(CGM)导致了更流线型的 治疗和减轻1型糖尿病(T1D)患者的负担。随着该领域越来越多地 用于管理T1D、输液器故障(ISF)的自主闭环系统仍对 患者和人工胰腺系统发展的障碍。ISF，流体流动的中断 胰岛素泵给患者造成血糖控制丧失，估计影响50%的泵佩戴者，放置 他们有患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液性能的机制，患者可能不知道 在出现高血糖症状之前，一直会发生ISF。没有现有的技术能够 在血糖(BG)失调之前，实时准确识别ISF。 Diatech糖尿病公司正在通过SmartFusion解决这一未得到满足的需求，SmartFusion是一个基于人工智能的监测输液的平台 性能，当ISF发生时立即提醒患者，并帮助用户自信和安全地输液。Diatech‘s 新的算法利用组织反压力(TCP)和CGM数据为ISF提供了一种更好的方法 侦测。该公司的长期愿景是，通过实时检测ISF，SmartFusion将改善患者的 控制血糖，预防高血糖并发症，降低超额医疗费用。Diatech已经 收集的初步数据表明，可以可行地利用TCP波形来区分健康和 错误的输液。这项第一阶段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，以训练和优化TCP-CGM算法并演示概念验证 它可以准确地检测到ISF。Diatech将通过以下目标实现这一目标：1)收集和 表征典型和故障输液的标记体内TCP和X-射线成像数据，2)收集和 固定式糖尿病患者中与ISF一致的失效模式的体内标记的TCP和BG/CGM数据的特征 3)从故障模式一致的动态糖尿病猪采集3天的TCP和BG/CGM数据 与ISF合作。 该项目的成功完成将导致一种新的TCP-CGM算法，以准确地检测封闭的 循环系统。该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，提供 实时ISF检测和针对ISF预防的个性化建议。此外，通过启用新的 作为控制闭环系统的途径，SmartFusion可以实现重大飞跃 人工胰腺技术的发展，改善了T1D患者的健康和生活质量。