SCH: INT: Collaborative Research: A Non-Invasive and Wearable Molecular Diagnostic Platform for Remote and Passive Monitoring of Patients at Risk for Sepsis

该项目将设计一个集成的传感和分析框架，以便通过可穿戴诊断平台对有败血症风险的家庭/住院患者进行非侵入性远程监测。脓毒症是住院患者死亡的主要原因，也是美国医院治疗费用最高的疾病之一（每年200亿美元）。早期发现和及时干预是改善这些患者预后的最关键因素，但脓毒症的症状是非特异性的，并且需要进行适当监测的重复血液检查是耗时的，并且以次优速率进行。这些局限性显著降低了早期目标导向治疗的疗效。该项目的核心假设是，通过对汗液的实时分析，可以检测脓毒症并对其严重程度进行分类。在这方面，将开发集成的感测/分析框架以将汗液读数与脓毒症状态相关联。具体而言，研究计划包括：1）设计化学增强的汗液提取界面，2）开发疾病特异性推理模型和汗液分析框架，以及3）评估应用于脓毒症患者的框架。这些努力将集中在患者监护平台的开发上，该平台可以以最小的重新配置针对其他临床和生理应用进行优化。计划中的研究将解决对推进基于汗液的生物传感领域至关重要的基本问题。一个集成的传感技术和分析框架，规范化纵向汗液读数相对于多条件诱导的分泌参数将提供定量的了解汗液分泌过程，并促进我们对这个复杂的和多变量的系统的理解。实现这一目标需要解决多个方面的各种科学瓶颈，包括调制速率下不明显的汗液诱导，纵向/多条件原位传感以及可以解释各种不确定性来源的统计模型的开发和验证。研究人员团队将利用他们在柔性设备制造、生物接口/传感器设计、药理学、汗腺生理学、临床研究和统计建模方面的专业知识来实现拟议目标。通过现场分析汗液乳酸盐作为血液乳酸盐的替代物，使用可穿戴汗液提取/分析设备，该项目可以检测血液中的急剧升高并检测/分类败血症的严重程度。该项目的外展部分将侧重于通过创建一个多元化的、以STEM为动力的社区，促进在高中和本科阶段代表性不足的少数群体参与STEM。此外，该项目的教育部分将把计划的研究活动的结果纳入课程材料。

This project will devise an integrated sensing and analytical framework to enable non-invasive remote monitoring of in-home/in-hospital patients at risk for sepsis with a wearable diagnostic platform. Sepsis is the leading cause of admitted patient mortality and is one of the most expensive conditions ($20 billion per year) treated in U.S. hospitals. Early detection and timely intervention are the most crucial factors in improving the outcome for these patients, but the symptoms of sepsis are nonspecific and the repeated blood tests that are required to appropriately monitor are time-consuming and performed at suboptimal rates. These limitations significantly degrade the efficacy of early goal-directed therapy. The core hypothesis of this project is that through the real-time analysis of sweat, sepsis can be detected and its severity can be classified. In that regard, an integrated sensing/analytical framework will be developed to correlate the sweat readings to the sepsis status. Specifically, the research plan includes: 1) devising a chemically-enhanced sweat extraction interface, 2) developing disease-specific inference models and sweat analysis framework, and 3) evaluating the framework applied to septic patients. These efforts will converge toward the development of a patient monitoring platform, which with minimal reconfiguration, can be optimized toward other clinical and physiological applications. The planned research will address fundamental questions critical to advancing the field of sweat-based biosensing. An integrated sensing technology and analytical framework that normalizes longitudinal sweat readings with respect to multi-conditionally induced secretion parameters will provide quantitative insight into sweat secretion processes and promote our understanding of this complex and multivariate system. Achieving this requires resolving various scientific bottlenecks at multiple fronts spanning from inconspicuous sweat induction at modulated rates, longitudinal/multiconditional in-situ sensing and development and validation of statistical models that can account for the various sources of uncertainty. The team of investigators will capitalize upon their expertise in flexible device fabrication, bio-interface/sensor design, pharmacology, sweat gland physiology, clinical research, and statistical modeling to deliver the proposed objectives. Through in-situ analysis of sweat lactate as a proxy for blood lactate, with a wearable sweat extraction/analysis device, the project can detect the dramatic elevation in blood and detect/classify the severity of sepsis. The outreach component of this project will focus on promoting the STEM participation of underrepresented minorities at high school and undergraduate levels by creating a diverse, STEM-motivated community. Moreover, the educational component of this project will integrate findings from the planned research activities into the course materials.