An automated portable system for detecting and treating opioid induced respiratory depression

项目总结 在截至2020年11月的一年里，阿片类药物过量在美国导致近7万人死亡。其中许多 发生在处方阿片类药物的治疗性使用期间，特别是当消费不稳定或在 来自某些职业的工人。尽管纳洛酮对阿片类药物过量有促进作用，但有效的抢救 由于以下几个原因，在阿片类药物治疗期间过量服药的个人仍然非常具有挑战性： (1)患者或其同伙可能很难迅速识别阿片类药物过量的开始； (2)出现呼吸抑制和不可逆转的脑损伤或死亡之间的时间很短； 寻求医疗帮助和干预的短暂时间窗口；以及(3)自助者或旁观者采取的方法 治疗阿片类药物过量可能是不可用的，或者外行个人使用起来很复杂。因此，有一个 对阿片类药物过量的实时检测和自动化治疗的紧急和未得到满足的需求，即使在 阿片类药物的治疗用途。这个U01应用程序的总体目标是开发一种自动便携式 实时检测和治疗阿片类药物过量的系统。研究团队致力于在工程方面取得进展 开发用于实时跟踪多种生理参数和治疗贴片的可穿戴传感器 分别用于纳洛酮的精确透皮给药。拟议的项目将进一步开发可穿戴设备 用于跟踪生理参数(例如呼吸模式、血氧水平和心脏)变化的传感器 速率)，用于实时检测阿片类药物过量。拟议的项目还旨在优化新的声学 用于治疗阿片类药物过量的纳洛酮贴片。通过以下途径建立闭环系统 集成了可穿戴传感器、治疗贴片、由手机驱动的基于机器学习的控制器。 建议的系统将使用PI的实验室开发的阿片类药物过量的小鼠模型进行验证， 并对其进行了改造，以适应在人类患者中的潜在翻译应用。这项研究的最终成果是 构建阿片类药物过量的实时检测和自动化治疗原型系统。

PROJECT SUMMARY Opioid overdoses caused almost 70,000 deaths in the US in the year ending in November 2020. Many of these occur during the therapeutic use of prescription opioids, particularly when consumption is erratic or among workers from certain professions. Despite the promotion of naloxone for opioid overdose, the effective rescue of an individual from an overdose during the therapeutic use of opioids is still very challenging for several reasons: (1) the onset of an opioid overdose may be very difficult for the patient or their associates to rapidly recognize; (2) the time between the onset of respiratory depression and irreversible brain damage or death is brief; leaving a brief time window to seek medical help and intervene; and (3) methods employed by self- or bystanders to treat an opioid overdose may not be available or are complicated for lay individuals to use. Thus, there is an urgent and unmet need for real-time detection and automated treatment of opioid overdose, even during the therapeutic use of opioids. The overall objective of this U01 application is to develop an automated portable system to detect and treat an opioid overdose in real time. The research team pursues engineering advances in developing wearable sensors for real-time tracking of multiple physiological parameters and therapeutic patches for precise transdermal delivery of naloxone, respectively. The proposed project will further develop wearable sensors to track the variation of physiological parameters (e.g., breathing pattern, blood oxygen level, and heart rate) for the real-time detection of an opioid overdose. The proposed project also aims to optimize novel acoustic patches to deliver naloxone for treating an opioid overdose. A closed-loop system will be established through integration of a wearable sensor, a therapeutic patch, a machine learning-based controller driven by a cell phone. The proposed system will be validated using a mouse model of opioid overdose well developed in the PI’s lab, and adapted for the potential translational applications in human patients. The ultimate product of this study is to construct a prototype system for real-time detection and automated treatment of an opioid overdose.