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

用于检测和治疗阿片类药物引起的呼吸抑制的自动化便携式系统

• 批准号: 10478481
• 负责人: Feng Guo
• 金额: $ 134.95万
• 依托单位: TRUSTEES OF INDIANA UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2025-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10478481
• 关键词: Acoustics; Address; Anesthesiology; Animal Model; Blood; Brain Death; Brain Injuries; Breathing; Cells; Cellular Phone; Cessation of life; Classification; Clinical Data; Consumption; Data; Depressed mood; Detection; Devices; Dose; Engineering; Exercise; Expert Systems; Failure; Fentanyl; Heart Rate; Human; Individual; Injections; Intervention; Letters; Machine Learning; Medical; Medicine; Methods; Monitor; Morphologic artifacts; Motion; Mus; Naloxone; Needles; Opioid; Outcome; Overdose; Oxygen; Patients; Pattern; Physical activity; Physiological; Real-Time Systems; Research; Respiration; Sleep; System; Therapeutic; Therapeutic Uses; Time; Training; Variant; Ventilatory Depression; awake; base; clinical pain; convolutional neural network; detection platform; digital; dosage; human data; improved; innovation; machine learning algorithm; mouse model; novel; opioid overdose; portability; prescription opioid; prototype; respiratory; sensor; therapeutic opioid; therapeutic patch; translation to humans; translational applications; translational potential; user-friendly; wearable sensor technology

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.

项目摘要 阿片类药物过量在截至2020年11月的一年中造成近70,000人死亡。其中许多 在处方阿片类药物的治疗使用期间发生，尤其是在消费不稳定或之中 来自某些晋升的工人。尽管纳洛酮用于阿片类药物过量，但有效营救 由于多种原因，在治疗使用阿片类药物期间过量使用过量的人仍然受到挑战： （1）阿片类药物过量的发作对于患者或其同事来说可能很难迅速识别； （2）呼吸道抑郁发作与不可逆转的脑损伤或死亡之间的时间是短暂的；离开 一个简短的时间窗口寻求医疗帮助和干预； （3）自我或旁观者采用的方法 治疗阿片类药物过量可能不可用，或者对于外行人来说很复杂。那有一个 即使在 阿片类药物的治疗用途。该U01应用程序的总体目的是开发自动化的便携式 实时检测和治疗阿片类药物过量的系统。研究团队追求工程的进步 开发可穿戴传感器，用于实时跟踪多个物理参数和热斑 分别为纳洛酮的精确透皮递送。拟议的项目将进一步发展 传感器跟踪物理参数的变化（例如呼吸模式，血氧水平和心脏 速率）实时检测阿片类药物过量。拟议的项目还旨在优化新颖的声学 贴片以提供纳洛酮来治疗阿片类药物过量。将通过 可穿戴传感器的集成，治疗补丁，由手机驱动的基于机器学习的控制器。 所提出的系统将使用阿片类药物过量的鼠标模型在PI实验室中开发得很好的鼠标， 并适用于人类患者的潜在翻译应用。这项研究的最终产品是 构建原型系统，用于实时检测和对阿片类药物过量的自动处理。