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 在截至2020年11月的一年中，阿片类药物过量在美国造成近7万人死亡。许多这些 发生在处方类阿片的治疗使用过程中，特别是当消费不稳定或 某些职业的工人。尽管促进纳洛酮用于阿片类药物过量， 由于以下几个原因，治疗性使用类阿片期间过量用药的个体仍然非常具有挑战性： (1)阿片类药物过量的发作可能很难让患者或其相关人员迅速识别; (2)从呼吸抑制发作到不可逆转的脑损伤或死亡之间的时间很短;离开 寻求医疗帮助和干预的短暂时间窗口;（3）自我或旁观者采用的方法， 治疗阿片类药物过量对于外行人使用可能是不可用的或复杂的。因此， 对阿片类药物过量的实时检测和自动治疗的迫切和未满足的需求，即使在 阿片类药物的治疗用途。本U 01应用程序的总体目标是开发一种自动便携式 系统来检测和治疗阿片类药物过量在真实的时间。研究团队追求工程进步， 开发可穿戴传感器，用于实时跟踪多个生理参数和治疗贴片 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 跟踪生理参数变化的传感器（例如，呼吸模式、血氧水平和心脏 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 用于递送纳洛酮以治疗阿片类药物过量的贴剂。将通过以下方式建立闭环系统： 可穿戴传感器、治疗贴片、手机驱动的基于机器学习的控制器的集成。 将使用PI实验室中开发的阿片类药物过量小鼠模型对拟议的系统进行验证， 并适于在人类患者中的潜在翻译应用。这项研究的最终成果是 构建一个原型系统，用于实时检测和自动治疗阿片类药物过量。