Wednesday, April 2, 2025
4/2/2025
An automated portable system for detecting and treating opioid induced respiratory depression - 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.
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