Mitigating Medication Tampering and Diversion via Real-Time Intravenous Opioid Quantification

Tyler Hack;Joel Bisarra;Saeromi Chung;Shekher Kummari;Drew A. Hall
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Abstract

Opioid tampering and diversion pose a serious problem for hospital patients with potentially life-threatening consequences. The ongoing opioid crisis has resulted in medications used for pain management and anesthesia, such as fentanyl and morphine, being stolen, substituted with a different substance, and abused. This work aims to mitigate tampering and diversion through analytical verification of the administered drug before it enters the patient. We present an electrochemical-based sensor and miniaturized wireless potentiostat that enable real-time intravenous (IV) monitoring of opioids, specifically fentanyl and morphine. The proposed system is connected to an IV drip system during surgery or post-operation recovery. Measurement results of two opioids are presented, including calibration curves and data on the sensor performance concerning pH, temperature, interference, reproducibility, and long-term stability. Finally, we demonstrate real-time fluidic measurements connected to a flow cell to simulate IV administration and a blind study classified using a machine-learning algorithm. The system achieves limits of detection (LODs) of 1.26 µg/mL and 2.75 µg/mL for fentanyl and morphine, respectively, while operating with >1-month battery lifetime due to an optimized ultra-low power 36 µA sleep mode.
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通过实时静脉注射阿片类药物定量减少药物篡改和转用。
阿片类药物的篡改和转移给医院病人带来了严重的问题,其后果可能危及生命。持续的阿片类药物危机已导致芬太尼和吗啡等用于止痛和麻醉的药物被盗、被其他药物替代以及被滥用。这项工作旨在通过在药物进入病人体内之前对给药进行分析验证,减少篡改和转移。我们提出了一种基于电化学的传感器和微型无线恒电位仪,可对阿片类药物(尤其是芬太尼和吗啡)进行实时静脉注射(IV)监测。该系统可在手术或术后恢复期间连接到静脉点滴系统。我们展示了两种阿片类药物的测量结果,包括校准曲线以及传感器在 pH 值、温度、干扰、再现性和长期稳定性方面的性能数据。最后,我们演示了与流动池相连的实时流体测量,以模拟静脉注射,并使用机器学习算法对盲法研究进行分类。该系统对芬太尼和吗啡的检测限(LOD)分别为 1.26 μg/mL 和 2.75 μg/mL,同时由于采用了优化的 36 μA 超低功耗睡眠模式,电池寿命大于 1 个月。
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