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Analysis of over 250 novel synthetic opioids and xylazine by LC–MS-MS in blood and urine

尿 色谱法 分析物 法医毒理学 化学 医学 内科学
作者
Katie Diekhans,Jihau Yu,Megan Farley,Luke N. Rodda
出处
期刊:Journal of Analytical Toxicology [Oxford University Press]
卷期号:48 (3): 150-164 被引量:5
标识
DOI:10.1093/jat/bkae009
摘要

Abstract Novel Synthetic Opioids (NSO) are frequently found in postmortem (PM) and human performance (HP) forensic toxicology casework, resulting in impairment and fatal overdoses. Developing a broad NSO method benefits public health, as it can be used to identify trends in potent opioid use to develop risk management programs. This project aimed to design a comprehensive, rapid and routine method for the selective analysis of over 250 novel synthetic opioids in blood and urine. This method rapidly extracted 150 µL of blood or urine via protein precipitation followed by size-exclusion filtration, evaporation and reconstitution. Separation and data acquisition were achieved on a 12 min LC–MS-MS method using an F5 column. Data processing was expedited with a custom built-in query created in-house that automated processing and enhanced quality assurance. Validation according to ASB/ANSI Standard 036 was performed and applicability of the method was assessed using proficiency test and authentic casework samples. Assessed in blood and urine qualitatively were 261 unique analytes including fentanyl analogs (fentalogs), nitazenes and other miscellaneous synthetic opioids. As 59 isomeric target analytes were placed into groups due to co-elution, there were 202 distinct acquired targets or target - groups. To demonstrate applicability, 27 proficiency test blood samples received over an approximate 4-year period were analyzed with 126 expected results assessed comprising 25 unique target analytes. Additionally, 617 fatal accidental overdoses within San Francisco in 2022 were retroactively analyzed by this method with almost 10% of cases containing a new NSO substance(s). Such trends and NSO substances were previously unknown in this community.

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