Department of Laboratory Medicine, University Hospital of Northern Norway, Tromsø, Norway.
Department of Laboratory Medicine, University Hospital of Northern Norway, Tromsø, Norway.
J Pharm Biomed Anal. 2021 Mar 20;196:113936. doi: 10.1016/j.jpba.2021.113936. Epub 2021 Jan 29.
A comprehensive HR-MS screening can be used to identify thousands of drugs from a single analysis, which makes it a valuable tool for broad-scope component-resolved toxicological analysis. However, it is common practice in clinical toxicology to perform restricted data analysis to avoid examining and/or reporting data not requested for examination. In this study, a HR-MS screening workflow was developed to allow a comprehensive toxicological evaluation, but also restricted and levelled data analysis to fit in a clinical setting. Following precipitation and reconstitution, samples were injected on an UHPLC-HR-MS and data were analyzed with the data processing software UNIFI. Analytical validation of 38 selected drugs of abuse (DoA), included determination of matrix effect, recovery, process efficiency, and limit of identification (LOI). The method was tested on 49 authentic samples and matrix-matched ranges of calibrators for 95 drugs. The LOI ranged from 0.3 to 1426.7 ng mL for most analytes which was within expected concentration range for authentic samples with THC-COOH (>1722.0 ng mL) and morphine (1426.7 ng mL) as notable exceptions. Four individual screening workflows were developed: 1) a targeted workflow to serve as orthogonal identification of the 38 selected DOAs from another in-house method, 2) a general toxicology workflow, 3) an extended toxicology workflow including new psychoactive substances (NPS), and 4) a workflow for NPS based on the online HighResNPS library. Our study presents a comprehensive LC-HR-MS toxicology screening method optimized for laboratory medicine. The workflow allows for levelled data reviewing when requested without compromising the ability to perform full toxicological analyses.
一种全面的 HR-MS 筛选可以用于从单一分析中识别数千种药物,这使其成为广泛范围的组分解析毒理学分析的有价值工具。然而,在临床毒理学中,通常进行受限数据分析,以避免检查和/或报告未请求检查的数据。在这项研究中,开发了 HR-MS 筛选工作流程,以允许进行全面的毒理学评估,但也允许进行受限和均衡数据分析,以适应临床环境。沉淀和再溶解后,将样品注入 UHPLC-HR-MS 中,并使用数据处理软件 UNIFI 对数据进行分析。对 38 种选定的滥用药物 (DoA) 进行了分析验证,包括基质效应、回收率、过程效率和鉴定限 (LOI) 的测定。该方法在 49 份真实样品和 95 种药物的基质匹配校准器范围内进行了测试。大多数分析物的 LOI 范围为 0.3 至 1426.7 ng/mL,这在 THC-COOH (>1722.0 ng/mL) 和吗啡 (1426.7 ng/mL) 等真实样品的预期浓度范围内,这两种物质的 LOI 值是例外。开发了四种单独的筛选工作流程:1) 靶向工作流程,用作另一种内部方法中 38 种选定 DOA 的正交鉴定,2) 一般毒理学工作流程,3) 包括新精神活性物质 (NPS) 的扩展毒理学工作流程,4) 基于在线 HighResNPS 库的 NPS 工作流程。我们的研究提出了一种全面的 LC-HR-MS 毒理学筛选方法,针对实验室医学进行了优化。该工作流程允许在请求时进行均衡数据分析,而不会影响进行全面毒理学分析的能力。