Novel psychoactive substances (NPS) are constantly emerging in the drug market, and synthetic cannabinoids (SCs) are included in this NPS family. Forensic laboratories often struggle with these continually emerging SCs, forcing them to develop an untargeted workflow to incorporate these psychoactive drugs in their procedures. Usually, forensic laboratories select analytical methods based on targeted mass spectrometry (MS) technologies for strictly tracking already known NPS. The appropriate way to tackle unknown substances is to develop pipelines for untargeted analysis that include LC-HRMS analytical methods and data analysis. Once established, this strategy would allow drug testing laboratories to be always one step ahead of the new trends concerning the "designer drugs" market. To address this challenge an untargeted workflow based on mass spectrometry data acquisition and data analysis was developed to detect SCs in oral fluid (OF) samples at a low concentration range. The samples were extracted by mixed-mode solid-phase extraction and analyzed by Liquid Chromatography - High-Resolution Mass Spectrometry (LC-HRMS). Tandem mass spectra (MS2) were recorded performing a variable isolation width across a mass range of all theoretical precursor ions (vDIA) after the chromatographic separation. After raw data processing with the MSDial software, the deconvoluted features were sent to GNPS for Feature-Based Molecular Networking (FBMN) construction for nontargeted data mining. The FBMN analysis created a unique integrated network for most of the SCs assessed in the OF at a low level (20 ng/mL). These results demonstrate the potential of an untargeted approach to detect different derivatives of SCs at trace levels for forensic applications.

中文翻译：

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变量数据独立采集和数据挖掘探索基于特征的分子网络分析，用于非靶向筛选口腔液中的合成大麻素。

新型精神活性物质 (NPS) 不断出现在药品市场中，合成大麻素 (SCs) 也包含在这一 NPS 家族中。法医实验室经常与这些不断出现的 SC 作斗争，迫使他们开发一种非针对性的工作流程，将这些精神活性药物纳入他们的程序。通常，法医实验室选择基于靶向质谱 (MS) 技术的分析方法来严格跟踪已知的 NPS。处理未知物质的适当方法是开发用于非靶向分析的管道，包括 LC-HRMS 分析方法和数据分析。一旦确立，这一战略将使药物检测实验室始终领先于“设计药物”市场的新趋势。为了应对这一挑战，开发了一种基于质谱数据采集和数据分析的非靶向工作流程，以检测低浓度范围内的口腔液 (OF) 样品中的 SCs。通过混合模式固相萃取对样品进行萃取，并通过液相色谱 - 高分辨率质谱 (LC-HRMS) 进行分析。记录串联质谱 (MS2)，在色谱分离后在所有理论前体离子 (vDIA) 的质量范围内执行可变分离宽度。在使用 MSDial 软件处理原始数据后，将去卷积的特征发送到 GNPS 进行基于特征的分子网络 (FBMN) 构建，以进行非目标数据挖掘。FBMN 分析为在 OF 中以低水平 (20 ng/mL) 评估的大多数 SCs 创建了一个独特的集成网络。