Program on Pharmacology, Federal University of Santa Catarina, Campus Universitário, s/n, Sala 208, Bloco E, Prédio Administrativo - Córrego Grande, Florianópolis, SC 88040-900, Brazil.
Department of Pathology, Federal University of Santa Catarina, Rua Engenheiro Agronômico Andrei Cristian Ferreira, s/n - Trindade, Florianópolis, SC 88040-900, Brazil.
J Chromatogr A. 2024 Sep 13;1732:465225. doi: 10.1016/j.chroma.2024.465225. Epub 2024 Aug 2.
Endocannabinoid system, including endocannabinoid neurotransmitters (eCBs), has gained much attention over the last years due to its involvement with the pathophysiology of diseases and the potential use of Cannabis sativa (marijuana). The identification of eCBs and phytocannabinoids in biological samples for forensic, clinical, or therapeutic drug monitoring purposes constitutes a still significant challenge. In this scoping review, the recent advantages, and limitations of the eCBs and phytocannabinoids quantification in biological samples are described. Published studies from 2018-2023 were searched in 8 databases, and after screening and exclusions, the selected 38 articles had their data tabulated, summarized, and analyzed. The main characteristics of the eCBs and phytocannabinoids analyzed and the potential use of each biological sample were described, indicating gaps in the literature that still need to be explored. Well-established and innovative sample preparation protocols, and chromatographic separations, such as GC, HPLC, and UHPLC, are reviewed highlighting their respective advantages, drawbacks, and challenges. Lastly, future approaches, challenges, and tendencies in the quantification analysis of cannabinoids are discussed.
内源性大麻素系统，包括内源性大麻素神经递质 (eCBs)，近年来由于其与疾病的病理生理学的关系以及大麻 (大麻) 的潜在用途而受到广泛关注。为了法医、临床或治疗药物监测目的，在生物样本中鉴定 eCBs 和植物大麻素仍然是一个重大挑战。在本次范围界定综述中，描述了生物样本中 eCBs 和植物大麻素定量分析的最新优势和局限性。从 2018 年至 2023 年在 8 个数据库中搜索了已发表的研究，并经过筛选和排除后，选择了 38 篇文章进行数据制表、总结和分析。描述了分析的 eCBs 和植物大麻素的主要特征以及每种生物样本的潜在用途，表明文献中仍存在需要探索的空白。综述了 GC、HPLC 和 UHPLC 等经过良好验证和创新的样品制备方案和色谱分离方法，突出了它们各自的优点、缺点和挑战。最后，讨论了大麻素定量分析的未来方法、挑战和趋势。
