The psychoactive drug market is ever-evolving and difficult to track as new designer drugs are rapidly released into the market each year. These drugs are characterized by various structures and unknown metabolic profiles that make them difficult to detect in traditional tests. Novel synthetic opioids are one of the most dangerous drugs and have been involved in around 80% of opioid abuse-related deaths. A study in Scientific Reports describes a methodology in mice to obtain metabolic data connected to opioid consumption. After testing in mice the clinical effects of a natural and a synthetic opioid, morphine and fentanyl, respectively, the team developed a strategy to quantify and analyze the metabolic changes associated with their administration. This methodology could detect changes in urine metabolites in mice administered with one of the two drugs while identifying the common metabolites between these two classes of drugs. These findings, using untargeted metabolomics, will help identify distinctive biomarkers of drug class abuse and, in the future, improve drug screenings.

Original reference: Di Francesco, G. et al. Sci. Rep. 14, 9432 (2024)

由于每年都有新的设计药物迅速投放市场，精神活性药物市场不断发展且难以追踪。这些药物具有不同的结构和未知的代谢特征，这使得它们很难在传统测试中检测到。新型合成阿片类药物是最危险的药物之一，约 80% 的阿片类药物滥用相关死亡与此有关。 《科学报告》中的一项研究描述了一种在小鼠中获取与阿片类药物消耗相关的代谢数据的方法。在分别在小鼠中测试天然和合成阿片类药物、吗啡和芬太尼的临床效果后，研究小组制定了一种策略来量化和分析与其给药相关的代谢变化。这种方法可以检测服用两种药物之一的小鼠尿液代谢物的变化，同时识别这两类药物之间的共同代谢物。这些发现利用非靶向代谢组学，将有助于识别药物滥用的独特生物标志物，并在未来改进药物筛选。

原始参考文献： Di Francesco, G. et al.科学。代表。 14、9432 (2024)