Advances in the application of machine learning in the identification and authentication of synthetic cannabinoids

VernacularTitle:机器学习在合成大麻素识别鉴定中的应用进展
Author: Qing XU ^{1
,

2} ; Min LYU ; Hongxiao DENG ; Chi HU ; Ping XIANG ; Hang CHEN
Author Information

1. 司法鉴定科学研究院,司法部司法鉴定重点实验室,上海市法医学重点实验室,上海市司法鉴定专业技术服务平台,上海 200063
2. 中国药科大学药学院,南京 210009
Keywords: synthetic cannabinoids; machine learning; non-targeted screening
From: Journal of China Pharmaceutical University 2024;55(3):316-325
CountryChina
Language:Chinese
Abstract: Synthetic cannabinoids(SCs)are synthetic psychoactive substances that can pose a public health risk.The SCs are structurally variable and susceptible to structural modification.The rapid emergence of structurally unknown synthetic cannabinoids has led to new challenges in their identification.In recent years,machine learning has made great progress and has been widely applied to other fields,providing new strategies for the identification of unknown synthetic cannabinoids and the inference of possible sources.This paper describes the principles of commonly used machine learning methods and the application of machine learning techniques to mass spectrometry,Raman spectroscopy,metabolomics and quantitative conformational relationships of synthetic cannabinoids,aiming to provide new ideas for the identification of unknown synthetic cannabinoids.