In silico metabolite prediction and LC-HRMS confirmation for forensic analysis of a fatal case involving novel synthetic opioid <i>N, N</i> -dimethyl etonitazene

In this study, Sygma software was used to predict metabolites, and LC-HRMS method was employed to specifically analyse the metabolites of N, N-dimethyl etonitazene in authentic forensic human samples. The time required for data analysis was significantly reduced through in silico metabolite prediction. We recommend the 5-amination metabolite (M2) as a potential biomarker in blood and urine samples of N, N-dimethyl etonitazene. In addition, this study filled the gap in the study of N, N-dimethyl etonitazene metabolism. It also provided real data supplementation for the metabolism of nitazene analogues. The prediction of metabolites by using Sygma provided a certain reference for the future application of artificial intelligence in the field of forensic analysis.