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

Nitazenes are a class of new psychoactive substances (NPS) belonging to the synthetic opioids. It has potent μ-opioid receptor agonist activity. In this study, we investigated an authentic forensic human blood and urine sample from an individual that died from the use of N, N-dimethyl etonitazene. To enable rapid analysis in authentic forensic sample, a method was developed utilizing in silico metabolite prediction and liquid chromatography high-resolution mass spectrometry (LC-HRMS) for blood and urine samples.In this study, LC-HRMS was used to analyze authentic blood and urine samples, and Sygma software was used to predict metabolites. Based on the predicted results, targeted analysis methods of LC-HRMS data were used to study the metabolites of blood and urine. N, N-dimethyl etonitazene and seven metabolites were identified in blood and urine samples. Among them, there were four phase I metabolites, which respectively correspond to four metabolic pathways: N-demethylation (M1), 5-amination (M2), 4'-hydroxylation (M4), N-oxidation (M6). There were three phase II metabolites corresponding to two metabolic pathways, respectively: acetylation (M3), glucuronidation (M5, M7). M1, M2, and M3 were identified in blood sample, and all metabolites were identified in urine sample. In this study, Sygma software was used to predict metabolites, and LC-HRMS method was employed to specifically analyze 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.