Segmental hair analysis for flunitrazepam and 7-aminoflunitrazepam in users: a comparison to existing literature

Forensic Sci Res. 2020 Oct 22;7(2):299-307. doi: 10.1080/20961790.2020.1824600. eCollection 2022.

Abstract

The availability of more quantitative data on flunitrazepam (FLU) and 7-aminoflunitrazepam (7AF) would aid in obtaining a better understanding of the interpretation of FLU concentrations in human hair. The purpose of this study was to provide concentrations of FLU and 7AF in hair segments of 22 FLU users. Quantitative data regarding hair concentrations of FLU and 7AF from various types of cases were also reviewed to give a comprehensive overview of the comparability of different studies. Three to six 1 cm segments of scalp hair from 22 FLU users were analyzed by a liquid chromatography-tandem mass spectrometry (LC-MS/MS) method. FLU and its metabolite were confirmed in the hair segments from all cases. Concentrations of FLU and 7AF in the segments ranged from 0.01-0.16 ng/mg (median of 0.03) and 0.01-0.34 ng/mg (median of 0.09), respectively. Most cases had FLU and 7AF distributions along the hair segments that were suggestive of repeated drug use. A summary of the published concentrations gives valuable data and can assist forensic investigators in their estimations of drug use history and patterns.Key pointsA method using LC-MS/MS to quantify flunitrazepam and its metabolite was described.Segmental analysis of flunitrazepam and its metabolite in human hair was reported.A comprehensive overview of quantitative data was given.

Keywords: 7-aminoflunitrazepam; Forensic sciences; flunitrazepam; forensic toxicology; liquid chromatography–tandem mass spectrometry; segmental hair analysis.

Grants and funding

This work was supported by the National Natural Science Foundation of China [grant numbers 81871531]; the Science and Technology Commission of Shanghai Municipality [grant numbers 17DZ2273200, 19DZ2292700]; Shanghai Sailing Program [grant number 19YF1450400]; and China Postdoctoral Science Foundation [grant number 2018M640417].