Issue 11, 2020

Rapid identification of the “smart drug” modafinil in suspicious tablets by DART-HRMS combined with micropunching

Abstract

Recently, increasing numbers of imported parcels have contained tablets that have been mixed with others containing modafinil; thus, it is necessary to develop a rapid screening method for this compound. A rapid and accurate approach using direct analysis in real time coupled to high-resolution mass spectrometry (DART-HRMS) and combined with the micropunching method was developed to detect modafinil. The effects of the injected concentration, ion source temperature and capillary temperature on the detection of modafinil by DART-HRMS combined with micropunching were evaluated. The optimized injection concentration of modafinil, ion source temperature and capillary temperature were determined to be 1 μg mL−1, 200 °C and 150 °C, respectively. DART-HRMS combined with micropunching can control the concentrations of target compounds in the seized modafinil tablets that are injected into an instrument, effectively avoiding the interference of dimer formation caused by excessive concentrations on the rapid identification of unknowns. This high-throughput approach was successfully applied to quickly identify seized modafinil tablets collected from authentic forensic cases, which was further confirmed by traditional gas chromatography-MS (GC-MS) techniques. The results demonstrated that DART-HRMS combined with micropunching is a useful approach for the rapid identification of suspicious modafinil tablets, allowing the detection and identification of modafinil with minimal sample preparation.

Graphical abstract: Rapid identification of the “smart drug” modafinil in suspicious tablets by DART-HRMS combined with micropunching

Article information

Article type
Paper
Submitted
06 Dec 2019
Accepted
02 Feb 2020
First published
05 Feb 2020

Anal. Methods, 2020,12, 1430-1440

Rapid identification of the “smart drug” modafinil in suspicious tablets by DART-HRMS combined with micropunching

L. Zhou, X. Wang, W. Liu, P. Xiang and H. Chen, Anal. Methods, 2020, 12, 1430 DOI: 10.1039/C9AY02624J

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