Development and evaluation of a synthetic cathinone targeted gas chromatography mass spectrometry (GC-MS) method

Simultaneous Determination of 16 Kinds of Synthetic Cathinones in Human Urine Using a Magnetic Nanoparticle Solid-Phase Extraction Combined with Gas Chromatography-Mass Spectrometry

A specific and sensitive approach using magnetic nanoparticle solid-phase extraction combined with gas chromatography-mass spectrometry (GC-MS) was carried out and applied in the simultaneous determination of 16 kinds of synthetic cathinones in human urine. The functionalized extraction material (Fe3O4/NH2-MWCNTs) was synthesized and factors affecting the extraction efficiency were all tested. Under the optimized conditions of magnetic nanoparticle solid-phase extraction, the determination of synthetic cathinones in human urine was carried out with GC-MS. Good linear relationships of 16 kinds of synthetic cathinones were obtained in the range of 0.005–5.00 μg/mL with the correlation coefficients (r) ranging from 0.9901 to 0.9979, the limits of detection were in the range between 0.005 and 0.01 μg/mL, and the limits of quantitation were between 0.01 and 0.02 μg/mL. Furthermore, the average intra-day precisions were below 8.90%, the average inter-day precisions were less than 9.52%, and the average recoveries were between 87.03% and 99.13%, respectively. The results show the advantages of the approach in the determination of trace synthetic cathinones in complex matrixes, such as environmentally friendly, fast detection, high efficiency and sensitivity. The practical application indicated that this method could provide scientific basis for the determination of drugs of abuse in forensic laboratories.

Comparing two seized drug workflows for the analysis of synthetic cannabinoids, cathinones, and opioids

As the challenges faced by drug chemists persist, due to the presence of emerging drugs, laboratories continue to look for new solutions, ranging from existing methods to implementation of entirely new technology. A common barrier for making workflow changes is a lack of pre-existing data demonstrating the potential impact of these changes. In this study, we compare, qualitatively and quantitatively, an existing workflow for seized drug analysis to an experimental workflow. Four chemists were asked to analyze a total of 50 mock case samples across the two workflows. The existing workflow employed color tests for screening alongside general purpose GC-FID and GC-MS analyses for confirmation. The experimental workflow combined DART-MS screening with class-specific (targeted) GC-MS analysis for confirmation. Comparison of the workflows showed that screening by DART-MS required the same amount of time as color tests but yielded more accurate and specific information. Confirmation using the existing workflow required more than twice the amount of instrument time and data interpretation time while also presenting other analytical challenges that prevented compound confirmation in select samples. Targeted GC-MS methods simplified data interpretation, reduced consumption of reference materials, and addressed almost all limitations of general-purpose methods. While the experimental workflow requires modifications and answering of additional research questions, this study shows how rethinking analytical workflows for seized drug analysis could reduce turnaround times, backlogs, and standards consumption. It also demonstrates the potential impact of being able to investigate workflow changes prior to implementation.

The Min-Max Test: An Objective Method for Discriminating Mass Spectra

Deciding whether the mass spectra of seized drug evidence and a reference standard are measurements of two different compounds is a central challenge in forensic chemistry. Normally, an analyst will collect mass spectra from the sample and a reference standard under identical conditions, compute a mass spectral similarity score, and make a judgment about the sample using both the similarity score and their visual interpretation of the spectra. This approach is inherently subjective and not ideal when a rapid assessment of several samples is necessary. Making decisions using only the score and a threshold value greatly improves analysis throughput and removes analyst-to-analyst subjectivity, but selecting an appropriate threshold is itself a nontrivial task. In this paper, we describe and evaluate the min-max test-a simple and objective method for classifying mass spectra that leverages replicate measurements from each sample to remove analyst subjectivity. We demonstrate that the min-max test has an intuitive interpretation for decision-making, and its performance exceeds thresholding with similarity scores even when the best performing threshold for a fixed dataset is prescribed. Determining whether the underlying framework of the min-max test can incorporate retention indices for objectively deciding whether spectra are measurements of the same compound is an ongoing work.