LAUSR

The chemical identification of new psychoactive substances (NPS) in the field is challenging due not only to the plethora of substances available, but also as a result of the chemical complexity of products and the chemical similarity of NPS analogues. In this study, handheld Raman spectroscopy and the use of two excitation wavelengths, 785 and 1064nm, were evaluated for the identification of 60 NPS products. The products contained a range of NPS from classes including the aminoindanes, arylalkylamines, benzodiazepines, and piperidines & pyrrolidines. Identification was initially assessed using the instruments' in built algorithm (i.e., % HQI) and then further by visual inspection of the Raman spectra. Confirmatory analysis was preformed using gas chromatography mass spectrometry. For the 60 diverse products, an NPS was successfully identified via the algorithm in 11 products (18%) using the 785nm source and 29 products (48%) using the 1064nm source. Evaluation of the Raman spectra showed that increasing the excitation wavelength from 785 to 1064nm improved this 'first pass' identification primarily due to a significant reduction in fluorescence, which increased S/N of the characteristic peaks of the substance identified. True positive correlations between internet products and NPS signatures ranged from 57.0 to 91.3% HQI with typical RSDs<10%. Tablet formulations and branded products were particularly challenging as a result of low NPS concentration and high chemical complexity, respectively. This study demonstrates the advantage of using a 1064nm source with handheld Raman spectroscopy for improved 'first pass' NPS identification when minimal spectral processing is required, such as when working in field. Future investigations will focus on the use of mixture algorithms, effect of NPS concentration, and further improvement of spectral libraries.