Screening method for rapid classification of psychoactive substances in illicit tablets using mid infrared spectroscopy and PLS-DA

[Display omitted] •ATR-FTIR and PLS-DA were combined to identify drugs in seized ecstasy tablets.•Sequential hierarchical modeling was able to distinguish structurally similar drugs.•A rapid method for the supervised classification of 4 drug classes in seized tablets.•Qualitative validation was perf...

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Veröffentlicht in:Forensic science international 2018-07, Vol.288, p.227-235
Hauptverfasser: Pereira, Leandro S.A., Lisboa, Fernanda L.C., Coelho Neto, José, Valladão, Frederico N., Sena, Marcelo M.
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Sprache:eng
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Zusammenfassung:[Display omitted] •ATR-FTIR and PLS-DA were combined to identify drugs in seized ecstasy tablets.•Sequential hierarchical modeling was able to distinguish structurally similar drugs.•A rapid method for the supervised classification of 4 drug classes in seized tablets.•Qualitative validation was performed and the trueness of the models was above 96.8%.•Spectral assignments to specific drugs supported the reliability of the models. Several new psychoactive substances (NPS) have reached the illegal drug market in recent years, and ecstasy-like tablets are one of the forms affected by this change. Cathinones and tryptamines have increasingly been found in ecstasy-like seized samples as well as other amphetamine type stimulants. A presumptive method for identifying different drugs in seized ecstasy tablets (n=92) using ATR-FTIR (attenuated total reflectance – Fourier transform infrared spectroscopy) and PLS-DA (partial least squares discriminant analysis) was developed. A hierarchical strategy of sequential modeling was performed with PLS-DA. The main model discriminated four classes: 5-MeO-MIPT, methylenedioxyamphetamines (MDMA and MDA), methamphetamine, and cathinones. Two submodels were built to identify drugs present in MDs and cathinones classes. Models were validated through the estimate of figures of merit. The average reliability rate (RLR) of the main model was 96.8% and accordance (ACC) was 100%. For the submodels, RLR and ACC were 100%. The reliability of the models was corroborated through their spectral interpretation. Thus, spectral assignments were performed by associating informative vectors of each specific modeled class to the respective drugs. The developed method is simple, fast, and can be applied to the forensic laboratory routine, leading to objective results reports useful for forensic scientists and law enforcement.
ISSN:0379-0738
1872-6283
DOI:10.1016/j.forsciint.2018.05.001