Rapid identification of novel psychoactive and other controlled substances using low-field 1H NMR spectroscopy

Antonides, Lysbeth H., Brignall, Rachel M., Costello, Andrew, Ellison, Jamie, Firth, Samuel E., Gilbert, Nicolas, Groom, Bethany J., Hudson, Samuel J., Hulme, Matthew C., Marron, Jack, Pullen, Zoe A., Robertson, Thomas B. R., Schofield, Christopher J., Williamson, David C., Kemsley, E. Kate ORCID: https://orcid.org/0000-0003-0669-3883, Sutcliffe, Oliver B. and Mewis, Ryan E. (2019) Rapid identification of novel psychoactive and other controlled substances using low-field 1H NMR spectroscopy. ACS Omega, 4 (4). pp. 7103-7112. ISSN 2470-1343

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Abstract

An automated approach to the collection of H-1 NMR (nuclear magnetic resonance) spectra using a benchtop NAIR spectrometer and the subsequent analysis, processing, and elucidation of components present in seized drug samples are reported. An algorithm is developed to compare spectral data to a reference library of over 300 H-1 NMR spectra, ranking matches by a correlation-based score. A threshold for identification was set at 0.838, below which identification of the component present was deemed unreliable. Using this system, 432 samples were surveyed and validated against contemporaneously acquired GC-MS (gas chromatography-mass spectrometry) data. Following removal of samples which possessed no peaks in the GC-MS trace or in both the NMR spectrum and GC-MS trace, the remaining 416 samples matched in 93% of cases. Thirteen of these samples were binary mixtures. A partial match (one component not identified) was obtained for 6% of samples surveyed whilst only 1% of samples did not match at all.

Item Type:	Article
Uncontrolled Keywords:	raman-spectroscopy,synthetic cannabinoids,liquid-chromatography,herbal mixtures,legal highs,gc-ms,drugs,quantification,field,differentiation
Faculty \ School:	Faculty of Science > School of Chemistry
Depositing User:	LivePure Connector
Date Deposited:	27 Oct 2020 01:07
Last Modified:	16 May 2024 11:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/77439
DOI:	10.1021/acsomega.9b00302

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