STUDIES OF THE COMPOSITION OF SMOKING MIXTURES CONTAINING SYNTHETIC CANNABINOIDS

DOI: https://doi.org/10.29296/25877313-2021-05-04
Issue: 
5
Year: 
2021

A.V. Oberenko Senior Expert, Expertise Centre of Directorate for Law Enforcement in Transport Means of Russian Ministry of Internal Affairs for Siberian Federal District (Krasnoyarsk); Post-graduate Student, Siberian Federal University (Krasnoyarsk, Russia) E-mail: krasandrew@mail.ru S.V. Kachin Dr.Sc. (Chem.), Professor, Siberian Federal University (Krasnoyarsk, Russia) S.A. Sagalakov Associate Professor, Siberian Federal University (Krasnoyarsk, Russia)

Currently, in many countries, including Russia, there is an alarming increase in the consumption of potentially dangerous smoking mixtures containing synthetic cannabinoids (SM-SC). Against the background of a persistent trend of constant change («updates») it is very important to monitor their com-ponent composition in order to assess the potential risk of harm to the health of potential consumers and to take adequate therapeutic measures in the event of drug cases, as well as to establish the source of production and the chain of their illegal distribution. The purpose of the work: a scientific review of publications with the results of component composition studies and the definition of the SM-SC analysis algorithm. An overview of the results of the SM-SC studies was presented. Information on the composition of SM-SC, procedures of sample preparation, methods of identification and determination of the main components and impurities, obtaining and processing chromatographic data were provided. The main components of the mixtures are the matrix, the physiologically active substance and various impurities. The modern classification of SC in accordance with their chemical structure was presented.Recommendations on the selection of profile impurities with identification significance were given. For the determination of volatile impurities, in some cases, it is effective to pre-vapor-phase separation from the matrix, capture from the gas phase with a solid sorbent and liquid microextraction of sorbates for further gas chromatographic (GC) studies. To establish a measure of similarity (difference) be-tween SM-SC samples, numerical methods of processing GC data are used with calculations of Pearson correlation coefficients or Euclidean distances and the construction of corresponding dendrograms. An algorithm for SM-SC analysis was proposed, including visual examination of the sample, GC-MS identification of the physiologically active substance, impurity profiling, selection of target compounds, and mathematical processing of chromato-grams. The implementation of the proposed algorithm for the analysis of SM-SC allows us to obtain the most complete information about the component composition of samples, which is very important for assessing their toxicity and taking adequate therapeutic precautions. Impurity profiling and the se-lection of target compounds with identification significance, followed by mathematical processing of chromatographic data, are additional tools in de-termining the measure of similarity (difference) between samples taken from illegal circulation.The latter can be used to establish the source of pro-duction and the chain of their illegal distribution

Keywords: 
smoking mixtures
composition
synthetic cannabinoids
GC-MS
analysis

References: 
  1. World drug report 2020. Booklet 2. Drug use and health consequences. United Nations Office on Drags and Crime. 2020; 52 p. https://wdr.unodc.org/wdr2020/ (дата обращения 01.02.2021).
  2. European drug report. Trends and developments / European Monitoring Centre for Drugs and Drug Addiction (EMCDDA). 2019; 94 p.
  3. https://www.emcdda.europa.eu/system/files/publications/11364/20191724_TDAT19001ENN_PDF.pdf (дата обращения 01.02.2021).
  4. Baumann M.H., Glennon R.A., Wiley J.L. (Eds.). Neuropharmacology of new psychoactive substances (NPS): The science behind the headlines. Cham: Springer. 2017; 388 p. https://doi.org/10.1007/978-3-319-52444-3.
  5. Synthetic cannabinoids in herbal products. United Nations Office on Drugs and Crime. 2011; 24 p. www.unodc.org/do-cuments/scientific/Synthetic_Cannabinoids.pdf (data obrashhenija 01.02.2021).
  6. Makiev K.T., Gladyrev V.V., Ljubeckij G.V. i dr. Sovremennye ugrozy nacional'noj bezopasnosti Rossii (kuritel'nye smesi, soderzhashhie analogi kannabinoi-dov) i puti ih preodolenija. Sovremennye problemy nauki i obrazovanija. 2015; 2: 667. URL: http://science-education.ru/ru/article/view?id=20928
  7. Shanks K.G., Winston D., Heidingsfelder J., et. al. Case reports of synthetic cannabinoid XLR-11 associated fatalities. Forensic Science International. 2015; 252: e6–e9. https://doi.org/10.1016/j.forsciint.2015.04.021
  8. Shevyrin V.A. Sinteticheskie kannabinoidy v kachestve novyh psihoaktivnyh soedinenij. Ustanovlenie struktur, analiticheskie harakteristiki, metody opredele-nija i identifikacija v ob#ektah analiza narkoticheskih sredstv. M.: Pero, 2015; 608 s.
  9. Ajzberg O.R., Shilejko I.D., Liskovskij O.V. Novye psihoaktivnye veshhestva. Medicinskij zhurnal. 2018; 4: 49. URI http://rep.bsmu.by:8080/handle/BSMU/21771
  10. Oberenko A.V., Kachin S.V., Sagalakov S.A. Types of synthetic cannabinoids seized from illicit trafficking in the territory of the Siberian Federal District (Russia) between 2009–2018. Forensic Science International. 2019; 302: 109902. http://dx.doi.org/10.1016/j.forsciint.2019.109902.
  11. Huffman J.W., Szklennik P.V., Almond A., et. al. 1-Pentyl-3-phenylacetylindoles, a new class of cannabimimetic indoles. Bioorganic & Medicinal Chemistry Let-ters. 2005; 15(18): 41104113. https://doi.org/10.1016/j.bmcl.2005.06.008
  12. Patent US20110065685A1 USA, 2011.
  13. Patent WO 2014/167530 NZ, 2014.
  14. Oberenko A.V., Kachin S.V., Sagalakov S.A. Profiling of impurities in samples of synthetic cannabinoids seized from illegal circulation in the siberianregion of the Russian Federation. Journal of Siberian Federal University. Chemistry. 2018; 11(3): 310322. https://doi.org/10.17516/1998-2836-0077
  15. Oberenko A.V., Kachin S.V., Sagalakov S.A. Hromato-mass-spektrometricheskoe opredelenie neletuchih komponentov napolnitelej plastichnyh kuritel'nyh smesej, soderzhashhih sinteticheskie kannabinoidy. Voprosy biologicheskoj, medicinskoj i farmacevticheskoj himii. 2019; 22(4): 2428. https://doi.org/10.29296/25877313-2019-04-04.
  16. Snow N.H., Slack G.C. Head-space analysis in modern gas chromatography. TRAC  Trends in Analytical Chemistry. 2002; 21(9–10): 608617. https://doi.org/10.1016/S0165-9936(02)00802-6.
  17. Oberenko A.V., Kachin S.V., Sagalakov S.A. Gazohromatograficheskoe opredelenie letuchih primesej v sinteticheskih kannabinoidah s ispol'zovaniem parofaznoj sorbcionnoj mikrojekstrakcii. Materialy Mezhdunar. nauchn.-praktich. konf. «Sovremennye problemy himii, tehnologii i farmacii» (Cheboksary, 1718 nojabrja 2020 g.). Cheboksary: Izdatel'stvo Chuvashskogo un-ta, 2020; 186190.
  18. Oberenko A.V., Kachin S.V., Sagalakov S.A. Sravnitel'noe issledovanie plastichnyh kuritel'nyh smesej, soderzhashhih sinteticheskie kannabinoidy, metodom gazovoj hromatografii. Zavodskaja laboratorija. Diagnostika materialov. 2020; 86(8): 5-11. DOI: https://doi.org/10.26896/ 1028-6861-2020-86-8-5-11