Svetlana Skobeeva

Research project: Application of Chemometrics in Forensic Science

Abstract

Synthetic cannabinoid Receptor Agonists (SCRAs) refer to a variety of psychoactive substances sprayed onto a dry matrix, such as herbs or tobacco and first became available in early 2000's through convenience stores and online sources and became increasingly popular in recreational use due to their high potency, relatively low prices and ease of availability compared to cannabis. Most of the recent research utilising NIR and chemometrics is focused on identifying adulterated food samples, fraudulent pharmaceuticals/tobaccos and identifying samples' geographical origin and those done exclusively on SCRAs have mostly used more complex, costly and destructive techniques, such as GC-MS, UHPLC and NMR. 

This project will focus on developing a targeted model for classifying SCRAs and building a database of such using NIR and multivariate analysis methods, such as PCA, SIMCA, PLS-DA and LDA. In the second and third year these methods will be applied to fingerprint analysis and trace cosmetic evidence. 

Biography

After completing my BSc in Biochemistry I chose to pursue my interest in forensic sciences in Kingston University. At the end of my MSc I did a project on classification of adulterated and unadulterated tobaccos, which inspired me to apply for a PhD in Kingston and research this area further, focusing on analysing trace evidence using analytical chemistry and chemometrics. 

Areas of research interest

  • Chemometrics
  • Multivariate Analysis
  • Forensic Trace Evidence
  • SCRAs
  • New Psychoactive Substances

Qualifications

  • BSc in Biochemistry, University of Leicester
  • MSc in Forensic Analysis, Kingston University

Publications

Near-infrared spectroscopy combined with chemometrics to classify cosmetic foundations from a crime scene

https://doi.org/10.1016/j.scijus.2022.03.002

Synthetic cannabinoid receptor agonists (Spice): the problem they represent and a chemometric solution

https://doi.org/10.23736/S2784-8922.23.01832-0