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Practical tool for sampling and fast analysis of large cocaine seizures

Journal Contribution - Journal Article

Large quantities of illicit drugs are frequently seized by law enforcement. In such cases, a representative number of samples needs to be quickly examined prior to destruction. No procedure has yet been set up which rapidly provides information regarding the homogeneity of the samples, the presence of controlled substances and the degree of purity. This study establishes a protocol for fast analysis of cocaine and its most common cutting agent, levamisole, in large seizures. The protocol is based on a hypergeometric sampling approach combined with FTIR spectrometry and Support Vector Machines (SVM) algorithms as analysis methods. To demonstrate the practical use of this approach, five large cocaine seizures (consisting between 45 and 85 units) were analysed simultaneously with GC-MS, GC-FID and a portable FTIR spectrometer using Attenuated Total Reflectance (ATR) sampling combined with SVM models. According to the hypergeometric sampling plan of the Drugs Working Group ENFSI guidelines, the required number of subsamples ranged between 19 and 23. Considering the identification analyses, the SVM models detected cocaine and levamisole in all subsamples of cases 1 to 5 (100% correct classification), which was confirmed by GC-MS analysis. Considering the quantification analyses, the SVM models were able to estimate the cocaine and levamisole content in each subsample, compared to GC-FID data. The developed strategy is easy, cost effective and provides immediate information about both the presence and concentration of cocaine and levamisole. By using this new strategy, the number of confirmation analyses with laborious and expensive chromatographic techniques could be significantly reduced.
Journal: Drug testing and analysis
ISSN: 1942-7603
Volume: 10
Pages: 1039 - 1042
Publication year:2018
Keywords:A1 Journal article
BOF-keylabel:yes
BOF-publication weight:1
CSS-citation score:1
Authors from:Higher Education
Accessibility:Open