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Weyermann C, Marquis R, Delaporte C, Esseiva P, Lock E, Aalberg L, Bozenko JS, Dieckmann S, Dujourdy L, Zrcek F.
“Drug intelligence based on MDMA tablets data / I. Organic impurities profiling”.
Forensic Sci Int. 2007 Oct 21;177(1):11-6.
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Abstract
The main objectives of the European project Collaborative Harmonization of Methods for Profiling of Amphetamine Type Stimulants (CHAMP) funded by the sixth framework programme of the European Commission, included the harmonization of MDMA profiling methods and the creation of a common database in a drug intelligence perspective. In the preliminary stages of this project, the participating laboratories analysed the physical characteristics, the chemical composition and the organic impurities of MDMA tablets, using the previously harmonized methods. The aim of the present work was to apply statistical treatments to the recorded data in order to evaluate their potential in the fight against drug trafficking. Comparable working procedures were applied on the different types of data. The first part of this article deals with organic impurities data, while the second part focuses on the potential of the physical characteristics. Organic impurities data were recorded by a harmonized Gas Chromatography/Mass Spectrometry (GC/MS) method previously developed. Statistical analysis provided a selection of pertinent variables among the 46 organic impurities identified in the chromatograms. Correlation coefficients were used to yield separation between populations of samples coming from the same synthesis batch and samples coming from different batches. It was shown that correlation measurements based on Pearson and cosine functions applied to the data pre-treated by normalisation to the sum of peak responses followed by the square root provided an excellent discrimination between the two populations. The statistical methods applied to organic impurities profiles proved to be excellent techniques to differentiate samples from different batches and to highlight operational links between samples.
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