A compact Fourier-transform near-infrared spectrophotometer and chemometrics for characterizing a comprehensive set of seized ecstasy samples.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy – June 05, 2024
Source: PubMed
Summary
Law enforcement can now identify ecstasy compounds with 96% accuracy using a portable device and advanced analysis techniques. This breakthrough in forensic analysis combines compact infrared scanning with sophisticated statistical methods to quickly determine drug composition and purity. The technology helps police rapidly test seized illicit drugs on-site, distinguishing MDMA from other substances while minimizing false results.
Abstract
A comprehensive data set of ecstasy samples containing MDMA (N-methyl-3,4-methylenedioxyamphetamine) and MDA (3,4-methylenedioxyamphetamine) seized by the Brazilian Federal Police was characterized using spectral data obtained by a compact, low-cost, near-infrared Fourier-transform based spectrophotometer. Qualitative and quantitative characterization was accomplished using soft independent modeling of class analogy (SIMCA), linear discriminant analysis (LDA) classification, discriminating partial least square (PLS-DA), and regression models based on partial least square (PLS). By applying chemometric analysis, a protocol can be proposed for the in-field screening of seized ecstasy samples. The validation led to an efficiency superior to 96 % for ecstasy classification and estimating total actives, MDMA, and MDA content in the samples with a root mean square error of validation of 4.4, 4.2, and 2.7 % (m/m), respectively. The feasibility and drawbacks of the NIR technology applied to ecstasy characterization and the compromise between false positives and false negatives rate achieved by the classification models are discussed and a new approach to improve the classification robustness was proposed considering the forensic context.