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Robust Detection of Ecstasy-Like and Adulterants Through ASAP-MS and DD-SIMCA.

Rafael D Soares, Danielle K John, Marcos P Thomé, Patrícia S Corrêa, Klester S Souza, Marco F Ferrão

Drug testing and analysis February 4, 2025 DOI: 10.1002/dta.3860 via PubMed

Summary

AI-generated from the abstract

A rapid and reliable method combining ASAP-MS with DD-SIMCA accurately identifies ecstasy (MDMA) and its adulterants, including emerging psychoactive substances missed by traditional tests. Principal component analysis (PCA) captured 69% of data variability in the first three components, and the DD-SIMCA model showed high sensitivity for MDA samples and high specificity in training and test sets. The chemometric model matched standard technique results even with adulterants present, suggesting these tools are valuable for forensic drug analysis.

Study at a glance

Characteristics Method validation study Peer reviewed
Population Ecstasy tablets and their adulterants
Topics MDMA
Keywords Asap‐ms Dd‐simca Mda Pca Forensic drug analysis
Citations 1
Key finding ASAP-MS combined with DD-SIMCA provides a rapid, reliable, and versatile method for identifying ecstasy and its adulterants, including emerging psychoactive substances.

Abstract

Ecstasy is a complex and hazardous substance, and its identification is increasingly challenging. Conventional analytical methods have limitations in terms of sensitivity and selectivity, and more precise techniques are time-consuming and necessitate sample preparation. ASAP-MS and DD-SIMCA are two methods that have the potential to address these issues. This research delves into the efficacy of ASAP-MS and DD-SIMCA as a rapid and dependable approach for detecting ecstasy and its adulterants. PCA was conducted as an initial exploration, with the first three principal components (PCs) capturing 69% of the overall data variability. The score plot of PC1 × PC3 revealed the distribution of samples containing MDA and MDMA. The DD-SIMCA model exhibited high sensitivity in identifying the target samples (MDA) and relatively high specificity in training and test sets. These results underscore the effectiveness of ASAP-MS, PCA, and DD-SIMCA for precise identification of ecstasy and its adulterants, indicating their potential in drug identification and analysis. We observed that the chemometric model associated with ASAP-MS was able to accurately identify, when compared to the results obtained by the standard technique, the constituents of ecstasy tablets, even in the presence of adulterants. Furthermore, the method could detect emerging psychoactive substances that are typically not targeted by traditional analytical approaches. These findings suggest that ASAP-MS and DD-SIMCA could be valuable tools in forensic drug analysis laboratories. The method is rapid, reliable, and versatile for identifying a wide range of ecstasy and its adulterants.

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