The following graphical abstract presents the chemometric analysis applied to ASAP-MS data for the classification of ecstasy samples and their adulterants.

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.