Abstract

Forensic and anti-doping laboratories have used strategies based on targeted approaches in data processing, which means that only targeted compounds have been analyzed. The new challenges lie beyond the anticipation of molecular targets, such as the detection of designer drugs. In this research, after automatic extraction of all signals obtained by liquid chromatography–high-resolution mass spectrometry (LC–HRMS), the atypical pattern of stimulant-positive samples is evaluated to indicate potential doping substances by principal component analysis (PCA) when compared to negative samples. The capacity for discrimination of positive samples by PCA was evaluated using 24 samples reported as an adverse analytical finding (AAF) for stimulants from different sports against their corresponding negative controls. The method was then evaluated on routine analysis of 620 samples. AAF samples for stimulants presented an atypical pattern positioning when compared to negative samples in the multidimensional space of PCA. The method was able to identify 22 samples reported as AAF before checking the targeted substance windows. In that scenario, it also allows the detection of designer stimulants when the present procedure is applied complementarily in screening routine analysis. The present approach was applied simultaneously with the targeted procedure through the evaluation of 620 samples without jeopardizing the results deadline. Non-targeted analysis of stimulants by PCA as applied to athlete urine samples was demonstrated for the first time to be capable of flagging positive samples in sport competitions, showing its promise as a complementary screening tool alongside classical methods and as a straightforward approach for selecting samples for long-term storage.

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