A suspect screening strategy with automated data processing tools for the comprehensive detection of emerging chemical hazards in food

In a rapidly evolving agri-food landscape fraught with unforeseen chemical risks, the establishment of proactive analytical strategies become paramount to safeguard food safety and public health. Leveraging ultra-high-performance liquid chromatography high resolution tandem mass spectrometry (UHPLC-HRMS/MS), this study presents a comprehensive suspect screening strategy which was designed for the efficient detection of emerging contaminants in food. Employing a generic extraction protocol and an extensive suspect list, the strategy was implemented on representative food samples fortified at parts per billion (ppb) level. A notable range of the observed True Positive Rates (TPR) spanning 84%–100% underscores the strategy's robustness and versatility in accurately identifying a wide array of compounds in complex food matrices. Moreover, the integration of a python-powered graphical user interface (GUI) plays a pivotal role in automating data processing steps, streamlining data and facilitating data prioritisation through the application of a metabolomics-inspired approach. This enhancement significantly elevates the strategy's efficiency for high throughput analyses, thus reflecting a more agile approach in addressing emerging hazards. •A comprehensive suspect screening strategy was developed for the efficient detection of emerging chemical hazards in food.•A python-powered GUI that is capable of automated data processing steps was incorporated for high throughput non-targeted screening.•The strategy's robustness and versatility in accurately identifying a wide array of compounds in complex food matrices were evaluated in this study.