Validation of a large volume-solid phase extraction methodology for biotoxicity assessment of pharmaceuticals in aquatic organisms

Abstract

The growing scarcity of freshwater has intensified the need for alternative water sources, which often require advanced treatments to eliminate contaminants. Among emerging pollutants, pharmaceuticals have become a significant concern due to their persistence and potential impact, making their detection essential. However, analysing these contaminants is challenging due to the extremely low concentrations at which they are present. For chemical analysis, minimal or no sample enrichment is often necessary, while bioanalysis typically requires larger sample volumes and an enrichment factor to conduct comprehensive bioassays across various endpoints. Consequently, sample preconcentration techniques for large water volumes are necessary to improve the sensitivity of subsequent toxicological experiments. In this study, a novel large volume solid-phase extraction (LV-SPE) procedure was validated and evaluated for monitoring multiple pharmaceutical compounds in water samples, while maintaining the traditional solid-phase extraction (SPE) methodology using cartridges. This method proved effective extraction and preconcentration of significant amounts of water, with recoveries between 19 % and 109 % in spiked wastewaters (except for fluvoxamine, remdesivir, tamoxifen and tetracycline, with recoveries <10 %). Furthermore, the optimization of this approach covers an expansive chemical space, enabling the capture of a diverse range of pharmaceutical compounds and enhancing the validity of toxicological studies. Bioassays conducted with Daphnia magna juveniles and Danio rerio embryos validated the method's applicability regarding optimized exposure conditions, the absence of adverse effects from SPE blanks or solvent controls and sensitivity in detecting effects across field samples. Overall, the LV-SPE approach enhances sensitivity and reliability for evaluating pharmaceutical mixtures' risks under realistic conditions.