µSPEED microextraction of veterinary antibiotics in environmental water samples by UPLC

The pharmaceutical industry is one of the fastest-growing sectors. Antibiotics are widely used in human and veterinary medicine. A significant fraction of administered antibiotics is excreted unchanged and enters the environment via manure application, wastewater discharge, and improper disposal. Their presence in aquatic systems is of increasing concern due to ecological risks and the development of antimicrobial resistance. Therefore, there is a strong need for rapid, sensitive, and environmentally friendly analytical methods for their determination in environmental waters [1-4].

A miniaturized and semi-automated solid-phase microextraction procedure based on µSPEed technology was developed and coupled with ultraperformance liquid chromatography (UPLC) with UV detection. Six veterinary antibiotics were selected for analysis: tetracycline, chlortetracycline, oxytetracycline, doxycycline, sulfamethoxazole, and trimethoprim. The extraction procedure used a PS/DVB-RP sorbent cartridge. The cartridge was conditioned with 250 µL of MeOH, equilibrated with 250 µL of H₂O, and then 500 µL of the sample was loaded three times. The elution step was performed in two cycles using 50 µL of acidified MeOH. The total extraction time was 6 minutes per sample.

The developed method showed excellent chromatographic performance. Good linearity was obtained for all analytes (R² > 0.99). Limits of detection ranged from 0.30 to 1.23 µg/L, while limits of quantification were between 0.92 and 3.73 µg/L. Recoveries ranged from 46% to 86%. The method was successfully applied to environmental water samples collected from Madeira Island, where no target antibiotics were detected.

The proposed method enables fast, efficient, and environmentally friendly determination of veterinary antibiotics in water samples. The approach significantly reduces solvent consumption and sample volume while maintaining good analytical performance. The semi-automated format improves reproducibility and reduces analyst workload, making it a suitable tool for routine environmental monitoring.