ArticleScientific reports2025
Development and validation of a green/blue UHPLC-MS/MS method for trace pharmaceutical monitoring.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
In response to the growing concerns regarding pharmaceutical contamination of our aquatic systems, targeted actions are being implemented to align with the recommendations of the European Commission. However, a challenge lies in finding effective, accurate, and green chemistry-compliant methods for analyzing these compounds in complex matrices. This study introduces a highly sensitive and sustainable ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method for simultaneously determining carbamazepine, caffeine, and ibuprofen in water and wastewater. This method exhibits impressive advantages: exceptional sensitivity, high selectivity, and an economical sample preparation strategy resulting from the absence of an evaporation step after solid-phase extraction (SPE), as well as a short analysis time (10 min). Following the International Council for Harmonization (ICH) guidelines Q2(R2), the developed and validated method proved to be specific, linear (correlation coefficients ≥ 0.999), precise (RSD < 5.0%), and accurate (recovery rates ranging from 77 to 160%). The limits of detection were 300 ng/L for caffeine, 200 ng/L for ibuprofen, and 100 ng/L for carbamazepine, respectively. The limits of quantification (LOQs) were 1000 ng/L for caffeine, 600 ng/L for ibuprofen, and 300 ng/L for carbamazepine. The advanced UHPLC-MS/MS method presented in this article constitutes a green and blue analytical technique for the precise detection and quantification of trace levels of pharmaceutical contaminants in aquatic environments. This method has been validated and exemplified using a case study from the Kraków area, highlighting its high efficiency, reliability, and minimal environmental impact. This approach aligns with the concept of sustainable analytics, combining ecological aspects with high-quality results. This study is therefore crucial for the effective monitoring of pollutants, the assessment of environmental and health risks, and ensuring water quality.
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