Identification of Potential Metabolites of Pharmaceutical Residues Detected in an Environmental Water Sample

Importance of the Topic

Presence of pharmaceuticals and personal care products in water poses risks to ecosystems and public health. High-resolution mass spectrometry combined with advanced chromatography enables comprehensive monitoring of these contaminants and their breakdown products. Identifying potential metabolites is essential to understand environmental fate and potential toxicity of residues.

Objectives and Study Overview

The study aimed to apply a non-targeted HRMS approach coupled with informatics to detect and characterize metabolites of pharmaceutical residues in environmental water. A previously screened well water sample enriched 1000-fold was reanalyzed to isolate metabolites using the UNIFI software platform.

Methodology and Instrumentation

• Sample preparation: local well water enriched 1000×.
• Chromatography: UPLC with an ACQUITY UPLC HSS C18 column.
• Mass spectrometry: Xevo G2-S QTof operated in MS^E mode with alternating low/high collision energy.
• Data processing: UNIFI Screening Platform with toxicology library (>1000 compounds), metabolite identification workflows using structure files and predefined transformation rules.

Key Results and Discussion

• Initial screening detected four pharmaceuticals in the well water sample.
• Using chemical intelligence and systematic cleavage, potential metabolites were generated from parent structures.
• Three oxidized metabolites of carbamazepine were identified with high confidence based on retention time, accurate mass precursor and fragment matches.
• No metabolites were observed for the other three parent compounds under the applied conditions.
• Common fragment and neutral loss analyses further confirmed the structural assignments.

Benefits and Practical Applications

• Integrated HRMS acquisition with informatics enables rapid, confident screening for both parent contaminants and metabolites.
• Inclusion of retention times and fragment ions in the library reduces false positives and streamlines data review.
• Discovered metabolites can be added to scientific libraries to enhance future environmental monitoring workflows.

Future Trends and Potential Applications

• Expansion of non-targeted screening libraries to include more transformation pathways and uncommon metabolites.
• Application of machine learning to predict environmental metabolite profiles and prioritize targets.
• Integration with real-time monitoring platforms for dynamic assessment of water quality.
• Advancements in automation and data mining to accelerate unknown metabolite discovery.

Conclusion

The combination of fast UPLC-MS^E acquisition and an integrated scientific information system provides a robust workflow for detecting pharmaceutical residues and their metabolites in environmental waters. This approach improves confidence in identifications and enriches screening libraries for ongoing monitoring efforts.

Reference

1. Richardson SJ. Environmental Mass Spectrometry: Emerging Contaminants and Current Issues. Anal Chem. 2012;84:747–778.
2. Mallet C, Cleland G, Burgess J. Screening Environmental Samples for a Diverse Range of Compounds with Accurate Mass LC-MS and an Integrated Scientific Information System. Waters Application Note No. 720004810EN; 2013.
3. Mallet C, Cleland G, Burgess J. Multi-residue analysis of pharmaceuticals and personal care products (PPCPs) in water using the ACQUITY UPLC H-Class and the Xevo TQD tandem mass spectrometer. Waters Application Note No. 720004813EN; 2013.
4. Mortishire-Smith RJ, Castro-Pérez JM, Yu K, et al. Generic dealkylation: a tool for increasing the hit-rate of metabolite rationalization, and automatic customization of mass defect filters. Rapid Commun Mass Spectrom. 2009;23(7):939–948.