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Options for veterinary drug analysis using mass spectrometry
Bruno Le Bizec1, Gaud Pinel, Jean-Philippe Antignac
1Laboratoire d'Etude des Résidus et Contaminants dans les Aliments, Ecole Nationale Vétérinaire de Nantes, USC INRA 2013, F-44307 Nantes Cedex 3, France. laberca@vet-nantes.fr
This review explores mass spectrometry (MS) techniques for detecting veterinary drug residues in food and animal samples. It highlights various MS strategies and their applications in ensuring food safety and regulatory compliance.
Area of Science:
- Food Safety and Veterinary Medicine
- Analytical Chemistry
- Mass Spectrometry
Background:
- Strict EU regulations govern the use of veterinary drugs in animal breeding for food safety.
- Control systems have been established to ensure compliance with these regulations.
- Current strategies involve targeted analysis of drug residues and metabolites in various matrices.
Purpose of the Study:
- To review and discuss various mass spectrometry (MS) strategies for veterinary drug residue analysis.
- To illustrate the application of different MS approaches in residue analysis.
- To examine the balance between analytical challenges and available MS technologies.
Main Methods:
- Review of single MS, multidimensional MS, high-resolution MS, and isotope ratio MS.
- Discussion of ionization techniques (e.g., ESI) and mass analyzers (e.g., triple quadrupole, TOF).
- Consideration of sample preparation, derivatization, chromatographic separation, and data analysis.
Main Results:
- Mass spectrometry is the primary confirmatory method for unambiguous identification of residues at trace levels.
- Various MS strategies offer different balances of specificity, sensitivity, and applicability.
- Key challenges include ion suppression, resolution, and adapting methods to evolving regulations.
Conclusions:
- Mass spectrometry is crucial for enforcing veterinary drug regulations and ensuring food safety.
- The choice of MS strategy depends on the specific analyte, matrix, and concentration.
- Future trends in chromatography and data analysis will further enhance residue detection capabilities.
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