1. Application of a generic PBK model for beef cattle: Tissue/fluid correlations of paracetamol and NSAIDs.
- Author
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Lautz LS, Melchers TC, Noorlander A, Stoopen G, and Arrizabalaga-Larrañaga A
- Subjects
- Animals, Cattle, Kidney drug effects, Kidney chemistry, Kidney metabolism, Models, Biological, Meat analysis, Tissue Distribution, Red Meat analysis, Acetaminophen urine, Acetaminophen blood, Acetaminophen pharmacokinetics, Anti-Inflammatory Agents, Non-Steroidal blood, Anti-Inflammatory Agents, Non-Steroidal analysis
- Abstract
Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) and paracetamol can be administered off-label to cattle. Since the use of these veterinary medicines in cattle may pose a public health risk after meat consumption, it is important to translate measured concentrations in urine and tissues into concentrations in meat for human consumption. A generic physiologically-based kinetic (PBK) model for cattle can enable this translation. In this work, a beef cattle PBK model was applied to calculate the relationships between concentrations in different bovine tissues and those were compared to measured concentrations in different matrices. Sixty-seven kidney samples, the corresponding urine and meat samples, and available 19 serum samples were analysed. Overall, 70% of the PBK model predictions are within a 2-fold factor and relationships for kidney/meat, urine/meat, and plasma/meat ratios were established. The conversions of measured kidney concentrations into meat concentrations were mostly within a factor two, while those based on plasma and urine were underpredicted. Based on these ratios, plasma and urine could be used as an appropriate surrogate matrix for a fast, simple in vivo sample screening test under field conditions, such as in local farms and slaughterhouses, to predict a maximum residue level exceedance in meat, reducing the number of test samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)
- Published
- 2024
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