Literature DB >> 29945226

Probabilistic Physiologically Based Pharmacokinetic Model for Penicillin G in Milk From Dairy Cows Following Intramammary or Intramuscular Administrations.

Miao Li1, Ronette Gehring1, Jim E Riviere1, Zhoumeng Lin1.   

Abstract

Penicillin remains one of the most frequently identified violative drug residues in food-producing animals. The predominant violations of penicillin were found in cull dairy cows. In the United States, procaine penicillin G is approved to be used in dairy cows through intramuscular (IM) and intramammary (IMM) administrations. Physiologically based pharmacokinetic (PBPK) models are useful tools to predict withdrawal intervals and tissue residues of drugs in food animals to ensure food safety, especially for extralabel drug use due to the scarcity of experimental data after extralabel administrations. Currently, no PBPK model is available to predict penicillin concentrations in milk. A population PBPK model with a physiologically based compartment for the mammary gland was established for penicillin G in dairy cows. The model predicted the tissue and milk residues well based on comparison with data from previous pharmacokinetic studies. The predicted milk discard interval of procaine penicillin G administered at 10 times the label dose for 3 repeated IM administrations was 182 h, and 122 h at 4 times the label dose after 3 repeated IMM infusions. Predicted results showed that even 4 times label dose did not lead to violative tissue residues in healthy dairy cows with IMM infusions. The predominant violations found in cull dairy cows may be caused by altered pharmacokinetics due to mastitis, other diseases, and/or interactions with other drugs, which have impacts on penicillin distribution and elimination. The current PBPK model can help predict milk discard interval for penicillin following extralabel use through IM and IMM administrations.

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Year:  2018        PMID: 29945226     DOI: 10.1093/toxsci/kfy067

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.849


  6 in total

Review 1.  Physiological parameter values for physiologically based pharmacokinetic models in food-producing animals. Part I: Cattle and swine.

Authors:  Zhoumeng Lin; Miao Li; Yu-Shin Wang; Lisa A Tell; Ronald E Baynes; Jennifer L Davis; Thomas W Vickroy; Jim E Riviere
Journal:  J Vet Pharmacol Ther       Date:  2020-04-08       Impact factor: 1.786

Review 2.  Pharmacometrics: The Already-Present Future of Precision Pharmacology.

Authors:  Lorena Cera Bandeira; Leonardo Pinto; Cláudia Martins Carneiro
Journal:  Ther Innov Regul Sci       Date:  2022-08-18       Impact factor: 1.337

3.  Development and Application of a Water Temperature Related Physiologically Based Pharmacokinetic Model for Enrofloxacin and Its Metabolite Ciprofloxacin in Rainbow Trout.

Authors:  Fan Yang; Fang Yang; Dan Wang; Chao-Shuo Zhang; Han Wang; Zhe-Wen Song; Hao-Tian Shao; Mei Zhang; Meng-Li Yu; Yang Zheng
Journal:  Front Vet Sci       Date:  2021-01-25

4.  Development of a Gestational and Lactational Physiologically Based Pharmacokinetic (PBPK) Model for Perfluorooctane Sulfonate (PFOS) in Rats and Humans and Its Implications in the Derivation of Health-Based Toxicity Values.

Authors:  Wei-Chun Chou; Zhoumeng Lin
Journal:  Environ Health Perspect       Date:  2021-03-17       Impact factor: 9.031

5.  Optimization and Validation of Dosage Regimen for Ceftiofur against Pasteurella multocida in Swine by Physiological Based Pharmacokinetic-Pharmacodynamic Model.

Authors:  Kun Mi; Shanju Pu; Yixuan Hou; Lei Sun; Kaixiang Zhou; Wenjin Ma; Xiangyue Xu; Meixia Huo; Zhenli Liu; Changqing Xie; Wei Qu; Lingli Huang
Journal:  Int J Mol Sci       Date:  2022-03-28       Impact factor: 5.923

6.  An Interactive Generic Physiologically Based Pharmacokinetic (igPBPK) Modeling Platform to Predict Drug Withdrawal Intervals in Cattle and Swine: A Case Study on Flunixin, Florfenicol, and Penicillin G.

Authors:  Wei-Chun Chou; Lisa A Tell; Ronald E Baynes; Jennifer L Davis; Fiona P Maunsell; Jim E Riviere; Zhoumeng Lin
Journal:  Toxicol Sci       Date:  2022-07-28       Impact factor: 4.109

  6 in total

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