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Drug testing and analysis2025; 18(1); 32-50; doi: 10.1002/dta.3961

A Meta-Analysis of International Flunixin Pharmacokinetics in Horses: Toward Regulatory Harmonization and Individualized Detection Times Using Bayesian Paradigm.

Abstract: Flunixin meglumine is widely used to manage pain and inflammation in horses, and its regulation requires robust pharmacokinetic analysis for harmonization. In this study, we conducted a meta-analysis of flunixin disposition using plasma and urine concentration data from 65 horses across four countries to robustly estimate pharmacokinetic parameters in setting screening limits (SLs) for controlling medications in horses. A population (POP) model was developed using nonlinear mixed-effects model analysis. The irrelevant plasma concentration (IPC) and irrelevant urine concentration (IUC) were determined to be 1.9 and 70.2 ng/mL, respectively, with a typical urine-to-plasma ratio (Rss) of 35.9. Using the current International Federation of Horseracing Authorities (IFHA) screening limits (ISLs) (1 ng/mL for plasma; 100 ng/mL for urine), a longer detection time (DT) was observed for plasma than for urine, especially after multiple doses, as plasma ISL corresponds to a slower terminal elimination phase. Increasing the current plasma ISL from 1 to 3 ng/mL-while keeping the current urine ISL at 100 ng/mL-could better align the plasma and urine DTs. As a limitation of this study, both Standardbred and Thoroughbred data were included, and further data collection is needed to fully ascertain potential breed-specific effects. Moreover, this POP model also enabled relatively accurate Bayesian estimation of individual withdrawal times (WTs) from limited data. Clinicians could apply this Bayesian approach to making informed WT recommendations for horses when sufficient data is available. While existing non-POP statistical models remain viable, they may require a more conservative approach to WT estimation than Bayesian methods.
© 2025 The Author(s). Drug Testing and Analysis published by John Wiley & Sons Ltd.
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Publication Date: 2025-10-25 PubMed ID: 41137541PubMed Central: PMC12796560DOI: 10.1002/dta.3961Google Scholar: Lookup
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  • Journal Article
  • Meta-Analysis

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Research Overview

  • This study performed a meta-analysis of flunixin pharmacokinetics in horses using data from multiple countries to improve the regulation and detection of the drug in equine plasma and urine.
  • The research developed a population pharmacokinetic model to refine screening limits and support individualized withdrawal time recommendations through Bayesian methods.

Background and Purpose

  • Flunixin meglumine is a commonly used medication in horses for pain and inflammation management.
  • Effective regulation requires a robust understanding of how the drug is processed by different horses (pharmacokinetics) to harmonize screening limits internationally.
  • The study aimed to aggregate plasma and urine concentration data across countries to create a comprehensive pharmacokinetic model.
  • The goal was to achieve:
    • Regulatory harmonization of medication screening limits.
    • Improvement of detection time estimates for flunixin in horses.
    • Development of individualized withdrawal time (WT) estimates using Bayesian approaches based on limited data.

Data and Methods

  • Data were collected from 65 horses across four countries, including both Standardbred and Thoroughbred breeds.
  • Both plasma and urine concentrations of flunixin were analyzed.
  • A nonlinear mixed-effects population (POP) pharmacokinetic model was developed to analyze the data.
  • Key pharmacokinetic parameters were estimated to help set meaningful screening limits (SLs), such as:
    • Irrelevant plasma concentration (IPC): 1.9 ng/mL
    • Irrelevant urine concentration (IUC): 70.2 ng/mL
    • Typical urine-to-plasma ratio at steady state (Rss): 35.9

Findings and Interpretation

  • Current screening limits from the International Federation of Horseracing Authorities (IFHA) are:
    • Plasma ISL: 1 ng/mL
    • Urine ISL: 100 ng/mL
  • The study found that with these ISLs, the detection time (DT) for plasma was longer than that for urine, especially after multiple doses.
  • This is because the plasma ISL corresponded to a slower terminal elimination phase of the drug.
  • Simulation results suggested that increasing the plasma ISL to 3 ng/mL, while keeping the urine ISL at 100 ng/mL, better aligned detection times between plasma and urine samples.
  • This adjustment could harmonize regulatory thresholds and provide more consistent control of medication use.

Limitations

  • The model included data from both Standardbred and Thoroughbred horses, which may have inherent breed-specific pharmacokinetic differences.
  • Further data collection is required to confirm whether breed differences significantly affect pharmacokinetics and to refine breed-specific regulation if needed.

Applications and Significance

  • The population pharmacokinetic model supports Bayesian estimation of individual withdrawal times (WT) with limited data.
  • Clinicians can apply this Bayesian approach to more accurately determine when a horse’s flunixin levels have dropped below regulatory limits, improving management of medication withdrawal.
  • Compared to traditional non-population statistical methods, Bayesian methods may offer more precise and less conservative WT estimates, enhancing individualized care and compliance.
  • Overall, this study advances toward international harmonization of flunixin regulation and enables personalized withdrawal time recommendations, promoting fair competition and animal welfare in equine sports.

Cite This Article

APA
Kuroda T, Knych HK, Noble GK, Minamijima Y, Leung GN, Nomura M, Mizobe F, Ishikawa Y, Kusano K, Toutain PL. (2025). A Meta-Analysis of International Flunixin Pharmacokinetics in Horses: Toward Regulatory Harmonization and Individualized Detection Times Using Bayesian Paradigm. Drug Test Anal, 18(1), 32-50. https://doi.org/10.1002/dta.3961

Publication

Drug testing and analysis
ISSN: 1942-7611
NlmUniqueID: 101483449
Country: England
Language: English
Volume: 18
Issue: 1
Pages: 32-50

Researcher Affiliations

Kuroda, Taisuke
  • Clinical Veterinary Medicine Division, Equine Research Institute, Japan Racing Association, Shimotsuke, Japan.
  • Graduate School of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Japan.
Knych, Heather K
  • K.L. Maddy Equine Analytical Chemistry Laboratory (Pharmacology Section), School of Veterinary Medicine, University of California, Davis, California, USA.
  • Department of Molecular Biosciences, School of Veterinary Medicine, University of California, Davis, California, USA.
Noble, Glenys K
  • School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, Wagga Wagga, New South Wales, Australia.
Minamijima, Yohei
  • Drug Analysis Department, Laboratory of Racing Chemistry, Utsunomiya, Japan.
Leung, Gary Ngai-Wa
  • Drug Analysis Department, Laboratory of Racing Chemistry, Utsunomiya, Japan.
Nomura, Motoi
  • Clinical Veterinary Medicine Division, Equine Research Institute, Japan Racing Association, Shimotsuke, Japan.
Mizobe, Fumiaki
  • Equine Department Main Office, Japan Racing Association, Tokyo, Japan.
Ishikawa, Yuhiro
  • Equine Department Main Office, Japan Racing Association, Tokyo, Japan.
Kusano, Kanichi
  • London Representative Office, Japan Racing Association, London, United Kingdom.
Toutain, Pierre-Louis
  • Comparative Biomedical Sciences, The Royal Veterinary College, London, United Kingdom.

MeSH Terms

  • Animals
  • Horses / blood
  • Horses / urine
  • Horses / metabolism
  • Bayes Theorem
  • Clonixin / analogs & derivatives
  • Clonixin / pharmacokinetics
  • Clonixin / blood
  • Clonixin / urine
  • Anti-Inflammatory Agents, Non-Steroidal / pharmacokinetics
  • Anti-Inflammatory Agents, Non-Steroidal / blood
  • Anti-Inflammatory Agents, Non-Steroidal / urine
  • Doping in Sports / prevention & control

Conflict of Interest Statement

The authors declare no conflicts of interest.

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