Applications of Physiologically Based Pharmacokinetic Models in Veterinary Medicine.
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Date
2007-04-06
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Abstract
Classical approaches to pharmacokinetics, such as compartmental and non-compartmental analysis, provide the basis for most dosing regimens and meat and milk withholding intervals. These models are limited by their descriptive nature to dose, route of administration, and species. In addition, current pharmacokinetic modeling approaches are unable to predict possible adverse drug reactions due to drug interactions. As combination drug therapy is rapidly increasing, so too does the chance for an adverse drug reaction due to drug interactions. There is a need within veterinary medicine for more predictive and flexible pharmacokinetic modeling approaches that can also be used to explore the possibilities and consequences of adverse drug reactions.
Physiologically based pharmacokinetic (PBPK) models predict drug disposition based on mass balance. This mechanistic approach is predictive and flexible in terms of dose, route of administration, and species. Current uses of PBPK models include human health risk assessment, design of rational dosing regimens, and mechanistic studies of drug interactions. In veterinary medicine, there are only a few validated models.
Protection of the safety of the food supply is an important application of pharmacokinetics. By federal law, no animal products are allowed into the food chain until drug residue levels are below set tolerance limits. Sulfamethazine is a sulfonamide antibiotic that is commonly found above tolerance limits in swine. Sulfonamide drugs are associated with hypersensitivity reactions in humans and are carcinogenic in certain strains of rats. Thus violative residues could contribute to a significant public health hazard. To address this concern, a PBPK model was designed and validated for intravenous use of sulfamethazine in swine. This model had tissue blocks for all edible tissues. Correlation coefficients for each tissue ranged from 0.86 to 0.99. The model accurately predicted withdrawal intervals after intravenous extralabel drug use. This model was expanded to include population variability and oral route of administration. The model was subjected to Monte Carlo analysis where parameter values were defined by log normal distributions. After validation, this probabilistic PBPK model approach was used to establish the meat withdrawal time for the upper limit of the 95% confidence interval for the 99th percentile of the population for the labeled oral dose. The model predicted a withdrawal time of 21 days.
Sulfamethazine has also been implicated in adverse drug reactions. It was postulated that the altered drug disposition in horses was due to protein binding interactions between sulfamethazine and flunixin meglumine. Flunixin meglumine has recently been approved for use in swine. Thus there is an increased likelihood that a drug interaction could be seen in swine. To explore this possibility, a PBPK model for sulfamethazine was designed that included linear plasma protein binding and competitive inhibition of plasma protein binding due to flunixin meglumine. The validated PBPK model accurately predicted both free and total sulfamethazine concentrations alone and in the presence of flunixin meglumine. The interaction predicted and identified in vivo was transient and would not contribute to a clinically relevant adverse drug reaction. However, this was the first time a validated PBPK model was used to predict drug interactions due to alterations in protein binding.
Based on the success of the PBPK models for sulfamethazine in swine, it can be concluded that the PBPK approach can be effectively applied to problems in veterinary medicine. Ultimately, this type of modeling will enhance the safety and efficacy of dosing regimens while further protecting our food supply. In addition, the investigation of drug interactions based on physiological mechanisms will continue to enhance our understanding of basic pharmacology.
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Keywords
swine, veterinary pharmacology, sulfamethazine, PBPK, physiologically based pharmacokinetic models
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Degree
PhD
Discipline
Comparative Biomedical Sciences
