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Updated: Jul 2, 2026

An Intestine/Liver Microphysiological System for Drug Pharmacokinetic and Toxicological Assessment
Published on: December 3, 2020
A physiologically based pharmacokinetic model linking plasma protein binding interactions with drug disposition
J L Buur1, R E Baynes, G W Smith
1Food Animal Residue Avoidance Databank, Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, College of Veterinary Medicine, 4700 Hillsborough St. Raleigh, NC 27606, USA. jbuur@westernu.edu
Drug interactions in swine can alter drug levels. A new model predicts these changes, showing no significant impact on tissue residues, aiding food safety.
Area of Science:
- Pharmacology
- Veterinary Medicine
- Drug Metabolism
Background:
- Combination drug therapy can increase adverse drug reactions through drug-drug interactions.
- Altered disposition of sulfamethazine (SMZ) with flunixin meglumine (FLU) in swine may increase tissue residues.
- Predictive pharmacokinetic modeling is needed to assess drug interaction consequences.
Purpose of the Study:
- To develop a physiologically based pharmacokinetic model linking plasma protein binding interactions to drug disposition for SMZ and FLU in swine.
- To predict the impact of drug interactions on drug disposition and tissue residues.
- To validate model predictions with in vivo data.
Main Methods:
- Development of a physiologically based pharmacokinetic model.
- Incorporation of plasma protein binding interactions into the model.
- In vivo study to confirm drug interaction and assess tissue disposition.
Main Results:
- The model predicted a sustained decrease in total drug concentration and a temporary increase in free drug concentration.
- An in vivo study confirmed the presence of a drug interaction between SMZ and FLU.
- Neither the model nor the in vivo study indicated clinically significant changes in tissue disposition.
Conclusions:
- A novel modeling approach successfully linked plasma protein binding interactions to drug disposition.
- The developed model can predict the clinical impact of drug interactions.
- This approach can aid in designing dosing regimens and ensuring food supply safety by minimizing tissue residues.
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