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An Intestine/Liver Microphysiological System for Drug Pharmacokinetic and Toxicological Assessment
Published on: December 3, 2020
A physiologically-based flow network model for hepatic drug elimination I: regular lattice lobule model
Vahid Rezania1, Rebeccah Marsh, Dennis Coombe
1Department of Physics, University of Alberta, Edmonton, AB T6G 2J1, Canada. jackt@ualberta.ca.
Theoretical Biology & Medical Modelling
|September 7, 2013
Summary
We created a liver lobule model to study drug transport and metabolism. Our findings highlight convection
Area of Science:
- Pharmacokinetics and drug metabolism
- Physiological modeling
- Liver biology
Background:
- Drug distribution in the liver is complex.
- Understanding drug transport within the liver lobule is crucial for predicting efficacy and toxicity.
- Previous models often simplified the role of blood flow in drug distribution.
Purpose of the Study:
- To develop a physiologically-based lattice model of drug transport and metabolism within the liver lobule.
- To investigate the dominant role of convection in drug distribution in well-vascularized liver tissue.
- To compare predicted drug distribution with experimentally observable exit concentrations.
Main Methods:
- Development of a physiologically-based lattice model.
- Incorporation of convective, diffusive, and metabolic processes.
- Simulation of drug transport and concentration gradients within the liver lobule.
- Comparison of simulated lobule exit concentrations with internal predicted distributions.
Main Results:
- Convection plays a dominant role in drug transport within the liver lobule.
- The model provides estimates for convective, diffusive, and reaction contributions to drug disposition.
- Predicted detailed drug distribution inside the lobule correlates with lobule exit concentrations.
- The model allows for prediction of internal drug concentrations from external measurements.
Conclusions:
- Physiologically-based modeling, emphasizing convection, accurately represents drug transport in the liver lobule.
- This approach enhances understanding of drug pharmacokinetics within the liver.
- The model bridges the gap between accessible (exit) and inaccessible (internal) drug concentration data.
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