An Age-Dependent Physiologically Based Pharmokinetic Model of Methadone Distribution and Metabolism
Catherine
Lloyd
Auckland Bioengineering Institute, The University of Auckland
Model Status
This CellML version of the model has been checked in COR and PCEnv. It will recreate published results, although it only models a single organ (the liver) as well as the veins and arteries, and is based on a 5 year old boy. The model cannot replicate the population analysis described in the paper, which needs stochastic tools that are unavailable to CellML at present.
Model Structure
Abstract: Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use in methadone dosing recommendations in pediatric patients for either opioid abstinence or analgesia. Considering the extreme inter-individual variability of absorption and metabolism of methadone, population-based PK would be useful to provide insight into the relationship between dose, blood concentrations, and clinical effects of methadone. To address this need, an age-dependent physiologically based pharmacokinetic (PBPK) model has been constructed to systematically study methadone metabolism and PK. The model will facilitate the design of cost-effective studies that will evaluate methadone PK and PD relationships, and may be useful to guide methadone dosing in children. The PBPK model, which includes whole-body multi-organ distribution, plasma protein binding, metabolism, and clearance, is parameterized based on a database of pediatric PK parameters and data collected from clinical experiments. The model is further tailored and verified based on PK data from individual adults, then scaled appropriately to apply to children aged 0-24 months. Based on measured variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2) concentrations, a Monte-Carlo-based simulation of methadone kinetics in a pediatric population was performed. The simulation predicts extreme variability in plasma concentrations and clearance kinetics for methadone in the pediatric population, based on standard dosing protocols. In addition, it is shown that when doses are designed for individuals based on prior protein expression information, inter-individual variability in methadone kinetics may be greatly reduced.
The complete original paper reference is cited below:
Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model, Feng Yang, Xianping Tong, D. Gail. McCarver, Ronald N. Hines and Daniel A. Beard, 2006,
Journal of Pharmacokinetics and Pharmacodynamics
, volume 33, issue 4.
PubMed ID: 16758333
model diagram
Schematic diagram of a PBPK model consisting of 17 compartments. The lines represent blood flow while the boxes represent organs or systems. Methadone is primarily metabolised in the liver and gastro-intestinal (GI) system, while its elimination mainly occurs through the kidneys. Organs in which methadone are not distributed include skin, adipose, thyroid, pancreas, and bone marrow are grouped together as
others
.
bound concentration of methadone
Partition coefficient of organ
Unbound fraction of methadone
Scaling factor for scaling adult Vmax to infant Vmax
Metabolizing Tissue of Organ
Metabolism of Methadone in Organ
Metabolic rate of methadone
Population-Based Analysis of Methadone Distribution and Metabolism Using an Age-Dependent Physiologically Based Pharmacokinetic Model
Journal of Pharmacokinetics and Pharmacodynamics
2006-00-00 00:00
Time domain
Free Methadone
Free methadone concentration in plasma
Total methadone concentration in the organ's metabolizing tissue
Free methadone concentration in plasma
https://models.physiomeproject.org/exposure/95df296549513e45bca595a9b6011446/yang_tong_mccarver_hines_beard_2006.cellml/view
yang_tong_mccarver_hines_beard_2006_version01
Chris Thompson
Chris Thompson
Age-Dependent Physiologically Based Pharmacokinetic Model of Methadone Distribution and Metabolism
yang_tong_mccarver_hines_beard_2006_version01
Michaelis-Menten constant
Free Methadone
Arterial blood concentration of methadone
Binding Constant
Arterial blood volume
Volumetric blood flow of organ
Michaelis-Menten constant
Total cardiac output
Mixed venous concentration of drug
Mixed venous concentration of drug
Volume of organ
Time domain
Metabolic rate of methadone
Venous blood volume
The University of Auckland, Bioengineering Institute
Geoff Nunns
This CellML version of the model has been checked in COR and PCEnv. It will recreate published results, although it only models a single organ (the liver) as well as the veins and arteries, and is based on a 5 year old boy. The model cannot replicate the population analysis described in the paper, which needs stochastic tools that are unavailable to CellML at present.
The University of Auckland
The Bioengineering Institute
Redirected some variable mapping to recreate published results, also had to input new values for volume of blood.
Fixed the units and one of the equations
Yang et al.'s age-dependent, physiologically based pharmokinetic model of methadone distribution and metabolism.
Catherine Lloyd
This is the CellML description of Yang et al.'s age-dependent, physiologically based pharmokinetic model of methadone distribution and metabolism. In this particular example of the model, the liver has been chosen to represent the organ k, and therefore all the parameter values are specific for this organ. Further, the model has been focused on a 5 year old child.
Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model
Journal of pharmacokinetics and pharmacodynamics
2006-08-00 00:00
Arterial blood concentration of methadone
Bound Methadone
Bound concentration of methadone
Bound concentration of methadone
Number of non-competitive binding sites on the protein molecule
Arterial blood concentration of methadone
Total methadone concentration in the organ's metabolizing tissue
Total cardiac output
Total methadone concentration in the organ's metabolizing tissue
Partition coefficient of organ
Total cardiac output
Partition coefficient of organ
Volumetric blood flow of organ
Time domain
Volumetric blood flow of organ