Population-based analysis of methadone distribution and metabolism using an age-dependent physiologically based pharmacokinetic model. 2006

Feng Yang, and Xianping Tong, and D Gail McCarver, and Ronald N Hines, and Daniel A Beard
Department of Physiology, Medical College of Wisconsin, Biotechnology and Bioengineering Center, Milwaukee, WI 53226, USA.

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.

UI MeSH Term Description Entries
D007223 Infant A child between 1 and 23 months of age. Infants
D007231 Infant, Newborn An infant during the first 28 days after birth. Neonate,Newborns,Infants, Newborn,Neonates,Newborn,Newborn Infant,Newborn Infants
D008297 Male Males
D008691 Methadone A synthetic opioid that is used as the hydrochloride. It is an opioid analgesic that is primarily a mu-opioid agonist. It has actions and uses similar to those of MORPHINE. (From Martindale, The Extra Pharmacopoeia, 30th ed, p1082-3) Amidone,Biodone,Dolophine,Metadol,Metasedin,Methaddict,Methadone Hydrochloride,Methadose,Methex,Phenadone,Phymet,Physeptone,Pinadone,Symoron,Hydrochloride, Methadone
D008875 Middle Aged An adult aged 45 - 64 years. Middle Age
D008954 Models, Biological Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment. Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D009010 Monte Carlo Method In statistics, a technique for numerically approximating the solution of a mathematical problem by studying the distribution of some random variable, often generated by a computer. The name alludes to the randomness characteristic of the games of chance played at the gambling casinos in Monte Carlo. (From Random House Unabridged Dictionary, 2d ed, 1993) Method, Monte Carlo
D011485 Protein Binding The process in which substances, either endogenous or exogenous, bind to proteins, peptides, enzymes, protein precursors, or allied compounds. Specific protein-binding measures are often used as assays in diagnostic assessments. Plasma Protein Binding Capacity,Binding, Protein
D012044 Regression Analysis Procedures for finding the mathematical function which best describes the relationship between a dependent variable and one or more independent variables. In linear regression (see LINEAR MODELS) the relationship is constrained to be a straight line and LEAST-SQUARES ANALYSIS is used to determine the best fit. In logistic regression (see LOGISTIC MODELS) the dependent variable is qualitative rather than continuously variable and LIKELIHOOD FUNCTIONS are used to find the best relationship. In multiple regression, the dependent variable is considered to depend on more than a single independent variable. Regression Diagnostics,Statistical Regression,Analysis, Regression,Analyses, Regression,Diagnostics, Regression,Regression Analyses,Regression, Statistical,Regressions, Statistical,Statistical Regressions
D002675 Child, Preschool A child between the ages of 2 and 5. Children, Preschool,Preschool Child,Preschool Children

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