Prediction of Drug Disposition in Diabetic Patients by Means of a Physiologically Based Pharmacokinetic Model

• Published in: Clinical pharmacokinetics Vol. 54; no. 2; pp. 179 - 193
• Main Authors: Li, Jia, Guo, Hai-fang, Liu, Can, Zhong, Zeyu, Liu, Li, Liu, Xiao-dong
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.02.2015; Springer Nature B.V
• Subjects: Area Under Curve; Computer Simulation; Diabetes Mellitus, Type 2 - blood; Diabetes Mellitus, Type 2 - drug therapy; Diabetes Mellitus, Type 2 - metabolism; Humans; Hypoglycemic Agents - blood; Hypoglycemic Agents - pharmacokinetics; Internal Medicine; Kidney - metabolism; Liver - metabolism; Male; Medicine; Medicine & Public Health; Models, Biological; Monte Carlo Method; Original Research Article; Pharmacology/Toxicology; Pharmacotherapy; Antipyrine; PBPK Model; Diabetic Patient; Metformin; Glibenclamide
• DOI: 10.1007/s40262-014-0192-8
• ISSN: 0312-5963; 1179-1926

Background and Objective Accumulating evidence has shown that diabetes mellitus may affect the pharmacokinetics of some drugs, leading to alteration of pharmacodynamics and/or toxic effects. The aim of this study was to develop a novel physiologically based pharmacokinetic (PBPK) model for predicting drug pharmacokinetics in patients with type 2 diabetes mellitus quantitatively. Methods Contributions of diabetes-induced alteration of physiological parameters including gastric emptying rates, intestinal transit time, drug metabolism in liver and kidney functions were incorporated into the model. Plasma concentration–time profiles and pharmacokinetic parameters of seven drugs (antipyrine, nisoldipine, repaglinide, glibenclamide, glimepiride, chlorzoxazone, and metformin) in non-diabetic and diabetic patients were predicted using the developed model. The PBPK model coupled with a Monte-Carlo simulation was also used to predict the means and variability of pharmacokinetic parameters. Results The predicted area under the plasma concentration–time curve (AUC) and maximum (peak) concentration ( C max ) were reasonably consistent (<2-fold errors) with the reported values. Sensitivity analysis showed that gut transit time, hepatic enzyme activity, and renal function affected the pharmacokinetic characteristics of these drugs. Shortened gut transit time only decreased the AUC of controlled-released drugs and drugs with low absorption rates. Impairment of renal function markedly altered pharmacokinetics of drugs mainly eliminated via the kidneys. Conclusion All of these results indicate that the developed PBPK model can quantitatively predict pharmacokinetic alterations induced by diabetes.