A Semiphysiological Population Model for Prediction of the Pharmacokinetics of Drugs under Liver and Renal Disease Conditions

Abstract

The application of model-based drug development in special populations becomes increasingly important for clinical trial optimization, mostly by providing a rationale for dose selection and thereby aiding risk-benefit assessment. In this article, a semiphysiological approach is presented, enabling the extrapolation of the pharmacokinetics from healthy subjects to patients with different disease conditions. This semiphysiological approach was applied to solifenacin, using clinical data on total and free plasma and urine concentrations in healthy subjects. The analysis was performed using nonlinear mixed-effects modeling and relied on the use of a general partitioning framework to account for binding to plasma proteins and to nonplasma tissues together with principles from physiology that apply to the main pharmacokinetic process, i.e., bioavailability, distribution, and elimination. Application of these physiology principles allowed quantification of the impact of key physiological parameters (i.e., body composition, glomerular function, liver enzyme capacity, and liver blood flow) on the pharmacokinetics of solifenacin. The prediction of the time course of the drug concentration in liver- and renal-impaired patients only required adjustment of the physiological parameters that are known to change upon liver and renal dysfunction without modifying the pharmacokinetic model structure and/or its respective parameter estimates. Visual predictive checks showed that the approach applied was able to adequately predict the pharmacokinetics of solifenacin in liver- and renal-impaired patients. In addition, better insight into the pharmacokinetic properties of solifenacin was obtained. In conclusion, the proposed semiphysiological approach is attractive for prediction of altered pharmacokinetics of compounds influenced by liver and renal disease conditions.