An Application of Nonlinear Mixed-Effects Modeling to Pharmacokinetic Data Exhibiting Nonlinear and Time-Dependent Behavior

A population pharmacokinetic (PK) analysis was performed on plasma concentrations of GW468816 observed in dogs after 10, 25, and 50 mg/kg/day repeated intravenous administration. A two-compartment model was fitted to the concentration-time data using the NONMEM program. Dose and time dependency of PK parameters was investigated. Selection of the best model was performed using a stepwise approach. A Michaelis-Menten elimination process was used to describe the PK dose dependency, whereas an interoccasion variability on Vm (the maximum elimination rate of the Michaelis-Menten elimination process) was initially used to describe the time dependency of the PKs, and the final model included an exponential function to account for time variance on Vm. The Km value of the final model was 29.6 μg/mL, whereas Vm was estimated to vary with time from 4.97 μg/h/kg at day 1 to a maximum mean value of 9.64 μg/h/kg at day 14. This approach can be applied to either rich or sparse data leading to estimates of individual parameters by using Bayesian feedback. The overall information obtained can be used to interpret toxicological and pharmacological endpoints and integrated with further in vitro–in vivo studies to supply a comprehensive PK behavior before the first time in human studies.