Kinetic evaluation of nonlinear drug elimination by a disposition decomposition analysis. Application to the analysis of the nonlinear elimination kinetics of erythropoietin in adult humans

The disposition–decomposition analysis (DDA) methodology enables isolation of the overall elimination and distribution effects in pharmacokinetics and facilitates analysis which focuses on drug elimination kinetics and does not require a specific structured modeling of drug distribution processes. A computer algorithm enables a curve fitting and a kinetic estimation by integration of the convolution type integrodifferential equation in the DDA. The approach is demonstrated in an analysis of the nonlinear disposition kinetics of erythropoietin (Epo) in 10 healthy, adult human subjects who each received 10, 100, and 500 U/kg iv bolus doses of Epo. The nonlinearity is analyzed according to a Michaelis–Menten type nonlinear elimination function, considering simultaneous fitting to the data from all three doses in each subject. The simultaneous fittings produced estimates of the Michaelis–Menten parameters (mean, % CV) Vm, (901 mU/mL/h, 19.4%) and km (4814 mU/mL, 24.6%). A linear clearance parameter is defined as the asymptotic clearance value approached when the drug level decreases toward zero. The degree of nonlinearity reached from various dosings was quantified in terms of a clearance ratio which is defined as the ratio between the linear clearance and the clearance estimated for the maximum drug concentration encountered at the given dose level. The subjects showed very little nonlinearity at the 10 U/kg dosing with a mean clearance ratio of 1.07 (2.1% CV) A statistically significant increase in the degree of nonlinearity was observed in the Epo elimination kinetics as the dosing level was increased to 100 and 500 U/kg, reaching clearance ratios of 1.66 (14% CV) and 4.33 (27% CV), respectively. A zero value for the global elimination rate parameter in all 30 dosings indicates that Epo's elimination is entirely accounted for by nonlinear pathway(s).