SIMULATION FOR POPULATION ANALYSIS OF MICHAELIS-MENTEN ELIMINATION KINETICS

A simulation study was conducted to compare the cost and performance o f various models for population analysis of the steady state pharmacok inetic data arising from a non-compartment model with Michaelis-Menten elimination. The usual Michaelis-Menten model (MM) and its variants p rovide no estimate of the volume of distribution, and generally give p oor estimates of the maximal elimination rate and the Michaelis-Menten constant. The exact solution to the Michaelis-Menten differential equ ation (TRUE) requires a precise analysis method designed for estimatio n of population pharmacokinetic parameters (the first-order conditiona l estimation method) and also considerable computational time to estim ate population mean parameters accurately. The one-compartment model w ith dose-dependent clearance (DDCL). In conjunction with the first-ord er conditional estimation or Laplacian method, ran approximately 20-fo ld faster than TRUE and gave accurate population mean parameters for a drug having a long biological half-life relative to the dosing interv al. These findings suggest that the well-known MM and its variants sho uld be used carefully for the analysis of blood concentrations of a dr ug with Michaelis-Menten elimination kinetics, and that TRUE, in conju nction with a precise analysis method, should be considered for estima ting population pharmacokinetic parameters. in addition, DDCL is a pro mising alternative to TRUE with respect to computation time, when the dosing interval is short relative to the biological half-life of a dru g.