Linear relationships in systems with non linear kinetics.

The elimination rate of drug from a capacity-limited one-compartment model can be expressed by equation (1): [formula: see text] Traditionally equation (1) was linearized according to equation (2): [formula: see text] Here, an alternative linear relationships between concentration and the area under the curve of C/(Km + c]) is proposed: [formula: see text] By iteration of Km into equation (3) until the statistic of analysis of variance for the regression is maximized, both Km and Vmax can be obtained. Several cases were considered: a) Intravenous bolus (single dose): Km (mg/L), Vmax (mg/L h), Vd (L) and V (mg/h) can be estimated. b) Extravascular administration (single dose): by the method of residuals it is possible to make additional estimations of FD/Vd (mg/L) and Ka (1/h). c) Bioequivalence studies: with parameters obtained at single dose, the simulated levels at steady-state are considered for the bioequivalence assessments. d) Km, Vmax estimation with two (C,t) points (single dose): double iteration (Km values and interpolated fictitious third points) are needed. e) Multiple dose: [formula: see text] If t2-t1 = T (interval of administration) it is possible to calculate operatives Km, Vmax, FD/Vd and to estimate Css (steady-state concentration). C1 and C2 correspond to different intervals. All the areas were calculated by the trapezoidal rule.

Alternative approach to relative bioavailability and bioequivalence evaluation, with drugs following Michaelis-Menten elimination kinetics.

An alternative approach to bioavailability and bioequivalence assessment is presented. By a modified Wagner-Nelson procedure, the parameters of a monocompartmental model are calculated, after single oral dose administration trials. The usefulness of the procedure described here is that it permits comparison between two different brands of drug in multiple doses, without the need to administer repeated doses. Only one dose is necessary in order to calculate model parameters and infer steady-state levels.