Estimating bioavailability when clearance varies with time.

The influence of interoccasion variability in clearance on bioavailability estimates from a traditional two-period crossover design is reported for five methods of analysis: (1) the standard crossover analysis, (2) a groupwise, parallel, analysis, (3) and (4) two correction procedures suggested by J.G. Wagner and by P.S. Collier and S. Riegelman, and (5) a pharmacokinetic nonlinear mixed-effects model analysis. Three bioavailability parameters are considered the population mean bioavailability (F), the interindividual variance of bioavailability (omega 2F) and the correlation of bioavailability with clearance [cor (CL,F)]. Data are simulated with different degrees of interoccasion variability and/or non-zero cor(CL,F). With the standard crossover analysis of these data, estimates of F, omega F, and cor(CL,F) are all biased in the presence of interoccasion variability in clearance. Estimates of F and omega 2F obtained from the parallel-group analysis are not reliable because the approach relies on the assumption that cor(CL,F) is zero. The two correction procedures are very sensitive to random error in the estimates of terminal half-life. The mixed-effect model approach produces unbiased estimates of all three bioavailability parameters. These results from simulations are supported by a real data example.