A pharmacodynamic approach to the estimate of carbamazepine autoinduction

Abstract

Population-based pharmacokinetic prediction algorithms have been developed for several medications. A fundamental assumption has been that the kinetics remain constant over time. Carbamazepine (CBZ), however, induces its own metabolism in a concentration- and time-dependent manner. A Bayesian estimation program is presented that models the changing catabolic enzyme activity, linearly related to hepatic microsomal enzyme concentration, along with the serum drug concentration. An Emax model is used for enzyme formation with respect to drug concentration: elimination of enzyme activity is modeled as a first-order process. This program was tested in 22 drug-naive outpatients begun on CBZ monotherapy. The 1 week concentrations were used to prospectively predict concentrations at 1 month of therapy and were very close to actual measurements: prediction bias (mean error of prediction) = -0.1 micrograms/mL and precision (median absolute error of prediction) = 1.2 micrograms/mL. Comparison estimates, made by assuming a constant concentration/dose ratio, had bias = 2.6 micrograms/mL (p < 0.001) and precision = 2.2 micrograms/mL (p = 0.01). We conclude that (1) CBZ autoinduction is not complete after 1 week of therapy and (2) the methodology permits accurate estimation of CBZ pharmacokinetics.