Predictive performance of Bayesian method in a simulation work: One-compartment open linear model containing an oral route.

Abstract

The Bayesian weighted least-squares method (BWLS) was evaluated by simulationwork. One hundred simulated patients were created by random number generatorthrough a logarithm transformation. Theophylline was examined as a typical drugwhich obeys a one-compartment open linear model: total body clearance (CL), 0.04±0.02l/hr/kg; volume of distribution (Vd), 0.50±0.09l/kg; rate constant of absorption (ka), 0.96±0.62hr-1. A non-uniform but periodic dosage regimen containing an oral route, designed to give a range of 10 to 20μg/ml of serum drug concentration (SDC) in thesteady-state period, was assumed.The BWLS with one SDC measurement provided time-dependent precision and biasin both CL and Vd estimates; by increasing the time between the sampling and theonset of therapy, the precision in CL esimates increased but the precision in Vd decreased, and BWLS etimated the CL and Vd with a prediction error of approximately 10% and20% respectively, after 14 hr from the onset of therapy (mean half-life was 10.5 hr).The ka could be estimated inaccurately (>110% RMSE). In the predictions of steadystate SDCs, the precision and bias also showed the time-dependent profile as a functionof the sampling times and, moreover, the prediction times: 1.6 to 8.6μg/ml as a rootmean squared error (RMSE), -2.9 to 1.1μg/ml as a mean prediction error (ME).The utilization of two SDC measurements partly improved the predictive performance of BWLS for estimating CL and Vd. From the simulation work it was concluded thatthe BWLS would provide reliable estimations of parameters such as CL and Vd, andclinically acceptable predictions of the subsequent SDCs, given appropriate populationparameter values, means and variances, and sampling times, even when as few as oneor two SDC measurements are available.