論文

The pharmacokinetics of zonisamide was studied using routine therapeutic drug monitoring data from 68 epileptic patients. The 266 serum concentration data at steady-state after repetitive oral administration were analyzed using the nonlinear mixed effects model (NONMEM) program designed for estimation of population pharmacokinetic parameters. A one-compartment model with dose- dependent clearance was used for the pharmacokinetic analysis of zonisamide. The volume of distribution (V) was estimated to be 1.27 l/kg in a typical 33- kg patient, assuming that the bioavailability of orally administered zonisamide is 100%. The maximal daily dose to be cleared (V(max)) and the concentration giving half maximal clearance (a Michaelis-Menten constant) was 27.6 mg/d/kg and 45.9 μg/ml, respectively. The parameter of a power function of weight to adjust V and V(max) was estimated to be 0.741. In addition, V(max) for zonisamide appears to be 13% increased in patients receiving carbamazepine concurrently. The population pharmacokinetic parameters of zonisamide will be useful for designing dosage regimens in epileptic patients.

The population pharmacodynamics of vamicamide, a new anticholinergic drug, were analyzed by nonlinear mixed effect modeling (NONMEM) in 16 healthy male subjects. The subjects were given orally 18, 36 or 48 mg of vamicamide in a single- or multiple-dose regimen. Serum concentrations of vamicamide were measured frequently; the average urine flow rates (AFRs) estimated simply by dividing the urine volume by the time during voiding, were measured on each occasion of urination. Serum concentrations corresponding to the time of urination were predicted by curve-fitting the individual data (a total of 293 serum data) to a one-compartment model with first-order absorption. The serum concentration-AFR data (381 data pairs) thus obtained were used for NONMEM analysis. The Emax model with baseline controls was used for serum cncentration-AFR response data. The voided volume significantly affected not only the baseline AFR but also maximum response (Emax). However, the concentration which causes half of Emax (EC50) was independent of voided volume and was estimated to be 167 ng/ml. At the serum concentration of 140 ng/ml, which is the maximum serum concentration at therapeutic standard dosage regimen, the percent reduction of AFR from the baseline value was estimated to be 32 and 38% when the voided volume is assumed to be 400 ml, respectively. Despite the wide range of variability in AFR, the NONMEM analysis provided clinically significant concentration-response curves. This population approach appears recommendable for further clinical applications.

The renal handling of tobramycin (TOB), an aminoglycoside antibiotic (AG), was studied using a single-pass isolated perfused rat kidney with moment analysis. In the bolus administration study at tracer concentration (7.4 μM), 32% of the glomerular-filtrated TOB remained in the lumen, but no TOB was found in the vein. This ratio of the luminal uptake was reduced in a dose-dependent manner. Other aminoglycosides such as gentamicin inhibited this uptake, but tetraethylammonium and glucosamine had no effect. In addition, under the alkalinuria condition, TOB uptake was decreased to 67% of the control value. This indicated that TOB has mainly been taken into the renal epithelial cells from their luminal site and that this uptake process was saturable and specific for AGs which have more than one cationic group. The present findings should be helpful in developing a method to reduce the nephrotoxicity of AGs and to identify their toxicity mechanisms.

The present paper reports theoretical equations for the predictive performance of the Bayesian forecasting method. The precision of parameter estimates and predicted concentrations for an individual was described by general equations with the aid of a variance-covariance matrix of parameter estimates that involved the Bayes theorem. The equations were applied to assess the predictive performance of the one-point Bayesian method in association with blood sampling time, the population parameters, and the pharmacostatistical model. The simulation study showed that the prediction error in parameter estimates essentially depended upon the sampling time but the magnitude of dependency was affected by the size of inter-and intraindividual variances. With a smaller value of interindividual variance, the dependency on sampling time was less apparent. Effects of sampling time were further examined using clinical data obtained from 20 patients taking theophylline, and the results were in good agreement with the theoretical consideration. The present general equations are useful to investigate the sampling strategy as well as structural and variance modeling on the predictive performance of the Bayesian method. © 1994 Plenum Publishing Corporation.