ABSTRACT
We analyzed mexiletine in Japanese patients using population pharmacokinetics. 139 serum concentration data, which were collected for therapeutic drug monitoring from 121 patients, were used for this analysis. We also investigated influence of age and gender on pharmacokinetics, and age was found to be an influential factor on clearance. The final pharmacokinetic parameters are, CL/F=0.580-0.00369 x AGE (l/h/kg) and Vd/F=6.63 (l/kg). These results should be useful for adjusting the dosage to a patient's age for the prevention of an adverse reaction caused by overexposure.
Subject(s)
Anti-Arrhythmia Agents/pharmacokinetics , Arrhythmias, Cardiac/metabolism , Mexiletine/pharmacokinetics , Adult , Age Factors , Aged , Aged, 80 and over , Arrhythmias, Cardiac/drug therapy , Female , Humans , Male , Middle AgedABSTRACT
The population pharmacokinetic parameters of phenytoin were estimated using routine therapeutic drug monitoring data from 116 epileptic patients. The 531 serum concentration values at steady-state after repetitive oral administration were analyzed using a 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 phenytoin. The volume of distribution (V) was estimated to be 1.231/kg in a typical 42-kg patient, assuming that the bioavailability of orally administered phenytoin is 100%. The maximal elimination rate (V(max)) and the Michaelis-Menten constant (K(m)) were 9.80 mg/d/kg and 9.19 micrograms/ml, respectively. The parameter of power function of weight to adjust V and V(max) was estimated to be 0.463. In addition, K(m) for phenytoin appeared to be 16% increased in patients receiving zonisamide concurrently. The population pharmacokinetic parameters of phenytoin will be useful for designing dosage regimens in epileptic patients.
Subject(s)
Anticonvulsants/pharmacokinetics , Epilepsy/metabolism , Phenytoin/pharmacokinetics , Adolescent , Adult , Age Factors , Anticonvulsants/blood , Biological Availability , Child , Child, Preschool , Dose-Response Relationship, Drug , Epilepsy/epidemiology , Female , Humans , Infant , Japan/epidemiology , Male , Models, Biological , Phenytoin/blood , Population , Statistics as TopicABSTRACT
A simulation study was conducted to compare the cost and performance of various models for population analysis of the steady state pharmacokinetic data arising from a one-compartment model with Michaelis-Menten elimination. The usual Michaelis-Menten model (MM) and its variants provide no estimate of the volume of distribution, and generally give poor estimates of the maximal elimination rate and the Michaelis-Menten constant. The exact solution to the Michaelis-Menten differential equation (TRUE) requires a precise analysis method designed for estimation of population pharmacokinetic parameters (the first-order conditional estimation method) and also considerable computational time to estimate population mean parameters accurately. The one-compartment model with dose-dependent clearance (DDCL), in conjunction with the first-order conditional estimation or Laplacian method, ran approximately 20-fold faster than TRUE and gave accurate population mean parameters for a drug having a long biological half-life relative to the dosing interval. These findings suggest that the well-known MM and its variants should be used carefully for the analysis of blood concentrations of a drug with Michaelis-Menten elimination kinetics, and that TRUE, in conjunction with a precise analysis method, should be considered for estimating population pharmacokinetic parameters. In addition, DDCL is a promising alternative to TRUE with respect to computation time, when the dosing interval is short relative to the biological half-life of a drug.
Subject(s)
Pharmacokinetics , Computer Simulation , Half-Life , Humans , Models, Biological , PopulationABSTRACT
A simulation study was conducted to compare the performance of alternative approaches for analyzing the distorted pharmacodynamic data. The pharmacodynamic data were assumed to be obtained from the natriurertic peptide-type drug, where the diuretic effect arises from the hyperbolic (Emax) dose-response model and is biased by the dose-dependent hypotensive effect. The nonlinear mixed effect model (NONMEM) method enabled assessment of the effects of hemodynamics on the diuretic effects and also quantification of intrinsic diuretic activities, but the standard two-stage (STS) and naive pooled data (NPD) methods did not give accurate estimates. Both the STS and the NONMEM methods performed well for unbiased data arising from a one-compartment model with saturable (Michaelis-Menten) elimination, whereas the NPD method resulted in inaccurate estimates. The findings suggest that nonlinearity and/or bias problems result in poor estimation by NPD and STS analyses and that the NONMEM method is useful for analyzing such nonlinear and distorted pharmacodynamic data.
