Effect of treatment and additional disease on pharmacokinetic of @entity1092 in @entity1 with XXXX .

@entity1 @entity2050 @entity1092 @entity2052 @entity302 @entity354 @entity2049
BACKGROUND: Most of bayesian pharmacokinetic studies and the influence of clinical variables have been carried out in adults. PURPOSE: The aim was to estimate population-based pharmacokinetic of @entity1092 ( @entity2052 ) and to determine the effect of treatment and additional disease on its performance in @entity1 with @entity302 . MATERIAL AND METHODS: For the study steady-state serum concentrations of @entity2052 were determined from 108 @entity302 @entity1 (44 females and 64 males) who were receiving the anticonvulsant as main drug of treatment with age range since 1 to 16 years (median 4y, 6m) and weight since 5.2 to 50 kg (median 17.5 kg). All @entity1 had their renal, hepatic and nutritional functions normal. One compartment model using interactive two-stage Bayesian approach was employed in the analysis. RESULTS; Population estimates of CL/F and V/F for @entity2052 were 0.022 +/- 0.013 L/h and 0.217 +/- 0.134 L/kg, respectively. These estimates were significantly affected by weight, age, @entity2049 ( @entity2050 ) and @entity354 ( @entity354 ). The final regression models were: CL/F (L/h) = 0.0696 + 0.0031 (Age) + 0.0075 (Weight); and V/F (L) = 0.674 + 0.0308 (Age) + 0.0756 (Weight). Prediction of @entity2052 serum concentration in other validation group revealed an important improvement in the predictive performance of @entity2052 concentrations in comparison with the basic model that did not include any co-variables. CONCLUSIONS: Based on a population model of @entity1 with @entity302 , the pharmacokinetic of @entity2052 could be altered by weight, age and the administration of @entity2050 and additional @entity354 to @entity302 .
