Patient characteristics are summarized in Table?1. A one compartment model parameterized in terms of clearance and volume of distribution with a proportional error model best described the plasma concentrations of PG. In the systematic covariate analysis, birth weight was found the most important covariate for clearance causing a drop in OFV of 82 points (P?<?0.001). Birth weight was best implemented on clearance using an allometric function in which a value of 1.69 was estimated for the exponent. When evaluating other covariates, current weight was found the most important covariate for volume of distribution using an allometric function with an estimated exponent of 1.48 (��OFV 48 points, P?<?0.001). Furthermore, a significant difference in volume of distribution was seen between neonates receiving phenobarbital and paracetamol. The volume of distribution was estimated to be 1.77 times higher (95% confidence <a href="http://www.selleckchem.com/products/sotrastaurin-aeb071.html">Sotrastaurin in vitro interval Mdm2 1.35, 2.19) for neonates receiving phenobarbital (��OFV 18 points, P?<?0.001). Finally, further improvement of the model fit was seen when PNA was introduced on clearance using an allometric function with an estimated exponent of 0.201. This last covariate was responsible for the smallest but still significant drop in the objective function (��OFV = 15 points, P?<?0.001). All parameter estimates of the final pharmacokinetic model are summarized in Table?2. The diagnostic plots are represented in Figure?1. By introducing these covariates a large part of the interindividual variability on clearance (65%) as well as on volume of distribution (53%) is explained (Table?2). This is reflected by the estimates of interindividual variability in clearance and volume of distribution which were reduced from 0.69 to 0.12 and 0.64 to 0.18, respectively. The values for the parameter estimates obtained during <a href="http://www.selleckchem.com/products/Cyclopamine.html">http://www.selleckchem.com/ the bootstrap procedure are shown in Table?2. The parameter estimates obtained after bootstrapping were within 8% of the values obtained in the final pharmacokinetic model. Of the total number of runs (n= 1000), 100% were successful and only 34 runs did not have a covariance step. The results of the NPDE analysis are depicted in Figure?2. The histogram follows the normal distribution indicated by the black solid line (Figure?2A). No trend is seen in the NPDE vs. time (Figure?2B) and the NPDE vs. predicted concentrations (Figure?2C). The plot with the individual predicted parameter estimates and population parameter estimates for clearance and volume of distribution vs. the most predictive covariate, birth weight and current body weight respectively, showed that the individual predicted parameter estimates are randomly scattered around the population parameter estimates (figures not provided). The number of ill-conditioning (8.28) was far below the critical value of 1000 meaning that the final pharmacokinetic model was not over-parameterized.

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