Literature DB >> 8641326

Determination of phenobarbitone population clearance values for South African children.

J H Botha1, A L Gray, R Miller.   

Abstract

Non-liner Mixed Effects Modelling (NON-MEM) was used to estimate phenobarbitone population clearance values for South African children, using 52 serum levels gathered from 32 patients during their routine care. NONMEM was also used to evaluate the influence of fixed effects such as weight, age and concomitant medication. The final model describing phenobarbitone clearance was CL = [Exp(0.0288 Wt - 2.53)]M, where CL clearance (l x h(-1)), Exp = the base of the natural logarithm, Wt = patient weight (kg) and M = a scaling factor for concomitant medication with a value of 1 for patients on phenobarbitone monotherapy, 0.62 for those receiving concomitant valproate and 0.87 for those patients receiving concomitant carbamazepine or phenytoin. Mean (95% confidence interval) phenobarbitone clearance values were 7.6 ml x h(-1) x kg(-1) (6.2, 9.0 ml x h(-1) x kg(-1) for the monotherapy group, 5.0 ml x h(-1) x hg(-1) (4.0, 6.0 ml x h(-1) x kg(-1)) in the presence of concomitant valproate and 6.8 ml x h(-1) x kg(-1) (5.6, 8.0 ml x h(-1) x kg(-1)) in the presence of concomitant carbamazepine or phenytoin. These values are similar to those previously reported from both traditional and NONMEM pharmacokinetic studies.

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Year:  1995        PMID: 8641326     DOI: 10.1007/bf00194954

Source DB:  PubMed          Journal:  Eur J Clin Pharmacol        ISSN: 0031-6970            Impact factor:   2.953


  12 in total

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Journal:  Eur J Clin Pharmacol       Date:  1977-12-02       Impact factor: 2.953

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Authors:  Janthima Methaneethorn; Nattawut Leelakanok
Journal:  Eur J Clin Pharmacol       Date:  2020-10-19       Impact factor: 2.953

2.  Nonlinear mixed effects modelling approach in investigating phenobarbital pharmacokinetic interactions in epileptic patients.

Authors:  Katarina Vučićević; Marija Jovanović; Bojana Golubović; Sandra Vezmar Kovačević; Branislava Miljković; Žarko Martinović; Milica Prostran
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Review 3.  Bayesian forecasting in paediatric populations.

Authors:  M M Fernández de Gatta; M J García; J M Lanao; A Domínguez-Gil
Journal:  Clin Pharmacokinet       Date:  1996-11       Impact factor: 6.447

Review 4.  Role of population pharmacokinetics in drug development. A pharmaceutical industry perspective.

Authors:  E Samara; R Granneman
Journal:  Clin Pharmacokinet       Date:  1997-04       Impact factor: 6.447

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