Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage.

Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Research Abstract Details 

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Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Abstract Text:

OBJECTIVE: To estimate individual and population postinduction pharmacokinetics of carbamazepine (CBZ) in epileptic adult and paediatric patients who received chronic CBZ monotherapy. METHODS: We have used the USC*PACK collection of PC programs for the estimations. The preinduction CBZ metabolism was also estimated in 16 volunteers after a single dose of CBZ (200 mg). We used a linear one-compartmental model with oral absorption and found the pharmacokinetic parameter values of CBZ behaviour to be in good agreement with those reported earlier. RESULTS: Serum CBZ concentrations correlated poorly with daily doses in both the adult and child populations. Because of the diversity within the population, use of the mean population model without knowledge of an individual patient's pharmacokinetic characteristics gives poor prediction. In contrast, the individual Bayesian posterior models gave good prediction for all subjects in the population, due to the removal of the interindividual variability. CONCLUSION: This approach permits one to individualize drug therapy for patients even when only sparse therapeutic drug monitoring (TDM) data are available. Future individual CBZ serum level predictions were acceptable from a clinical point of view (mean absolute error = 13.2 +/- 9.7%). The optimal sampling strategy approach helped to design an optimal cost-effective TDM protocol for CBZ therapy management.

Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Publishing Authors By Initials

For similar investigative techniques: epidemiologic methods: statistics as topic: statistics, nonparametric research abstracts see: investigative techniques: epidemiologic methods: statistics as topic: statistics, nonparametric research

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Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: Journal of clinical pharmacy and therapeutics

VOLUME: 26

Page Numbers: 213-23

Journal Abbreviation: J Clin Pharm Ther

ISSN: 0269-4727

DAY: 28

MONTH: Jun

YEAR: 2001

Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Information

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LANGUAGE: eng

NlmUniqueID: 8704308

Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Keywords Mesh Terms:

KEYWORDS: Statistics, Nonparametric

MESH TERMS: metabolism

Chemical & Substance for Abstract: Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage. Information

Substance Name: Carbamazepine

Registry Number: 298-46-4

Grant and Affiliation Information for Population pharmacokinetic modelling of carbamazepine by using the iterative Bayesian (IT2B) and the nonparametric EM (NPEM) algorithms: implications for dosage.

AFFILIATION: Laboratory of Mathematical Modelling, The Research Institute of Physico-Chemical Medicine, Kuusinena str, 4/6-b-101, Moscow, 123 308 Russia. lidos@aha.ru

Country: England

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MEDLINETA: J Clin Pharm Ther

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