Gender- or age-related binding characteristics of valproic acid to serum proteins in adult patients with epilepsy

Kodama, Yasuo; Kodama, Hirofumi; Kuranari, Masae; Tsutsumi, Kimiko; Ono, Shunsuke; Yukawa, Eiji; Fujimura, Akio

doi:10.1016/s0939-6411(01)00151-5

Cited by 19 publications

(15 citation statements)

References 27 publications

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“…Data suggest that unbound fraction increases in elderly patients [43,44] and this may has an effect on result interpretation [45]. These agerelated differences may be important among adult [46] but not children patients [47], suggesting a confusing factor that should not be ignored when studying pharmacogenomics in adult patients. In addition, changes in liver function [43,44,48] may also contribute as a confusing age-related factor leading to discrepancies found in literature.…”

Section: Discussionmentioning

confidence: 99%

UGT1A6 - and UGT2B7 -Related Valproic Acid Pharmacogenomics According to Age Groups and Total Drug Concentration Levels

et al. 2016

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Section: Discussionmentioning

confidence: 99%

UGT1A6 - and UGT2B7 -Related Valproic Acid Pharmacogenomics According to Age Groups and Total Drug Concentration Levels

et al. 2016

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“…Analysis was performed with the non‐linear mixed effects modelling program ( nonmem ™ version V; GloboMax, Ellicott City, MD, USA). In this analysis, the unbound fraction is assumed to vary according to the Langmuir equation (19, 20), in which the total serum concentration of VPA ( C t ) in the j th record of the i th patient is described as follows, taking into account intra‐individual variability, ɛ : where C b and C f designate the bound and unbound serum concentrations of VPA, respectively. B m (μg/mL) is the apparent maximum concentration of the binding site of VPA, and K d (μg/mL) is the apparent dissociation constant of VPA.…”

Section: Methodsmentioning

confidence: 99%

“…Analysis was performed with the non-linear mixed effects modelling program (NONMEM NONMEM ä version V; GloboMax, Ellicott City, MD, USA). In this analysis, the unbound fraction is assumed to vary according to the Langmuir equation (19,20), in which the total serum concentration of VPA (C t ) in the jth record of the ith patient is described as follows, taking into account intra-individual variability, e:…”

Section: Methodsmentioning

confidence: 99%

Characterization of non-linear relationship between total and unbound serum concentrations of valproic acid in epileptic children

Ueshima¹,

Aiba²,

Makita³

et al. 2008

Journal of Clinical Pharmacy and Therapeutics

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“…The binding becomes saturated when VPA concentrations are above 50 mg l −1 , resulting in a disproportionate increase in VPA concentrations . Several factors can affect VPA protein binding such as age, concomitant medications, renal and hepatic diseases and pregnancy status , resulting in a high variability in apparent volume of distribution ranging from 0.1 to 0.5 l kg −1 .…”

Section: Introductionmentioning

confidence: 99%

A systematic review of population pharmacokinetics of valproic acid

Methaneethorn

2018

Brit J Clinical Pharma

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Keywords nonlinear mixed effect modelling, population pharmacokinetics, systematic review, valproic acid AIMSPopulation pharmacokinetics is an essential tool that helps guide individualized dosing regimens. The aims of this systematic review are to provide knowledge concerning population pharmacokinetics of valproic acid (VPA) and to identify factors influencing VPA pharmacokinetic variability. METHODSPubMed and Embase databases were systematically searched from inception to June, 2017. Relevant articles from reference lists were also included. All population pharmacokinetic studies of VPA conducted in humans and that employed a nonlinear mixed effect modelling approach were included in this review. RESULTSTwenty-six studies were included in this review. Most studies characterized VPA pharmacokinetics as a one-compartment model. Three studies reported a two-compartment model. Body weight, dose and age were significant predictors for VPA volume of distribution (V d ). The estimated V d for one-compartment models ranged from 8.4 to 23.3 l. For two-compartment models, peripheral volumes of distribution ranged from 4.08 to 42.1 l. Frequently reported significant predictors for VPA clearance (CL VPA ) included body weight, VPA dose, concomitant medications, gender and age. The estimated CL VPA ranged from 0.206 to 1.154 l h À1 and the inter-individual variability ranged from 13.40 to 35.90%. Two studies reported population pharmacokinetics/pharmacodynamics of VPA in patients with epilepsy. Seventeen studies evaluated the performance of their final models. CONCLUSIONSSignificant predictors influencing VPA pharmacokinetics as well as model methodologies are highlighted in this review. For clinical application, CL VPA could be predicted using body weight, VPA dose, concomitant medications, gender or age. For future research, there is a knowledge gap regarding population pharmacokinetics/pharmacodynamics of VPA in a population other than epileptic patients.British Journal of Clinical Pharmacology Br J Clin Pharmacol (2018) 84 816-834 816

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Gender- or age-related binding characteristics of valproic acid to serum proteins in adult patients with epilepsy

Cited by 19 publications

References 27 publications

UGT1A6 - and UGT2B7 -Related Valproic Acid Pharmacogenomics According to Age Groups and Total Drug Concentration Levels

UGT1A6 - and UGT2B7 -Related Valproic Acid Pharmacogenomics According to Age Groups and Total Drug Concentration Levels

Characterization of non-linear relationship between total and unbound serum concentrations of valproic acid in epileptic children

A systematic review of population pharmacokinetics of valproic acid

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