Literature DB >> 27839691

Modeling of aceclofenac metabolism to major metabolites in healthy volunteers.

Eunyoung Kim1, Chunhwa Ihm2, Wonku Kang3.   

Abstract

Aceclofenac has been used widely as a potent analgesic and anti-inflammatory drug. Aceclofenac is converted to 4'-hydroxyaceclofenac and diclofenac via CYP2C9-mediated hydroxylation and hydrolysis, respectively. CYP2C9 also mediates the hydroxylation of diclofenac to yield 4'-hydroxydiclofenac and the hydrolysis of 4'-hydroxyaceclofenac to 4'-hydroxydiclofenac. We aimed to model the metabolism of aceclofenac in volunteers using a compartmental modeling approach. After an oral dose of 100 mg aceclofenac in volunteers, plasma concentrations of aceclofenac and its three metabolites were measured. The pharmacokinetics of aceclofenac and the sequential formation of its three metabolites were analyzed using ADAPT 5. The delay parameter shifted the plasma aceclofenac concentration-time profile to the right and provided a large improvement of fit. Two compartments were needed to fit the aceclofenac and 4'-hydroxyaceclofenac data, and one additional compartment was sufficient to describe the time courses of the generated plasma concentrations of diclofenac and 4'-hydroxydiclofenac. The metabolism rate constant for 4'-hydroxyaceclofenac was much greater than that for diclofenac. The generation rate constant of 4'-hydroxydiclofenac from diclofenac was greater than that of its generation from 4'-hydroxyaceclofenac. Our model fully describes the time course of plasma aceclofenac concentration as well as the formation and disposition of its three major metabolites in volunteers.
Copyright © 2016 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

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Keywords:  4′-Hydroxydiclofenac; 4′-Hydroxydiclofenac, Diclofenac; Aceclofenac; Human; Metabolism; Pharmacokinetic modeling

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Year:  2016        PMID: 27839691     DOI: 10.1016/j.dmpk.2016.10.001

Source DB:  PubMed          Journal:  Drug Metab Pharmacokinet        ISSN: 1347-4367            Impact factor:   3.614


  1 in total

1.  Trends in Ambulatory Analgesic Usage after Myocardial Infarction: A Nationwide Cross-Sectional Study of Real-World Data.

Authors:  Sun-Young Jung; Seung Yeon Song; Eunyoung Kim
Journal:  Healthcare (Basel)       Date:  2022-02-26
  1 in total

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