Literature DB >> 29274818

Population Pharmacokinetics and Dosing Simulations of Ceftazidime in Chinese Neonates.

Honghong Wang1, Xingang Li2, Shusen Sun3, Guifu Mao4, Ping Xiao1, Chan Fu5, Zhuoxin Liang6, Min Zheng7, Yuling Huang1, Haihong Tang5, Renhao Ou1, Ni Yang1, Xi Ling8, Zhigang Zhao9.   

Abstract

An accurate dosage determination is required in neonates when antibiotics are used. The adult data cannot be simply extrapolated to the pediatric population due to significant individual differences. We aimed to identify factors impacting ceftazidime exposure in neonates and to provide drug dosing guidance to clinicians. Forty-three neonates aged less than 60 days with proven or suspected infections were enrolled in this study. After intravenous administration, blood samples were collected, and plasma ceftazidime concentration was determined using a HPLC method. Pharmacokinetic data were fitted using a nonlinear mixed-effects model approach. One-compartmental model could nicely characterize the ceftazidime in vivo behavior. The covariate test found that the postmenstrual age (day) was strongly associated with systemic drug clearance (L/h), and the effect of body weight (kg) was identified as the covariate on distribution volume (L). Compared with the base model, the addition of covariates improved the goodness-of-fit of the final model. Model validation (bootstrap, visual predictive check, and prediction-corrected visual predictive check) suggested a robust and reliable pharmacokinetic model was developed. Personalized dosage regimens were provided based on model simulations. The intravenous dose should be adjusted according to postmenstrual age, body weight, and minimum inhibitory concentration.
Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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Keywords:  ceftazidime; modeling and simulation; neonates; population pharmacokinetics; postmenstrual age

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Year:  2017        PMID: 29274818     DOI: 10.1016/j.xphs.2017.12.018

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  1 in total

1.  Impact of gender, albumin, and CYP2C19 polymorphisms on valproic acid in Chinese patients: a population pharmacokinetic model.

Authors:  Jinlin Guo; Yayu Huo; Fang Li; Yuanping Li; Zhaojun Guo; Huaqing Han; Yuhong Zhou
Journal:  J Int Med Res       Date:  2020-08       Impact factor: 1.671

  1 in total

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