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Comparison of Pharmacokinetic Effects of Ibuprofen Based on Three Statistical Methods

Published: 21 March 2021 Publication History

Abstract

Ibuprofen is an antipyretic and analgesic anti-inflammatory drug. In order to study the pharmacokinetic characteristics of Chinese healthy adults after ibuprofen injection, this article establishes a pharmacokinetic nonlinear mixed effect model to analyze the blood concentration and clinical characteristics of ibuprofen of 12 healthy volunteers after a single dose. Three statistical methods, FO (First-order), FOCE-I (First-order conditional estimation with interaction), and BAYES (Markov chain Monte Carlo Bayesian) are used to estimate the parameters of the population pharmacokinetics, then analyze and compare in terms of relative standard error, goodness of fit and convergence speed. BAYES is suitable for higher estimation requirements of goodness of fit, FOCE-I is suitable for estimation that needs to consider residuals and inter-individual variation, and FO is suitable for the evaluation of massive medical data, in which the estimands needs to be obtained with higher convergence speed.

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cover image ACM Other conferences
BIC '21: Proceedings of the 2021 International Conference on Bioinformatics and Intelligent Computing
January 2021
445 pages
ISBN:9781450390002
DOI:10.1145/3448748
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • University of Arizona: University of Arizona

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Published: 21 March 2021

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Author Tags

  1. ibuprofen
  2. nonlinear mixed effects model
  3. population pharmacokinetic effects
  4. statistical methods

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