Comparison of Pharmacokinetic Effects of Ibuprofen Based on Three Statistical Methods

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.