Population Pharmacokinetics and Limited Sampling Strategy for Therapeutic Drug Monitoring of Polymyxin B in Chinese Patients With Multidrug-Resistant Gram-Negative Bacterial Infections

Peile Wang; Qiwen Zhang; Zhenfeng Zhu; Min Feng; Tongwen Sun; Jing Yang; Xiaojian Zhang

doi:10.3389/fphar.2020.00829

Population Pharmacokinetics and Limited Sampling Strategy for Therapeutic Drug Monitoring of Polymyxin B in Chinese Patients With Multidrug-Resistant Gram-Negative Bacterial Infections

Front Pharmacol. 2020 Jun 5:11:829. doi: 10.3389/fphar.2020.00829. eCollection 2020.

Authors

Peile Wang^{1

2}, Qiwen Zhang^{1

2}, Zhenfeng Zhu^{1

2}, Min Feng³, Tongwen Sun⁴, Jing Yang^{1

2}, Xiaojian Zhang^{1

2}

Affiliations

¹ Department of Pharmacy, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
² Henan Key Laboratory of Precision Clinical Pharmacy, Zhengzhou University, Zhengzhou, China.
³ Department of ICU, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
⁴ Department of General ICU, First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

Abstract

Polymyxin B is used as a last therapeutic option for the treatment of multidrug-resistant Gram-negative bacterial infections. This study aimed to develop a population pharmacokinetic model and limited sampling strategy, a method to estimate the area under the concentration curve (AUC) by using a limited number of samples, to assist therapeutic drug monitoring of polymyxin B in Chinese patients. Population pharmacokinetic analysis was performed using Phoenix^® NLME with data obtained from 46 adult patients at steady state. Various demographic variables were investigated as potential covariates for population pharmacokinetic modeling. The limited sampling strategies based on the Bayesian approach and multiple linear regression were validated using the intraclass correlation coefficient and Bland-Altman analysis. As a result, the data was described by a two-compartment population pharmacokinetic model. Through the modeling, creatinine clearance was found to be a statistically significant covariate influencing polymyxin B clearance. The limited sampling strategies showed the two-point model (C_0h and C_2h) could predict polymyxin B exposure with good linear relativity (r² > 0.98), and the four-point model (C_1h, C1_.5h, C_4h, and C_8h) performed best in predicting polymyxin B AUC (r² > 0.99). In conclusion, this study successfully developed a population pharmacokinetic model and limited sampling strategies that could be applied in clinical practice to assist in therapeutic drug monitoring of polymyxin B in Chinese patients.

Keywords: limited sampling strategy; multidrug-resistant Gram-negative bacterial infection; polymyxin B; population pharmacokinetics; therapeutic drug monitoring.