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. 2025 Dec;57(1):2496792.
doi: 10.1080/07853890.2025.2496792. Epub 2025 May 15.

Influential predictors of azithromycin pharmacokinetics: a systematic review of population pharmacokinetics

Janthima Methaneethorn  1 , Zheng Jiao  2 , Rowan AlEjielat  3 , Totsapol Jirasomprasert  4
Affiliations

Influential predictors of azithromycin pharmacokinetics: a systematic review of population pharmacokinetics

Janthima Methaneethorn et al. Ann Med. 2025 Dec.

Abstract

Introduction: Azithromycin exhibits significant pharmacokinetic variability. Thus, dosage optimization is crucial for optimal therapeutic outcomes. This systematic review aims to analyze the population pharmacokinetics (PopPK) of azithromycin and identify key covariates influencing its pharmacokinetics.

Methods: A systematic search was conducted in PubMed, Scopus, and ScienceDirect databases. Azithromycin PopPK studies conducted using a nonlinear mixed-effects approach in humans were included. Studies published in non-English or non-Thai languages were excluded. Moreover, studies with insufficient information, review articles, or registered protocols were also excluded. The reporting quality of the included studies was assessed using adapted guidelines from a previously published framework. Data on study designs, population characteristics, pharmacokinetic parameters, and influential predictors were summarized. Forest plots were used to determine the influence of covariates on azithromycin pharmacokinetics.

Results: Fifteen studies were included. The volume of distribution (Vd) and the clearance in preterm newborns were approximately 68%-94% and 87%-100% lower than those of adults and children. Pregnant women had approximately 85% higher Vd. Patients with alanine aminotransferase >40 U/L had about 24% lower clearance. Azithromycin clearance slightly decreased with advancing age. There is limited data on the relationship between azithromycin exposure and safety outcomes. Finally, most models were not externally evaluated.

Conclusions: Significant predictors for azithromycin pharmacokinetics were identified in this review. However, the limited external validation of most models restricts their clinical utility. Further research is necessary to confirm the models' external validity.

Prospero registration: CRD42024609484.

Keywords: Azithromycin; Monte Carlo simulations; individualized dose; nonlinear mixed effect model; population pharmacokinetics.

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Conflict of interest statement

No potential conflict of interest was reported by the authors.

Figures

Figure 1.
Figure 1.
A PRISMA flow diagram of the study identification.
Figure 2.
Figure 2.
Forest plot of the covariates influencing azithromycin clearance.
Figure 3.
Figure 3.
The typical clearance values of each study.
See this image and copyright information in PMC

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