Tissue Distribution and Pharmacokinetic Characteristics of Aztreonam Based on Multi-Species PBPK Model

Abstract

Background/Objectives: As a monocyclic β-lactam antibiotic, aztreonam has regained attention recently because combining it with β-lactamase inhibitors helps fight drug-resistant bacteria. This study aimed to systematically characterize the plasma and tissue concentration-time profiles of aztreonam in rats, mice, dogs, monkeys, and humans by developing a multi-species, physiologically based pharmacokinetic (PBPK) model. Methods: A rat PBPK model was optimized and validated using plasma concentration-time curves determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) following intravenous administration, with reliability confirmed through another dose experiment. The rat model characteristics, modeling experience, ADMET Predictor (11.0) software prediction results, and allometric scaling were used to extrapolate to mouse, human, dog, and monkey models. The tissue-to-plasma partition coefficients (K_p values) were predicted using GastroPlus (9.0) software, and the sensitivity analyses of key parameters were evaluated. Finally, the cross-species validation was performed using the average fold error (AFE) and absolute relative error (ARE). Results: The cross-species validation showed that the model predictions were highly consistent with the experimental data (AFE < 2, ARE < 30%), but the deviation of the volume of distribution (V_ss) in dogs and monkeys suggested the need to supplement the species-specific parameters to optimize the prediction accuracy. The K_p values revealed a high distribution of aztreonam in the kidneys (K_p = 2.0-3.0), which was consistent with its clearance mechanism dominated by renal excretion. Conclusions: The PBPK model developed in this study can be used to predict aztreonam pharmacokinetics across species, elucidating its renal-targeted distribution and providing key theoretical support for the clinical dose optimization of aztreonam, the assessment of target tissue exposure in drug-resistant bacterial infections, and the development of combination therapy strategies.

Keywords: aztreonam; concentration-time profile; multi-species extrapolation; physiologically based pharmacokinetic model.

Figure 1

The model structure of the physiologically based pharmacokinetic (PBPK) model after the intravenous injection of aztreonam.

Figure 2

The observed and predicted concentration-time curves of aztreonam in rats (i.v.) of 50 mg/kg (A) and 20 mg/kg (B), (mean ± SD, n = 6).

Figure 3

Correlation between observed and predicted values of aztreonam in rats (i.v.) of 50 mg/kg (A) and 20 mg/kg (B).

Figure 4

The fold error of all of the observed and predicted concentration points in the rat model.

Figure 5

The observed and predicted concentrations of aztreonam in the kidney (A), liver (B), lung (C), and spleen (D) in rats (i.v.) of 20 mg/kg, (mean ± SD, n = 6).

Figure 5

The observed and predicted concentrations of aztreonam in the kidney (A), liver (B), lung (C), and spleen (D) in rats (i.v.) of 20 mg/kg, (mean ± SD, n = 6).

Figure 6

Correlation between observed and predicted values of aztreonam in kidney (A), liver (B), lung (C), and spleen (D) in rats (i.v.) of 20 mg/kg.

Figure 7

The observed and predicted concentrations of aztreonam in mice (A), humans (B), dogs (C), and monkeys (D).

Figure 8

The fold error of all of the observed and predicted concentration points in the mouse, human, dog, and monkey models.

Figure 9

Correlation between observed and predicted values of aztreonam in mice (A), humans (B), dogs (C), and monkeys (D).

Figure 10

Sensitivity of predicted AUC_0–∞ of aztreonam to changes in R_bp, f_up, Log D, CL_liver, and CL_kidney of PBPK model in rat (A), mouse (B), human (C), dog (D), and monkey (E).