Semi-mechanistic pharmacodynamics modeling of aztreonam- avibactam combination to understand its antimicrobial activity against multidrug-resistant Gram(-) bacteria

International audienceIntroduction: Aztreonam-avibactam (ATM-AVI) is a promising β-lactam-β-lactamase inhibitor combination to treat serious infections caused by multi-drug resistant (MDR) pathogens including those producing metallo-β-lactamases (MBLs). Three distinct effects have been previously characterized for AVI: inhibition of β-lactamases, proper bactericidal effect and enhancement of ATM bactericidal activity. The aim of this study was to investigate the individual contribution of each of the three AVI effects using a semi-mechanistic PK-PD modeling approach. Materials/methods: ATM MICs were determined both in the absence and in presence of AVI at different concentrations (from 0.004 to 32 mg/L) for four MDR Enterobacteriaceae with different β-lactamase profiles. For static time-kill studies, ATM concentrations were set at 0.25, 0.5, 1, 2 and 4 times the MIC in combination with different AVI concentrations ranging from 0 to 8 mg/L. The effect of AVI alone was also evaluated. The presence of pre-existing resistant bacteria in the initial inoculum was investigated. In order to take into account ATM degradation by β-lactamases, the actual concentrations of ATM and AVI were determined by LC-MS/MS. ATM bactericidal effect and the three different effects of AVI were estimated using NONMEM 7.4. Simulations using the final model were then conducted in order to evaluate the impact of the three AVI effects separately at clinical range of ATM and AVI concentrations.Results: A common structural model with two sub-populations, slightly different from the one previously developed by Sy et al. for ATM-AVI and ceftazidime-AVI, was applied for all strains. There was no transformation between bacterial states, and the fraction of resistant bacteria was fixed at the value determined experimentally. ATM bactericidal effect was modeled as an increase in the killing rate for both subpopulations, according to a sigmoidal Emax model with a higher EC50 for the resistant state explaining regrowth. In addition, the three previously reported effects of AVI could be well characterized by the PK-PD model. Bacterial counts impacted on ATM degradation according to an exponential function and the prevention of degradation by AVI was modeled according to a fractional inhibitory Emax model, except for E. coli strain for which no ATM degradation was observed even in the absence of AVI. AVI bactericidal effect was characterized by a sigmoidal Emax model affecting the susceptible subpopulation. And, the enhancement of ATM bactericidal activity by AVI was modeled as a decrease of ATM EC50 with increasing AVI concentrations using a bi-exponential function. According to the simulation results, among the three AVI effects, the enhancing effect was the most important, leading to a percentage of maximum effect close to 100% whatever the strain. On the other hand, the inhibitory effect of AVI poorly contributed to total effect resulting in bacterial response similar to that for ATM aloneConclusions: Even though AVI prevented ATM degradation, model predicted that the combined bactericidal activity was mostly explained by the enhancement of ATM effect within concentrations currently used in the clinic for ATM alone and AVI in the combination with CAZ. Therefore, when selecting a β-lactamase inhibitor for combination with a β-lactam, its capability to enhance the β-lactam activity should be considered in addition to the spectrum of β-lactamases inhibited