A mathematical model-based analysis of the time-kill kinetics of ceftazidime/avibactam against Pseudomonas aeruginosa

Comprehensive stability analysis of 13 β-lactams and β-lactamase inhibitors in in vitro media, and novel supplement dosing strategy to mitigate thermal drug degradation

Non-clinical antibiotic development relies on in vitro susceptibility and infection model studies. Validating the achievement of the targeted drug concentrations is essential to avoid under-estimation of drug effects and over-estimation of resistance emergence. While certain β-lactams (e.g., imipenem) and β-lactamase inhibitors (BLIs; clavulanic acid) are believed to be relatively unstable, limited tangible data on their stability in commonly used in vitro media are known. We aimed to determine the thermal stability of 10 β-lactams and 3 BLIs via LC-MS/MS in cation-adjusted Mueller Hinton broth at 25 and 36°C as well as agar at 4 and 37°C, and in water at -20, 4, and 25°C. Supplement dosing algorithms were developed to achieve broth concentrations close to their target over 24 h. During incubation in broth (pH 7.25)/agar, degradation half-lives were 16.9/21.8 h for imipenem, 20.7/31.6 h for biapenem, 29.0 h for clavulanic acid (studied in broth only), 23.1/71.6 h for cefsulodin, 40.6/57.9 h for doripenem, 46.5/64.6 h for meropenem, 50.8/97.7 h for cefepime, 61.5/99.5 h for piperacillin, and >120 h for all other compounds. Broth stability decreased at higher pH. All drugs were ≥90% stable for 72 h in agar at 4°C. Degradation half-lives in water at 25°C were >200 h for all drugs except imipenem (14.7 h, at 1,000 mg/L) and doripenem (59.5 h). One imipenem supplement dose allowed concentrations to stay within ±31% of their target concentration. This study provides comprehensive stability data on β-lactams and BLIs in relevant in vitro media using LC-MS/MS. Future studies are warranted applying these data to antimicrobial susceptibility testing and assessing the impact of β-lactamase-related degradation.

Pharmacokinetic/pharmacodynamic analysis of ceftazidime/avibactam and fosfomycin combinations in an in vitro hollow fiber infection model against multidrug-resistant Escherichia coli

IMPORTANCE

Mechanistic understanding of pharmacodynamic interactions is key for the development of rational antibiotic combination therapies to increase efficacy and suppress the development of resistances. Potent tools to provide those insights into pharmacodynamic drug interactions are semi-mechanistic modeling and simulation techniques. This study uses those techniques to provide a detailed understanding with regard to the direction and strength of the synergy of ceftazidime-avibactam and ceftazidime-fosfomycin in a clinical Escherichia coli isolate expressing extended spectrum beta-lactamase (CTX-M-15 and TEM-4) and carbapenemase (OXA-244) genes. Enhanced killing effects in combination were identified as a driver of the synergy and were translated from static time-kill experiments into the dynamic hollow fiber infection model. These findings in combination with a suppression of the emergence of resistance in combination emphasize a potential clinical benefit with regard to increased efficacy or to allow for dose reductions with maintained effect sizes to avoid toxicity.

Evaluation of in vitro pharmacodynamic drug interactions of ceftazidime/avibactam and fosfomycin in Escherichia coli

BACKGROUND

Combination therapy can increase efficacy of antibiotics and prevent emergence of resistance. Ceftazidime/avibactam and fosfomycin may be empirically combined for this purpose, but a systematic and quantitative evaluation of this combination is needed.

OBJECTIVES

In this study, a systematic analysis of the pharmacodynamic interactions of ceftazidime/avibactam and fosfomycin in clinical and isogenic Escherichia coli strains carrying genes coding for several carbapenemases or ESBLs was performed and pharmacodynamic interactions were quantified by modelling and simulations.

METHODS

Pharmacodynamic interactions were evaluated in 'dynamic' chequerboard experiments with quantification of viable bacteria in eight isogenic and six clinical E. coli strains. Additionally, supplemental time-kill experiments were performed and genomic analyses were conducted on representative fosfomycin-resistant subpopulations. Models were fitted to all data using R and NONMEM®.

RESULTS

Synergistic drug interactions were identified for 67% of the clinical and 75% of the isogenic isolates with a mean EC50 reduction of >50%. Time-kill experiments confirmed the interactions and modelling quantified EC50 reductions up to 97% in combination and synergy prevented regrowth of bacteria by enhanced killing effects. In 9 out of 12 fosfomycin-resistant mutants, genomic analyses identified previously reported mutations.

CONCLUSIONS

The broad synergistic in vitro activity of ceftazidime/avibactam and fosfomycin confirms the potential of the application of this drug combination in clinics. The substantial reduction of the EC50 in combination may allow use of lower doses or treatment of organisms with higher MIC values and encourage further research translating these findings into the clinical setting.

All Roads Lead to Rome: Enhancing the Probability of Target Attainment with Different Pharmacokinetic/Pharmacodynamic Modelling Approaches

In light of rising antimicrobial resistance and a decreasing number of antibiotics with novel modes of action, it is of utmost importance to accelerate development of novel treatment options. One aspect of acceleration is to understand pharmacokinetics (PK) and pharmacodynamics (PD) of drugs and to assess the probability of target attainment (PTA). Several in vitro and in vivo methods are deployed to determine these parameters, such as time-kill-curves, hollow-fiber infection models or animal models. However, to date the use of in silico methods to predict PK/PD and PTA is increasing. Since there is not just one way to perform the in silico analysis, we embarked on reviewing for which indications and how PK and PK/PD models as well as PTA analysis has been used to contribute to the understanding of the PK and PD of a drug. Therefore, we examined four recent examples in more detail, namely ceftazidime-avibactam, omadacycline, gepotidacin and zoliflodacin as well as cefiderocol. Whereas the first two compound classes mainly relied on the ‘classical’ development path and PK/PD was only deployed after approval, cefiderocol highly profited from in silico techniques that led to its approval. Finally, this review shall highlight current developments and possibilities to accelerate drug development, especially for anti-infectives.

The primary pharmacology of ceftazidime/avibactam: resistance in vitro

This article reviews resistance to ceftazidime/avibactam as an aspect of its primary pharmacology, linked thematically with recent reviews of the basic in vitro and in vivo translational biology of the combination (J Antimicrob Chemother 2022; 77: 2321-40 and 2341-52). In Enterobacterales or Pseudomonas aeruginosa, single-step exposures to 8×  MIC of ceftazidime/avibactam yielded frequencies of resistance from <∼0.5 × 10-9 to 2-8 × 10-9, depending on the host strain and the β-lactamase harboured. β-Lactamase structural gene mutations mostly affected the avibactam binding site through changes in the Ω-loop: e.g. Asp179Tyr (D179Y) in KPC-2. Other mutations included ones proposed to reduce the permeability to ceftazidime and/or avibactam through changes in outer membrane structure, up-regulated efflux, or both. The existence, or otherwise, of cross-resistance between ceftazidime/avibactam and other antibacterial agents was also reviewed as a key element of the preclinical primary pharmacology of the new agent. Cross-resistance between ceftazidime/avibactam and other β-lactam-based antibacterial agents was caused by MBLs. Mechanism-based cross-resistance was not observed between ceftazidime/avibactam and fluoroquinolones, aminoglycosides or colistin. A low level of general co-resistance to ceftazidime/avibactam was observed in MDR Enterobacterales and P. aeruginosa. For example, among 2821 MDR Klebsiella spp., 3.4% were resistant to ceftazidime/avibactam, in contrast to 0.07% of 8177 non-MDR isolates. Much of this was caused by possession of MBLs. Among 1151 MDR, XDR and pandrug-resistant isolates of P. aeruginosa from the USA, 11.1% were resistant to ceftazidime/avibactam, in contrast to 3.0% of 7452 unselected isolates. In this case, the decreased proportion susceptible was not due to MBLs.

The primary pharmacology of ceftazidime/avibactam: in vivo translational biology and pharmacokinetics/pharmacodynamics (PK/PD)

This review describes the translational in vivo and non-clinical pharmacokinetics/pharmacodynamics (PK/PD) research that supported clinical trialling and subsequently licensing approval of ceftazidime/avibactam, a new β-lactam/β-lactamase inhibitor combination aimed at the treatment of infections by Enterobacterales and Pseudomonas aeruginosa. The review thematically follows on from the co-published article, Nichols et al. (J Antimicrob Chemother 2022; dkac171). Avibactam protected ceftazidime in animal models of infection with ceftazidime-resistant, β-lactamase-producing bacteria. For example, a single subcutaneous dose of ceftazidime at 1024 mg/kg yielded little effect on the growth of ceftazidime-resistant, blaKPC-2-carrying Klebsiella pneumoniae in the thighs of neutropenic mice (final counts of 4 × 108 to 8 × 108 cfu/thigh). In contrast, co-administration of avibactam in a 4:1 ratio (ceftazidime:avibactam) was bactericidal in the same model (final counts of 2 × 104 to 3 × 104 cfu/thigh). In a rat abdominal abscess model, therapy with ceftazidime or ceftazidime/avibactam (4:1 w/w) against blaKPC-2-positive K. pneumoniae resulted in 9.3 versus 3.3 log cfu/abscess, respectively, after 52 h. With respect to PK/PD, in Monte Carlo simulations, attainment of unbound drug exposure targets (ceftazidime fT>8 mg/L and avibactam fT>1 mg/L, each for 50% of the dosing interval) for the labelled dose of ceftazidime/avibactam (2 and 0.5 g, respectively, q8h by 2 h IV infusion), including dose adjustments for patients with impaired renal function, ranged between 94.8% and 99.6% of patients, depending on the infection modelled.

Pharmacodynamic Parameters of Pharmacokinetic/Pharmacodynamic (PK/PD) Integration Models

Pharmacokinetic/pharmacodynamic (PK/PD) integration models are used to investigate the antimicrobial activity characteristics of drugs targeting pathogenic bacteria through comprehensive analysis of the interactions between PK and PD parameters. PK/PD models have been widely applied in the development of new drugs, optimization of the dosage regimen, and prevention and treatment of drug-resistant bacteria. In PK/PD analysis, minimal inhibitory concentration (MIC) is the most commonly applied PD parameter. However, accurately determining MIC is challenging and this can influence the therapeutic effect. Therefore, it is necessary to optimize PD indices to generate more rational results. Researchers have attempted to optimize PD parameters using mutant prevention concentration (MPC)-based PK/PD models, multiple PD parameter-based PK/PD models, kill rate-based PK/PD models, and others. In this review, we discuss progress on PD parameters for PK/PD models to provide a valuable reference for drug development, determining the dosage regimen, and preventing drug-resistant mutations.

Application of Semi-Mechanistic Pharmacokinetic and Pharmacodynamic Model in Antimicrobial Resistance

Antimicrobial resistance is a major public health issue. The pharmacokinetic/pharmacodynamic (PK/PD) model is an essential tool to optimize dosage regimens and alleviate the emergence of resistance. The semi-mechanistic PK/PD model is a mathematical quantitative tool to capture the relationship between dose, exposure, and response, in terms of the mechanism. Understanding the different resistant mechanisms of bacteria to various antibacterials and presenting this as mathematical equations, the semi-mechanistic PK/PD model can capture and simulate the progress of bacterial growth and the variation in susceptibility. In this review, we outline the bacterial growth model and antibacterial effect model, including different resistant mechanisms, such as persisting resistance, adaptive resistance, and pre-existing resistance, of antibacterials against bacteria. The application of the semi-mechanistic PK/PD model, such as the determination of PK/PD breakpoints, combination therapy, and dosage optimization, are also summarized. Additionally, it is important to integrate the PD effect, such as the inoculum effect and host response, in order to develop a comprehensive mechanism model. In conclusion, with the semi-mechanistic PK/PD model, the dosage regimen can be reasonably determined, which can suppress bacterial growth and resistance development.

Predicting Antimicrobial Activity at the Target Site: Pharmacokinetic/Pharmacodynamic Indices versus Time-Kill Approaches

Antibiotic dosing strategies are generally based on systemic drug concentrations. However, drug concentrations at the infection site drive antimicrobial effect, and efficacy predictions and dosing strategies should be based on these concentrations. We set out to review different translational pharmacokinetic-pharmacodynamic (PK/PD) approaches from a target site perspective. The most common approach involves calculating the probability of attaining animal-derived PK/PD index targets, which link PK parameters to antimicrobial susceptibility measures. This approach is time efficient but ignores some aspects of the shape of the PK profile and inter-species differences in drug clearance and distribution, and provides no information on the PD time-course. Time–kill curves, in contrast, depict bacterial response over time. In vitro dynamic time–kill setups allow for the evaluation of bacterial response to clinical PK profiles, but are not representative of the infection site environment. The translational value of in vivo time–kill experiments, conversely, is limited from a PK perspective. Computational PK/PD models, especially when developed using both in vitro and in vivo data and coupled to target site PK models, can bridge translational gaps in both PK and PD. Ultimately, clinical PK and experimental and computational tools should be combined to tailor antibiotic treatment strategies to the site of infection.

Model-Informed Drug Development for Anti-Infectives: State of the Art and Future

Model-informed drug development (MIDD) has a long and rich history in infectious diseases. This review describes foundational principles of translational anti-infective pharmacology, including choice of appropriate measures of exposure and pharmacodynamic (PD) measures, patient subpopulations, and drug-drug interactions. Examples are presented for state-of-the-art, empiric, mechanistic, interdisciplinary, and real-world evidence MIDD applications in the development of antibacterials (review of minimum inhibitory concentration-based models, mechanism-based pharmacokinetic/PD (PK/PD) models, PK/PD models of resistance, and immune response), antifungals, antivirals, drugs for the treatment of global health infectious diseases, and medical countermeasures. The degree of adoption of MIDD practices across the infectious diseases field is also summarized. The future application of MIDD in infectious diseases will progress along two planes; "depth" and "breadth" of MIDD methods. "MIDD depth" refers to deeper incorporation of the specific pathogen biology and intrinsic and acquired-resistance mechanisms; host factors, such as immunologic response and infection site, to enable deeper interrogation of pharmacological impact on pathogen clearance; clinical outcome and emergence of resistance from a pathogen; and patient and population perspective. In particular, improved early assessment of the emergence of resistance potential will become a greater focus in MIDD, as this is poorly mitigated by current development approaches. "MIDD breadth" refers to greater adoption of model-centered approaches to anti-infective development. Specifically, this means how various MIDD approaches and translational tools can be integrated or connected in a systematic way that supports decision making by key stakeholders (sponsors, regulators, and payers) across the entire development pathway.

Evaluation of the post-antibiotic effect in vivo for the combination of a β-lactam antibiotic and a β-lactamase inhibitor: ceftazidime-avibactam in neutropenic mouse thigh and lung infections

The post-antibiotic effect (PAE) of ceftazidime-avibactam in vivo was evaluated using models of thigh- and lung-infection with Pseudomonas aeruginosa in neutropenic mice. In thigh-infected mice, the PAE was negative (-2.18 to -0.11 h) for three of four strains: caused by a 'burst' of rapid bacterial growth after the drug concentrations had fallen below their pre-specified target values. With lung infection, PAE was positive, and longer for target drug concentrations in ELF (>2 h) than plasma (1.69-1.88 h). The time to the start of regrowth was quantified as a new parameter, PAE_R, which was positive (0.35-1.00 h) in both thigh- and lung-infected mice. In the context that measurements of the PAE of β-lactam/β-lactamase inhibitor combinations in vivo have not previously been reported, it is noted that the negative values were consistent with previous measurements of the PAE of ceftazidime-avibactam in vitro and of ceftazidime alone in vivo.

Semimechanistic Pharmacodynamic Modeling of Aztreonam-Avibactam Combination to Understand Its Antimicrobial Activity Against Multidrug-Resistant Gram-Negative Bacteria

Aztreonam‐avibactam (ATM‐AVI) is a promising combination to treat serious infections caused by multidrug‐resistant (MDR) pathogens. Three distinct mechanisms of action have been previously characterized for AVI: inhibition of ATM degradation by β‐lactamases, proper bactericidal effect, and enhancement of ATM bactericidal activity. The aim of this study was to quantify the individual contribution of each of the three AVI effects. In vitro static time‐kill studies were performed on four MDREnterobacteriaceae with different β‐lactamase profiles. β‐Lactamase activity was characterized by measuring ATM concentrations over 27 hours. Data were analyzed by a semimechanistic pharmacodynamics modeling approach. Surprisingly, even though AVI prevented ATM degradation, the combined bactericidal activity was mostly explained by the enhancement of ATM effect within clinical range of ATM (5–125 mg/L) and AVI concentrations (0.9–22.5 mg/L). 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.

Pharmacodynamic Attainment of the Synergism of Meropenem and Fosfomycin Combination against Pseudomonas aeruginosa Producing Metallo-β-Lactamase

Fosfomycin combined with other antimicrobials has shown good efficacy against multidrug-resistant (MDR) bacteria in both in vitro and clinical studies; however, the activity of fosfomycin combined with other antimicrobials against metallo-β-lactamase (MBL)-producing Pseudomonas aeruginosa strains has not been tested. The objective of this study was to determine the synergism and optimal intravenous dosing regimens of fosfomycin with meropenem against MDR and MBL-producing P. aeruginosa strains. The MICs of both antimicrobials were determined by the checkerboard method and analyzed by two synergism tests with 19 clones of P. aeruginosa isolates, 10 of which were MBL producers. A pharmacodynamic (PD) analysis was performed for meropenem (administered at 1 g every 8 h [q8h], 1.5 g every 6 h [q6h], and 2 g q8h) and fosfomycin (administered at 4 g q8h, 4 g q6h, 6 g q8h, and 8 g q8h) regimens with a dose reduction for renal impairment by determining the probability of target attainment (PTA) for target PD indices of meropenem (the percentage of the time in a 24-h duration at which the free drug concentration remains above the MIC [fT _>MIC], ≥40%) and fosfomycin (the ratio of the area under the free drug concentration-versus-time curve over 24 h and the MIC [fAUC/MIC], ≥40.8). The combination reduced the MIC₅₀ and MIC₉₀ by 8-fold. Seven (44%) isolates with MICs in the intermediate or resistant ranges became sensitive to meropenem. For the MBL-producing isolates, the combination resulted in 40% of isolates becoming sensitive to meropenem. The meropenem regimens reached a PTA of ≥90% (MIC = 4 μg/ml) in 6 (32%) isolates when they were used as monotherapy and 13 (68%) isolates when they were combined with fosfomycin. None of the fosfomycin monotherapy regimens reached the PTA of ≥90% (MIC = 16 μg/ml). When combined with meropenem, the fosfomycin regimens reached the PTA of ≥90% in 14 (74%) isolates. The increase in pharmacodynamic activities resulting from the synergistic action of meropenem with fosfomycin demonstrates the potential relevance of this combination to fight infections caused by MDR and MBL-producing P. aeruginosa strains.

A model-based analysis of pharmacokinetic-pharmacodynamic (PK/PD) indices of avibactam against Pseudomonas aeruginosa

OBJECTIVE

The aim of the present work was to use a semi-mechanistic pharmacokinetic-pharmacodynamic (PK/PD) model developed from in vitro time-kill measurements with P. aeruginosa to compare different pharmacodynamic indices derived from simulated human avibactam exposures, with respect to their degree of correlation with the modelled bacterial responses.

METHODS

A mathematical model of the effect of ceftazidime-avibactam on the growth dynamics of P. aeruginosa was used to simulate bacterial responses to modelled human exposures from fractionated avibactam dosing regimens with a fixed ceftazidime dosing regimen (2 or 8 g q8h as a 2-h infusion). The relatedness of the 24-h change in bacterial density and avibactam exposure parameters was evaluated to determine exposure parameter that closely correlated with bacterial growth/killing responses.

RESULTS

Frequent dosing was associated with higher efficacy, resulting in a reduction of avibactam daily dose. The best-fit PD index of avibactam determined from the simulation was fT > C_T of 1 mg/L avibactam and q8h was the longest dosing interval able to achieve 2-log kill: 41-87% (3.3 h to 7.0 h out of 8-h interval, respectively). The avibactam exposure magnitude required to achieve a 2-log kill in the simulations was dependent on the susceptibility of the bacterial isolate to ceftazidime.

CONCLUSIONS

Avibactam activity in combination with ceftazidime against multidrug resistant P. aeruginosa correlated with fT > C_T. Setting a threshold avibactam concentration to 1 mg/L, superimposed over a simulated human-like exposure of ceftazidime, achieved at least 2-log kill for the clinical dose of 500 mg q8h avibactam as a 2-h infusion, depending on the minimum inhibitory concentration of ceftazidime alone.

Ceftazidime-Avibactam Population Pharmacokinetic Modeling and Pharmacodynamic Target Attainment Across Adult Indications and Patient Subgroups

Ceftazidime‐avibactam is a novel β‐lactam/β‐lactamase inhibitor combination for the treatment of serious infections caused by resistant gram‐negative pathogens. Population pharmacokinetic (PopPK) models were built to incorporate pharmacokinetic (PK) data from five phase III trials in patients with complicated intra‐abdominal infection (cIAI), complicated urinary tract infection (cUTI), or nosocomial (including ventilator‐associated) pneumonia. Ceftazidime and avibactam pharmacokinetics were well‐described by two‐compartment disposition models, with creatinine clearance (CrCL) the key covariate determining clearance variability. Steady‐state ceftazidime and avibactam exposure for most patient subgroups differed by ≤ 20% vs. healthy volunteers. Probability of PK/pharmacodynamic (PD) target attainment (free plasma ceftazidime > 8 mg/L and avibactam > 1 mg/L for ≥ 50% of dosing interval) was ≥ 94.9% in simulations for all patient subgroups, including indication and renal function categories. No exposure‐microbiological response relationship was identified because target exposures were achieved in almost all patients. These modeling results support the approved ceftazidime‐avibactam dosage regimens (2000‐500 mg every 8 hours, adjusted for CrCL ≤ 50 mL/min).

Antibacterial Activity of Human Simulated Epithelial Lining Fluid Concentrations of Ceftazidime-Avibactam Alone or in Combination with Amikacin Inhale (BAY41-6551) against Carbapenem-Resistant Pseudomonas aeruginosa and Klebsiella pneumoniae

The role of inhalational combination therapy when treating carbapenem-resistant Pseudomonas aeruginosa and Klebsiella pneumoniae with newer beta-lactam/beta-lactamase inhibitors has not been established. Using a 72-h in vitro pharmacodynamic chemostat model, we simulated the human exposures achieved in epithelial lining fluid (ELF) following intravenous treatment with ceftazidime-avibactam (CZA) 2.5 g every 8 h (q8h) alone and in combination with inhaled amikacin (AMK-I) 400 mg q12h, a reformulated aminoglycoside designed for inhalational administration, against three P. aeruginosa isolates (CZA [ceftazidime/avibactam] MICs, 4/4 to 8/4 μg/ml; AMK-I MICs, 8 to 64 μg/ml) and three K. pneumoniae isolates (CZA MICs, 1/4 to 8/4 μg/ml; AMK-I MICs, 32 to 64 μg/ml). Combination therapy resulted in a significant reduction in 72-h CFU compared with that of CZA monotherapy against two of three P. aeruginosa isolates (-4.14 log₁₀ CFU/ml, P = 0.027; -1.42 log₁₀ CFU/ml, P = 0.020; and -0.4 log₁₀ CFU/ml, P = 0.298) and two of three K. pneumoniae isolates (0.04 log₁₀ CFU/ml, P = 0.963; -4.34 log₁₀ CFU/ml, P < 0.001; and -2.34 log₁₀ CFU/ml, P = 0.021). When measured by the area under the bacterial growth curve (AUBC) over 72 h, significant reductions were observed in favor of the combination regimen against all six isolates tested. AMK-I combination therapy successfully suppressed CZA resistance development in one K. pneumoniae isolate harboring bla_KPC-3 that was observed during CZA monotherapy. These studies suggest a beneficial role for combination therapy with intravenous CZA and inhaled AMK when treating pneumonia caused by carbapenem-resistant Gram-negative bacteria.