Characterization of Pseudomonas aeruginosa resistance to ceftolozane-tazobactam due to ampC and/or ampD mutations observed during treatment using semi-mechanistic PKPD modeling

A double ampC (AmpCG183D) and ampD (AmpDH157Y) genes mutations have been identified by whole genome sequencing in a Pseudomonas aeruginosa (PaS) that became resistant (PaR) in a patient treated by ceftolozane/tazobactam (C/T). To precisely characterize the respective contributions of these mutations on the decreased susceptibility to C/T and on the parallel increased susceptibility to imipenem (IMI), mutants were generated by homologous recombination in PAO1 reference strain (PAO1- AmpCG183D, PAO1-AmpDH157Y, PAO1-AmpCG183D/AmpDH157Y) and in PaR (PaR-AmpCPaS/AmpDPaS). Sequential time-kill curve experiments were conducted on all strains and analyzed by semi-mechanistic PKPD modeling. A PKPD model with adaptation successfully described the data, allowing discrimination between initial and time-related (adaptive resistance) effects of mutations. With PAO1 and mutant-derived strains, initial EC50 values increased by 1.4, 4.1, and 29-fold after AmpCG183D , AmpDH157Y and AmpCG183D/AmpDH157Y mutations, respectively. EC50 values were increased by 320, 12.4, and 55-fold at the end of the 2 nd experiment. EC50 of PAO1-AmpCG183D/AmpDH157Y was higher than that of single mutants at any time of the experiments. Within the PaR clinical background, reversal of AmpCG183D, and AmpDH157Y mutations led to an important decrease of EC50 value, from 80.5 mg/L to 6.77 mg/L for PaR and PaR-AmpCPaS/AmpDPaS, respectively. The effect of mutations on IMI susceptibility mainly showed that the AmpCG183D mutation prevented the emergence of adaptive resistance. The model successfully described the separate and combined effect of AmpCG183D and AmpDH157Y mutations against C/T and IMI, allowing discrimination and quantification of the initial and time-related effects of mutations. This method could be reproduced in clinical strains to decipher complex resistance mechanisms.

Pharmacokinetic and pharmacodynamic properties of polymyxin B in Escherichia coli and Klebsiella pneumoniae murine infection models

BACKGROUND

Although polymyxin B has been in use since the late 1950s, there have been limited studies done to unravel its pharmacokinetics (PK) and pharmacodynamics (PD) index.

METHODS

We determined, in neutropenic infected mice, the PK, plasma protein binding and PK/PD index best correlating with efficacy for Escherichia coli and Klebsiella pneumoniae strains.

RESULTS

The pharmacokinetic profile showed non-linear PK; dose was significantly correlated with absorption rate and clearance. The inhibitory sigmoid dose-effect model for the fCmax/MIC index of E. coli fitted best, but was only modestly higher than the R2 of %fT>MIC and fAUC/MIC (R2 0.91-0.93). For K. pneumoniae the fAUC/MIC index had the best fit, which was slightly higher than the R2 of %fT>MIC and fCmax/MIC (R2 0.85-0.91). Static targets of polymyxin B fAUC/MIC were 27.5-102.6 (median 63.5) and 5.9-60.5 (median 11.6) in E. coli and in K. pneumoniae isolates, respectively. A 1 log kill effect was only reached in two E. coli isolates and one K. pneumoniae. The PTA with the standard dosing was low for isolates with MIC >0.25 mg/L.

CONCLUSIONS

This study confirms that fAUC/MIC can describe the exposure-response relationship for polymyxin B. The 1 log kill effect was achieved in the minority of the isolates whereas polymyxin B PK/PD targets cannot be attained for the majority of clinical isolates with the standard dosing regimen, indicating that polymyxin B may be not effective against serious infections as monotherapy.

Variability of murine bacterial pneumonia models used to evaluate antimicrobial agents

Antimicrobial resistance has become one of the greatest threats to human health, and new antibacterial treatments are urgently needed. As a tool to develop novel therapies, animal models are essential to bridge the gap between preclinical and clinical research. However, despite common usage of in vivo models that mimic clinical infection, translational challenges remain high. Standardization of in vivo models is deemed necessary to improve the robustness and reproducibility of preclinical studies and thus translational research. The European Innovative Medicines Initiative (IMI)-funded “Collaboration for prevention and treatment of MDR bacterial infections” (COMBINE) consortium, aims to develop a standardized, quality-controlled murine pneumonia model for preclinical efficacy testing of novel anti-infective candidates and to improve tools for the translation of preclinical data to the clinic. In this review of murine pneumonia model data published in the last 10 years, we present our findings of considerable variability in the protocols employed for testing the efficacy of antimicrobial compounds using this in vivo model. Based on specific inclusion criteria, fifty-three studies focusing on antimicrobial assessment against Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii were reviewed in detail. The data revealed marked differences in the experimental design of the murine pneumonia models employed in the literature. Notably, several differences were observed in variables that are expected to impact the obtained results, such as the immune status of the animals, the age, infection route and sample processing, highlighting the necessity of a standardized model.

Expert workshop summary: Advancing toward a standardized murine model to evaluate treatments for antimicrobial resistance lung infections

The rise in antimicrobial resistance (AMR), and increase in treatment-refractory AMR infections, generates an urgent need to accelerate the discovery and development of novel anti-infectives. Preclinical animal models play a crucial role in assessing the efficacy of novel drugs, informing human dosing regimens and progressing drug candidates into the clinic. The Innovative Medicines Initiative-funded “Collaboration for prevention and treatment of MDR bacterial infections” (COMBINE) consortium is establishing a validated and globally harmonized preclinical model to increase reproducibility and more reliably translate results from animals to humans. Toward this goal, in April 2021, COMBINE organized the expert workshop “Advancing toward a standardized murine model to evaluate treatments for AMR lung infections”. This workshop explored the conduct and interpretation of mouse infection models, with presentations on PK/PD and efficacy studies of small molecule antibiotics, combination treatments (β-lactam/β-lactamase inhibitor), bacteriophage therapy, monoclonal antibodies and iron sequestering molecules, with a focus on the major Gram-negative AMR respiratory pathogens Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii. Here we summarize the factors of variability that we identified in murine lung infection models used for antimicrobial efficacy testing, as well as the workshop presentations, panel discussions and the survey results for the harmonization of key experimental parameters. The resulting recommendations for standard design parameters are presented in this document and will provide the basis for the development of a harmonized and bench-marked efficacy studies in preclinical murine pneumonia model.

Pharmacokinetic-pharmacodynamic models for time courses of antibiotic effects: VSI: Antimicrobial Pharmacometrics

Pharmacokinetic-pharmacodynamic (PKPD) models have emerged as valuable tools for the characterisation and translation of antibiotic effects, and consequently for drug development and therapy. In contrast to traditional PKPD concepts for antibiotics like MIC and PKPD indices, PKPD models enable to describe the continuous, often species- or population-dependent time course of antimicrobial effects, commonly considering mechanistic pathogen- and drug-related knowledge. This review presents a comprehensive overview of previously published PKPD models describing repeated measurements of antibiotic effects. We conducted a literature review to identify PKPD models based on (i) antibiotic compounds, (ii) Gram-positive or Gram-negative pathogens, and (iii) in vitro or in vivo longitudinal colony forming unit data. We identified 132 publications released between 1963 and 2021, including models based on exposure with single antibiotics (n=92) and drug combinations (n=40), as well as different experimental settings (e.g., static/traditional dynamic/hollow-fibre/animal time-kill models, n=90/27/32/11). An interactive, fully searchable table summarises the details of each model, i.e. variants and mechanistic elements of PKPD submodels capturing observed bacterial growth, regrowth, drug effects, and interactions. Furthermore, the review highlights main purposes of PKPD model development, including the translation of preclinical PKPD to clinical settings and the assessment of varied dosing regimens and patient characteristics for their impact on clinical antibiotic effects. In summary, this comprehensive overview of PKPD models shall assist in identifying PKPD modelling strategies to describe growth, killing, regrowth and interaction patterns for pathogen-antibiotic combinations over time and ultimately facilitate model-informed antibiotic translation, dosing and drug development.

PKPD Modeling of the Inoculum Effect of Acinetobacter baumannii on Polymyxin B in vivo

The reduction in antimicrobial activity at high bacterial counts is a microbiological phenomenon known as the inoculum effect (IE). In a previous in vitro study, a significant IE was observed for polymyxin B (PMB) against a clinical isolate of Acinetobacter baumannii, and well described by a new pharmacokinetic-pharmacodynamic model. Few in vivo studies have investigated the impact of inoculum size on survival or antibiotic efficacy. Therefore, our objective was to confirm the influence of inoculum size of this A. baumannii clinical isolate on PMB in vivo effect over time. Pharmacokinetics and pharmacodynamics of PMB after a single subcutaneous administration (1, 15 and 40 mg/kg) were studied in a neutropenic murine thigh infection model. The impact of A. baumannii inoculum size (10⁵, 10⁶ and 10⁷ CFU/thigh) on PMB efficacy was also evaluated. In vivo PMB PK was well described by a two-compartment model including saturable absorption from the subcutaneous injection site and linear elimination. The previous in vitro PD model was modified to adequately describe the decrease of PMB efficacy with increased inoculum size in infected mice. The IE was modeled as a decrease of 32% in the in vivo PMB bactericidal effect when the starting inoculum increases from 10⁵ to 10⁷ CFU/thigh. Although not as important as previously characterized in vitro an IE was confirmed in vivo.

Efficacy of EBL-1003 (apramycin) against Acinetobacter baumannii lung infections in mice

OBJECTIVES

Novel therapeutics are urgently required for the treatment of carbapenem-resistant Acinetobacter baumannii (CRAB) causing critical infections with high mortality. Here we assessed the therapeutic potential of the clinical-stage drug candidate EBL-1003 (crystalline free base of apramycin) in the treatment of CRAB lung infections.

METHODS

The genotypic and phenotypic susceptibility of CRAB clinical isolates to aminoglycosides and colistin was assessed by database mining and broth microdilution. The therapeutic potential was assessed by target attainment simulations on the basis of time-kill kinetics, a murine lung infection model, comparative pharmacokinetic analysis in plasma, epithelial lining fluid (ELF) and lung tissue, and pharmacokinetic/pharmacodynamic (PKPD) modelling.

RESULTS

Resistance gene annotations of 5451 CRAB genomes deposited in the National Database of Antibiotic Resistant Organisms (NDARO) suggested >99.9% of genotypic susceptibility to apramycin. Low susceptibility to standard-of-care aminoglycosides and high susceptibility to EBL-1003 were confirmed by antimicrobial susceptibility testing of 100 A. baumannii isolates. Time-kill experiments and a mouse lung infection model with the extremely drug-resistant CRAB strain AR Bank #0282 resulted in rapid 4-log CFU reduction both in vitro and in vivo. A single dose of 125 mg/kg EBL-1003 in CRAB-infected mice resulted in an AUC of 339 h × μg/mL in plasma and 299 h × μg/mL in ELF, suggesting a lung penetration of 88%. PKPD simulations suggested a previously predicted dose of 30 mg/kg in patients (creatinine clearance (CLCr) = 80 mL/min) to result in >99% probability of -2 log target attainment for MICs up to 16 μg/mL.

CONCLUSIONS

This study provides proof of concept for the efficacy of EBL-1003 in the treatment of CRAB lung infections. Broad in vitro coverage, rapid killing, potent in vivo efficacy, and a high probability of target attainment render EBL-1003 a strong therapeutic candidate for a priority pathogen for which treatment options are very limited.

A Generic Multi-Compartmental CNS Distribution Model Structure for 9 Drugs Allows Prediction of Human Brain Target Site Concentrations

Purpose

Predicting target site drug concentration in the brain is of key importance for the successful development of drugs acting on the central nervous system. We propose a generic mathematical model to describe the pharmacokinetics in brain compartments, and apply this model to predict human brain disposition.

Methods

A mathematical model consisting of several physiological brain compartments in the rat was developed using rich concentration-time profiles from nine structurally diverse drugs in plasma, brain extracellular fluid, and two cerebrospinal fluid compartments. The effect of active drug transporters was also accounted for. Subsequently, the model was translated to predict human concentration-time profiles for acetaminophen and morphine, by scaling or replacing system- and drug-specific parameters in the model.

Results

A common model structure was identified that adequately described the rat pharmacokinetic profiles for each of the nine drugs across brain compartments, with good precision of structural model parameters (relative standard error <37.5%). The model predicted the human concentration-time profiles in different brain compartments well (symmetric mean absolute percentage error <90%).

Conclusions

A multi-compartmental brain pharmacokinetic model was developed and its structure could adequately describe data across nine different drugs. The model could be successfully translated to predict human brain concentrations.

Electronic supplementary material

The online version of this article (doi:10.1007/s11095-016-2065-3) contains supplementary material, which is available to authorized users.