Contribution of semi-mechanistic modelling to pharmacokinetic/pharmacodynamic studies of antibiotics alone and in combination in the fight against resistant bacteria

La lutte contre les bactéries multirésistantes est une priorité majeure définie par l’Organisation Mondiale de la Santé, puisque les dernières prédictions estiment que les infections par des bactéries multirésistantes feront plus de morts que le cancer d’ici 2050. Dans le contexte actuel, avec un faible nombre de nouveaux antibiotiques mis sur le marché pour lutter contre les bactéries multirésistantes, il est important de d’optimiser l’utilisation des antibiotiques à notre disposition. C’est dans ce but que les modèles semi-mécanistiques servant à analyser les résultats d’études de PK/PD des antibiotiques peuvent être développés. Ces outils mathématiques permettent de quantifier les relations concentration-effet, de molécules seules ou de combinaisons de molécules afin d’optimiser leur efficacité, prévenir les résistances et donc prolonger la durée de vie des antibiotiques. Dans ce travail, après une présentation des méthodes d’étude de la PK/PD des antibiotiques seuls et en combinaison, les résultats de deux projets sont présentés :1. Une étude de la PK/PD de la céfoxitine contre une souche de Mycobacterium abscessus. Dans une première partie, il a été montré que l’administration de la céfoxitine par nébulisation permet d’obtenir des concentrations pulmonaires 1000 fois plus importantes qu’après une administration intraveineuse, faisant de la céfoxitine un bon candidat à la nébulisation. Dans la seconde partie un modèle PK/PD semi-mécanistique a été développé à partir de données in vitro, ce qui permet d’identifier la relation concentration-effet pour deux sous-populations bactériennes tout en tenant compte de la dégradation de la molécule.2. Une étude de la PK/PD de l’association polymyxine B et minocycline contre une souche d’Acinetobacter baumannii résistante à la polymyxine B. Cette étude in vitro comprend des données de bactéricidie avec suivi de la densité de bactéries résistantes à la polymyxine B, enrichies d’expériences complémentaires servant à préciser les caractéristiques de cette sous-population résistante. Ces données ont toutes été analysées par modélisation PK/PD semi-mécanistique, ce qui a notamment permis de quantifier l’importance de l’interaction entre les deux molécules et de formuler des hypothèses sur les mécanismes de cette interaction.Fighting against multidrug-resistant bacteria is a major priority set by World Health Organisation, since it is forecasted that multi-drug-resistant bacteria will be responsible for more deaths than cancer by 2050. In the current context, with only a few new antibiotic drugs active against multidrug-resistant bacteria approved every year, it is of importance to optimize the use of already available antibiotics. It is with this goal in mind, that semi-mechanistic models used to analyse results from PK/PD studies of antibiotics, can be developed. These mathematical tools enable quantification of concentration-effect relationships of drugs, used alone or in combination, in order to optimize their efficacy, prevent bacterial resistance, thus lengthening the period of usability of antibiotics. In this work, after a presentation of the methods used to study PK/PD of antibiotics alone and in combination, results from two projects are presented:1. A study of cefoxitin PK/PD against a Mycobacterium abscessus strain. Firstly, it was shown that after nebulisation of cefoxitin, pulmonary concentrations were 1000-fold higher than after intravenous administration, making cefoxitin a good candidate for nebulisation. In a second part, a semi-mechanistic PK/PD model was developed from in vitro data, enabling identification of concentration-effect relationships for two bacterial sub-populations while taking into account degradation of cefoxitin. 2. A study of the PK/PD of polymyxin B and minocycline association against a polymyxin B resistant Acinetobacter baumannii strain. This in vitro study incorporates data from time-kill experiments with quantification of a bacterial sub-population resistant to polymyxin B, enriched by complementary experiments providing information on the characteristics of this resistant sub-population. This data was analysed by semi-mechanistic PK/PD modelling, which made possible quantification of the strength of interaction between the two drugs and to form hypotheses about the mechanisms of the observed interaction

Apport de la modélisation semi-mécanistique dans l'étude pharmacocinétique/pharmacodynamique des antibiotiques seuls et en combinaison dans la lutte contre les bactéries résistantes.

Fighting against multidrug-resistant bacteria is a major priority set by World Health Organisation, since it is forecasted that multi-drug-resistant bacteria will be responsible for more deaths than cancer by 2050. In the current context, with only a few new antibiotic drugs active against multidrug-resistant bacteria approved every year, it is of importance to optimize the use of already available antibiotics. It is with this goal in mind, that semi-mechanistic models used to analyse results from PK/PD studies of antibiotics, can be developed. These mathematical tools enable quantification of concentration-effect relationships of drugs, used alone or in combination, in order to optimize their efficacy, prevent bacterial resistance, thus lengthening the period of usability of antibiotics. In this work, after a presentation of the methods used to study PK/PD of antibiotics alone and in combination, results from two projects are presented:1. A study of cefoxitin PK/PD against a Mycobacterium abscessus strain. Firstly, it was shown that after nebulisation of cefoxitin, pulmonary concentrations were 1000-fold higher than after intravenous administration, making cefoxitin a good candidate for nebulisation. In a second part, a semi-mechanistic PK/PD model was developed from in vitro data, enabling identification of concentration-effect relationships for two bacterial sub-populations while taking into account degradation of cefoxitin.2. A study of the PK/PD of polymyxin B and minocycline association against a polymyxin B resistant Acinetobacter baumannii strain. This in vitro study incorporates data from time-kill experiments with quantification of a bacterial sub-population resistant to polymyxin B, enriched by complementary experiments providing information on the characteristics of this resistant sub-population. This data was analysed by semi-mechanistic PK/PD modelling, which made possible quantification of the strength of interaction between the two drugs and to form hypotheses about the mechanisms of the observed interaction.La lutte contre les bactéries multirésistantes est une priorité majeure définie par l’Organisation Mondiale de la Santé, puisque les dernières prédictions estiment que les infections par des bactéries multirésistantes feront plus de morts que le cancer d’ici 2050. Dans le contexte actuel, avec un faible nombre de nouveaux antibiotiques mis sur le marché pour lutter contre les bactéries multirésistantes, il est important de d’optimiser l’utilisation des antibiotiques à notre disposition. C’est dans ce but que les modèles semi-mécanistiques servant à analyser les résultats d’études de PK/PD des antibiotiques peuvent être développés. Ces outils mathématiques permettent de quantifier les relations concentration-effet, de molécules seules ou de combinaisons de molécules afin d’optimiser leur efficacité, prévenir les résistances et donc prolonger la durée de vie des antibiotiques. Dans ce travail, après une présentation des méthodes d’étude de la PK/PD des antibiotiques seuls et en combinaison, les résultats de deux projets sont présentés :1. Une étude de la PK/PD de la céfoxitine contre une souche de Mycobacterium abscessus. Dans une première partie, il a été montré que l’administration de la céfoxitine par nébulisation permet d’obtenir des concentrations pulmonaires 1000 fois plus importantes qu’après une administration intraveineuse, faisant de la céfoxitine un bon candidat à la nébulisation. Dans la seconde partie un modèle PK/PD semi-mécanistique a été développé à partir de données in vitro, ce qui permet d’identifier la relation concentration-effet pour deux sous-populations bactériennes tout en tenant compte de la dégradation de la molécule.2. Une étude de la PK/PD de l’association polymyxine B et minocycline contre une souche d’Acinetobacter baumannii résistante à la polymyxine B. Cette étude in vitro comprend des données de bactéricidie avec suivi de la densité de bactéries résistantes à la polymyxine B, enrichies d’expériences complémentaires servant à préciser les caractéristiques de cette sous-population résistante. Ces données ont toutes été analysées par modélisation PK/PD semi-mécanistique, ce qui a notamment permis de quantifier l’importance de l’interaction entre les deux molécules et de formuler des hypothèses sur les mécanismes de cette interaction

Pharmacokinetic/pharmacodynamic models for time courses of antibiotic effects

Pharmacokinetic/pharmacodynamic (PKPD) models have emerged as valuable tools for the characterization and translation of antibiotic effects, and consequently for drug development and therapy. In contrast to traditional PKPD concepts for antibiotics such as minimum inhibitory concentration and PKPD indices, PKPD models enable description of 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. A literature review was conducted 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. In total, 132 publications were identified that were released between 1963 and 2021, including models based on exposure to single antibiotics (n=92) and drug combinations (n=40), as well as different experimental settings (e.g. static/traditional dynamic/hollowfibre/animal time-kill models, n=90/27/32/11). An interactive, fully searchable table summarizes the details of each model, namely variants and mechanistic elements of PKPD submodels capturing observed bacterial growth, regrowth, drug effects and interactions. Furthermore, the review highlights the 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 will 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. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/

Clinical Pharmacokinetics and Pharmacodynamics of Colistin

International audienceIn this review, we give an updated summary on colistin pharmacokinetics and pharmacodynamics. Colistin is an old molecule that is frequently used as last line treatment for infections caused by multidrug-resistant Gram-negative bacteria. Colistin is a decapeptide administered either as a prodrug, colistin methanesulfonate (CMS) when used intravenously, or as colistin sulfate when used orally. Because colistin binds to laboratory materials, many experimental issues are raised and studies on colistin can be tricky. Due to its large molecular weight and its cationic properties at physiological pH, colistin poorly passes through physiological membranes and is mainly distributed within the extracellular space. Renal clearance of colistin is very low, but the dosing regimen should be adapted to the renal function of the patient because CMS is partly eliminated by the kidney. Therapeutic drug monitoring of colistin is warranted because the pharmacokinetics of colistin is very variable, and because its therapeutic window is narrow. Resistance of bacteria to colistin is increasing worldwide in parallel to its clinical and veterinary uses and recently, a plasmid-mediated resistance mechanism (MCR-1) was described in animals and humans. In vitro, when exposed to colistin, bacteria develop various resistance mechanisms rapidly. The use of a loading dose might reduce the emergence of resistance but the use of colistin in combination also seems necessary

Clinical Pharmacokinetics and Pharmacodynamics of Colistin

International audienceIn this review, we give an updated summary on colistin pharmacokinetics and pharmacodynamics. Colistin is an old molecule that is frequently used as last line treatment for infections caused by multidrug-resistant Gram-negative bacteria. Colistin is a decapeptide administered either as a prodrug, colistin methanesulfonate (CMS) when used intravenously, or as colistin sulfate when used orally. Because colistin binds to laboratory materials, many experimental issues are raised and studies on colistin can be tricky. Due to its large molecular weight and its cationic properties at physiological pH, colistin poorly passes through physiological membranes and is mainly distributed within the extracellular space. Renal clearance of colistin is very low, but the dosing regimen should be adapted to the renal function of the patient because CMS is partly eliminated by the kidney. Therapeutic drug monitoring of colistin is warranted because the pharmacokinetics of colistin is very variable, and because its therapeutic window is narrow. Resistance of bacteria to colistin is increasing worldwide in parallel to its clinical and veterinary uses and recently, a plasmid-mediated resistance mechanism (MCR-1) was described in animals and humans. In vitro, when exposed to colistin, bacteria develop various resistance mechanisms rapidly. The use of a loading dose might reduce the emergence of resistance but the use of colistin in combination also seems necessary

Spotting method as a high throughput alternative to the conventional spread plating method conventional spread plating method for bacterial time killexperiments

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

International audienceThe 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 (10 5 , 10 6 and 10 7 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 10 5 to 10 7 CFU/thigh. Although not as important as previously characterized in vitro an IE was confirmed in vivo

A Minimal Physiologically Based Pharmacokinetic Model to Characterize CNS Distribution of Metronidazole in Neuro Care ICU Patients

International audienceUnderstanding antibiotic concentration-time profiles in the central nervous system (CNS) is crucial to treat severe life-threatening CNS infections, such as nosocomial ventriculitis or meningitis. Yet CNS distribution is likely to be altered in patients with brain damage and infection/inflammation. Our objective was to develop a physiologically based pharmacokinetic (PBPK) model to predict brain concentration-time profiles of antibiotics and to simulate the impact of pathophysiological changes on CNS profiles. A minimal PBPK model consisting of three physiological brain compartments was developed from metronidazole concentrations previously measured in plasma, brain extracellular fluid (ECF) and cerebrospinal fluid (CSF) of eight brain-injured patients. Volumes and blood flows were fixed to their physiological value obtained from the literature. Diffusion clearances characterizing transport across the blood–brain barrier and blood–CSF barrier were estimated from system- and drug-specific parameters and were confirmed from a Caco-2 model. The model described well unbound metronidazole pharmacokinetic profiles in plasma, ECF and CSF. Simulations showed that with metronidazole, an antibiotic with extensive CNS distribution simply governed by passive diffusion, pathophysiological alterations of membrane permeability, brain ECF volume or cerebral blood flow would have no effect on ECF or CSF pharmacokinetic profiles. This work will serve as a starting point for the development of a new PBPK model to describe the CNS distribution of antibiotics with more limited permeability for which pathophysiological conditions are expected to have a greater effect

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

Translational in vitro and in vivo PKPD modelling for apramycin against Gram-negative lung pathogens to facilitate prediction of human efficacious dose in pneumonia

Objectives: New drugs and methods to efficiently fight carbapenem-resistant Gram-negative pathogens are sorely needed. In this study we characterized the preclinical pharmacokinetics and pharmacodynamics of the clinical-stage drug candidate apramycin in time kill and mouse lung infection models. Based on in vitro and in vivo data, we developed a mathematical model to predict human efficacy. Methods: Three pneumonia-inducing Gram-negative species Acinetobacter baumannii, Pseudomonas aeruginosa, and Klebsiella pneumoniae were studied. Bactericidal kinetics were evaluated with time-kill curves; in vivo pharmacokinetics were studied in healthy and infected mice, with sampling in plasma and epithelial lining fluid after subcutaneous administration; in vivo efficacy was measured in a neutropenic mouse pneumonia model. A pharmacokinetic-pharmacodynamic model, integrating all the data, was developed and simulations were performed. Results: Good lung penetration of apramycin in epithelial lining fluid (ELF) was shown (AUCELF/AUCplasma = 88%). Plasma clearance was 48% lower in lung infected mice compared to healthy mice. For two out of five strains studied, a delay in growth (∼5h) was observed in vivo but not in vitro. The mathematical model enabled integration of lung pharmacokinetics to drive mouse PKPD. Simulations predicted that 30 mg/kg of apramycin once daily would result in bacteriostasis in patients. Conclusion: Apramycin is a candidate for treatment of carbapenem-resistant Gram-negative pneumonia as demonstrated in an integrated modeling framework for three bacterial species. We show that mathematical modelling is a useful tool for simultaneous inclusion of multiple data sources, notably plasma and lung in vivo PK and simulation of expected scenarios in a clinical setting, notably lung infections