Therapeutics for Vancomycin-Resistant Enterococcal Bloodstream Infections

Vancomycin-resistant enterococci (VRE) are common causes of bloodstream infections (BSIs) with high morbidity and mortality rates. They are pathogens of global concern with a limited treatment pipeline. Significant challenges exist in the management of VRE BSI, including drug dosing, the emergence of resistance, and the optimal treatment for persistent bacteremia and infective endocarditis. Therapeutic drug monitoring (TDM) for antimicrobial therapy is evolving for VRE-active agents; however, there are significant gaps in the literature for predicting antimicrobial efficacy for VRE BSIs. To date, TDM has the greatest evidence for predicting drug toxicity for the three main VRE-active antimicrobial agents daptomycin, linezolid, and teicoplanin. This article presents an overview of the treatment options for VRE BSIs, the role of antimicrobial dose optimization through TDM in supporting clinical infection management, and challenges and perspectives for the future.

The mysteries of target site concentrations of antibiotics in bone and joint infections: what is known? A narrative review

INTRODUCTION

Currently, antibiotic treatment is often a standard dosing regimen in bone and joint infections (BJI). However, it remains unknown if exposure at the target-site is adequate. The aim of this review is to gain more insight in the relationship between the target site concentration of antibiotic and the minimal inhibitory concentration to target the bacteria in bone and joint infections (BJI).

AREAS COVERED

A literature search was performed by Erasmus MC Medical library. Bone, bone tissue and synovial concentration of antibiotics were covered in humans. In addition, we reported number of patients, dose, sampling method, analytical method and tissue and plasma concentrations. We used the epidemiological cut-off value (ECOFF) values of the targeted micro-organisms. If more than 3 publications were available on the antibiotic, we graphically presented ECOFFS values against reported antibiotic concentrations.

EXPERT OPINION

For most antibiotics the literature is sparse. In addition, a lot of variable and total antibiotic concentrations are published. Ciprofloxacin, cefazolin, cefuroxime, vancomycin and linezolid seem to have adequate average exposure if correlating total concentration to ECOFF, when standard dosing is used. With regards to other antibiotics, results are inconclusive. More extensive pharmacokinetic/pharmacodynamic modeling in BJI is needed.

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.

Pharmacodynamics of Linezolid Plus Fosfomycin Against Vancomycin-Resistant Enterococcus faecium in a Hollow Fiber Infection Model

The optimal therapy for severe infections caused by vancomycin-resistant Enterococcus faecium (VREfm) remains unclear, but the combination of linezolid and fosfomycin may be a good choice. The 24-h static-concentration time-kill study (SCTK) was used to preliminarily explore the pharmacodynamics of linezolid combined with fosfomycin against three clinical isolates. Subsequently, a hollow-fibre infection model (HFIM) was used for the first time to further investigate the pharmacodynamic activity of the co-administration regimen against selected isolates over 72 h. To further quantify the relationship between fosfomycin resistance and bacterial virulence in VREfm, the Galleria mellonella infection model and virulence genes expression experiments were also performed. The results of SCTK showed that the combination of linezolid and fosfomycin had additive effect on all strains. In the HFIM, the dosage regimen of linezolid (12 mg/L, steady-state concentration) combined with fosfomycin (8 g administered intravenously every 8 h as a 1 h infusion) not only produced a sustained bactericidal effect of 3∼4 log₁₀ CFU/mL over 72 h, but also completely eradicated the resistant subpopulations. The expression of virulence genes was down-regulated to at least 0.222-fold in fosfomycin-resistant strains compared with baseline isolate, while survival rates of G. mellonella was increased (G. mellonella survival ≥45% at 72 h). For severe infections caused by VREfm, neither linezolid nor fosfomycin monotherapy regimens inhibited amplification of the resistant subpopulations, and the development of fosfomycin resistance was at the expense of the virulence of VREfm. The combination of linezolid with fosfomycin produced a sustained bactericidal effect and completely eradicated the resistant subpopulations. Linezolid plus Fosfomycin is a promising combination for therapy of severe infections caused by VREfm.

Optimization of Linezolid Dosing Regimens for Treatment of Vancomycin-Resistant Enterococci Infection

BACKGROUND

Linezolid, an oxazolidinone antibiotic, is recommended for vancomycin-resistant enterococci (VRE). However, 100% free-drug concentration above the minimum inhibitory concentration (fT>MIC) and an area under the curve of free drug to MIC ratio (fAUC24/MIC) >100 were associated with favorable clinical outcome with less emerging resistance. A plasma trough concentration (C_trough) of linezolid ≥9 μg/mL was also related to hematologic toxicity. Thus, linezolid dose optimization is needed for VRE treatment. The study aimed to determine the in vitro linezolid activity against clinical VRE isolates and linezolid dosing regimens in critically ill patients who met the target pharmacokinetics/pharmacodynamics (PK/PD) for VRE treatment.

MATERIALS AND METHODS

Enterococcal isolates from enterococcal-infected patients were obtained between 2014 and 2018 at Phramongkutklao Hospital. We used Monte Carlo simulation to calculate the probability of target attainment, and the cumulative fraction of response (CFR) of the free area under the curve to MIC ratio (fAUIC₂₄) was used to calculate the fAUC24/MIC 80 - 100 and fT/MIC >85 - 100% of the interval time of administration for clinical response and microbiological eradication as well as the C_trough ≥9 μg/mL for the probability of hematologic toxicity.

RESULTS

For linezolid MIC determination, the MIC median (MIC₅₀), MIC for 90% growth (MIC₉₀), and range for linezolid were 1.5 μg/mL, 2 μg/mL, and 0.72 - 2 μg/mL, respectively. A dosing regimen of 1,200 mg either once daily or as a divided dose every 12 h gave target attainments of fAUC24/MICs >80 and >100, which exceeded 90% for MICs ≤1 and ≤1 μg/mL, respectively, with a rate of hematologic toxicity <15%. If the expected fT>MICs were >85% and 100%, a 1,200-mg divided dose every 12 h could cover VRE isolates having linezolid MICs ≤1 μg/mL and ≤0.75 μg/mL. Even 600 mg every 8 h and 1,200 mg as a continuous infusion gave a higher target attainment of fAUC24/MIC and a fT>MIC and the target CFR, but those regimens gave C_trough ≥9 μg/mL rates of 40.7% and 99.6%.

CONCLUSION

The current dosing of 1,200 mg/day might be optimal treatment for infection by VRE isolates with documented MICs ≤1 μg/mL. For treatment of VRE with a MIC of 2 μg/mL or to achieve the target CFR, the use of linezolid with other antibiotic combinations might help achieve the PK/PD target, provide better clinical outcome, and prevent resistance.

Combating Multidrug-Resistant Bacteria by Integrating a Novel Target Site Penetration and Receptor Binding Assay Platform Into Translational Modeling

Multidrug-resistant bacteria are causing a serious global health crisis. A dramatic decline in antibiotic discovery and development investment by pharmaceutical industry over the last decades has slowed the adoption of new technologies. It is imperative that we create new mechanistic insights based on latest technologies, and use translational strategies to optimize patient therapy. Although drug development has relied on minimal inhibitory concentration testing and established in vitro and mouse infection models, the limited understanding of outer membrane permeability in Gram-negative bacteria presents major challenges. Our team has developed a platform using the latest technologies to characterize target site penetration and receptor binding in intact bacteria that inform translational modeling and guide new discovery. Enhanced assays can quantify the outer membrane permeability of β-lactam antibiotics and β-lactamase inhibitors using multiplex liquid chromatography tandem mass spectrometry. While β-lactam antibiotics are known to bind to multiple different penicillin-binding proteins (PBPs), their binding profiles are almost always studied in lysed bacteria. Novel assays for PBP binding in the periplasm of intact bacteria were developed and proteins identified via proteomics. To characterize bacterial morphology changes in response to PBP binding, high-throughput flow cytometry and time-lapse confocal microscopy with fluorescent probes provide unprecedented mechanistic insights. Moreover, novel assays to quantify cytosolic receptor binding and intracellular drug concentrations inform target site occupancy. These mechanistic data are integrated by quantitative and systems pharmacology modeling to maximize bacterial killing and minimize resistance in in vitro and mouse infection models. This translational approach holds promise to identify antibiotic combination dosing strategies for patients with serious infections.

Interaction of Staphylococcus aureus and Acinetobacter baumannii during In Vitro β-Lactam Exposure

We sought to determine if Acinetobacter baumannii is capable of altering the pharmacodynamics of an antistaphylococcal β-lactam. Two strains of methicillin-susceptible Staphylococcus aureus (MSSA) and two A. baumannii isolates were studied in 24-h static time-killing experiments under monoculture or coculture conditions. Bacterial killing of meropenem was described using an empirical pharmacokinetics/pharmacodynamics model that was developed using Hill functions. A mechanism-based pharmacodynamic model was also used to describe the effect of meropenem on each species of bacterium, interspecies interactions, and strain-based covariate effects. Monte Carlo simulations of bacterial killing effects were generated based on the population pharmacokinetics of meropenem in 2,500 simulated critically ill subjects over 48 h. Against one of the two MSSA isolates, the magnitude of bacterial killing (E _Δ) decreased from -4.61 (95% confidence interval [CI], -5.85 to -3.38) to -2.23 (95% CI, -2.85 to -1.61) when cultured in the presence of carbapenem-resistant A. baumannii (CRAB). Similarly, the data were best described by a mechanism-based model where the number of A. baumannii cells produced a systematic increase in the S. aureus concentration for a 50% maximum killing effect (KC₅₀) of 3.53-fold, thereby decreasing MSSA sensitivity to meropenem. A covariate effect by the CRAB isolate resulted in a more pronounced increase in the MSSA KC₅₀ for meropenem (31.8-fold increase). However, Monte Carlo simulations demonstrated that a high-intensity meropenem regimen is capable of sustained killing against both MSSA isolates despite protection from A. baumannii Thus, A. baumannii and MSSA engage in complex interactions during β-lactam exposure, but optimal antimicrobial dosing is likely capable of killing MSSA despite the potentially beneficial interplay with A. baumannii.

Sequential Time-Kill, a Simple Experimental Trick To Discriminate between Pharmacokinetics/Pharmacodynamics Models with Distinct Heterogeneous Subpopulations versus Homogenous Population with Adaptive Resistance

Experiments were conducted with polymyxin B and two Klebsiella pneumonia isogenic strains (the wild type, KP_WT, and its transconjugant carrying the mobile colistin resistance gene, KP_MCR-1) to demonstrate that conducting two consecutive time-kill experiments (sequential TK) represents a simple approach to discriminate between pharmacokinetics/pharmacodynamics models with two heterogeneous subpopulations or adaptive resistance.

Calculated parenteral initial treatment of bacterial infections: Bone and joint infections

This is the 10^th chapter of the guideline “Calculated initial parenteral treatment of bacterial infections in adults – update 2018” in the 2^nd updated version. The German guideline by the Paul-Ehrlich-Gesellschaft für Chemotherapie e.V. (PEG) has been translated to address an international audience.

This chapter deals with bacterial Infections of bones, joints and prosthetic joints. One of the most pressing points is that after an initial empirical therapy a targeted antimicrobial which penetrates well to the point of infection and is tolerated well over the usually long duration of the therapy is chosen.

Using machine learning to optimize antibiotic combinations: dosing strategies for meropenem and polymyxin B against carbapenem-resistant Acinetobacter baumannii

OBJECTIVES

Increased rates of carbapenem-resistant strains of Acinetobacter baumannii have forced clinicians to rely upon last-line agents, such as the polymyxins, or empirical, unoptimized combination therapy. Therefore, the objectives of this study were: (a) to evaluate the in vitro pharmacodynamics of meropenem and polymyxin B (PMB) combinations against A. baumannii; (b) to utilize a mechanism-based mathematical model to quantify bacterial killing; and (c) to develop a genetic algorithm (GA) to define optimal dosing strategies for meropenem and PMB.

METHODS

A. baumannii (N16870; MIC_meropenem = 16 mg/L, MIC_PMB = 0.5 mg/L) was studied in the hollow-fibre infection model (initial inoculum 10⁸ cfu/mL) over 14 days against meropenem and PMB combinations. A mechanism-based model of the data and population pharmacokinetics of each drug were used to develop a GA to define the optimal regimen parameters.

RESULTS

Monotherapies resulted in regrowth to ~10¹⁰ cfu/mL by 24 h, while combination regimens employing high-intensity PMB exposure achieved complete bacterial eradication (0 cfu/mL) by 336 h. The mechanism-based model demonstrated an SC₅₀ (PMB concentration for 50% of maximum synergy on meropenem killing) of 0.0927 mg/L for PMB-susceptible subpopulations versus 3.40 mg/L for PMB-resistant subpopulations. The GA had a preference for meropenem regimens that improved the %T > MIC via longer infusion times and shorter dosing intervals. The GA predicted that treating 90% of simulated subjects harbouring a 10⁸ cfu/mL starting inoculum to a point of 10⁰ cfu/mL would require a regimen of meropenem 19.6 g/day 2 h prolonged infusion (2 hPI) q5h + PMB 5.17 mg/kg/day 2 hPI q6h (where the 0 h meropenem and PMB doses should be 'loaded' with 80.5% and 42.2% of the daily dose, respectively).

CONCLUSION

This study provides a methodology leveraging in vitro experimental data, a mathematical pharmacodynamic model, and population pharmacokinetics provide a possible avenue to optimize treatment regimens beyond the use of the 'traditional' indices of antibiotic action.

Evaluation of Tobramycin and Ciprofloxacin as a Synergistic Combination Against Hypermutable Pseudomonas Aeruginosa Strains via Mechanism-Based Modelling

Hypermutable Pseudomonas aeruginosa strains have a greatly increased mutation rate and are prevalent in chronic respiratory infections. Initially, we systematically evaluated the time-course of total and resistant populations of hypermutable (PAO∆mutS) and non-hypermutable (PAO1) P. aeruginosa strains in 48-h static concentration time-kill studies with two inocula. Both strains were exposed to clinically relevant concentrations of important antibiotics (aztreonam, ceftazidime, imipenem, meropenem, tobramycin, and ciprofloxacin) in monotherapy. The combination of tobramycin and ciprofloxacin was subsequently assessed in 48-h static concentration time-kill studies against PAO1, PAO∆mutS, and two hypermutable clinical P. aeruginosa strains. Mechanism-based mathematical modelling was conducted to describe the time-course of total and resistant bacteria for all four strains exposed to the combination. With all monotherapies, bacterial regrowth and resistant populations were overall more pronounced for PAO∆mutS compared to PAO1. The combination of tobramycin and ciprofloxacin was synergistic, with up to 10^6.1 colony forming units (CFU)/mL more bacterial killing than the most active monotherapy for all strains, and largely suppressed less-susceptible populations. This work indicates that monotherapies against hypermutable P. aeruginosa strains are not a viable option. Tobramycin with ciprofloxacin was identified as a promising and tangible option to combat hypermutable P. aeruginosa strains.

Generating Robust and Informative Nonclinical In Vitro and In Vivo Bacterial Infection Model Efficacy Data To Support Translation to Humans

In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration.

In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration. This and the accompanying review on clinical PK/PD summarize the workshop discussions and recommendations. Nonclinical PK/PD models play a critical role in designing human dosage regimens and are essential tools for drug development. These include in vitro and in vivo efficacy models that provide valuable and complementary information for dose selection and translation from the laboratory to human. It is crucial that studies be designed, conducted, and interpreted appropriately. For antibacterial PK/PD, extensive published data and expertise are available. These have been leveraged to develop recommendations, identify common pitfalls, and describe the applications, strengths, and limitations of various nonclinical infection models and translational approaches. Despite these robust tools and published guidance, characterizing nonclinical PK/PD relationships may not be straightforward, especially for a new drug or new class. Antimicrobial PK/PD is an evolving discipline that needs to adapt to future research and development needs. Open communication between academia, pharmaceutical industry, government, and regulatory bodies is essential to share perspectives and collectively solve future challenges.

Individualising Therapy to Minimize Bacterial Multidrug Resistance

The scourge of antibiotic resistance threatens modern healthcare delivery. A contributing factor to this significant issue may be antibiotic dosing, whereby standard antibiotic regimens are unable to suppress the emergence of antibiotic resistance. This article aims to review the role of pharmacokinetic and pharmacodynamic (PK/PD) measures for optimising antibiotic therapy to minimise resistance emergence. It also seeks to describe the utility of combination antibiotic therapy for suppression of resistance and summarise the role of biomarkers in individualising antibiotic therapy. Scientific journals indexed in PubMed and Web of Science were searched to identify relevant articles and summarise existing evidence. Studies suggest that optimising antibiotic dosing to attain defined PK/PD ratios may limit the emergence of resistance. A maximum aminoglycoside concentration to minimum inhibitory concentration (MIC) ratio of > 20, a fluoroquinolone area under the concentration-time curve to MIC ratio of > 285 and a β-lactam trough concentration of > 6 × MIC are likely required for resistance suppression. In vitro studies demonstrate a clear advantage for some antibiotic combinations. However, clinical evidence is limited, suggesting that the use of combination regimens should be assessed on an individual patient basis. Biomarkers, such as procalcitonin, may help to individualise and reduce the duration of antibiotic treatment, which may minimise antibiotic resistance emergence during therapy. Future studies should translate laboratory-based studies into clinical trials and validate the appropriate clinical PK/PD predictors required for resistance suppression in vivo. Other adjunct strategies, such as biomarker-guided therapy or the use of antibiotic combinations require further investigation.

Combating Carbapenem-Resistant Acinetobacter baumannii by an Optimized Imipenem-plus-Tobramycin Dosage Regimen: Prospective Validation via Hollow-Fiber Infection and Mathematical Modeling

We aimed to prospectively validate an optimized combination dosage regimen against a clinical carbapenem-resistant Acinetobacter baumannii (CRAB) isolate (imipenem MIC, 32 mg/liter; tobramycin MIC, 2 mg/liter). Imipenem at constant concentrations (7.6, 13.4, and 23.3 mg/liter, reflecting a range of clearances) was simulated in a 7-day hollow-fiber infection model (inoculum, ∼10^7.2 CFU/ml) with and without tobramycin (7 mg/kg q24h, 0.5-h infusions). While monotherapies achieved no killing or failed by 24 h, this rationally optimized combination achieved >5 log₁₀ bacterial killing and suppressed resistance.

Evaluation of Pharmacokinetic/Pharmacodynamic Model-Based Optimized Combination Regimens against Multidrug-Resistant Pseudomonas aeruginosa in a Murine Thigh Infection Model by Using Humanized Dosing Schemes

We previously optimized imipenem and tobramycin combination regimens against a double-resistant clinical Pseudomonas aeruginosa isolate by using in vitro infection models, mechanism-based pharmacokinetic/pharmacodynamic modeling (MBM), and Monte Carlo simulations. The current study aimed to evaluate these regimens in a neutropenic murine thigh infection model and to characterize the time course of bacterial killing and regrowth via MBM. We studied monotherapies and combinations of imipenem with tobramycin in vivo against the double-resistant clinical P. aeruginosa isolate by using humanized dosing schemes. Viable count profiles of total and resistant populations were quantified over 24 h. Tobramycin monotherapy (7 mg/kg every 24 h [q24h] as a 0.5-h infusion) was ineffective. Imipenem monotherapies (continuous infusion of 4 or 5 g/day with a 1-g loading dose) yielded 2.47 or 2.57 log₁₀ CFU/thigh killing at 6 h. At 24 h, imipenem at 4 g/day led to regrowth up to the initial inoculum (4.79 ± 0.26 log₁₀ CFU/thigh), whereas imipenem at 5 g/day displayed 1.75 log₁₀ killing versus the initial inoculum. The combinations (i.e., imipenem at 4 or 5 g/day plus tobramycin) provided a clear benefit, with bacterial killing of ≥2.51 or ≥1.50 log₁₀ CFU/thigh compared to the respective most active monotherapy at 24 h. No colonies were detected on 3×MIC agar plates for combinations, whereas increased resistance (at 3×MIC) emerged for monotherapies (except imipenem at 5 g/day). MBM suggested that tobramycin considerably enhanced the imipenem target site concentration up to 2.6-fold. The combination regimens, rationally optimized via a translational modeling approach, demonstrated substantially enhanced bacterial killing and suppression of regrowth in vivo against a double-resistant isolate and are therefore promising for future clinical evaluation.

The role of infection models and PK/PD modelling for optimising care of critically ill patients with severe infections

Critically ill patients with severe infections are at high risk of suboptimal antimicrobial dosing. The pharmacokinetics (PK) and pharmacodynamics (PD) of antimicrobials in these patients differ significantly from the patient groups from whose data the conventional dosing regimens were developed. Use of such regimens often results in inadequate antimicrobial concentrations at the site of infection and is associated with poor patient outcomes. In this article, we describe the potential of in vitro and in vivo infection models, clinical pharmacokinetic data and pharmacokinetic/pharmacodynamic models to guide the design of more effective antimicrobial dosing regimens. Individualised dosing, based on population PK models and patient factors (e.g. renal function and weight) known to influence antimicrobial PK, increases the probability of achieving therapeutic drug exposures while at the same time avoiding toxic concentrations. When therapeutic drug monitoring (TDM) is applied, early dose adaptation to the needs of the individual patient is possible. TDM is likely to be of particular importance for infected critically ill patients, where profound PK changes are present and prompt appropriate antibiotic therapy is crucial. In the light of the continued high mortality rates in critically ill patients with severe infections, a paradigm shift to refined dosing strategies for antimicrobials is warranted to enhance the probability of achieving drug concentrations that increase the likelihood of clinical success.

Optimization of Synergistic Combination Regimens against Carbapenem- and Aminoglycoside-Resistant Clinical Pseudomonas aeruginosa Isolates via Mechanism-Based Pharmacokinetic/Pharmacodynamic Modeling

Optimizing antibiotic combinations is promising to combat multidrug-resistant Pseudomonas aeruginosa This study aimed to systematically evaluate synergistic bacterial killing and prevention of resistance by carbapenem and aminoglycoside combinations and to rationally optimize combination dosage regimens via a mechanism-based mathematical model (MBM). We studied monotherapies and combinations of imipenem with tobramycin or amikacin against three difficult-to-treat double-resistant clinical P. aeruginosa isolates. Viable-count profiles of total and resistant populations were quantified in 48-h static-concentration time-kill studies (inoculum, 107.5 CFU/ml). We rationally optimized combination dosage regimens via MBM and Monte Carlo simulations against isolate FADDI-PA088 (MIC of imipenem [MICimipenem] of 16 mg/liter and MICtobramycin of 32 mg/liter, i.e., both 98th percentiles according to the EUCAST database). Against this isolate, imipenem (1.5× MIC) combined with 1 to 2 mg/liter tobramycin (MIC, 32 mg/liter) or amikacin (MIC, 4 mg/liter) yielded ≥2-log10 more killing than the most active monotherapy at 48 h and prevented resistance. For all three strains, synergistic killing without resistance was achieved by ≥0.88× MICimipenem in combination with a median of 0.75× MICtobramycin (range, 0.032× to 2.0× MICtobramycin) or 0.50× MICamikacin (range, 0.25× to 0.50× MICamikacin). The MBM indicated that aminoglycosides significantly enhanced the imipenem target site concentration up to 3-fold; achieving 50% of this synergistic effect required aminoglycoside concentrations of 1.34 mg/liter (if the aminoglycoside MIC was 4 mg/liter) and 4.88 mg/liter (for MICs of 8 to 32 mg/liter). An optimized combination regimen (continuous infusion of imipenem at 5 g/day plus a 0.5-h infusion with 7 mg/kg of body weight tobramycin) was predicted to achieve >2.0-log10 killing and prevent regrowth at 48 h in 90.3% of patients (median bacterial killing, >4.0 log10 CFU/ml) against double-resistant isolate FADDI-PA088 and therefore was highly promising.

Resistance suppression by high-intensity, short-duration aminoglycoside exposure against hypermutable and non-hypermutable Pseudomonas aeruginosa

OBJECTIVES

Hypermutable bacteria are causing a drastic problem via their enhanced ability to become resistant. Our objectives were to compare bacterial killing and resistance emergence between differently shaped tobramycin concentration-time profiles at a given fAUC/MIC, and determine the tobramycin exposure durations that prevent resistance.

METHODS

Static concentration time-kill studies over 24 h used Pseudomonas aeruginosa WT strains (ATCC 27853 and PAO1) and hypermutable PAOΔmutS. fAUC/MIC values of 36, 72 and 168 were assessed at initial inocula of 10⁶ and 10⁴ cfu/mL (all strains) and 10^1.2 cfu/mL (PAOΔmutS only) in duplicate. Tobramycin was added at 0 h and removed at 1, 4, 10 or 24 h. Proportions of resistant bacteria and MICs were determined at 24 h. Mechanism-based modelling was conducted.

RESULTS

For all strains, high tobramycin concentrations over 1 and 4 h resulted in more rapid and extensive initial killing compared with 10 and 24 h exposures at a given fAUC/MIC. No resistance emerged for 1 and 4 h durations of exposure, although extensive regrowth of susceptible bacteria occurred. The 24 h duration of exposure revealed less regrowth, but tobramycin-resistant populations had completely replaced susceptible bacteria by 24 h for the 10⁶ cfu/mL inoculum. The hypermutable PAOΔmutS showed the highest numbers of resistant bacteria. Total and resistant bacterial counts were described well by novel mechanism-based modelling.

CONCLUSIONS

Extensive resistance emerged for 10 and 24 h durations of exposure, but not for shorter durations. The tobramycin concentration-time profile shape is vital for resistance prevention and should aid the introduction of optimized combination regimens.

Two mechanisms of killing of Pseudomonas aeruginosa by tobramycin assessed at multiple inocula via mechanism-based modeling

Bacterial resistance is among the most serious threats to human health globally, and many bacterial isolates have emerged that are resistant to all antibiotics in monotherapy. Aminoglycosides are often used in combination therapies against severe infections by multidrug-resistant bacteria. However, models quantifying different antibacterial effects of aminoglycosides are lacking. While the mode of aminoglycoside action on protein synthesis has often been studied, their disruptive action on the outer membrane of Gram-negative bacteria remains poorly characterized. Here, we developed a novel quantitative model for these two mechanisms of aminoglycoside action, phenotypic tolerance at high bacterial densities, and adaptive bacterial resistance in response to an aminoglycoside (tobramycin) against three Pseudomonas aeruginosa strains. At low-intermediate tobramycin concentrations (<4 mg/liter), bacterial killing due to the effect on protein synthesis was most important, whereas disruption of the outer membrane was the predominant killing mechanism at higher tobramycin concentrations (≥8 mg/liter). The extent of killing was comparable across all inocula; however, the rate of bacterial killing and growth was substantially lower at the 10(8.9) CFU/ml inoculum than that at the lower inocula. At 1 to 4 mg/liter tobramycin for strain PAO1-RH, there was a 0.5- to 6-h lag time of killing that was modeled via the time to synthesize hypothetical lethal protein(s). Disruption of the outer bacterial membrane by tobramycin may be critical to enhance the target site penetration of antibiotics used in synergistic combinations with aminoglycosides and thereby combat multidrug-resistant bacteria. The two mechanisms of aminoglycoside action and the new quantitative model hold great promise to rationally design novel, synergistic aminoglycoside combination dosage regimens.

Antibiotic dosing in obesity: the search for optimum dosing strategies

Global obesity has nearly doubled and is now a common occurrence in high-income and developing countries. The World Health Organization estimates that more than 1.4 billion adults are obese. Although the prevalence of obesity is increasing over the last decades, pharmacokinetic evaluations are still conducted in individuals with a body weight of approximately 70 kg. Morbid obesity is associated with several pathophysiological changes that can profoundly affect drug distribution and clearance. There are currently no specific dosing recommendations for antibiotics in obese patients, making dosing suggestions primarily based on pharmacokinetic characteristics of the medications and dosing recommendations in other disease states. Understanding of the pharmacokinetic alterations and maximum doses of antibiotics safely used is paramount to appropriate treatment in the obese population.

New colistin population pharmacokinetic data in critically ill patients suggesting an alternative loading dose rationale

Colistin is an old antibiotic that has recently gained a considerable renewal of interest as the last-line defense therapy against multidrug-resistant Gram-negative bacteria. It is administered as colistin methanesulfonate (CMS), an inactive prodrug, and it was shown that due to slow CMS conversion, colistin plasma concentrations increase very slowly after treatment initiation, which constitutes the rationale for a loading dose in critically ill patients. However, faster CMS conversion was observed in healthy volunteers but using a different CMS brand, which may also have a major impact on colistin pharmacokinetics. Seventy-three critically ill patients not undergoing dialysis received multiple doses of CMS. The CMS concentrations were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS), and a pharmacokinetic analysis was conducted using a population approach. We confirmed that CMS renal clearance and colistin concentrations at steady state are mostly governed by creatinine clearance, but we predict a typical maximum concentration of drug in serum (Cmax) of colistin close to 2 mg/liter, occurring 3 h after an initial dose of 2 million international units (MIU) of CMS. Accordingly, the estimated colistin half-life (t1/2) was relatively short (3.1 h), with rapid attainment of steady state. Our results are only partially consistent with other recently published results. We confirm that the CMS maintenance dose should be adjusted according to renal function in critically ill patients. However, much higher than expected colistin concentrations were observed after the initial CMS dose, with rapid steady-state achievement. These discrepancies challenge the pharmacokinetic rationale for a loading dose, which may still be appropriate for rapid bacterial eradication and an improved clinical cure rate.

Vancomycin-resistant enterococci: Troublemaker of the 21st century

The emergence of multidrug-resistant and vancomycin-resistant enterococci during the last decade has made it difficult to treat nosocomial infections. Although various enterococcal species have been identified, only two (Enterococcus faecalis and Enterococcus faecium) are responsible for the majority of human infections. Vancomycin is an important therapeutic alternative against multidrug-resistant enterococci but is associated with a poor prognosis. Resistance to vancomycin dramatically reduces the therapeutic options for enterococcal infections. The bacterium develops resistance by modifying the C-terminal d-alanine of peptidoglycan to d-lactate, creating a d-Ala-d-Lac sequence that effectively reduces the affinity of vancomycin for the peptidoglycan by 1000-fold. Moreover, the resistance genes can be transferred from enterococci to Staphylococcus aureus, thereby posing a threat to patient safety and also a challenge for treating physicians. Judicious use of vancomycin and broad-spectrum antibiotics must be implemented, but strict infection control measures must also be followed to prevent nosocomial transmission of these organisms. Furthermore, improvements in clinical practice, rotation of antibiotics, herbal drugs, nanoantibiotics and the development of newer antibiotics based on a pharmacogenomic approach may prove helpful to overcome dreadful vancomycin-resistant enterococcal infections.

Clinical population pharmacokinetics and toxicodynamics of linezolid

Thrombocytopenia is a common side effect of linezolid, an oxazolidinone antibiotic often used to treat multidrug-resistant Gram-positive bacterial infections. Various risk factors have been suggested, including linezolid dose and duration of therapy, baseline platelet counts, and renal dysfunction; still, the mechanisms behind this potentially treatment-limiting toxicity are largely unknown. A clinical study was conducted to investigate the relationship between linezolid pharmacokinetics and toxicodynamics and inform strategies to prevent and manage linezolid-associated toxicity. Forty-one patients received 42 separate treatment courses of linezolid (600 mg every 12 h). A new mechanism-based, population pharmacokinetic/toxicodynamic model was developed to describe the time course of plasma linezolid concentrations and platelets. A linezolid concentration of 8.06 mg/liter (101% between-patient variability) inhibited the synthesis of platelet precursor cells by 50%. Simulations predicted treatment durations of 5 and 7 days to carry a substantially lower risk than 10- to 28-day therapy for platelet nadirs of <100 ×10(9)/liter. The risk for toxicity did not differ noticeably between 14 and 28 days of therapy and was significantly higher for patients with lower baseline platelet counts. Due to the increased risk of toxicity after longer durations of linezolid therapy and large between-patient variability, close monitoring of patients for development of toxicity is important. Dose individualization based on plasma linezolid concentration profiles and platelet counts should be considered to minimize linezolid-associated thrombocytopenia. Overall, oxazolidinone therapy over 5 to 7 days even at relatively high doses was predicted to be as safe as 10-day therapy of 600 mg linezolid every 12 h.

Exploration of optimal dosing regimens of vancomycin in patients infected with methicillin-resistant Staphylococcus aureus by modeling and simulation

WHAT IS KNOWN AND OBJECTIVE

Vancomycin is the drug of choice for methicillin-resistant Staphylococcus aureus (MRSA) infection and shows time-dependent bacterial killing. The current study evaluated the pharmacokinetics (PK) and pharmacodynamics (PD) of vancomycin and explored its optimal dosing regimens by modeling and simulation.

METHODS

Pharmacokinetics study was performed for 20 patients who were treated with vancomycin intravenously, 1000 mg, every 12 h, and blood for PK was randomly drawn within prespecified time windows. PD study was in vitro time-kill experiment for vancomycin against 20 MRSA strains independent of the PK study, where bacterial titre was measured at 0, 2, 4, 8, 24 h after the beginning of vancomycin exposure at 0, 1, 2, 4, 8, 16, 32× minimum inhibitory concentrations. PK and PD models were built from each data set, and simulation for MRSA titre changes over time in human body was performed for various vancomycin dosing regimens using NONMEM(®) .

RESULTS

Vancomycin followed a two-compartment PK model, and creatinine clearance was the significant covariate affecting the clearance of vancomycin. PD model described the in vitro time-kill data well. The PK/PD model predicted clear dose-response relationships of vancomycin. The therapeutic dosing regimens of vancomycin, suggested by the simulation studies, showed good agreement with the current clinical practice guidance, which indicates that this PK/PD modeling and simulation approach could prove useful for identifying optimal dosing regimens of other antibiotics and expediting novel antibiotic development. Using PD model from in vitro time-kill study and human PK model from phase 1 study, we could predict whether the drug is going to be efficacious or obtain insight into the optimal dosing regimens for a novel antibiotic agent in the early phases of drug development process.

Quantifying subpopulation synergy for antibiotic combinations via mechanism-based modeling and a sequential dosing design

Quantitative modeling of combination therapy can describe the effects of each antibiotic against multiple bacterial populations. Our aim was to develop an efficient experimental and modeling strategy that evaluates different synergy mechanisms using a rapidly killing peptide antibiotic (nisin) combined with amikacin or linezolid as probe drugs. Serial viable counts over 48 h were obtained in time-kill experiments with all three antibiotics in monotherapy against a methicillin-resistant Staphylococcus aureus USA300 strain (inoculum, 10(8) CFU/ml). A sequential design (initial dosing of 8 or 32 mg/liter nisin, switched to amikacin or linezolid at 1.5 h) assessed the rate of killing by amikacin and linezolid against nisin-intermediate and nisin-resistant populations. Simultaneous combinations were additionally studied and all viable count profiles comodeled in S-ADAPT and NONMEM. A mechanism-based model with six populations (three for nisin times two for amikacin) yielded unbiased and precise (r = 0.99, slope = 1.00; S-ADAPT) individual fits. The second-order killing rate constants for nisin against the three populations were 5.67, 0.0664, and 0.00691 liter/(mg · h). For amikacin, the maximum killing rate constants were 10.1 h(-1) against its susceptible and 0.771 h(-1) against its less-susceptible populations, with 14.7 mg/liter amikacin causing half-maximal killing. After incorporating the effects of nisin and amikacin against each population, no additional synergy function was needed. Linezolid inhibited successful bacterial replication but did not efficiently kill populations less susceptible to nisin. Nisin plus amikacin achieved subpopulation synergy. The proposed sequential and simultaneous dosing design offers an efficient approach to quantitatively characterize antibiotic synergy over time and prospectively evaluate antibiotic combination dosing strategies.