Novel approach to optimize synergistic carbapenem-aminoglycoside combinations against carbapenem-resistant Acinetobacter baumannii

Two-way pharmacodynamic modeling of drug combinations and its application to pairs of repurposed Ebola and SARS-CoV-2 agents

Existing pharmacodynamic (PD) mathematical models for drug combinations discriminate antagonistic, additive, multiplicative, and synergistic effects, but fail to consider how concentration-dependent drug interaction effects may vary across an entire dose-response matrix. We developed a two-way pharmacodynamic (TWPD) model to capture the PD of two-drug combinations. TWPD captures interactions between upstream and downstream drugs that act on different stages of viral replication, by quantifying upstream drug efficacy and concentration-dependent effects on downstream drug pharmacodynamic parameters. We applied TWPD to previously published in vitro drug matrixes for repurposed potential anti-Ebola and anti-SARS-CoV-2 drug pairs. Depending on the drug pairing, the model recapitulated combined efficacies as or more accurately than existing models and can be used to infer efficacy at untested drug concentrations. TWPD fits the data slightly better in one direction for all drug pairs, meaning that we can tentatively infer the upstream drug. Based on its high accuracy, TWPD could be used in concert with PK models to estimate the therapeutic effects of drug pairs in vivo.

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.

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.

International consensus recommendations for the use of prolonged-infusion beta-lactam antibiotics: Endorsed by the American College of Clinical Pharmacy, British Society for Antimicrobial Chemotherapy, Cystic Fibrosis Foundation, European Society of Clinical Microbiology and Infectious Diseases, Infectious Diseases Society of America, Society of Critical Care Medicine, and Society of Infectious Diseases Pharmacists

Intravenous β-lactam antibiotics remain a cornerstone in the management of bacterial infections due to their broad spectrum of activity and excellent tolerability. β-lactams are well established to display time-dependent bactericidal activity, where reductions in bacterial burden are directly associated with the time that free drug concentrations remain above the minimum inhibitory concentration (MIC) of the pathogen during the dosing interval. In an effort to take advantage of these bactericidal characteristics, prolonged (extended and continuous) infusions (PIs) can be applied during the administration of intravenous β-lactams to increase time above the MIC. PI dosing regimens have been implemented worldwide, but implementation is inconsistent. We report consensus therapeutic recommendations for the use of PI β-lactams developed by an expert international panel with representation from clinical pharmacy and medicine. This consensus guideline provides recommendations regarding pharmacokinetic and pharmacodynamic targets, therapeutic drug-monitoring considerations, and the use of PI β-lactam therapy in the following patient populations: severely ill and nonseverely ill adult patients, pediatric patients, and obese patients. These recommendations provide the first consensus guidance for the use of β-lactam therapy administered as PIs and have been reviewed and endorsed by the American College of Clinical Pharmacy (ACCP), the British Society for Antimicrobial Chemotherapy (BSAC), the Cystic Fibrosis Foundation (CFF), the European Society of Clinical Microbiology and Infectious Diseases (ESCMID), the Infectious Diseases Society of America (IDSA), the Society of Critical Care Medicine (SCCM), and the Society of Infectious Diseases Pharmacists (SIDP).

Evaluation of synergistic activity of antibiotic combinations in extensive drug-resistant Acinetobacter species using checkerboard assay

Introduction. Acinetobacter is one of the challenging drug-resistant organisms that can endanger patients' lives if not treated properly.Aim. This study was designed to investigate the activity of three synergistic antimicrobial combinations against extensive drug-resistant Acinetobacter isolates; ampicillin/sulbactam plus amikacin, ampicillin/sulbactam plus ciprofloxacin, and meropenem plus amikacin.Methodology. Minimum inhibitory concentrations of 100 XDR-Acinetobacter isolates were determined using the Vitek2 system. The broth micro-dilution method was performed to determine tigecycline MIC. Checkerboard assay was used to evaluate in vitro activity of the three antibiotic combinations.Results. MIC results by the Vitek 2C system revealed that all Acinetobacter isolates were resistant to all tested antibiotics except for colistin against which no resistance was reported. As for tigecycline, all isolates were susceptible. Regarding MIC results of each antibiotic, all isolates were resistant to meropenem and ciprofloxacin. While 95 % of isolates were resistant to both ampicillin/sulbactam and amikacin. The activities of antibiotic combinations by checkerboard assay were as follows: ampicillin/sulbactam plus amikacin was synergic in 52 %, additive 40 % and indifferent in 8 % of isolates, ampicillin/sulbactam plus ciprofloxacin was synergic in 40 %, additive 46 % and indifferent in 14 % of isolates, meropenem/amikacin combination was synergic in 22 %, additive in 49 % of isolates and indifferent in 29 % of isolates. No antagonistic activity was detected against any of the tested antibiotic combinations.Conclusion. Ampicillin/sulbactam plus amikacin showed the highest synergistic activity followed by ampicillin/sulbactam plus ciprofloxacin. This reflects the value of adding aminoglycosides to either of a β-lactam or quinolone. The tested antibiotic combinations are promising treatment options for XDR-Acinetobacter.

Carbapenem Resistance Associated with Coliuria among Outpatient and Hospitalized Urology Patients

The World Health Organization in 2017 listed carbapenem resistant Enterobacteriaceae (CRE) with critical priority for research. A research to assess carbapenem resistant Escherichia coli (CREc) in coliuria among the outpatients and inpatients of a tertiary health institution was carried out using conventional methods, polymerase chain reaction, Sanger sequencing, and bioinformatics. There were 39 positive coliuria cases from the urine samples collected from a total of 126 patients with various genitourinary diseases. The E. coli enumeration (log₁₀ CFU/mL) revealed that 82.1% (n = 32) of the samples showed significant coliuria, 12.8% (n = 5) showed non-significant coliuria while 5.1% (n = 2) showed indeterminate coliuria even when repeated. Significantly higher numbers (p > 0.05) of the sampled inpatients yielded positive coliuria (57.9%) than the outpatients. Though there were significantly more (P > 0.05) urology female patients (n = 77) than male (n = 49), coliuria was more prevalent in sampled male patients (34.9%) than female (28.6%). Highest prevalence of coliuria was observed among the age range (18–30) years. Selected CREc that was sequenced and the sequences submitted to GenBank of National Center for Biotechnological Information (NCBI) were Escherichia coli AYO-WINI111 and Escherichia coli AYO-WINI112 with accession number MT735391 and MT735392, respectively. High resistance was observed against ertapenem (53%), imipenem (62%), meropenem (48%), and doripenem (47%), while 7%–22% of the isolates showed phenotypic intermediate carbapenem resistance. Critically dangerous CREc are harboured by large number urology patients in the study area, depicting the need for more attention in the management of the condition, as CREc are close to achieving totally antibiotic resistance.

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.

Efficient simulation of clinical target response surfaces

Simulation of combination therapies is challenging due to computational complexity. Either a simple model is used to simulate the response for many combinations of concentration to generate a response surface but parameter variability and uncertainty are neglected and the concentrations are constant—the link to the doses to be administered is difficult to make—or a population pharmacokinetic/pharmacodynamic model is used to predict the response to combination therapy in a clinical trial taking into account the time‐varying concentration profile, interindividual variability (IIV), and parameter uncertainty but simulations are limited to only a few selected doses. We devised new algorithms to efficiently search for the combination doses that achieve a predefined efficacy target while taking into account the IIV and parameter uncertainty. The result of this method is a response surface of confidence levels, indicating for all dose combinations the likelihood of reaching the specified efficacy target. We highlight the importance to simulate across a population rather than focus on an individual. Finally, we provide examples of potential applications, such as informing experimental design.

Effect of Different Piperacillin-Tazobactam Dosage Regimens on Synergy of the Combination with Tobramycin against Pseudomonas aeruginosa for the Pharmacokinetics of Critically Ill Patients in a Dynamic Infection Model

We evaluated piperacillin-tazobactam and tobramycin regimens against Pseudomonas aeruginosa isolates from critically ill patients. Static-concentration time-kill studies (SCTK) assessed piperacillin-tazobactam and tobramycin monotherapies and combinations against four isolates over 72 h. A 120 h-dynamic in vitro infection model (IVM) investigated isolates Pa1281 (MICpiperacillin 4 mg/L, MICtobramycin 0.5 mg/L) and CR380 (MICpiperacillin 32 mg/L, MICtobramycin 1 mg/L), simulating the pharmacokinetics of: (A) tobramycin 7 mg/kg q24 h (0.5 h-infusions, t1/2 = 3.1 h); (B) piperacillin 4 g q4 h (0.5 h-infusions, t1/2 = 1.5 h); (C) piperacillin 24 g/day, continuous infusion; A + B; A + C. Total and less-susceptible bacteria were determined. SCTK demonstrated synergy of the combination for all isolates. In the IVM, regimens A and B provided initial killing, followed by extensive regrowth by 72 h for both isolates. C provided >4 log10 CFU/mL killing, followed by regrowth close to initial inoculum by 96 h for Pa1281, and suppressed growth to <4 log10 CFU/mL for CR380. A and A + B initially suppressed counts of both isolates to <1 log10 CFU/mL, before regrowth to control or starting inoculum and resistance emergence by 72 h. Overall, the combination including intermittent piperacillin-tazobactam did not provide a benefit over tobramycin monotherapy. A + C, the combination regimen with continuous infusion of piperacillin-tazobactam, provided synergistic killing (counts <1 log10 CFU/mL) of Pa1281 and CR380, and suppressed regrowth to <2 and <4 log10 CFU/mL, respectively, and resistance emergence over 120 h. The shape of the concentration-time curve was important for synergy of the combination.

Systematic review and meta-analysis of in vitro efficacy of antibiotic combination therapy against carbapenem-resistant Gram-negative bacilli

The superiority of combination therapy for carbapenem-resistant Gram-negative bacilli (CR-GNB) infections remains controversial. In vitro models may predict the efficacy of antibiotic regimens against CR-GNB. A systematic review and meta-analysis was performed including pharmacokinetic/pharmacodynamic (PK/PD) and time-kill (TK) studies examining the in vitro efficacy of antibiotic combinations against CR-GNB [PROSPERO registration no. CRD42019128104]. The primary outcome was in vitro synergy based on the effect size (ES): high, ES ≥ 0.75, moderate, 0.35 < ES < 0.75; low, ES ≤ 0.35; and absent, ES = 0). A network meta-analysis assessed the bactericidal effect and re-growth rate (secondary outcomes). An adapted version of the ToxRTool was used for risk-of-bias assessment. Over 180 combination regimens from 136 studies were included. The most frequently analysed classes were polymyxins and carbapenems. Limited data were available for ceftazidime/avibactam, ceftolozane/tazobactam and imipenem/relebactam. High or moderate synergism was shown for polymyxin/rifampicin against Acinetobacter baumannii [ES = 0.91, 95% confidence interval (CI) 0.44-1.00], polymyxin/fosfomycin against Klebsiella pneumoniae (ES = 1.00, 95% CI 0.66-1.00) and imipenem/amikacin against Pseudomonas aeruginosa (ES = 1.00, 95% CI 0.21-1.00). Compared with monotherapy, increased bactericidal activity and lower re-growth rates were reported for colistin/fosfomycin and polymyxin/rifampicin in K. pneumoniae and for imipenem/amikacin or imipenem/tobramycin against P. aeruginosa. High quality was documented for 65% and 53% of PK/PD and TK studies, respectively. Well-designed in vitro studies should be encouraged to guide the selection of combination therapies in clinical trials and to improve the armamentarium against carbapenem-resistant bacteria.

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.

Key Challenges in Providing Effective Antibiotic Therapy for Critically Ill Patients with Bacterial Sepsis and Septic Shock

Early initiation of effective antibiotic therapy is vitally important for saving the lives of critically ill patients with sepsis or septic shock. The susceptibility of the infecting pathogen and the ability of the selected dosage regimen to safely achieve the required antibiotic exposure need to be carefully considered to achieve a high probability of a successful outcome. Critically ill patients commonly experience substantial pathophysiological changes that impact the functions of various organs, including the kidneys. Many antibiotics are predominantly renally eliminated and thus renal function is a major determinant of the regimen needed to achieve the required antibiotic exposure. However, currently, there is a paucity of guidelines to inform antibiotic dosing in critically ill patients, including those with sepsis or septic shock. This paper briefly reviews methods that are commonly used in critically ill patients to provide a measure of renal function, and approaches that describe the relationship between the exposure to an antibiotic and its antibacterial effects. Two common conditions that very substantially complicate the use of antibiotics in critically ill patients with sepsis, unstable renal function, and augmented renal clearance, are considered in detail and their potential therapeutic implications are explored. Suggestions are provided on how treatment of bacterial infections in critically ill patients with sepsis might be improved. Of high potential are model-informed approaches that aim to individualize initial treatment regimens based on patient and bacterial characteristics, with refinement of regimens during treatment in response to monitoring antibiotic concentrations, responsive measures of renal function, and other important clinical data.

Can phenotypic data complement our understanding of antimycobacterial effects for drug combinations?

Objectives

To demonstrate how phenotypic cell viability data can provide insight into antimycobacterial effects for the isoniazid/rifampicin treatment backbone.

Methods

Data from a Mycobacterium komossense hollow-fibre infection model comprising a growth control group, rifampicin at three different exposures (C_max = 0.14, 0.4 and 1.47 mg/L with t_½ = 1.57 h and τ = 8 h) and rifampicin plus isoniazid (C_max rifampicin = 0.4 mg/L and C_max isoniazid = 1.2 mg/L with t_½ = 1.57 h and τ = 8 h) were used for this investigation. A non-linear mixed-effects modelling approach was used to fit conventional cfu data, quantified using solid-agar plating. Phenotypic proportions of respiring (alive), respiring but with damaged cell membrane (injured) and ‘not respiring’ (dead) cells data were quantified using flow cytometry and Sytox Green™ (Sigma–Aldrich, UK) and resazurin sodium salt staining and fitted using a multinomial logistic regression model.

Results

Isoniazid/rifampicin combination therapy displayed a decreasing overall antimicrobial effect with time (θTime1/2 = 438 h) on cfu data, in contrast to rifampicin monotherapy where this trend was absent. In the presence of isoniazid a phenotype associated with cell injury was displayed, whereas with rifampicin monotherapy a pattern of phenotypic cell death was observed. Bacterial killing onset time on cfu data correlated negatively (θTime50 = 28.9 h, θLAGRIF50 = 0.132 mg/L) with rifampicin concentration up to 0.165 mg/L and this coincided with a positive relationship between rifampicin concentration and the probability of phenotypic cell death.

Conclusions

Cell viability data provide structured information on the pharmacodynamic interaction between isoniazid and rifampicin that complements the understanding of the antibacillary effects of this mycobacterial treatment backbone.

A review on bacterial resistance to carbapenems: epidemiology, detection and treatment options

Carbapenems are a class of antimicrobial agents reserved for infections caused by multidrug-resistant microorganisms. The emergence of carbapenem resistance has become a serious public health threat. This type of antimicrobial resistance is spreading at an alarming rate, resulting in major outbreaks and treatment failure of community-acquired and nosocomial infections caused by the clinically relevant carbapenem-producing Enterobacteriaceae or carbapenem-resistant Enterobacteriaceae. This review is focused on carbapenem resistance, including mechanisms of resistance, history and epidemiology, phenotypic and genotypic detection in the clinically relevant bacterial pathogens and the possible treatment options available.

Meropenem-Tobramycin Combination Regimens Combat Carbapenem-Resistant Pseudomonas aeruginosa in the Hollow-Fiber Infection Model Simulating Augmented Renal Clearance in Critically Ill Patients

Augmented renal clearance (ARC) is common in critically ill patients and is associated with subtherapeutic concentrations of renally eliminated antibiotics. We investigated the impact of ARC on bacterial killing and resistance amplification for meropenem and tobramycin regimens in monotherapy and combination. Two carbapenem-resistant Pseudomonas aeruginosa isolates were studied in static-concentration time-kill studies. One isolate was examined comprehensively in a 7-day hollow-fiber infection model (HFIM). Pharmacokinetic profiles representing substantial ARC (creatinine clearance of 250 ml/min) were generated in the HFIM for meropenem (1 g or 2 g administered every 8 h as 30-min infusion and 3 g/day or 6 g/day as continuous infusion [CI]) and tobramycin (7 mg/kg of body weight every 24 h as 30-min infusion) regimens. The time courses of total and less-susceptible bacterial populations and MICs were determined for the monotherapies and all four combination regimens. Mechanism-based mathematical modeling (MBM) was performed. In the HFIM, maximum bacterial killing with any meropenem monotherapy was ∼3 log₁₀ CFU/ml at 7 h, followed by rapid regrowth with increases in resistant populations by 24 h (meropenem MIC of up to 128 mg/liter). Tobramycin monotherapy produced extensive initial killing (∼7 log₁₀ at 4 h) with rapid regrowth by 24 h, including substantial increases in resistant populations (tobramycin MIC of 32 mg/liter). Combination regimens containing meropenem administered intermittently or as a 3-g/day CI suppressed regrowth for ∼1 to 3 days, with rapid regrowth of resistant bacteria. Only a 6-g/day CI of meropenem combined with tobramycin suppressed regrowth and resistance over 7 days. MBM described bacterial killing and regrowth for all regimens well. The mode of meropenem administration was critical for the combination to be maximally effective against carbapenem-resistant P. aeruginosa.

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.

Comparable Efficacy and Better Safety of Double β-Lactam Combination Therapy versus β‑Lactam plus Aminoglycoside in Gram-Negative Bacteria in Randomized, Controlled Trials

There is a great need for efficacious therapies against Gram-negative bacteria. Double β-lactam combination(s) (DBL) are relatively safe, and preclinical data are promising; however, their clinical role has not been well defined. We conducted a metaanalysis of the clinical and microbiological efficacy of DBL compared to β-lactam plus aminoglycoside combinations (BLAG). PubMed, Embase, ISI Web of Knowledge, and Cochrane Controlled Trials Register database were searched through July 2018. We included randomized controlled clinical trials that compared DBL with BLAG combinations. Clinical response was used as the primary outcome and microbiological response in Gram-negative bacteria as the secondary outcome; sensitivity analyses were performed for Pseudomonas aeruginosa, Klebsiella spp., and Escherichia coli Heterogeneity and risk of bias were assessed. Safety results were classified by systems and organs. Thirteen studies evaluated 2,771 cases for clinical response and 665 cases for microbiological response in various Gram-negative species. DBL achieved slightly, but not significantly, better clinical response (risk ratio, 1.05; 95% confidence interval [CI], 0.99 to 1.11) and microbiological response in Gram-negatives (risk ratio, 1.11; 95% CI, 0.99 to 1.25) compared with BLAG. Sensitivity analyses by pathogen showed the same trend. No significant heterogeneity across studies was found. DBL was significantly safer than BLAG regarding renal toxicity (6.6% versus 8.8%, P = 0.0338) and ototoxicity (0.7 versus 3.1%, P = 0.0137). Other adverse events were largely comparable. Overall, empirically designed DBL showed comparable clinical and microbiological responses across different Gram-negative species, and were significantly safer than BLAG. Therefore, DBL should be rationally optimized via the latest translational approaches, leveraging mechanistic insights and newer β-lactams for future evaluation in clinical trials.

Pharmacodynamic Drug-Drug Interactions

Pharmacodynamic drug-drug interactions (DDIs) occur when the pharmacological effect of one drug is altered by that of another drug in a combination regimen. DDIs often are classified as synergistic, additive, or antagonistic in nature, albeit these terms are frequently misused. Within a complex pathophysiological system, the mechanism of interaction may occur at the same target or through alternate pathways. Quantitative evaluation of pharmacodynamic DDIs by employing modeling and simulation approaches is needed to identify and optimize safe and effective combination therapy regimens. This review investigates the opportunities and challenges in pharmacodynamic DDI studies and highlights examples of quantitative methods for evaluating pharmacodynamic DDIs, with a particular emphasis on the use of mechanism-based modeling and simulation in DDI studies. Advancements in both experimental and computational techniques will enable the application of better, model-informed assessments of pharmacodynamic DDIs in drug discovery, development, and therapeutics.

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.

Novel Polymyxin Combination with the Antiretroviral Zidovudine Exerts Synergistic Killing against NDM-Producing Multidrug-Resistant Klebsiella pneumoniae

Polymyxins are used as a last-line therapy against multidrug-resistant (MDR) New Delhi metallo-β-lactamase (NDM)-producing Klebsiella pneumoniae However, polymyxin resistance can emerge with monotherapy; therefore, novel strategies are urgently needed to minimize the resistance and maintain their clinical utility. This study aimed to investigate the pharmacodynamics of polymyxin B in combination with the antiretroviral drug zidovudine against K. pneumoniae Three isolates were evaluated in static time-kill studies (0 to 64 mg/liter) over 48 h. An in vitro one-compartment pharmacokinetic/pharmacodynamic (PK/PD) model (IVM) was used to simulate humanized dosage regimens of polymyxin B (4 mg/liter as continuous infusion) and zidovudine (as bolus dose thrice daily to achieve maximum concentration of drug in broth [C _max] of 6 mg/liter) against K. pneumoniae BM1 over 72 h. The antimicrobial synergy of the combination was further evaluated in a murine thigh infection model against K. pneumoniae 02. In the static time-kill studies, polymyxin B monotherapy produced rapid and extensive killing against all three isolates followed by extensive regrowth, whereas zidovudine produced modest killing followed by significant regrowth at 24 h. Polymyxin B in combination with zidovudine significantly enhanced the antimicrobial activity (≥4 log₁₀ CFU/ml) and minimized bacterial regrowth. In the IVM, the combination was synergistic and the total bacterial loads were below the limit of detection for up to 72 h. In the murine thigh infection model, the bacterial burden at 24 h in the combination group was ≥3 log₁₀ CFU/thigh lower than each monotherapy against K. pneumoniae 02. Overall, the polymyxin B-zidovudine combination demonstrates superior antimicrobial efficacy and minimized emergence of resistance to polymyxins.

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.

Meropenem Combined with Ciprofloxacin Combats Hypermutable Pseudomonas aeruginosa from Respiratory Infections of Cystic Fibrosis Patients

Hypermutable Pseudomonas aeruginosa organisms are prevalent in chronic respiratory infections and have been associated with reduced lung function in cystic fibrosis (CF); these isolates can become resistant to all antibiotics in monotherapy. This study aimed to evaluate the time course of bacterial killing and resistance of meropenem and ciprofloxacin in combination against hypermutable and nonhypermutable P. aeruginosa Static concentration time-kill experiments over 72 h assessed meropenem and ciprofloxacin in mono- and combination therapies against PAO1 (nonhypermutable), PAOΔmutS (hypermutable), and hypermutable isolates CW8, CW35, and CW44 obtained from CF patients with chronic respiratory infections. Meropenem (1 or 2 g every 8 h [q8h] as 3-h infusions and 3 g/day as a continuous infusion) and ciprofloxacin (400 mg q8h as 1-h infusions) in monotherapies and combinations were further evaluated in an 8-day hollow-fiber infection model study (HFIM) against CW44. Concentration-time profiles in lung epithelial lining fluid reflecting the pharmacokinetics in CF patients were simulated and counts of total and resistant bacteria determined. All data were analyzed by mechanism-based modeling (MBM). In the HFIM, all monotherapies resulted in rapid regrowth with resistance at 48 h. The maximum daily doses of 6 g meropenem (T_>MIC of 80% to 88%) and 1.2 g ciprofloxacin (area under the concentration-time curve over 24 h in the steady state divided by the MIC [AUC/MIC], 176), both given intermittently, in monotherapy failed to suppress regrowth and resulted in substantial emergence of resistance (≥7.6 log₁₀ CFU/ml resistant populations). The combination of these regimens achieved synergistic killing and suppressed resistance. MBM with subpopulation and mechanistic synergy yielded unbiased and precise curve fits. Thus, the combination of 6 g/day meropenem plus ciprofloxacin holds promise for future clinical evaluation against infections by susceptible hypermutable P. aeruginosa.

Evaluation of Aminoglycoside and Carbapenem Resistance in a Collection of Drug-Resistant Pseudomonas aeruginosa Clinical Isolates

Pseudomonas aeruginosa, a Gram-negative bacterium, is a member of the ESKAPE pathogens and one of the leading causes of healthcare-associated infections worldwide. Aminoglycosides (AGs) are recognized for their efficacy against P. aeruginosa. The most common resistance mechanism against AGs is the acquisition of AG-modifying enzymes (AMEs) by the bacteria, including AG N-acetyltransferases (AACs), AG O-phosphotransferases (APHs), and AG O-nucleotidyltransferases (ANTs). In this study, we obtained 122 multidrug-resistant P. aeruginosa clinical isolates and evaluated the antibacterial effects of six AGs and two carbapenems alone against all clinical isolates, and in combination against eight selected strains. We further probed for four representatives of the most common AME genes [aac(6')-Ib, aac(3)-IV, ant(2")-Ia, and aph(3')-Ia] by polymerase chain reaction (PCR) and compared the AME patterns of these 122 clinical isolates to their antibiotic resistance profile. Among the diverse antibiotics resistance profile displayed by these clinical isolates, we found correlations between the resistance to various AGs as well as between the resistance to one AG and the resistance to carbapenems. PCR results revealed that the presence of aac(6')-Ib renders these isolates more resistant to a variety of antibiotics. The correlation between resistance to various AGs and carbapenems partially reflects the complex resistance strategies adapted in these pathogens and encourages the development of strategic treatment for each P. aeruginosa infection by considering the genetic information of each isolated bacteria.

Synergy effect of meropenem-based combinations against Acinetobacter baumannii: a systematic review and meta-analysis

PURPOSE

The main objective of our meta-analysis was to examine the in vitro synergistic effect of meropenem-based combination therapies against Acinetobacter baumannii through a systematic review of the existing literature.

METHODS

An extensive search was performed with no restrictions on date of publication, language, and publication type. Our study evaluated the main conclusions drawn from various studies describing the synergistic activity of combination therapies in vitro.

RESULTS

In this review, 56 published studies were included. Our report included data on 20 types of antibiotics combined with meropenem in 1,228 Acinetobacter baumannii isolates. In time-kill studies, meropenem combined with polymyxin B and rifampicin showed synergy rates of 98.3% (95% CI, 83.7%-100.0%) and 89.4% (95% CI, 57.2%-100.0%), respectively, for Acinetobacter baumannii, modest synergy rates were found for meropenem combined with several antibiotics such as colistin and sulbactam, and no synergy effect was displayed in the combination of meropenem and ciprofloxacin, whereas in checkerboard method, the synergy rates of polymyxin B and rifampicin were 37.0% (95% CI, 0.00%-100.0%) and 56.3% (95% CI, 8.7%-97.8%), respectively.

CONCLUSION

We found that time-kill studies generally identified the greatest synergy, while checkerboard and Etest methods yielded relatively poor synergy rates. Further well-designed in vivo studies should be carried out to confirm these findings.

Polymyxin B in Combination with Enrofloxacin Exerts Synergistic Killing against Extensively Drug-Resistant Pseudomonas aeruginosa

Polymyxins are increasingly used as a last-resort class of antibiotics against extensively drug-resistant (XDR) Gram-negative bacteria. However, resistance to polymyxins can emerge with monotherapy. As nephrotoxicity is the major dose-limiting factor for polymyxin monotherapy, dose escalation to suppress the emergence of polymyxin resistance is not a viable option. Therefore, novel approaches are needed to preserve this last-line class of antibiotics. This study aimed to investigate the antimicrobial synergy of polymyxin B combined with enrofloxacin against Pseudomonas aeruginosa Static time-kill studies were conducted over 24 h with polymyxin B (1 to 4 mg/liter) and enrofloxacin (1 to 4 mg/liter) alone or in combination. Additionally, in vitro one-compartment model (IVM) and hollow-fiber infection model (HFIM) experiments were performed against P. aeruginosa 12196. Polymyxin B and enrofloxacin in monotherapy were ineffective against all of the P. aeruginosa isolates examined, whereas polymyxin B-enrofloxacin in combination was synergistic against P. aeruginosa, with ≥2 to 4 log₁₀ kill at 24 h in the static time-kill studies. In both IVM and HFIM, the combination was synergistic, and the bacterial counting values were below the limit of quantification on day 5 in the HFIM. A population analysis profile indicated that the combination inhibited the emergence of polymyxin resistance in P. aeruginosa 12196. The mechanism-based modeling suggests that the synergistic killing is a result of the combination of mechanistic and subpopulation synergy. Overall, this is the first preclinical study to demonstrate that the polymyxin-enrofloxacin combination is of considerable utility for the treatment of XDR P. aeruginosa infections and warrants future clinical evaluations.

Optimization and Evaluation of Piperacillin-Tobramycin Combination Dosage Regimens against Pseudomonas aeruginosa for Patients with Altered Pharmacokinetics via the Hollow-Fiber Infection Model and Mechanism-Based Modeling

Augmented renal clearance (ARC) in critically ill patients can result in suboptimal drug exposures and treatment failure. Combination dosage regimens accounting for ARC have never been optimized and evaluated against Pseudomonas aeruginosa by use of the hollow-fiber infection model (HFIM). Using a P. aeruginosa isolate from a critically ill patient and static-concentration time-kill experiments (SCTKs), we studied clinically relevant piperacillin and tobramycin concentrations, alone and in combinations, against two inocula (10^5.8 and 10^7.6 CFU/ml) over 72 h. We subsequently evaluated the effects of optimized piperacillin (4 g every 4 h [q4h], given as 0.5-h infusions) plus tobramycin (5 mg/kg of body weight q24h, 7 mg/kg q24h, or 10 mg/kg q48h, given as 0.5-h infusions) regimens on killing and regrowth in the HFIM, simulating a creatinine clearance of 250 ml/min. Mechanism-based modeling was performed in S-ADAPT. In SCTKs, piperacillin plus tobramycin (except combinations with 8 mg/liter tobramycin and against the low inoculum) achieved synergistic killing (≥2 log₁₀ versus the most active monotherapy at 48 h and 72 h) and prevented regrowth. Piperacillin monotherapy (4 g q4h) in the HFIM provided 2.4-log₁₀ initial killing followed by regrowth at 24 h and resistance emergence. Tobramycin monotherapies displayed rapid initial killing (≥5 log₁₀ at 13 h) followed by extensive regrowth. As predicted by mechanism-based modeling, the piperacillin plus tobramycin dosage regimens were synergistic and provided ≥5-log₁₀ killing with resistance suppression over 8 days in the HFIM. Optimized piperacillin-tobramycin regimens provided significant bacterial killing and suppressed resistance emergence. These regimens appear to be highly promising for effective and early treatment, even in the near-worst-case scenario of ARC.

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.

Optimization of a Meropenem-Tobramycin Combination Dosage Regimen against Hypermutable and Nonhypermutable Pseudomonas aeruginosa via Mechanism-Based Modeling and the Hollow-Fiber Infection Model

Hypermutable Pseudomonas aeruginosa strains are prevalent in patients with cystic fibrosis and rapidly become resistant to antibiotic monotherapies. Combination dosage regimens have not been optimized against such strains using mechanism-based modeling (MBM) and the hollow-fiber infection model (HFIM). The PAO1 wild-type strain and its isogenic hypermutable PAOΔmutS strain (MIC_meropenem of 1.0 mg/liter and MIC_tobramycin of 0.5 mg/liter for both) were assessed using 96-h static-concentration time-kill studies (SCTK) and 10-day HFIM studies (inoculum, ∼10^8.4 CFU/ml). MBM of SCTK data were performed to predict expected HFIM outcomes. Regimens studied in the HFIM were meropenem at 1 g every 8 h (0.5-h infusion), meropenem at 3 g/day with continuous infusion, tobramycin at 10 mg/kg of body weight every 24 h (1-h infusion), and both combinations. Meropenem regimens delivered the same total daily dose. Time courses of total and less susceptible populations and MICs were determined. For the PAOΔmutS strain in the HFIM, all monotherapies resulted in rapid regrowth to >10^8.7 CFU/ml with near-complete replacement by less susceptible bacteria by day 3. Meropenem every 8 h with tobramycin caused >7-log₁₀ bacterial killing followed by regrowth to >6 log₁₀ CFU/ml by day 5 and high-level resistance (MIC_meropenem, 32 mg/liter; MIC_tobramycin, 8 mg/liter). Continuous infusion of meropenem with tobramycin achieved >8-log₁₀ bacterial killing without regrowth. For PAO1, meropenem monotherapies suppressed bacterial growth to <4 log₁₀ over 7 to 9 days, with both combination regimens achieving near eradication. An MBM-optimized meropenem plus tobramycin regimen achieved synergistic killing and resistance suppression against a difficult-to-treat hypermutable P. aeruginosa strain. For the combination to be maximally effective, it was critical to achieve the optimal shape of the concentration-time profile for meropenem.

Acinetobacter spp. as nosocomial pathogens: Epidemiology and resistance features

The genus Acinetobacter is a major cause of nosocomial infections; it is increasingly being associated with various epidemics and has become a widespread concern in a variety of hospitals worldwide. Multi-antibiotic resistant Acinetobacter baumannii, is now recognized to be of great clinical significance. Numerous reports relay to the spread of A. baumannii in the hospital settings which leads to enhanced nosocomial outbreaks associated with high death rates. However, many other Acinetobacter spp. also can cause nosocomial infections. This review focused on the role of Acinetobacter spp. as nosocomial pathogens in addition to their persistence, antimicrobial resistance patterns and epidemiology.

Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations

BACKGROUND

Deriving suitable dosing regimens for antibiotic combination therapy poses several challenges as the drug interaction can be highly complex, the traditional pharmacokinetic-pharmacodynamic (PKPD) index methodology cannot be applied straightforwardly, and exploring all possible dose combinations is unfeasible. Therefore, semi-mechanistic PKPD models developed based on in vitro single and combination experiments can be valuable to suggest suitable combination dosing regimens.

AIMS

To outline how the interaction between two antibiotics has been characterized in semi-mechanistic PKPD models. We also explain how such models can be applied to support dosing regimens and design future studies.

SOURCES

PubMed search for published semi-mechanistic PKPD models of antibiotic drug combinations.

CONTENT

Thirteen publications were identified where ten had applied subpopulation synergy to characterize the combined effect, i.e. independent killing rates for each drug and bacterial subpopulation. We report the various types of interaction functions that have been used to describe the combined drug effects and that characterized potential deviations from additivity under the PKPD model. Simulations from the models had commonly been performed to compare single versus combined dosing regimens and/or to propose improved dosing regimens.

IMPLICATIONS

Semi-mechanistic PKPD models allow for integration of knowledge on the interaction between antibiotics for various PK and PD profiles, and can account for associated variability within the population as well as parameter uncertainty. Decisions on suitable combination regimens can thereby be facilitated. We find the application of semi-mechanistic PKPD models to be essential for efficient development of antibiotic combination regimens that optimize bacterial killing and/or suppress resistance development.

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.

Aminoglycoside Concentrations Required for Synergy with Carbapenems against Pseudomonas aeruginosa Determined via Mechanistic Studies and Modeling

This study aimed to systematically identify the aminoglycoside concentrations required for synergy with a carbapenem and characterize the permeabilizing effect of aminoglycosides on the outer membrane of Pseudomonas aeruginosa Monotherapies and combinations of four aminoglycosides and three carbapenems were studied for activity against P. aeruginosa strain AH298-GFP in 48-h static-concentration time-kill studies (SCTK) (inoculum: 10^7.6 CFU/ml). The outer membrane-permeabilizing effect of tobramycin alone and in combination with imipenem was characterized via electron microscopy, confocal imaging, and the nitrocefin assay. A mechanism-based model (MBM) was developed to simultaneously describe the time course of bacterial killing and prevention of regrowth by imipenem combined with each of the four aminoglycosides. Notably, 0.25 mg/liter of tobramycin, which was inactive in monotherapy, achieved synergy (i.e., ≥2-log₁₀ more killing than the most active monotherapy at 24 h) combined with imipenem. Electron micrographs, confocal image analyses, and the nitrocefin uptake data showed distinct outer membrane damage by tobramycin, which was more extensive for the combination with imipenem. The MBM indicated that aminoglycosides enhanced the imipenem target site concentration up to 4.27-fold. Tobramycin was the most potent aminoglycoside to permeabilize the outer membrane; tobramycin (0.216 mg/liter), gentamicin (0.739 mg/liter), amikacin (1.70 mg/liter), or streptomycin (5.19 mg/liter) was required for half-maximal permeabilization. In summary, our SCTK, mechanistic studies and MBM indicated that tobramycin was highly synergistic and displayed the maximum outer membrane disruption potential among the tested aminoglycosides. These findings support the optimization of highly promising antibiotic combination dosage regimens for critically ill patients.

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling as tools to personalize gentamicin therapy

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling are all tools that can be applied to personalize gentamicin therapy. This review summarizes and evaluates literature knowledge on the population pharmacokinetics and pharmacodynamics of gentamicin and identifies areas where further research is required to successfully individualize gentamicin therapy using modelling and simulation techniques. Thirty-five studies have developed a population pharmacokinetic model of gentamicin and 15 studies have made dosing recommendations based on Monte Carlo simulation. Variability in gentamicin clearance was most commonly related to renal function in adults and body weight and age in paediatrics. Nine studies have related aminoglycoside exposure indices to clinical outcomes. Most commonly, efficacy has been linked to a Cmax/MIC ≥7-10 and a AUC24/MIC ≥70-100. No study to date has shown a relationship between predicted achievement of exposure targets and actual clinical success. Five studies have developed a semi-mechanistic pharmacokinetic/pharmacodynamic model to predict bacteria killing and regrowth following gentamicin exposure and one study has developed a deterministic model of aminoglycoside nephrotoxicity. More complex semi-mechanistic models are required that consider the immune response, use of multiple antibiotics, the severity of illness, and both efficacy and toxicity. As our understanding grows, dosing of gentamicin based on sound pharmacokinetic/pharmacodynamic principles should be applied more commonly in clinical practice.

Substantial Impact of Altered Pharmacokinetics in Critically Ill Patients on the Antibacterial Effects of Meropenem Evaluated via the Dynamic Hollow-Fiber Infection Model

Critically ill patients frequently have substantially altered pharmacokinetics compared to non-critically ill patients. We investigated the impact of pharmacokinetic alterations on bacterial killing and resistance for commonly used meropenem dosing regimens. A Pseudomonas aeruginosa isolate (MIC_meropenem 0.25 mg/liter) was studied in the hollow-fiber infection model (inoculum ∼10^7.5 CFU/ml; 10 days). Pharmacokinetic profiles representing critically ill patients with augmented renal clearance (ARC), normal, or impaired renal function (creatinine clearances of 285, 120, or ∼10 ml/min, respectively) were generated for three meropenem regimens (2, 1, and 0.5 g administered as 8-hourly 30-min infusions), plus 1 g given 12 hourly with impaired renal function. The time course of total and less-susceptible populations and MICs were determined. Mechanism-based modeling (MBM) was performed using S-ADAPT. All dosing regimens across all renal functions produced similar initial bacterial killing (≤∼2.5 log₁₀). For all regimens subjected to ARC, regrowth occurred after 7 h. For normal and impaired renal function, bacterial killing continued until 23 to 47 h; regrowth then occurred with 0.5- and 1-g regimens with normal renal function (fT_>5×MIC = 56 and 69%, fC_min/MIC < 2); the emergence of less-susceptible populations (≥32-fold increases in MIC) accompanied all regrowth. Bacterial counts remained suppressed across 10 days with normal (2-g 8-hourly regimen) and impaired (all regimens) renal function (fT_>5×MIC ≥ 82%, fC_min/MIC ≥ 2). The MBM successfully described bacterial killing and regrowth for all renal functions and regimens simultaneously. Optimized dosing regimens, including extended infusions and/or combinations, supported by MBM and Monte Carlo simulations, should be evaluated in the context of ARC to maximize bacterial killing and suppress resistance emergence.

Aminoglycosides against carbapenem-resistant Enterobacteriaceae in the critically ill: the pitfalls of aminoglycoside susceptibility

INTRODUCTION

The emergence of carbapenem-resistant Enterobacteriaceae (CRE) has brought aminoglycosides to the frontline since an aminoglycoside may be the only antimicrobial to which CRE isolates show in vitro susceptibility. The appropriateness of aminoglycoside-based therapies for severe infections by CRE is discussed considering the current breakpoints and recent pharmacokinetic (PK) studies in critically ill patients. Areas covered: Many aminoglycoside-susceptible CRE isolates present minimal inhibitory concentrations (MICs) at or slightly below the breakpoint of amikacin or gentamicin. However, recent PK studies with these aminoglycosides in critically ill have invariably shown that the PK/pharmacodynamic (PD) target is very unlikely attained even when high doses are administered, if the MICs are near the breakpoint. Expert commentary: While new antimicrobials are not widely available, the authors forecast an increasing use of aminoglycosides as backbone antibiotics against CRE isolates. However, the altered PK of aminoglycosides in critically ill patients severely impairs their predicted efficacy in these patients. Aminoglycoside breakpoints may hide 'aminoglycoside-susceptible' CRE isolates for that aminoglycosides will unlikely be effective if used in monotherapy. Therefore, these breakpoints may need to be revised due to the increasing use of aminoglycosides as backbone antibiotics to treat severe infections by CRE isolates in critically ill patients.

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.

Optimizing dosing of antibiotics in critically ill patients

PURPOSE OF REVIEW

Recent studies suggest that contemporary antibiotic dosing is unlikely to achieve best outcomes for critically ill patients because of extensive pharmacokinetic variability and altered pharmacodynamics. Dose adaptation is considered quite challenging because of unpredictable dose-exposure relationships. Consequently, individualization of antibiotic dosing has been advocated. Herein, we describe recent developments in the optimization of antibiotic dosing in the critically ill.

RECENT FINDINGS

Conventional doses of many antibiotics frequently result in sub or supratherapeutic exposures in the critically ill. Clinical studies continue to illustrate that dose-exposure relationships are highly variable in severely ill patients. Dose optimization based on pharmacokinetic/pharmacodynamic principles can effectively improve antibiotic exposure. Therapeutic drug monitoring (TDM) with adaptive feedback is likely to be the most robust approach to optimize dosing for individual patients. This more accurate approach to dosing is made possible with the user-friendly dosing software that is emerging.

SUMMARY

The scope of TDM is broadening from the traditional focus on prevention of toxicity, to include optimization of antibiotic exposure thereby improving patient outcomes. However, the evidence relating TDM practice with improved clinical outcome remains limited. Well designed, multicentre, randomized controlled studies are warranted.

High-intensity meropenem combinations with polymyxin B: new strategies to overcome carbapenem resistance in Acinetobacter baumannii

OBJECTIVES

The pharmacodynamics of polymyxin/carbapenem combinations against carbapenem-resistant Acinetobacter baumannii (CRAB) are largely unknown. Our objective was to determine whether intensified meropenem regimens in combination with polymyxin B enhance killing and resistance suppression of CRAB.

METHODS

Time-kill experiments for meropenem and polymyxin B combinations were conducted against three polymyxin B-susceptible (MIC of polymyxin B = 0.5 mg/L) CRAB strains with varying meropenem MICs (ATCC 19606, N16870 and 03-149-1; MIC of meropenem = 4, 16 and 64 mg/L, respectively) at 10⁸ cfu/mL. A hollow-fibre infection model was then used to simulate humanized regimens of polymyxin B and meropenem (2, 4, 6 and 8 g prolonged infusions every 8 h) versus N16870 at 10⁸ cfu/mL over 14 days. New mathematical mechanism-based models were developed using S-ADAPT.

RESULTS

Time-kill experiments were well described by the mathematical mechanism-based models, with the presence of polymyxin B drastically decreasing the meropenem concentration needed for half-maximal activity against meropenem-resistant populations from 438 to 82.1 (ATCC 19606), 158 to 93.6 (N16870) and 433 to 76.0 mg/L (03-149-1). The maximum killing effect of combination treatment was similar among all three strains despite divergent meropenem MIC values (E_max = 2.13, 2.08 and 2.15; MIC of meropenem = 4, 16 and 64 mg/L, respectively). Escalating the dose of meropenem in hollow-fibre combination regimens from 2 g every 8 h to 8 g every 8 h resulted in killing that progressed from a >2.5 log₁₀ cfu/mL reduction with regrowth by 72 h (2 g every 8 h) to complete eradication by 336 h (8 g every 8 h).

CONCLUSION

Intensified meropenem dosing in combination with polymyxin B may offer a unique strategy to kill CRAB irrespective of the meropenem MIC.

Antimicrobial-resistant Pseudomonas aeruginosa and Acinetobacter baumannii From Patients With Hospital-acquired or Ventilator-associated Pneumonia in Vietnam

PURPOSE

Multidrug-resistant bacterial pathogens are becoming a significant problem worldwide. Acinetobacter baumannii and Pseudomonas aeruginosa are problematic multidrug-resistant pathogens. This multicenter study in Vietnam determined the level of resistance to antimicrobial agents used to treat A baumannii and P aeruginosa infections in this country.

METHODS

Five medical centers in Vietnam provided 529 P aeruginosa and 971 Acinetobacter species (904 A baumannii) isolates from patients with hospital-acquired or ventilator-associated pneumonia from 2012 to 2014. A central laboratory verified identification of the isolates and performed susceptibility testing using Clinical and Laboratory Standards Institute methods.

FINDINGS

Resistance to cephalosporins, β-lactam/β-lactamase inhibitors, carbapenems, and fluoroquinolones was >90% against A baumannii. Aminoglycosides had only slightly better activity, with amikacin resistance >80%. Only colistin (MIC90, ≤0.25 mg/L) and tigecycline (MIC90, 4 mg/L) had appreciable activity against A baumannii. Similar activity was observed among the β-lactams tested against P aeruginosa. Cefepime demonstrated the highest activity (60.1% susceptible), which was similar to doripenem (58.6% susceptible), the most active carbapenem tested. Amikacin was the most active aminoglycoside tested against P aeruginosa, with susceptibility of 81.7% compared with tobramycin (58.0%) and gentamicin (56.5%). Fluoroquinolones had limited activity against P aeruginosa with susceptibility to ciprofloxacin (55.0%). All P aeruginosa isolates had colistin MIC values ≤2 mg/L.

IMPLICATIONS

The data from this 3-year longitudinal study in Vietnam demonstrate that 2 of the most common nonfermentative gram-negative pathogens associated with hospital-acquired and ventilator-associated pneumonia are significantly resistant to most of the available treatment options and require combination therapies unless new antimicrobial agents become available.

Effect of different renal function on antibacterial effects of piperacillin against Pseudomonas aeruginosa evaluated via the hollow-fibre infection model and mechanism-based modelling

BACKGROUND

Pathophysiological changes in critically ill patients can cause severely altered pharmacokinetics and widely varying antibiotic exposures. The impact of altered pharmacokinetics on bacterial killing and resistance has not been characterized in the dynamic hollow-fibre in vitro infection model (HFIM).

METHODS

A clinical Pseudomonas aeruginosa isolate (piperacillin MIC 4 mg/L) was studied in the HFIM (inoculum ∼10(7) cfu/mL). Pharmacokinetic profiles of three piperacillin dosing regimens (4 g 8-, 6- and 4-hourly, 30 min intravenous infusion) as observed in critically ill patients with augmented renal clearance (ARC), normal renal function or impaired renal function (creatinine clearances of 250, 110 or 30 mL/min, respectively) were simulated over 7 days. The time courses of total and less-susceptible populations and MICs were determined. Mechanism-based modelling was performed in S-ADAPT.

RESULTS

For all regimens with ARC and regimens with 8- or 6-hourly dosing with normal renal function, initial killing of ≤∼2 log10 was followed by regrowth to 10(8)-10(9) cfu/mL at 48 h. For 8- and 6-hourly dosing at normal renal function, the proportion of less-susceptible colonies increased ∼10-100-fold above those in ARC and control arms. Regimens achieving an fCmin of ≥5× MIC resulted in bacterial killing of 3-4 log10 without regrowth and suppressed less-susceptible populations to ≤∼2 log10. The mechanism-based model successfully quantified the time course of bacterial growth, killing and regrowth.

CONCLUSIONS

Only high piperacillin concentrations prevented regrowth of P. aeruginosa. Individualized dosing regimens that account for altered pharmacokinetics and aim for higher-than-standard antibiotic exposures to achieve an fCmin of ≥5× MIC were required to maximize bacterial killing and suppress emergence of resistance.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling

Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS) were performed for models with one susceptible bacterial population without (M1) or with a resting stage (M2), a one population model with adaptive resistance (M5), models with pre-existing susceptible and resistant populations without (M3) or with (M4) inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6). For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range) or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h). Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions) were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10%) and had good imprecision (<30%). However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and ultimately patients.

Mathematical models are increasingly used for analysis and interpretation of in vitro efficacy results of antimicrobial drugs. Various models are employed in the scientific literature and it seems that they are equally able to describe the observed data. The aim of the present study was to compare different models in various experimental designs and with different resistance mechanisms of bacteria. For that purpose we have generated experimental data through Monte-Carlo simulations and then used six different mathematical models to analyze these results. We showed that statistical comparison of models did not allow determining which was the true mechanism of resistance, i.e. the one used for the simulation step. Moreover mathematical parameters for bacterial resistance were estimated with bias and with a low precision except for the simpler cases. This suggests that the choice of the mathematical model for data analysis should be guided by experimental characterization of the bacterial mechanism of resistance.

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.