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

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.

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.

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.

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.

When One Drug Is Not Enough: Context, Methodology, and Future Prospects in Antibacterial Synergy Testing

Antibacterial combinations have long been used to accomplish a variety of therapeutic goals, including prevention of resistance and enhanced antimicrobial activity. In vitro synergy testing methods, including the checkerboard array, the time-kill study, diffusion assays, and pharmacokinetic/pharmacodynamic models, are used commonly in the research setting, but are not routinely performed in the clinical microbiology laboratory because of test complexity and uncertainty about their predictive value for patient outcomes. Optimized synergy testing techniques and better data on the relationship between in vitro results and clinical outcomes are needed to guide the rational use of antimicrobial combinations in the multidrug resistance era.

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.

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.