Pharmacodynamic Evaluation of Plasma and Epithelial Lining Fluid Exposures of Amikacin against Pseudomonas aeruginosa in a Dynamic In Vitro Hollow-Fiber Infection Model

Keeping up with the pathogens: improved antimicrobial resistance detection and prediction from Pseudomonas aeruginosa genomes

BACKGROUND

Antimicrobial resistance (AMR) is an intensifying threat that requires urgent mitigation to avoid a post-antibiotic era. Pseudomonas aeruginosa represents one of the greatest AMR concerns due to increasing multi- and pan-drug resistance rates. Shotgun sequencing is gaining traction for in silico AMR profiling due to its unambiguity and transferability; however, accurate and comprehensive AMR prediction from P. aeruginosa genomes remains an unsolved problem.

METHODS

We first curated the most comprehensive database yet of known P. aeruginosa AMR variants. Next, we performed comparative genomics and microbial genome-wide association study analysis across a Global isolate Dataset (n = 1877) with paired antimicrobial phenotype and genomic data to identify novel AMR variants. Finally, the performance of our P. aeruginosa AMR database, implemented in our AMR detection and prediction tool, ARDaP, was compared with three previously published in silico AMR gene detection or phenotype prediction tools-abritAMR, AMRFinderPlus, ResFinder-across both the Global Dataset and an analysis-naïve Validation Dataset (n = 102).

RESULTS

Our AMR database comprises 3639 mobile AMR genes and 728 chromosomal variants, including 75 previously unreported chromosomal AMR variants, 10 variants associated with unusual antimicrobial susceptibility, and 281 chromosomal variants that we show are unlikely to confer AMR. Our pipeline achieved a genotype-phenotype balanced accuracy (bACC) of 85% and 81% across 10 clinically relevant antibiotics when tested against the Global and Validation Datasets, respectively, vs. just 56% and 54% with abritAMR, 58% and 54% with AMRFinderPlus, and 60% and 53% with ResFinder. ARDaP's superior performance was predominantly due to the inclusion of chromosomal AMR variants, which are generally not identified with most AMR identification tools.

CONCLUSIONS

Our ARDaP software and associated AMR variant database provides an accurate tool for predicting AMR phenotypes in P. aeruginosa, far surpassing the performance of current tools. Implementation of ARDaP for routine AMR prediction from P. aeruginosa genomes and metagenomes will improve AMR identification, addressing a critical facet in combatting this treatment-refractory pathogen. However, knowledge gaps remain in our understanding of the P. aeruginosa resistome, particularly the basis of colistin AMR.

Optimization of an in vitro Pseudomonas aeruginosa Biofilm Model to Examine Antibiotic Pharmacodynamics at the Air-Liquid Interface

Pseudomonas aeruginosa is an important cause of lower respiratory tract infections, such as ventilator-associated bacterial pneumonia (VABP). Using inhaled antibiotics to treat VABP can achieve high drug concentrations at the infection site while minimizing systemic toxicities. Despite the theoretical advantages, clinical trials have failed to show a benefit for inhaled antibiotic therapy in treating VABP. A potential reason for this discordance is the presence of biofilm-embedded bacteria in lower respiratory tract infections. Drug selection and dosing are often based on data from bacteria grown planktonically. In the present study, an in vitro air-liquid interface pharmacokinetic/pharmacodynamic biofilm model was optimized to evaluate the activity of simulated epithelial lining fluid exposures of inhaled and intravenous doses of polymyxin B and tobramycin against two P. aeruginosa strains. Antibiotic activity was also determined against the P. aeruginosa strains grown planktonically. Our study revealed that inhaled antibiotic exposures were more active than their intravenous counterparts across biofilm and planktonic populations. Inhaled exposures of polymyxin B and tobramycin exhibited comparable activity against planktonic P. aeruginosa. Although inhaled polymyxin B exposures were initially more active against P. aeruginosa biofilms (through 6 h), tobramycin was more active by the end of the experiment (48 h). Together, these data slightly favor the use of inhaled tobramycin for VABP caused by biofilm-forming P. aeruginosa that are not resistant to either antibiotic. The optimized in vitro air-liquid interface pharmacokinetic/pharmacodynamic biofilm model may be beneficial for the development of novel anti-biofilm agents or to optimize antibiotic dosing for infections such as VABP.

Molecular pharmacodynamics of meropenem for nosocomial pneumonia caused by Pseudomonas aeruginosa

Hospital-acquired pneumonia (HAP) is a leading cause of morbidity and mortality, commonly caused by Pseudomonas aeruginosa. Meropenem is a commonly used therapeutic agent, although emergent resistance occurs during treatment. We used a rabbit HAP infection model to assess the bacterial kill and resistance pharmacodynamics of meropenem. Meropenem 5 mg/kg administered subcutaneously (s.c.) q8h (±amikacin 3.33-5 mg/kg q8h administered intravenously[i.v.]) or meropenem 30 mg/kg s.c. q8h regimens were assessed in a rabbit lung infection model infected with P. aeruginosa, with bacterial quantification and phenotypic/genotypic characterization of emergent resistant isolates. The pharmacokinetic/pharmacodynamic output was fitted to a mathematical model, and human-like regimens were simulated to predict outcomes in a clinical context. Increasing meropenem monotherapy demonstrated a dose-response effect to bacterial kill and an inverted U relationship with emergent resistance. The addition of amikacin to meropenem suppressed the emergence of resistance. A network of porin loss, efflux upregulation, and increased expression of AmpC was identified as the mechanism of this emergent resistance. A bridging simulation using human pharmacokinetics identified meropenem 2 g i.v. q8h as the licensed clinical regimen most likely to suppress resistance. We demonstrate an innovative experimental platform to phenotypically and genotypically characterize bacterial emergent resistance pharmacodynamics in HAP. For meropenem, we have demonstrated the risk of resistance emergence during therapy and identified two mitigating strategies: (i) regimen intensification and (ii) use of combination therapy. This platform will allow pre-clinical assessment of emergent resistance risk during treatment of HAP for other antimicrobials, to allow construction of clinical regimens that mitigate this risk.IMPORTANCEThe emergence of antimicrobial resistance (AMR) during antimicrobial treatment for hospital-acquired pneumonia (HAP) is a well-documented problem (particularly in pneumonia caused by Pseudomonas aeruginosa) that contributes to the wider global antimicrobial resistance crisis. During drug development, regimens are typically determined by their sufficiency to achieve bactericidal effect. Prevention of the emergence of resistance pharmacodynamics is usually not characterized or used to determine the regimen. The innovative experimental platform described here allows characterization of the emergence of AMR during the treatment of HAP and the development of strategies to mitigate this. We have demonstrated this specifically for meropenem-a broad-spectrum antibiotic commonly used to treat HAP. We have characterized the antimicrobial resistance pharmacodynamics of meropenem when used to treat HAP, caused by initially meropenem-susceptible P. aeruginosa, phenotypically and genotypically. We have also shown that intensifying the regimen and using combination therapy are both strategies that can both treat HAP and suppress the emergence of resistance.

All Roads Lead to Rome: Enhancing the Probability of Target Attainment with Different Pharmacokinetic/Pharmacodynamic Modelling Approaches

In light of rising antimicrobial resistance and a decreasing number of antibiotics with novel modes of action, it is of utmost importance to accelerate development of novel treatment options. One aspect of acceleration is to understand pharmacokinetics (PK) and pharmacodynamics (PD) of drugs and to assess the probability of target attainment (PTA). Several in vitro and in vivo methods are deployed to determine these parameters, such as time-kill-curves, hollow-fiber infection models or animal models. However, to date the use of in silico methods to predict PK/PD and PTA is increasing. Since there is not just one way to perform the in silico analysis, we embarked on reviewing for which indications and how PK and PK/PD models as well as PTA analysis has been used to contribute to the understanding of the PK and PD of a drug. Therefore, we examined four recent examples in more detail, namely ceftazidime-avibactam, omadacycline, gepotidacin and zoliflodacin as well as cefiderocol. Whereas the first two compound classes mainly relied on the ‘classical’ development path and PK/PD was only deployed after approval, cefiderocol highly profited from in silico techniques that led to its approval. Finally, this review shall highlight current developments and possibilities to accelerate drug development, especially for anti-infectives.

Pharmacodynamics of Piperacillin-Tazobactam/Amikacin Combination versus Meropenem against Extended-Spectrum β-Lactamase-Producing Escherichia coli in a Hollow Fiber Infection Model

Carbapenems are recommended for the treatment of urosepsis caused by extended-spectrum β-lactamase (ESBL)-producing, multidrug-resistant Escherichia coli; however, due to selection of carbapenem resistance, there is an increasing interest in alternative treatment regimens including the use of β-lactam-aminoglycoside combinations. We compared the pharmacodynamic activity of piperacillin-tazobactam and amikacin as mono and combination therapy versus meropenem monotherapy against extended-spectrum β-lactamase (ESBL)-producing, piperacillin-tazobactam resistant E. coli using a dynamic hollow fiber infection model (HFIM) over 7 days. Broth-microdilution was performed to determine the MIC of E. coli isolates. Whole genome sequencing was conducted. Four E. coli isolates were tested in HFIM with an initial inoculum of ~10⁷ CFU/mL. Dosing regimens tested were piperacillin-tazobactam 4.5 g, 6-hourly, plus amikacin 30 mg/kg, 24-hourly, as combination therapy, and piperacillin-tazobactam 4.5 g, 6-hourly, amikacin 30 mg/kg, 24-hourly, and meropenem 1 g, 8-hourly, each as monotherapy. We observed that piperacillin-tazobactam and amikacin monotherapy demonstrated initial rapid bacterial killing but then led to amplification of resistant subpopulations. The piperacillin-tazobactam/amikacin combination and meropenem experiments both attained a rapid bacterial killing (~4-5 log₁₀) within 24 h and did not result in any emergence of resistant subpopulations. Genome sequencing demonstrated that all ESBL-producing E. coli clinical isolates carried multiple antibiotic resistance genes including bla_CTX-M-15, bla_OXA-1, bla_EC, bla_TEM-1, and aac(6')-Ib-cr. These results suggest that the combination of piperacillin-tazobactam/amikacin may have a potential role as a carbapenem-sparing regimen, which should be tested in future urosepsis clinical trials.

The Application of Hollow Fiber Cartridge in Biomedicine

The hollow fiber cartridge has the advantages of good semi-permeability, high surface area to volume ratio, convenient operation, and so on. Its application in chemical analysis, drug in vitro experiment, hemodialysis, and other fields has been deeply studied. This paper introduces the basic structure of hollow fiber cartridge, compares the advantages and disadvantages of a hollow fiber infection model constructed by a hollow fiber cartridge with traditional static model and animal infection model and introduces its application in drug effects, mechanism of drug resistance, and evaluation of combined drug regimen. The principle and application of hollow fiber bioreactors for cell culture and hollow fiber dialyzer for dialysis and filtration were discussed. The hollow fiber cartridge, whether used in drug experiments, artificial liver, artificial kidney, etc., has achieved controllable experimental operation and efficient and accurate experimental results, and will provide more convenience and support for drug development and clinical research in the future.

Determination of Tedizolid in Bacterial Growth Medium Mueller-Hinton Broth by High-Performance Liquid Chromatography and Its Application to an In Vitro Study in the Hollow-Fiber Infection Model

Pharmacokinetic/pharmacodynamic (PKPD) studies of anti-infectives are frequently performed in in vitro infection models where accurate quantification of antibiotic concentrations in bacterial growth media is crucial to establish PK/PD relationships. Here, a sensitive and rapid high-performance liquid chromatography (HPLC) method was developed to quantify tedizolid (TDZ) in the bacterial growth medium Mueller-Hinton broth (MHB). Matrix components were separated by direct protein precipitation with methanol (1:1). The chromatographic separation was carried out in a Dionex Ultimate 3000 HPLC system using an Accucore® C-18 RPMS HPLC column (2.6 µm, 100 × 2.1 mm) using isocratic elution with 25% acetonitrile and 75% of 0.1% formic acid. The lower limit of quantification was 0.03 mg/L when measured at 300 nm. Following relevant European Medicine Agency guidelines, the method was successfully validated for linearity, selectivity, recovery, inter- and intra-day precision, and accuracy and stability. When applied to in vitro PKPD studies, the method successfully quantified a range of TDZ concentration (Cmin, 0.09-Cmax, 0.65 mg/L) in MHB. The analyzed concentrations were in line with the planned PK profiles. The application of the developed method to quantify TDZ in MHB in in vitro PKPD studies is warranted.