Validation of a Model Predicting Anti-infective Lung Penetration in the Epithelial Lining Fluid of Humans

Pharmacokinetic/Pharmacodynamic Optimization of Hospital-Acquired and Ventilator-Associated Pneumonia: Challenges and Strategies

Hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP) are correlated with high mortality rates worldwide. Thus, the administration of antibiotic therapy with appropriate dosing regimen is critical. An efficient antibiotic is needed to maintain an adequate concentration at the infection site, for a sufficient period of time, to achieve the best therapeutic outcome. It can, however, be challenging for antibiotics to penetrate the pulmonary system due to the complexity of its structure. Crossing the blood alveolar barrier is a difficult process determined by multiple factors that are either drug related or infection related. Thus, the understanding of pharmacokinetics/pharmacodynamics (PK/PD) of antibiotics identifies the optimum dosing regimens to achieve drug penetration into the epithelial lining fluid at adequate therapeutic concentrations. Critically ill patients in the ICU can express augmented renal clearance (ARC), characterized by enhanced renal function, or may have renal dysfunction necessitating supportive care such as continuous renal replacement therapy (CRRT). Both ARC and CRRT can alter drug elimination, thus affecting drug concentrations. PK of critically ill patients is less clear due to the multiple variabilities associated with their condition. Therefore, conventional dosing regimens often lead to therapeutic failure. Another major hurdle faced in optimizing treatment for HAP/VAP is the reduction of the in vitro potency. Therapeutic drug monitoring (TDM), if available, may allow health care providers to personalize treatment to maximize efficacy of the drug exposures while minimizing toxicity. TDM can be of significant importance in populations whom PK are less defined and for resistant infections to achieve the best therapeutic outcome.

Physiologically Based Modelling Framework for Prediction of Pulmonary Pharmacokinetics of Antimicrobial Target Site Concentrations

BACKGROUND AND OBJECTIVES

Prediction of antimicrobial target-site pharmacokinetics is of relevance to optimize treatment with antimicrobial agents. A physiologically based pharmacokinetic (PBPK) model framework was developed for prediction of pulmonary pharmacokinetics, including key pulmonary infection sites (i.e. the alveolar macrophages and the epithelial lining fluid).

METHODS

The modelling framework incorporated three lung PBPK models: a general passive permeability-limited model, a drug-specific permeability-limited model and a quantitative structure-property relationship (QSPR)-informed perfusion-limited model. We applied the modelling framework to three fluoroquinolone antibiotics. Incorporation of experimental drug-specific permeability data was found essential for accurate prediction.

RESULTS

In the absence of drug-specific transport data, our QSPR-based model has generic applicability. Furthermore, we evaluated the impact of drug properties and pathophysiologically related changes on pulmonary pharmacokinetics. Pulmonary pharmacokinetics were highly affected by physiological changes, causing a shift in the main route of diffusion (i.e. paracellular or transcellular). Finally, we show that lysosomal trapping can cause an overestimation of cytosolic concentrations for basic compounds when measuring drug concentrations in cell homogenate.

CONCLUSION

The developed lung PBPK model framework constitutes a promising tool for characterization of pulmonary exposure of systemically administrated antimicrobials.

Intracellular Accumulation of Novel and Clinically Used TB Drugs Potentiates Intracellular Synergy

The therapeutic repertoire for tuberculosis (TB) remains limited despite the existence of many TB drugs that are highly active in in vitro models and possess clinical utility. Underlying the lack of efficacy in vivo is the inability of TB drugs to penetrate microenvironments inhabited by the causative agent, Mycobacterium tuberculosis, including host alveolar macrophages. Here, we determined the ability of the phenoxazine PhX1 previously shown to be active against M. tuberculosis in vitro to differentially penetrate murine compartments, including plasma, epithelial lining fluid, and isolated epithelial lining fluid cells. We also investigated the extent of permeation into uninfected and M. tuberculosis-infected human macrophage-like Tamm-Horsfall protein 1 (THP-1) cells directly and by comparing to results obtained in vitro in synergy assays. Our data indicate that PhX1 (4,750 ± 127.2 ng/ml) penetrates more effectively into THP-1 cells than do the clinically used anti-TB agents, rifampin (3,050 ± 62.9 ng/ml), moxifloxacin (3,374 ± 48.7 ng/ml), bedaquiline (4,410 ± 190.9 ng/ml), and linezolid (770 ± 14.1 ng/ml). Compound efficacy in infected cells correlated with intracellular accumulation, reinforcing the perceived importance of intracellular penetration as a key drug property. Moreover, we detected synergies deriving from redox-stimulatory combinations of PhX1 or clofazimine with the novel prenylated amino-artemisinin WHN296. Finally, we used compound synergies to elucidate the relationship between compound intracellular accumulation and efficacy, with PhX1/WHN296 synergy levels shown to predict drug efficacy. Collectively, our data support the utility of the applied assays in identifying in vitro active compounds with the potential for clinical development. IMPORTANCE This study addresses the development of novel therapeutic compounds for the eventual treatment of drug-resistant tuberculosis. Tuberculosis continues to progress, with cases of Mycobacterium tuberculosis (M. tuberculosis) resistance to first-line medications increasing. We assess new combinations of drugs with both oxidant and redox properties coupled with a third partner drug, with the focus here being on the potentiation of M. tuberculosis-active combinations of compounds in the intracellular macrophage environment. Thus, we determined the ability of the phenoxazine PhX1, previously shown to be active against M. tuberculosis in vitro, to differentially penetrate murine compartments, including plasma, epithelial lining fluid, and isolated epithelial lining fluid cells. In addition, the extent of permeation into human macrophage-like THP-1 cells and H37Rv-infected THP-1 cells was measured via mass spectrometry and compared to in vitro two-dimensional synergy and subsequent intracellular efficacy. Collectively, our data indicate that development of new drugs will be facilitated using the methods described herein.

Design principles of collateral sensitivity-based dosing strategies

Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance.

What Are the Current Approaches to Optimising Antimicrobial Dosing in the Intensive Care Unit?

Antimicrobial dosing in the intensive care unit (ICU) can be problematic due to various challenges including unique physiological changes observed in critically ill patients and the presence of pathogens with reduced susceptibility. These challenges result in reduced likelihood of standard antimicrobial dosing regimens achieving target exposures associated with optimal patient outcomes. Therefore, the aim of this review is to explore the various methods for optimisation of antimicrobial dosing in ICU patients. Dosing nomograms developed from pharmacokinetic/statistical models and therapeutic drug monitoring are commonly used. However, recent advances in mathematical and statistical modelling have resulted in the development of novel dosing software that utilise Bayesian forecasting and/or artificial intelligence. These programs utilise therapeutic drug monitoring results to further personalise antimicrobial therapy based on each patient’s clinical characteristics. Studies quantifying the clinical and cost benefits associated with dosing software are required before widespread use as a point-of-care system can be justified.