Extension of Pharmacokinetic/Pharmacodynamic Time-Kill Studies To Include Lipopolysaccharide/Endotoxin Release from Escherichia coli Exposed to Cefuroxime

Evaluation the kill rate and mutant selection window of danofloxacin against Actinobacillus pleuropneumoniae in a peristaltic pump model

BACKGROUND

Actinobacillus pleuropneumoniae is a serious pathogen in pigs. The abundant application of antibiotics has resulted in the gradual emergence of drugresistant bacteria, which has seriously affected treatment of disease. To aid measures to prevent the emergence and spread of drug-resistant bacteria, herein, the kill rate and mutant selection window (MSW) of danofloxacin (DAN) against A. pleuropneumoniae were evaluated.

METHODS

For the kill rate study, the minimum inhibitory concentration (MIC) was tested using the micro dilution broth method and time-killing curves of DAN against A. pleuropneumoniae grown in tryptic soy broth (TSB) at a series drug concentrations (from 0 to 64 MIC) were constructed. The relationships between the kill rate and drug concentrations were analyzed using a Sigmoid Emax model during different time periods. For the MSW study, the MIC99 (the lowest concentration that inhibited the growth of the bacteria by ≥ 99%) and mutant prevention concentration (MPC) of DAN against A. pleuropneumoniae were measured using the agar plate method. Then, a peristaltic pump infection model was established to simulate the dynamic changes of DAN concentrations in pig lungs. The changes in number and sensitivity of A. pleuropneumoniae were measured. The relationships between pharmacokinetic/pharmacodynamic parameters and the antibacterial effect were analyzed using the Sigmoid Emax model.

RESULTS

In kill rate study, the MIC of DAN against A. pleuropneumoniae was 0.016 µg/mL. According to the kill rate, DAN exhibited concentration-dependent antibacterial activity against A. pleuropneumoniae. A bactericidal effect was observed when the DAN concentration reached 4-8 MIC. The kill rate increased constantly with the increase in DAN concentration, with a maximum value of 3.23 Log10 colony forming units (CFU)/mL/h during the 0-1 h period. When the drug concentration was in the middle part of the MSW, drugresistant bacteria might be induced. Therefore, the dosage should be avoided to produce a mean value of AUC24h/MIC99 (between 31.29 and 62.59 h. The values of AUC24h/MIC99 to achieve bacteriostatic, bactericidal, and eradication effects were 9.46, 25.14, and > 62.59 h, respectively.

CONCLUSION

These kill rate and MSW results will provide valuable guidance for the use of DAN to treat A. pleuropneumoniae infections.

Turning cationic antimicrobial peptide KR-12 into self-assembled nanobiotics with potent bacterial killing and LPS neutralizing activities

Gram-negative sepsis has become a substantial and escalating global healthcare challenge due to the growing antibiotic resistance crisis and the sluggish development of new antibiotics. LL-37, a unique Cathelicidin species found in humans, exhibits a wide range of bioactive properties, including direct bactericidal effects, inflammation regulation, and LPS neutralization. KR-12, the smallest yet potent peptide fragment of LL-37, has been modified to create more effective antimicrobials. In this study, we designed two myristoylated derivatives of KR-12, referred to as Myr-KR-12N and Myr-KR-12C. These derivatives displayed remarkable ability to spontaneously assemble into nanoparticles when mixed with deionized water. Myristoylated KR-12 derivatives exhibited broad-spectrum and intensified bactericidal activity by disrupting bacterial cell membranes. In particular, Myr-KR-12N showed superior capability to rescue mice from lethal E. coli-induced sepsis in comparison with the conventional antibiotic meropenem. We also confirmed that the myristoylated KR-12 nanobiotic possesses significant LPS binding capacity and effectively reduces inflammation in vitro. In an in vivo context, Myr-KR-12N outperformed polymyxin B in rescuing mice from LPS-induced sepsis. Crucially, toxicological assessments revealed that neither Myr-KR-12N nor Myr-KR-12C nanobiotics induced meaningful hemolysis or caused damage to the liver and kidneys. Collectively, our study has yielded an innovative nanobiotic with dual capabilities of bactericidal action and LPS-neutralization, offering substantial promise for advancing the clinical translation of antimicrobial peptides and the development of novel antibiotics. This addresses the critical need for effective solutions to combat Gram-negative sepsis, a pressing global medical challenge.

The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution

Pharmacokinetic-pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.

The ingredients for an antimicrobial mathematical modelling broth

Mathematical modelling has made significant contributions to the optimisation of the use of antimicrobial treatments. In this review we discuss the key processes that such mathematical modelling should attempt to capture. In particular, we highlight that the response of the host immune system requires quantification and illustrate this with a novel model structure.

Pharmacokinetic-pharmacodynamic models for time courses of antibiotic effects: VSI: Antimicrobial Pharmacometrics

Pharmacokinetic-pharmacodynamic (PKPD) models have emerged as valuable tools for the characterisation and translation of antibiotic effects, and consequently for drug development and therapy. In contrast to traditional PKPD concepts for antibiotics like MIC and PKPD indices, PKPD models enable to describe the continuous, often species- or population-dependent time course of antimicrobial effects, commonly considering mechanistic pathogen- and drug-related knowledge. This review presents a comprehensive overview of previously published PKPD models describing repeated measurements of antibiotic effects. We conducted a literature review to identify PKPD models based on (i) antibiotic compounds, (ii) Gram-positive or Gram-negative pathogens, and (iii) in vitro or in vivo longitudinal colony forming unit data. We identified 132 publications released between 1963 and 2021, including models based on exposure with single antibiotics (n=92) and drug combinations (n=40), as well as different experimental settings (e.g., static/traditional dynamic/hollow-fibre/animal time-kill models, n=90/27/32/11). An interactive, fully searchable table summarises the details of each model, i.e. variants and mechanistic elements of PKPD submodels capturing observed bacterial growth, regrowth, drug effects, and interactions. Furthermore, the review highlights main purposes of PKPD model development, including the translation of preclinical PKPD to clinical settings and the assessment of varied dosing regimens and patient characteristics for their impact on clinical antibiotic effects. In summary, this comprehensive overview of PKPD models shall assist in identifying PKPD modelling strategies to describe growth, killing, regrowth and interaction patterns for pathogen-antibiotic combinations over time and ultimately facilitate model-informed antibiotic translation, dosing and drug development.

Pharmacodynamic Parameters of Pharmacokinetic/Pharmacodynamic (PK/PD) Integration Models

Pharmacokinetic/pharmacodynamic (PK/PD) integration models are used to investigate the antimicrobial activity characteristics of drugs targeting pathogenic bacteria through comprehensive analysis of the interactions between PK and PD parameters. PK/PD models have been widely applied in the development of new drugs, optimization of the dosage regimen, and prevention and treatment of drug-resistant bacteria. In PK/PD analysis, minimal inhibitory concentration (MIC) is the most commonly applied PD parameter. However, accurately determining MIC is challenging and this can influence the therapeutic effect. Therefore, it is necessary to optimize PD indices to generate more rational results. Researchers have attempted to optimize PD parameters using mutant prevention concentration (MPC)-based PK/PD models, multiple PD parameter-based PK/PD models, kill rate-based PK/PD models, and others. In this review, we discuss progress on PD parameters for PK/PD models to provide a valuable reference for drug development, determining the dosage regimen, and preventing drug-resistant mutations.

A New Calcium(II)-Based Substitute for Enrofloxacin with Improved Medicinal Potential

Enrofloxacin (EFX) reacting with Ca(II) afforded a new complex, [Ca(EFX)₂(H₂O)₄] (EFX-Ca), which was structurally characterized both in solid and solution chemistry. E. coli and S. typhi were tested to be the most sensitive strains for EFX-Ca. The LD₅₀ value of EFX-Ca in mice was 7736 mg/kg, implying the coordination of EFX to Ca(II) effectively reduced its acute toxicity. EFX-Ca also decreased the plasma-binding rate and enhanced the drug distribution in rats along with longer elimination half-life. EFX-Ca also showed similar low in vivo acute toxicity and higher anti-inflammation induced by H₂O₂ or CuSO₄ in zebrafish, with reactive oxygen species (ROS)-related elimination. The therapeutic effects of EFX-Ca on two types (AA and 817) of E. coli-infected broilers were also better than those of EFX, with cure rates of 78% and 88%, respectively. EFX-Ca showed promise as a bio-safe metal-based veterinary drug with good efficacy and lower toxicity.

Application of Semi-Mechanistic Pharmacokinetic and Pharmacodynamic Model in Antimicrobial Resistance

Antimicrobial resistance is a major public health issue. The pharmacokinetic/pharmacodynamic (PK/PD) model is an essential tool to optimize dosage regimens and alleviate the emergence of resistance. The semi-mechanistic PK/PD model is a mathematical quantitative tool to capture the relationship between dose, exposure, and response, in terms of the mechanism. Understanding the different resistant mechanisms of bacteria to various antibacterials and presenting this as mathematical equations, the semi-mechanistic PK/PD model can capture and simulate the progress of bacterial growth and the variation in susceptibility. In this review, we outline the bacterial growth model and antibacterial effect model, including different resistant mechanisms, such as persisting resistance, adaptive resistance, and pre-existing resistance, of antibacterials against bacteria. The application of the semi-mechanistic PK/PD model, such as the determination of PK/PD breakpoints, combination therapy, and dosage optimization, are also summarized. Additionally, it is important to integrate the PD effect, such as the inoculum effect and host response, in order to develop a comprehensive mechanism model. In conclusion, with the semi-mechanistic PK/PD model, the dosage regimen can be reasonably determined, which can suppress bacterial growth and resistance development.

Effective Antimicrobial Solutions for Eradicating Multi-Resistant and β-Lactamase-Producing Nosocomial Gram-Negative Pathogens

Antimicrobial resistance (AMR) remains one of the greatest public health-perturbing crises of the 21st century, where species have evolved a myriad of defence strategies to resist conventional therapy. The production of extended-spectrum β-lactamase (ESBL), AmpC and carbapenemases in Gram-negative bacteria (GNB) is one such mechanism that currently poses a significant threat to the continuity of first-line and last-line β-lactam agents, where multi-drug-resistant GNB currently warrant a pandemic on their own merit. The World Health Organisation (WHO) has long recognised the need for an improved and coordinated global effort to contain these pathogens, where two factors in particular, international travel and exposure to antimicrobials, play an important role in the emergence and dissemination of antibiotic-resistant genes. Studies described herein assess the resistance patterns of isolated nosocomial pathogens, where levels of resistance were detected using recognised in vitro methods. Additionally, studies conducted extensively investigated alternative biocide (namely peracetic acid, triameen and benzalkonium chloride) and therapeutic options (specifically 1,10-phenanthroline-5,6-dione), where the levels of induced endotoxin from E. coli were also studied for the latter. Antibiotic susceptibility testing revealed there was a significant association between multi-drug resistance and ESBL production, where the WHO critical-priority pathogens, namely E. coli, K. pneumoniae, A. baumannii and P. aeruginosa, exhibited among the greatest levels of multi-drug resistance. Novel compound 1,10-phenanthroline-5,6-dione (phendione) shows promising antimicrobial activity, with MICs determined for all bacterial species, where levels of induced endotoxin varied depending on the concentration used. Tested biocide agents show potential to act as intermediate-level disinfectants in hospital settings, where all tested clinical isolates were susceptible to treatment.

Quantification of persister formation of Escherichia coli leveraging electronic cell counting and semi-mechanistic pharmacokinetic/pharmacodynamic modelling

BACKGROUND

Persister formation of Escherichia coli under fluoroquinolone exposure causes treatment failure and promotes emergence of resistant strains. Semi-mechanistic pharmacokinetic/pharmacodynamic modelling of data obtained from in vitro infection model experiments comprehensively characterizes exposure-effect relationships, providing mechanistic insights.

OBJECTIVES

To quantify persister formation of E. coli under levofloxacin exposure and to explain the observed growth-kill behaviour, leveraging electronic cell counting and pharmacokinetic/pharmacodynamic modelling.

METHODS

Three fluoroquinolone-resistant clinical E. coli isolates were exposed to levofloxacin in static and dynamic in vitro infection model experiments. Complementary to plate counting, bacterial concentrations over time were quantified by electronic cell counting and amalgamated in a semi-mechanistic pharmacokinetic/pharmacodynamic model (1281 bacterial and 394 levofloxacin observations).

RESULTS

Bacterial regrowth was observed under exposure to clinically relevant dosing regimens in the dynamic in vitro infection model. Electronic cell counting facilitated identification of three bacterial subpopulations: persisters, viable cells and dead cells. Two strain-specific manifestations of the levofloxacin effect were identified: a killing effect, characterized as a sigmoidal Emax model, and an additive increase in persister formation under levofloxacin exposure. Significantly different EC50 values quantitatively discerned levofloxacin potency for two isolates displaying the same MIC value: 8 mg/L [EC50 = 17.2 (95% CI = 12.6-23.8) mg/L and 8.46 (95% CI = 6.86-10.3) mg/L, respectively]. Persister formation was most pronounced for the isolate with the lowest MIC value (2 mg/L).

CONCLUSIONS

The developed pharmacokinetic/pharmacodynamic model adequately characterized growth-kill behaviour of three E. coli isolates and unveiled strain-specific levofloxacin potencies and persister formation. The mimicked dosing regimens did not eradicate the resistant isolates and enhanced persister formation to a strain-specific extent.

Novel Pharmacokinetic/Pharmacodynamic Parameters Quantify the Exposure-Effect Relationship of Levofloxacin against Fluoroquinolone-Resistant Escherichia coli

Minimal inhibitory concentration-based pharmacokinetic/pharmacodynamic (PK/PD) indices are commonly applied to antibiotic dosing optimisation, but their informative value is limited, as they do not account for bacterial growth dynamics over time. We aimed to comprehensively characterise the exposure–effect relationship of levofloxacin against Escherichia coli and quantify strain-specific characteristics applying novel PK/PD parameters. In vitro infection model experiments were leveraged to explore the exposure–effect relationship of three clinical Escherichia coli isolates, harbouring different genomic fluoroquinolone resistance mechanisms, under constant levofloxacin concentrations or human concentration–time profiles (≤76 h). As an exposure metric, the ‘cumulative area under the levofloxacin–concentration time curve’ was determined. The antibiotic effect was assessed as the ‘cumulative area between the growth control and the bacterial-killing and -regrowth curve’. PK/PD modelling was applied to characterise the exposure–effect relationship and derive novel PK/PD parameters. A sigmoidal E_max model with an inhibition term best characterised the exposure–effect relationship and allowed for discrimination between two isolates sharing the same MIC value. Strain- and exposure-pattern-dependent differences were captured by the PK/PD parameters and elucidated the contribution of phenotypic adaptation to bacterial regrowth. The novel exposure and effect metrics and derived PK/PD parameters allowed for comprehensive characterisation of the isolates and could be applied to overcome the limitations of the MIC in clinical antibiotic dosing decisions, drug research and preclinical development.

Decoding (patho-)physiology of the lung by advanced in vitro models for developing novel anti-infectives therapies

Advanced lung cell culture models provide physiologically-relevant and complex data for mathematical models to exploit host-pathogen responses during anti-infective drug testing.