PK/PD models in antibacterial development

A freely accessible, adaptable hollow-fiber setup to reproduce first-order absorption: illustration with linezolid cerebrospinal fluid pharmacokinetic data

The main objective of this study was to validate an algorithm and experimental setup to simulate first-order absorption pharmacokinetic profiles without altering the standard in vitro hollow-fiber infection model (HFIM). For that, clinical cerebrospinal fluid (CSF) linezolid concentrations after 30 min infusions at dosing regimens 600 mg q12 h, 900 mg q12 h, and 900 mg q8 h were reproduced in the HFIM over 4 days. To approximate the apparent first-order absorption observed on CSF pharmacokinetic profiles, we split the dosing interval into a series of sub-intervals during which continuous infusions were delivered to the system. During each sub-interval, the same amount of linezolid was delivered, but the sub-intervals had different durations and flow rates, which were computed by a newly developed algorithm. In addition, we independently reproduced plasma concentrations to validate our system. Samples were collected from the central reservoir and the extracapillary space (ECS) of the cartridge of the HFIM and assayed by liquid chromatography-tandem mass spectrometry. Observed pharmacokinetic parameters and concentrations in the ECS were compared with the target clinical pharmacokinetic parameters and concentrations. Observed pharmacokinetic parameters were within 20% of target pharmacokinetic parameters for all experiments, thus validating the ability of our experimental setup to reproduce plasma and CSF linezolid pharmacokinetic profiles. The algorithm and setup are available in the open-source web application (https://varacli.shinyapps.io/hollow_fiber_app/) to easily design other HFIM experiments.IMPORTANCEWe developed and validated a novel hollow-fiber setup that enables in vitro simulation of mono-compartmental pharmacokinetics with an absorption phase. This novel experimental setup was easily implemented on top of the traditional one since it only requires the addition of a programmable infusion pump. Using this streamlined approach, we successfully replicated pharmacokinetics at the infection site, specifically cerebrospinal fluid concentrations of linezolid, consistent with those observed in intensive care unit patients. Thus, this study addresses the challenge of accurately reproducing target site concentrations, rather than relying solely on plasma levels, offering a valuable tool for optimizing dosing regimens in antibiotic therapy. Importantly, this setup also allows for the reproduction of plasma pharmacokinetics following oral (or any other extravascular) administration, broadening its applicability. The algorithm and setup developed in this study were incorporated into an open-source web application designed to facilitate the design of hollow-fiber experimental protocols (https://varacli.shinyapps.io/hollow_fiber_app/).

The tradeoffs between persistence and mutation rates at sub-inhibitory antibiotic concentrations in Staphylococcus aureus

The rational design of the antibiotic treatment of bacterial infections employs these drugs to reach concentrations that exceed the minimum needed to prevent the replication of the target bacteria. However, within a treated patient, spatial and physiological heterogeneity promotes antibiotic gradients such that the concentration of antibiotics at specific sites is below the minimum needed to inhibit bacterial growth. Here, we investigate the effects of sub-inhibitory antibiotic concentrations on three parameters central to bacterial infection and the success of antibiotic treatment, using in vitro experiments with Staphylococcus aureus and mathematical and computer-simulation models. Our results, using drugs of six different classes, demonstrate that exposure to sub-inhibitory antibiotic concentrations alters bacterial growth dynamics, increases the mutation rate to antibiotic resistance, and decreases the production of persister cells thereby reducing persistence levels. Understanding this trade-off between mutation rates and persistence levels resulting from sub-inhibitory antibiotic exposure is crucial for optimizing, and mitigating the failure of, antibiotic therapy.

IMPORTANCE

Much of the research on antibiotics and antibiotic treatment has focused on drug concentrations sufficient to prevent the growth of bacteria. These concentrations, however, are not always reached everywhere in the body. Here, we look at the effects of exposure to these low concentrations of antibiotics on the common clinically important pathogen Staphylococcus aureus. We confirm a previous finding that sub-inhibitory antibiotic exposure decreases the total growth and the growth rate of the bacteria. Moreover, we demonstrate that the level of persistence, an important mechanism for bacteria to survive antibiotics, is decreased due to sub-inhibitory exposure. However, we find that the rate of generation of resistant mutants is substantially increased. Taken together, these results reveal an important trade-off that emerges as a consequence of bacteria being exposed to sub-inhibitory concentrations of antibiotics.

A hollow fiber infection model to study intracellular and extracellular antibiotic activity against Staphylococcus aureus

Antibiotic activity against intracellular pathogens is commonly evaluated in static models that do not reproduce plasma concentration fluctuations. However, efficacy is influenced by exposure conditions, related to drug pharmacokinetic profile. This study developed and validated an intracellular pharmacodynamic model using the hollow fiber system, the gold standard for evaluating extracellular antibiotic activity. The activity of fluoroquinolones, i.e., bactericidal antibiotics with intracellular tropism, was studied against intracellular Staphylococcus aureus, involved in persistence/recurrence of infections. In this model, moxifloxacin was more effective than in static conditions (0.87 log10 killing gain), while ciprofloxacin kill rate was slower (18 vs. 12 h to achieve 1 log10 killing). These differences were linked to the Cmax/MIC ratio, which was 2.5-fold higher for moxifloxacin but 3.4-fold lower for ciprofloxacin in dynamic vs. static conditions. This model could be applied to other drugs, cell types, or pathogens, offering a tool for optimizing dosing schemes and considering intracellular reservoirs.

Dynamic In Vitro PK/PD Infection Models for the Development and Optimisation of Antimicrobial Regimens: A Narrative Review

The antimicrobial concentration-time profile in humans affects antimicrobial activity, and as such, it is critical for preclinical infection models to simulate human-like dynamic concentration-time profiles for maximal translatability. This review discusses the setup, principle, and application of various dynamic in vitro PK/PD infection models commonly used in the development and optimisation of antimicrobial treatment regimens. It covers the commonly used dynamic in vitro infection models, including the one-compartment model, hollow fibre infection model, biofilm model, bladder infection model, and aspergillus infection model. It summarises the mathematical methods for the simulation of the pharmacokinetic profile of single or multiple antimicrobials when using the serial or parallel configurations of in vitro systems. Dynamic in vitro models offer reliable pharmacokinetic/pharmacodynamic data to help define the initial dosing regimens of new antimicrobials that can be developed further in clinical trials. They can also help in the optimisation of dosing regimens for existing antimicrobials, especially in the presence of emerging antimicrobial resistance. In conclusion, dynamic in vitro infection models replicate the interactions that occur between microorganisms and dynamic antimicrobial exposures in the human body to generate data highly predictive of the clinical efficacy. They are particularly useful for the development new treatment strategies against antimicrobial-resistant pathogens.

Model-based translation of results from in vitro to in vivo experiments for afabicin activity against Staphylococcus aureus

BACKGROUND

Translation of experimental data on antibiotic activity typically relies on pharmacokinetic/pharmacodynamic (PK/PD) indices. Model-based approaches, considering the full antibiotic killing time course, could be an alternative.

OBJECTIVES

To develop a mechanism-based modelling framework to assess the in vitro and in vivo activity of the FabI inhibitor antibiotic afabicin, and explore the ability of a model built on in vitro data to predict in vivo outcome.

METHODS

A PK/PD model was built to describe bacterial counts from 162 static in vitro time-kill curves evaluating the effect of afabicin desphosphono, the active moiety of the prodrug afabicin, against 21 Staphylococcus aureus strains. Combined with a mouse PK model, outcomes of afabicin doses of 0.011-190 mg/kg q6h against nine S. aureus strains in a murine thigh infection model were predicted, and thereafter refined by estimating PD parameters.

RESULTS

A sigmoid Emax model, with EC50 scaled by the MIC described the afabicin desphosphono killing in vitro. This model predicted, without parameter re-estimation, the in vivo bacterial counts at 24 h within a ±1 log margin for most dosing groups. When parameters were allowed to be estimated, EC50 was 38%-45% lower in vivo, compared with in vitro, within the studied MIC range.

CONCLUSIONS

The developed PK/PD model described the time course of afabicin activity across experimental conditions and bacterial strains. This model showed translational capacity as parameters estimated on in vitro time-kill data could well predict the in vivo outcome for a wide variety of doses in a mouse thigh infection model.

Concentration-resistance relationship and PK/PD evaluation of danofloxacin against emergence of resistant Pasteurella multocida in an in vitro dynamic model

AIMS

This study aimed to assess the pharmacokinetic/pharmacodynamic (PK/PD) targets of danofloxacin to minimize the risk of selecting resistant Pasteurella multocida mutants and to identify the mechanisms underlying their resistance in an in vitro dynamic model, attaining the optimum dosing regimen of danofloxacin to improve its clinical efficacy based on the mutant selection window (MSW) hypothesis.

METHODS AND RESULTS

Danofloxacin at seven dosing regimens and 5 days of treatment were simulated to quantify the bactericidal kinetics and enrichment of resistant mutants upon continuous antibiotic exposure. The magnitudes of PK/PD targets associated with different efficacies were determined in the model. The 24 h area under the concentration-time curve (AUC) to minimum inhibitory concentration (MIC) ratios (AUC24h/MIC) of danofloxacin associated with bacteriostatic, bactericidal and eradication effects against P. multocida were 34, 52, and 64 h. This translates to average danofloxacin concentrations (Cav) over 24 h being 1.42, 2.17, and 2.67 times the MIC, respectively. An AUC/MIC-dependent antibacterial efficacy and AUC/mutant prevention concentration (MPC)-dependent enrichment of P. multocida mutants in which maximum losses in danofloxacin susceptibility occurred at a simulated AUC24h/MIC ratio of 72 h (i.e. Cav of three times the MIC). The overexpression of efflux pumps (acrAB-tolC) and their regulatory genes (marA, soxS, and ramA) was associated with reduced susceptibility in danofloxacin-exposed P. multocida. The AUC24h/MPC ratio of 19 h (i.e. Cav of 0.8 times the MPC) was determined to be the minimum mutant prevention target value for the selection of resistant P. multocida mutants.

CONCLUSIONS

The emergence of P. multocida resistance to danofloxacin exhibited a concentration-dependent pattern and was consistent with the MSW hypothesis. The current clinical dosing regimen of danofloxacin (2.5 mg kg-1) may have a risk of treatment failure due to inducible fluoroquinolone resistance.

Evaluation of critical parameters in the hollow-fibre system for tuberculosis: A case study of moxifloxacin

Aims

The hollow‐fibre system for tuberculosis (HFS‐TB) is a preclinical model qualified by the European Medicines Agency to underpin the anti‐TB drug development process. It can mimic in vivo pharmacokinetic (PK)–pharmacodynamic (PD) attributes of selected antimicrobials, which could feed into in silico models to inform the design of clinical trials. However, historical data and published protocols are insufficient and omit key information to allow experiments to be reproducible. Therefore, in this work, we aim to optimize and standardize various HFS‐TB operational procedures.

Methods

First, we characterized bacterial growth dynamics with different types of hollow‐fibre cartridges, Mycobacterium tuberculosis strains and media. Second, we mimicked a moxifloxacin PK profile within hollow‐fibre cartridges, in order to check drug–fibres compatibility. Lastly, we mimicked the moxifloxacin total plasma PK profile in human after once daily oral dose of 400 mg to assess PK–PD after different sampling methods, strains, cartridge size and bacterial adaptation periods before drug infusion into the system.

Results

We found that final bacterial load inside the HFS‐TB was contingent on the studied variables. Besides, we demonstrated that drug–fibres compatibility tests are critical preliminary HFS‐TB assays, which need to be properly reported. Lastly, we uncovered that the sampling method and bacterial adaptation period before drug infusion significantly impact actual experimental conclusions.

Conclusion

Our data contribute to the necessary standardization of HFS‐TB experiments, draw attention to multiple aspects of this preclinical model that should be considered when reporting novel results and warn about critical parameters in the HFS‐TB currently overlooked.

Synergistic effects of inhaled aztreonam plus tobramycin on hypermutable cystic fibrosis Pseudomonas aeruginosa isolates in a dynamic biofilm model evaluated by mechanism-based modelling and whole genome sequencing

OBJECTIVE

Hypermutable Pseudomonas aeruginosa strains are highly prevalent in chronic lung infections of patients with cystic fibrosis (CF). Acute exacerbations of these infections have limited treatment options. This study aimed to investigate inhaled aztreonam and tobramycin against clinical hypermutable P. aeruginosa strains using the CDC dynamic in vitro biofilm reactor (CBR), mechanism-based mathematical modelling (MBM) and genomic studies.

METHODS

Two CF multidrug-resistant strains were investigated in a 168 h CBR (n = 2 biological replicates). Regimens were inhaled aztreonam (75 mg 8-hourly) and tobramycin (300 mg 12-hourly) in monotherapies and combination. The simulated pharmacokinetic profiles of aztreonam and tobramycin (t1/2 = 3 h) were based on published lung fluid concentrations in patients with CF. Total viable and resistant counts were determined for planktonic and biofilm bacteria. MBM of total and resistant bacterial counts and whole genome sequencing were completed.

RESULTS

Both isolates showed reproducible bacterial regrowth and resistance amplification for the monotherapies by 168 h. The combination performed synergistically, with minimal resistant subpopulations compared to the respective monotherapies at 168 h. Mechanistic synergy appropriately described the antibacterial effects of the combination regimen in the MBM. Genomic analysis of colonies recovered from monotherapy regimens indicated noncanonical resistance mechanisms were likely responsible for treatment failure.

CONCLUSION

The combination of aztreonam and tobramycin was required to suppress the regrowth and resistance of planktonic and biofilm bacteria in all biological replicates of both hypermutable multidrug-resistant P. aeruginosa CF isolates. The developed MBM could be utilised for future investigations of this promising inhaled combination.

The Tradeoffs Between Persistence and Mutation Rates at Sub-Inhibitory Antibiotic Concentrations in Staphylococcus aureus

The rational design of the antibiotic treatment of bacterial infections employs these drugs to reach concentrations that exceed the minimum needed to prevent the replication of the target bacteria. However, within a treated patient, spatial and physiological heterogeneity promotes antibiotic gradients such that the concentration of antibiotics at specific sites is below the minimum needed to inhibit bacterial growth. Here, we investigate the effects of sub-inhibitory antibiotic concentrations on three parameters central to bacterial infection and the success of antibiotic treatment, using in vitro experiments with Staphylococcus aureus and mathematical-computer simulation models. Our results, using drugs of six different classes, demonstrate that exposure to sub-inhibitory antibiotic concentrations not only alters the dynamics of bacterial growth but also increases the mutation rate to antibiotic resistance and decreases the rate of production of persister cells thereby reducing the persistence level. Understanding this trade-off between mutation rates and persistence levels resulting from sub-inhibitory antibiotic exposure is crucial for optimizing, and mitigating the failure of, antibiotic therapy.

Unraveling resistance mechanisms in combination therapy: A comprehensive review of recent advances and future directions

Antimicrobial resistance is a global health threat. Misuse and overuse of antimicrobials are the main drivers in developing drug-resistant bacteria. The emergence of the rapid global spread of multi-resistant bacteria requires urgent multisectoral action to generate novel treatment alternatives. Combination therapy offers the potential to exploit synergistic effects for enhanced antibacterial efficacy of drugs. Understanding the complex dynamics and kinetics of drug interactions in combination therapy is crucial. Therefore, this review outlines the current advances in antibiotic resistance's evolutionary and genetic dynamics in combination therapies-exposed bacteria. Moreover, we also discussed four pivotal future research areas to comprehend better the development of antibiotic resistance in bacteria treated with combination strategies.

Effective Antimicrobial Prophylaxis in Surgery: The Relevance and Role of Pharmacokinetics-Pharmacodynamics

Appropriate surgical antimicrobial prophylaxis (SAP) is an important measure in preventing surgical site infections (SSIs). Although antimicrobial pharmacokinetics-pharmacodynamics (PKPD) is integral to optimizing antibiotic dosing for the treatment of infections, there is less research on preventing infections postsurgery. Whereas clinical studies of SAP dose, preincision timing, and redosing are informative, it is difficult to isolate their effect on SSI outcomes. Antimicrobial PKPD aims to explain the complex relationship between antibiotic exposure during surgery and the subsequent development of SSI. It accounts for the many factors that influence the PKs and antibiotic concentrations in patients and considers the susceptibilities of bacteria most likely to contaminate the surgical site. This narrative review examines the relevance and role of PKPD in providing effective SAP. The dose-response relationship i.e., association between lower dose and SSI in cefazolin prophylaxis is discussed. A comprehensive review of the evidence for an antibiotic concentration-response (SSI) relationship in SAP is also presented. Finally, PKPD considerations for improving SAP are explored with a focus on cefazolin prophylaxis in adults and outstanding questions regarding its dose, preincision timing, and redosing during surgery.

A Quantitative Systems Pharmacology Model Describing the Cellular Kinetic-Pharmacodynamic Relationship for a Live Biotherapeutic Product to Support Microbiome Drug Development

Live biotherapeutic products (LBPs) are human microbiome therapies showing promise in the clinic for a range of diseases and conditions. Describing the kinetics and behavior of LBPs poses a unique modeling challenge because, unlike traditional therapies, LBPs can expand, contract, and colonize the host digestive tract. Here, we present a novel cellular kinetic-pharmacodynamic quantitative systems pharmacology model of an LBP. The model describes bacterial growth and competition, vancomycin effects, binding and unbinding to the epithelial surface, and production and clearance of butyrate as a therapeutic metabolite. The model is calibrated and validated to published data from healthy volunteers. Using the model, we simulate the impact of treatment dose, frequency, and duration as well as vancomycin pretreatment on butyrate production. This model enables model-informed drug development and can be used for future microbiome therapies to inform decision making around antibiotic pretreatment, dose selection, loading dose, and dosing duration.

What's the Matter with MICs: Bacterial Nutrition, Limiting Resources, and Antibiotic Pharmacodynamics

The MIC of an antibiotic required to prevent replication is used both as a measure of the susceptibility/resistance of bacteria to that drug and as the single pharmacodynamic parameter for the rational design of antibiotic treatment regimes. MICs are experimentally estimated in vitro under conditions optimal for the action of the antibiotic. However, bacteria rarely grow in these optimal conditions. Using a mathematical model of the pharmacodynamics of antibiotics, we make predictions about the nutrient dependency of bacterial growth in the presence of antibiotics. We test these predictions with experiments in broth and a glucose-limited minimal media with Escherichia coli and eight different antibiotics. Our experiments question the sufficiency of using MICs and simple pharmacodynamic functions as measures of the pharmacodynamics of antibiotics under the nutritional conditions of infected tissues. To an extent that varies among drugs: (i) the estimated MICs obtained in rich media are greater than those estimated in minimal media; (ii) exposure to these drugs increases the time before logarithmic growth starts, their lag; and (iii) the stationary-phase density of E. coli populations declines with greater sub-MIC antibiotic concentrations. We postulate a mechanism to account for the relationship between sub-MICs of antibiotics and these growth parameters. This study is limited to a single bacterial strain and two types of culture media with different nutritive content. These limitations aside, the results of our study clearly question the use of MIC as the unique pharmacodynamic parameter to develop therapeutically oriented protocols. IMPORTANCE For studies of antibiotics and how they work, the most-often used measurement of drug efficacy is the MIC. The MIC is the concentration of an antibiotic needed to inhibit bacterial growth. This parameter is critical to the design and implementation of antibiotic therapy. We provide evidence that the use of MIC as the sole measurement for antibiotic efficacy ignores important aspects of bacterial growth dynamics. Before now, there has not been a nexus between bacteria, the conditions in which they grow, and the MIC. Most importantly, few studies have considered sub-MICs of antibiotics, despite their clinical importance. Here, we explore these concentrations in-depth, and we demonstrate MIC to be an incomplete measure of how an infection will interact with a specific antibiotic. Understanding the critiques of MIC is the first of many steps needed to improve infectious disease treatment.

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.

Pharmacokinetics and Pharmacodynamics of a Novel Vancomycin Derivative LYSC98 in a Murine Thigh Infection Model Against Staphylococcus aureus

Introduction

LYSC98 is a novel vancomycin derivative used for gram-positive bacterial infections. Here we compared the antibacterial activity of LYSC98 with vancomycin and linezolid in vitro and in vivo. Besides, we also reported the pharmacokinetic/pharmacodynamic (PK/PD) index and efficacy-target values of LYSC98.

Methods

The MIC values of LYSC98 were identified through broth microdilution method. A mice sepsis model was established to investigate the protective effect of LYSC98 in vivo. Single-dose pharmacokinetics of LYSC98 was studied in thigh-infected mice and liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was used to determine LYSC98 concentration in plasma. Dose fractionation studies were performed to evaluate different PK/PD indices. Two methicillin-resistant Staphylococcus aureus (MRSA) clinical strains were used in the dose ranging studies to determine the efficacy-target values.

Results

LYSC98 showed a universal antibacterial effect in Staphylococcus aureus with a MIC range of 2-4 µg/mL. In vivo, LYSC98 demonstrated distinctive mortality protection in mice sepsis model with an ED₅₀ value of 0.41-1.86 mg/kg. The pharmacokinetics results displayed maximum plasma concentration (C_max) 11,466.67-48,866.67 ng/mL, area under the concentration-time curve from 0 to 24 h (AUC_0-24) 14,788.42-91,885.93 ng/mL·h, and elimination half-life (T_1/2) 1.70-2.64 h, respectively. C_max/MIC (R ² 0.8941) was proved to be the most suitable PK/PD index for LYSC98 to predict its antibacterial efficacy. The magnitude of LYSC98 C_max/MIC associated with net stasis, 1, 2, 3 and 4 - log ₁₀ kill were 5.78, 8.17, 11.14, 15.85 and 30.58, respectively.

Conclusion

Our study demonstrates that LYSC98 is more effective than vancomycin either in killing vancomycin-resistant Staphylococcus aureus (VRSA) in vitro or treating S. aureus infections in vivo, making it a novel and promising antibiotic. The PK/PD analysis will also contribute to the LYSC98 Phase I dose design.

Shedding Light on Amoxicillin, Amoxicillin-clavulanate, and Cephalexin Dosing in Children from a Pharmacist's Perspective

Selection of an antibiotic and dosing regimen requires consideration of multiple factors including microbiological data, site of infection, pharmacokinetics, and how it relates to the pharmacodynamic target. Given the multiple dosage regimens of amoxicillin with/without clavulanate and cephalexin, we review the principles of dose selection from a pharmacist's perspective.

Defining Exposure Predictors of Meropenem That Are Associated with Improved Survival for Severe Bacterial Infection: A Preclinical PK/PD Study in Sepsis Rat Model

Background: The pharmacokinetic/pharmacodynamic (PK/PD) index of carbapenems that best correlates with in vivo antimicrobial activity is percent time of dosing interval in which free drug concentration remains above MIC (%fT > MIC), while the magnitudes of the PK/PD index of carbapenems remains undefined in critically ill sepsis patients. Methods: A sepsis rat model was first developed by comparing the survival outcomes after intraperitoneal injection of different inoculum size (1−10 × 107 CFU) of Pseudomonas aeruginosa ATCC9027 (MIC = 0.125 mg/L) in neutropenic rats. The PK characteristics of the model drug meropenem in the developed sepsis rat model was then evaluated, and PK modeling and simulation was applied to design meropenem dosing regimens attaining various PD targets (40%fT > MIC, 100%fT > MIC, and 100%fT > 4 × MIC). The microbiological response and survival outcomes for different meropenem treatment regimens were investigated in the rat sepsis model (n = 12 for each group). Results: The optimal inoculum for the rat sepsis model was 1 × 107 CFU of Pseudomonas aeruginosa ATCC9027. A one-compartment model with first-order absorption best described the PK of meropenem in sepsis rats. Pronounced survival prolongation and lower hazard risk were observed in the treatment groups of 50 or 75 mg/kg/q2.4h (100%fT > MIC) and 75 mg/kg/q2h (100%fT > 4 × MIC) compared to the 75 mg/kg/q6h (40%fT > MIC) group, while meropenem groups with PD targets of 100%fT > MIC and 100%fT > 4 × MIC showed comparable survival curves. Microbiological response for different PD targets is inconclusive due to irregular bacterial counts in blood samples. Conclusions: The PD target of 40%fT > MIC is suboptimal for sepsis rats, and the aggressive 100%fT > 4 × MIC target does not provide a survival benefit against the target of 100%fT > MIC.

Pharmacokinetic/Pharmacodynamic Modeling and Application in Antibacterial and Antifungal Pharmacotherapy: A Narrative Review

Pharmacokinetics and pharmacodynamics are areas in pharmacology related to different themes in the pharmaceutical sciences, including therapeutic drug monitoring and different stages of drug development. Although the knowledge of these disciplines is essential, they have historically been treated separately. While pharmacokinetics was limited to describing the time course of plasma concentrations after administering a drug-dose, pharmacodynamics describes the intensity of the response to these concentrations. In the last decades, the concept of pharmacokinetic/pharmacodynamic modeling (PK/PD) emerged, which seeks to establish mathematical models to describe the complete time course of the dose-response relationship. The integration of these two fields has had applications in optimizing dose regimens in treating antibacterial and antifungals. The anti-infective PK/PD models predict the relationship between different dosing regimens and their pharmacological activity. The reviewed studies show that PK/PD modeling is an essential and efficient tool for a better understanding of the pharmacological activity of antibacterial and antifungal agents.

Parallel study of transient dosing of antibiotics in a microfluidic device

Microfluidic tools are well suited for studying bacteria as they enable the analysis of small colonies or single cells. However, current techniques for studying bacterial response to antibiotics are largely limited to static dosing. Here, we describe a microfluidic device and a method for entrapping and cultivating bacteria in hydrogel plugs. Ring-shaped isolation valves are used to define the shape of the plugs and also to control exposure of the plugs to the surrounding medium. We demonstrate bacterial cultivation, determination of the minimum inhibitory concentration of an antibiotic, and transient dosing of an antibiotic at sub-1-h doses. The transient dosing experiments reveal that at dose durations on the order of minutes, ampicillin's bactericidal effect has both a time and concentration dependency.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

RpoN-Based stapled peptides with improved DNA binding suppress Pseudomonas aeruginosa virulence

Stapled peptides have the ability to mimic α-helices involved in protein binding and have proved to be effective pharmacological agents for disrupting protein-protein interactions. DNA-binding proteins such as transcription factors bind their cognate DNA sequences via an α-helix interacting with the major groove of DNA. We previously developed a stapled peptide based on the bacterial alternative sigma factor RpoN capable of binding the RpoN DNA promoter sequence and inhibiting RpoN-mediated expression in Escherichia coli. We have elucidated a structure-activity relationship for DNA binding by this stapled peptide, improving DNA binding affinity constants in the high nM range. Lead peptides were shown to have low toxicity as determined by their low hemolytic activity at 100 μM and were shown to have anti-virulence activity in a Galleria mellonella model of Pseudomonas aeruginosa infection. These findings support further preclinical development of stapled peptides as antivirulence agents targeting P. aeruginosa.

Machine-learning-guided early drug discovery of small molecules

Machine learning (ML) approaches have been widely adopted within the early stages of the drug discovery process, particularly within the context of small-molecule drug candidates. Despite this, the use of ML is still limited in the pharmacokinetic/pharmacodynamic (PK/PD) application space. Here, we describe recent progress and the role of ML used in preclinical drug discovery. We summarize the advances and current strategies used to predict ADME properties of small molecules based on their structures, and predict structures based on the desired properties for molecular screening and optimization. Finally, we discuss the use of ML to predict PK to rank the ability of drug candidates to achieve appropriate exposures and hence provide important insights into safety and efficacy. Teaser: In this short review we highlight key advances in the application of machine learning to early drug discovery for small molecules in the preclinical setting.

Translating pharmacology models effectively to predict therapeutic benefit

Many in vitro and in vivo models are used in pharmacological research to evaluate the role of targeted proteins in a disease. Understanding the translational relevance and limitation of these models for analyzing the disposition, pharmacokinetic/pharmacodynamic (PK/PD) profile, mechanism, and efficacy of a drug, is essential when selecting the most appropriate model of the disease of interest and predicting clinically efficacious doses of the investigational drug. Here, we review selected animal models used in ophthalmology, infectious diseases, oncology, autoimmune diseases, and neuroscience. Each area has specific challenges around translatability and determination of an efficacious dose: new patient-specific dosing methods could help overcome these limitations.

Dose Selection for Phase III Clinical Evaluation of Gepotidacin (GSK2140944) in the Treatment of Uncomplicated Urinary Tract Infections

Antibiotics are the current standard-of-care treatment for uncomplicated urinary tract infections (uUTIs). However, increasing rates of bacterial antibiotic resistance necessitate novel therapeutic options. Gepotidacin is a first-in-class triazaacenaphthylene antibiotic that selectively inhibits bacterial DNA replication by interaction with the bacterial subunits of DNA gyrase (GyrA) and topoisomerase IV (ParC). Gepotidacin is currently in clinical development for the treatment of uUTIs and other infections. In this article, we review data for gepotidacin from nonclinical studies, including in vitro activity, in vivo animal efficacy, and pharmacokinetic (PK) and pharmacokinetic/pharmacodynamic (PK/PD) models that informed dose selection for phase III clinical evaluation of gepotidacin. Based on this translational package of data, a gepotidacin 1,500-mg oral dose twice daily for 5 days was selected for two ongoing, randomized, multicenter, parallel-group, double-blind, double-dummy, active-comparator phase III clinical studies evaluating the safety and efficacy of gepotidacin in adolescent and adult female participants with uUTIs (ClinicalTrials.gov identifiers NCT04020341 and NCT04187144).

Antimicrobial resistance: Prevalence, economic burden, mechanisms of resistance and strategies to overcome

Antibiotic resistance is a major health concern globally and has been estimated to cause 10 million deaths worldwide by year 2050 if the current trend of inappropriate and excessive use of antibiotics continues. Although, the discovery of antibiotics has saved countless of lives for the past 80 years, increasing levels of bacterial resistance to antibiotics would jeopardize the progress in clinical and agricultural sectors and may cause life-threatening situations even for previously treatable bacterial infections. Antibiotic resistance would increase the levels of poverty of low-middle income countries mostly due to extended hospital stays, higher cost of treatment and untimely deaths that directly affect the total productivity rate. Recent incidences of antibiotic resistance have been gradually increasing globally and this may potentiate horizontal transmission of the resistant gene and have been linked with cross-resistance to other antibiotic families as well. This review summarizes the global burden of antibiotic resistance from the economic viewpoint, highlights the recent incidences of antibiotic resistance mainly related to Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, Salmonella spp. and Staphylococcus aureus, describes the common mechanistic actions of antibiotic resistance and potential strategies to overcome antibiotic resistance.

Improving the Drug Development Pipeline for Mycobacteria: Modelling Antibiotic Exposure in the Hollow Fibre Infection Model

Mycobacterial infections are difficult to treat, requiring a combination of drugs and lengthy treatment times, thereby presenting a substantial burden to both the patient and health services worldwide. The limited treatment options available are under threat due to the emergence of antibiotic resistance in the pathogen, hence necessitating the development of new treatment regimens. Drug development processes are lengthy, resource intensive, and high-risk, which have contributed to market failure as demonstrated by pharmaceutical companies limiting their antimicrobial drug discovery programmes. Pre-clinical protocols evaluating treatment regimens that can mimic in vivo PK/PD attributes can underpin the drug development process. The hollow fibre infection model (HFIM) allows for the pathogen to be exposed to a single or a combination of agents at concentrations achieved in vivo-in plasma or at infection sites. Samples taken from the HFIM, depending on the analyses performed, provide information on the rate of bacterial killing and the emergence of resistance. Thereby, the HFIM is an effective means to investigate the efficacy of a drug combination. Although applicable to a wide variety of infections, the complexity of anti-mycobacterial drug discovery makes the information available from the HFIM invaluable as explored in this review.

Predicting Antimicrobial Activity at the Target Site: Pharmacokinetic/Pharmacodynamic Indices versus Time-Kill Approaches

Antibiotic dosing strategies are generally based on systemic drug concentrations. However, drug concentrations at the infection site drive antimicrobial effect, and efficacy predictions and dosing strategies should be based on these concentrations. We set out to review different translational pharmacokinetic-pharmacodynamic (PK/PD) approaches from a target site perspective. The most common approach involves calculating the probability of attaining animal-derived PK/PD index targets, which link PK parameters to antimicrobial susceptibility measures. This approach is time efficient but ignores some aspects of the shape of the PK profile and inter-species differences in drug clearance and distribution, and provides no information on the PD time-course. Time–kill curves, in contrast, depict bacterial response over time. In vitro dynamic time–kill setups allow for the evaluation of bacterial response to clinical PK profiles, but are not representative of the infection site environment. The translational value of in vivo time–kill experiments, conversely, is limited from a PK perspective. Computational PK/PD models, especially when developed using both in vitro and in vivo data and coupled to target site PK models, can bridge translational gaps in both PK and PD. Ultimately, clinical PK and experimental and computational tools should be combined to tailor antibiotic treatment strategies to the site of infection.

Limitations of Antibiotic MIC-Based PK-PD Metrics: Looking Back to Move Forward

Within a few years after the first successful clinical use of penicillin, investigations were conducted in animal infection models to explore a range of factors that were considered likely to influence the antibacterial response to the drug. Those studies identified that the response was influenced by not only the total daily dose but also the interval between individual doses across the day, and whether penicillin was administered in an intermittent or continuous manner. Later, as more antibiotics were discovered and developed, antimicrobial pharmacologists began to measure antibiotic concentrations in biological fluids. This enabled the linking of antibacterial response at a single time point in an animal or in vitro infection model with one of three summary pharmacokinetic (PK) measures of in vivo exposure to the antibiotic. The summary PK exposure measures were normalised to the minimum inhibitory concentration (MIC), an in vitro measure of the pharmacodynamic (PD) potency of the drug. The three PK-PD indices (ratio of maximum concentration to MIC, ratio of area under the concentration-time curve to MIC, time concentration is above MIC) have been used extensively since the 1980s. While these MIC-based summary PK-PD metrics have undoubtedly facilitated the development of new antibiotics and the clinical application of both new and old antibiotics, it is increasingly recognised that they have a number of substantial limitations. In this article we use a historical perspective to review the origins of the three traditional PK-PD indices before exploring in detail their limitations and the implications arising from those limitations. Finally, in the interests of improving antibiotic development and dosing in patients, we consider a model-based approach of linking the full time-course of antibiotic concentrations with that of the antibacterial response. Such an approach enables incorporation of other factors that can influence treatment outcome in patients and has the potential to drive model-informed precision dosing of antibiotics into the future.

Preclinical Pharmacokinetic/Pharmacodynamic Studies and Clinical Trials in the Drug Development Process of EMA-Approved Antibacterial Agents: A Review

Development of new antibacterial agents is necessary as drug-resistant bacteria are a threat to global health. In Europe, the European Medicines Agency has been guiding this development process for more than two decades. We investigated preclinical and clinical pre-approval studies to illuminate the current authorization process with emphasis on pharmacokinetic/pharmacodynamic approaches and clinical phases. All centrally authorized systemic antibacterial and antimycobacterial drugs within the European Union were included without any time restriction. Additionally, US Food and Drug Administration-approved antibiotics of the previous 3 years, which were not yet approved by the European Medicines Agency, were included. We focused on preclinical pharmacokinetic/pharmacodynamic studies and phase II and phase III clinical trials. Furthermore, we looked at the recommended dosing regimens and approved indications. In this review, we designed tree diagrams as a new means of illustrating the development process of antibiotics to relate pharmacokinetic/pharmacodynamic phase II and III studies to approved indications. We included 23 (European Medicines Agency, 18; US Food and Drug Administration, 5) antimicrobial agents. Tetracyclines, carbapenems, and cephalosporins were the leading classes. The recommended dosing intervals were significantly shorter in time- vs exposure-dependent drugs (median 8 vs 12, p = 0.006). The majority of approved indications (i.e., acute bacterial skin and soft-tissue infection, community-acquired pneumonia, complicated intra-abdominal infection, complicated urinary tract infection, and complicated skin and soft-tissue infection) used non-inferiority trials. Phase II and III clinical trials investigating community-acquired pneumonia involved the fewest patients. Some promising drugs were marketed in recent years; the individual steps to their authorizations are illuminated. We confirmed the relevance of preclinical pharmacokinetic/pharmacodynamic studies in dosing optimization and decision making in antimicrobial drug development. Non-inferiority clinical trials predominated.

Application of the hollow fibre infection model (HFIM) in antimicrobial development: a systematic review and recommendations of reporting

OBJECTIVES

This systematic review focuses on the use of the in vitro hollow fibre infection model (HFIM) for microbial culture. We summarize the direction of the field to date and propose best-practice principles for reporting of the applications.

METHODS

Searches in six databases (MEDLINE®, EMBASE®, PubMed®, BIOSIS®, SCOPUS® and Cochrane®) up to January 2020 identified 129 studies meeting our inclusion criteria. Two reviewers independently assessed and extracted data from each publication. The quality of reporting of microbiological and technical parameters was analysed.

RESULTS

Forty-seven out of 129 (36.4%) studies did not report the minimum pharmacokinetic parameters required in order to replicate the pharmacokinetic profile of HFIM experiments. Fifty-three out of 129 (41.1%) publications did not report the medium used in the HFIM. The overwhelming majority of publications did not perform any technical repeats [107/129 (82.9%)] or biological repeats [97/129 (75.2%)].

CONCLUSIONS

This review demonstrates that most publications provide insufficient data to allow for results to be evaluated, thus impairing the reproducibility of HFIM experiments. Therefore, there is a clear need for the development of laboratory standardization and improved reporting of HFIM experiments.

Determination of Susceptibility Breakpoint for Cefquinome against Streptococcus suis in Pigs

Streptococcus suis (S. suis), a zoonotic pathogen, causes severe diseases in both pigs and human beings. Cefquinome can display excellent antibacterial activity against gram-negative and gram-positive bacteria. The aim of this study was to derive an optimal dosage of cefquinome against S. suis with a pharmacokinetic/pharmacodynamic (PK/PD) integration model in the target infection site and to investigate the cutoffs monitoring the changes of resistance. The minimum inhibitory concentration (MIC) distribution of cefquinome against 342 S. suis strains was determined. MIC₅₀ and MIC₉₀ were 0.06 and 0.25 μg/mL, respectively. The wild-type cutoff was calculated as 1 μg/mL. A two-compartmental model was applied to calculate the main pharmacokinetic parameters after 2 mg/kg cefquinome administered intramuscularly. An optimized dosage regimen of 3.08 mg/kg for 2-log₁₀ CFU reduction was proposed by ex vivo PK/PD model of infected swine. The pharmacokinetic-pharmacodynamic cutoff was calculated as 0.06 μg/mL based on PK/PD targets. Based on the clinical effectiveness study of pathogenic MIC isolates, the clinical cutoff was calculated as 0.5 μg/mL. A clinical breakpoint was proposed as 1 μg/mL. In conclusion, the results offer a reference for determining susceptibility breakpoint of cefquinome against S. suis and avoiding resistance emergence by following the optimal dosage regimen.

The Role of PK/PD Analysis in the Development and Evaluation of Antimicrobials

Pharmacokinetic/pharmacodynamic (PK/PD) analysis has proved to be very useful to establish rational dosage regimens of antimicrobial agents in human and veterinary medicine. Actually, PK/PD studies are included in the European Medicines Agency (EMA) guidelines for the evaluation of medicinal products. The PK/PD approach implies the use of in vitro, ex vivo, and in vivo models, as well as mathematical models to describe the relationship between the kinetics and the dynamic to determine the optimal dosing regimens of antimicrobials, but also to establish susceptibility breakpoints, and prevention of resistance. The final goal is to optimize therapy in order to maximize efficacy and minimize side effects and emergence of resistance. In this review, we revise the PK/PD principles and the models to investigate the relationship between the PK and the PD of antibiotics. Additionally, we highlight the outstanding role of the PK/PD analysis at different levels, from the development and evaluation of new antibiotics to the optimization of the dosage regimens of currently available drugs, both for human and animal use.

Revisiting the inoculum effect for Streptococcus pyogenes with a hollow fibre infection model

Severe, invasive Streptococcus pyogenes (Strep A) infections result in greater than 500,000 deaths annually. First line treatment for such infections is benzylpenicillin, often with the addition of clindamycin, but treatment failure can occur with this regimen. This failure has been partially attributed to the inoculum effect, which presents as reduced antibiotic susceptibility during high bacterial density and plateau-phase growth. Hollow fibre infection models (HFIM) have been proposed as an in vitro alternative to in vivo research to study these effects. To re-evaluate the inoculum effect for benzylpenicillin, clindamycin, linezolid, and trimethoprim-sulfamethoxazole using a Strep A HFIM. Differential antibiotic susceptibility of Strep A was measured in a HFIM starting from low- and high-density inocula with an average difference in bacterial concentration of 56-fold. Dynamic antibiotic concentrations were delivered over 48 h to simulate in vivo human pharmacokinetics in an in vitro model. Differences in antibiotic susceptibility were measured by plate count of colony-forming units over time. Inoculum effects were seen in benzylpenicillin and linezolid at 24 h, and benzylpenicillin, linezolid, and clindamycin at 48 h. The effect size was greatest for continuously infused benzylpenicillin at 48 h with a log₁₀-fold difference of 4.02 between groups. No inoculum effect was seen in trimethoprim-sulfamethoxazole, with a maximal log₁₀-fold difference of 0.40. Inoculum effects were seen using benzylpenicillin, linezolid, and clindamycin, which may predict reduced clinical efficacy following treatment delay. The model has proven robust and largely in agreeance with published data, recommending it for further Strep A study.

Combatting the Rising Tide of Antimicrobial Resistance: Pharmacokinetic/Pharmacodynamic Dosing Strategies for Maximal Precision

OBJECTIVE

Antimicrobial pharmacokinetics/pharmacodynamics (PK/PD) principles and PK/PD models have been essential in characterizing the mechanism of antibiotic bacterial killing and determining the most optimal dosing regimen that maximizes clinical outcomes. This review summarized the fundamentals of antimicrobial PK/PD and the various types of PK/PD experiments that shaped the utilization and dosing strategies of antibiotics today.

METHODS

Multiple databases - including PubMed, Scopus, and EMBASE - were searched for published articles that involved PK/PD modelling and precision dosing. Data from in vitro, in vivo and mechanistic PK/PD models were reviewed as a basis for compiling studies that guide dosing regimens used in clinical trials.

RESULTS

Literature regarding the utilization of exposure-response analyses, mathematical modelling and simulations that were summarized are able to provide a better understanding of antibiotic pharmacodynamics that influence translational drug development. Optimal pharmacokinetic sampling of antibiotics from patients can lead to personalized dosing regimens that attain target concentrations while minimizing toxicity. Thus the development of a fully integrated mechanistic model based on systems pharmacology can continually adapt to data generated from clinical responses, which can provide the framework for individualized dosing regimens.

CONCLUSIONS

The promise of what PK/PD can provide through precision dosing for antibiotics has not been fully realized in the clinical setting. Antimicrobial resistance, which has emerged as a significant public health threat, has forced clinicians to empirically utilize therapies. Future research focused on implementation and translation of PK/PD-based approaches integrating novel approaches that combine knowledge of combination therapies, systems pharmacology and resistance mechanisms are necessary. To fully realize maximally precise therapeutics, optimal PK/PD strategies are critical to maximize antimicrobial efficacy against extremely-drug-resistant organisms, while minimizing toxicity.

In vivo studies on antibiotic combination for the treatment of carbapenem-resistant Gram-negative bacteria: a systematic review and meta-analysis protocol

OBJECTIVE

There is poor evidence to determine the superiority of combination regimens versus monotherapy against infections due to carbapenem-resistant (CR) Gram-negative bacteria. In vivo models can simulate the pathophysiology of infections in humans and assess antibiotic efficacy. We aim to investigate in vivo effects of antibiotic combination on mortality and disease burden for infections due to CR Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacteriaceae and provide an unbiased overview of existing knowledge. The results of the study can help prioritising future research on the most promising therapies against CR bacteria.

METHODS AND ANALYSIS

This protocol was formulated using the Systematic Review Protocol for Animal Intervention Studies (SYRCLE) Checklist. Publications will be collected from PubMed, Scopus, Embase and Web of Science. Quality checklists adapted by Collaborative Approach to Meta-Analysis and Review of Animal Data from Experimental Studies and SYRCLE's risk of bias tool will be used. If the meta-analysis seems feasible, the ES and the 95% CI will be analysed. The heterogeneity between studies will be assessed by I2 test. Subgroup meta-analysis will be performed when possible to assess the impact of the studies on efficacy of the treatments. Funnel plotting will be used to evaluate the risk of publication bias.

DISSEMINATION

This systematic review and meta-analysis is part of a wider research collaboration project, the COmbination tHErapy to treat sepsis due to carbapenem-Resistant bacteria in adult and paediatric population: EvideNCE and common practice (COHERENCE) study that includes also the analyses of in vitro and human studies. Data will be presented at international conferences and the results will be published in peer-reviewed journals.

PROSPERO REGISTRATION NUMBER

CRD42019128104(available at: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128104).

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.

XDR-Klebsiella pneumoniae isolates harboring blaOXA-48: In vitro and in vivo evaluation using a murine thigh-infection model

Blood stream infection with extensively drug-resistant-carbapenamase producing Klebsiella (K.) pneumoniae usually represents a major threat with medical challenges among hospitalized cancer patients with poor functional status and underlying diseases. Accordingly, the aim of the study was to evaluate the efficacy of different antibiotics either alone or in combinations against extensively drug-resistant-OXA-48 producing K. pneumoniae clinical isolates that were previously recovered from febrile neutropenic pediatric cancer patients. The antimicrobial activity of amikacin, gentamicin, colistin, ertapenem, imipenem, meropenem and tigecycline was assessed by broth microdilution method. The results revealed that all the tested OXA-48 producing K. pneumoniae isolates exhibited extensively drug-resistant phenotype and all of them were susceptible to tigecycline. Checkerboard method was used to determine the fraction inhibitory concentration index, to further classify the effect of antibiotic combination as synergistic, additive, indifferent, or antagonistic effect. The results revealed that in vitro dual carbapenem combination of ertapenem with meropenem had shown synergistic effect against all of the tested isolates. Additionally, synergistic effect of meropenem with colistin was detected among three of four isolates tested. Herein we investigated the in vivo activity of colistin, meropenem alone and in combination in a rat thigh infection model. The results showed that addition of meropenem to colistin was not effective at reduction of bacterial count as compared to colistin alone at 24 h post treatment. Accordingly, we can conclude that in vitro antibiotic combinations of dual carbapenems (ertapenem plus meropenem) and meropenem plus colistin showed synergism in 100% and 75% of the tested isolates, respectively. Colistin alone had significantly reduced bacterial count while its combination with meropenem was not superior to monotherapy in murine thigh infection model.

Impact statement

The present study aimed to evaluate the effectiveness of various antibiotics both in vitro and in vivo using murine animal model either alone or in combination against various strains of extensively drug-resistant (XDR) Klebsiella pneumoniae, life-threatening pathogens of relevant medical importance isolated from febrile neutropenic pediatric cancer patients. This work also emphasizes how to select the appropriate antibiotics options and help the physicians to choice the appropriate antibiotic for the treatment of such superbugs (extensively drug-resistant (XDR) Klebsiella pneumoniae). The results showed that in vitro dual carbapenem combination of ertapenem with meropenem had shown synergistic effect against all of the tested XDR isolates. Antibiotic combinations of dual carbapenems and meropenem plus colistin showed synergism in 100% and 75% of the testes isolates, respectively. Results of the in vivo evaluation, colistin alone had significantly reduced bacterial count while its combination with meropenem was not superior to monotherapy.

Rapid Evolution of Reduced Susceptibility against a Balanced Dual-Targeting Antibiotic through Stepping-Stone Mutations

Multitargeting antibiotics, i.e., single compounds capable of inhibiting two or more bacterial targets, are generally considered to be a promising therapeutic strategy against resistance evolution. The rationale for this theory is that multitargeting antibiotics demand the simultaneous acquisition of multiple mutations at their respective target genes to achieve significant resistance. The theory presumes that individual mutations provide little or no benefit to the bacterial host. Here, we propose that such individual stepping-stone mutations can be prevalent in clinical bacterial isolates, as they provide significant resistance to other antimicrobial agents. To test this possibility, we focused on gepotidacin, an antibiotic candidate that selectively inhibits both bacterial DNA gyrase and topoisomerase IV. In a susceptible organism, Klebsiella pneumoniae, a combination of two specific mutations in these target proteins provide an >2,000-fold reduction in susceptibility, while individually, none of these mutations affect resistance significantly. Alarmingly, strains with decreased susceptibility against gepotidacin are found to be as virulent as the wild-type Klebsiella pneumoniae strain in a murine model. Moreover, numerous pathogenic isolates carry mutations which could promote the evolution of clinically significant reduction of susceptibility against gepotidacin in the future. As might be expected, prolonged exposure to ciprofloxacin, a clinically widely employed gyrase inhibitor, coselected for reduced susceptibility against gepotidacin. We conclude that extensive antibiotic usage could select for mutations that serve as stepping-stones toward resistance against antimicrobial compounds still under development. Our research indicates that even balanced multitargeting antibiotics are prone to resistance evolution.

Efficacy of Human Exposures of Gepotidacin (GSK2140944) against Escherichia coli in a Rat Pyelonephritis Model

Gepotidacin is a first-in-class triazaacenaphthylene antibacterial that inhibits bacterial type II topoisomerases and has in vitro activity against a range of bacterial pathogens, including Escherichia coli Urinary tract infections often progress to pyelonephritis and are a worldwide problem due to the prevalence of multidrug-resistant E. coli strains. This study evaluated the in vivo efficacy of gepotidacin against four strains of multidrug-resistant E. coli in a rat pyelonephritis model. Infected rats received controlled intravenous infusions of gepotidacin every 12 h for 4 days that recreated human systemic exposures from oral gepotidacin (800 or 1,500 mg twice daily for 4 days). Liquid chromatography-tandem mass spectrometry analysis of blood samples and kidney homogenates showed that gepotidacin levels were 6- to 7-fold higher in kidneys than in blood. Across experiments with 4-day gepotidacin treatments, bacterial CFU in kidneys were reduced by 2.9 to 4.9 log10 compared to pretreatment levels, and bladder CFU were reduced to the lower limit of detection (1.2 log10). The efficacies of 800- and 1,500-mg gepotidacin exposures were statistically similar. A time-course experiment indicated that a period of more than 24 h of gepotidacin treatment was required for efficacy and that 4 days were needed for maximal response. Overall, these results demonstrate that the recreated human exposures of gepotidacin studied were effective in an animal model of pyelonephritis caused by multidrug-resistant E. coli and that further evaluation for clinical use is warranted.

Pharmacokinetics/pharmacodynamics of lefamulin in a neutropenic murine pneumonia model with Staphylococcus aureus and Streptococcus pneumoniae

OBJECTIVES

To present results of preclinical studies that supported further development of lefamulin for treating patients with community-acquired bacterial pneumonia (CABP).

METHODS

The effect of bovine lung surfactant on the antibacterial activity of lefamulin against Streptococcus pneumoniae and Staphylococcus aureus was determined by broth microdilution assay. In vitro accumulation of lefamulin was evaluated in J774 mouse macrophages. Pharmacokinetics was assessed in female BALB/c (Bagg albino) mice treated with subcutaneous lefamulin (35 or 70 mg/kg). In neutropenic lung infection experiments, BALB/c mice received intraperitoneal cyclophosphamide before challenge with single S. pneumoniae or S. aureus strains; subcutaneous lefamulin (1.25-160 mg/kg) was given twice daily post-infection. Hill models described relationships between AUC/MIC ratios and changes in log10 cfu.

RESULTS

Lung surfactant did not significantly increase lefamulin MIC values against test strains. Lefamulin uptake in macrophages was rapid (a plateau was reached in ∼3 h). In mice, distribution of lefamulin [plasma to epithelial lining fluid (ELF)] was rapid, showing an ∼2-fold increase in lefamulin exposure in the ELF during the 5.5 h period. Median plasma AUC/MIC ratios associated with 1 and 2 log10 cfu reductions from baseline were 1.37 and 2.15, respectively, for S. pneumoniae and 2.13 and 6.24 for S. aureus. Corresponding ELF results were 14.0 and 22.0 for S. pneumoniae and 21.7 and 63.9 for S. aureus.

CONCLUSIONS

Overall, lefamulin displays desirable pharmacokinetic/pharmacodynamic relationships that are predictive of the clinical effectiveness of lefamulin and other antibacterial agents used to treat CABP.

The FICI paradigm: Correcting flaws in antimicrobial in vitro synergy screens at their inception

Antibiotics have become the corner stone of modern medicine. However, our society is currently facing one of the greatest challenges of its time: the emergence of antimicrobial resistance. It is estimated that if no new therapies are implemented by 2050, 10 million people will die worldwide every year as a result of infections caused by bacteria resistant to current antibiotics; new antimicrobials are thus urgently needed. However, drug development is a tedious and very costly endeavor of hundreds of millions that can take up to 15-20 years from the bench discovery to the bedside. Under this scenario, drug repurposing, which consists in identifying new uses for old, clinically approved drugs, has gathered momentum within the pharmaceutical industry. Because most of these drugs have safety and toxicity information packages available, clinical evaluation could be done in a much shorter period than standard timelines. Synergistic combinations of these clinically approved drugs could also be a promising approach to identify novel antimicrobial therapies that might provide rational choices of available drugs to shorten treatment, increase efficacy, reduce toxicity, prevent resistance and treat infections caused by drug-resistant strains. However, although simple in its conception, translating results from in vitro synergy screens into in vivo efficacy or the clinical practice has proven to be a paramount challenge. In this Commentary, we will discuss common flaws at the inception of synergy research programs, with a special focus on the use of the Fractional Inhibitory Concentration Index (FICI), and evaluate potential interventions that can be made at different developmental pre-clinical stages in order to improve the odds of translation from in vitro studies.

Pharmacokinetics of enrofloxacin HCl-2H2 O (ENRO-C), PK/PD, and Monte Carlo modeling vs. Leptospira spp. in cows

The pharmacokinetics, PK/PD ratios, and Monte Carlo modeling of enrofloxacin HCl-2H₂ O (Enro-C) and its reference preparation (Enro-R) were determined in cows. Fifty-four Jersey cows were randomly assigned to six groups receiving a single IM dose of 10, 15, or 20 mg/kg of Enro-C (Enro-C₁₀ , Enro-C₁₅ , Enro-C₂₀ ) or Enro-R. Serial serum samples were collected and enrofloxacin concentrations quantified. A composite set of minimum inhibitory concentrations (MIC) of Leptospira spp. was utilized to calculate PK/PD ratios: maximum serum concentration/MIC (C_max /MIC₉₀ ) and area under the serum vs. time concentration of enrofloxacin/MIC (AUC_0-24 /MIC₉₀ ). Monte Carlo simulations targeted C_max /MIC = 10 and AUC_0-24 /MIC = 125. Mean C_max obtained were 6.17 and 2.46 μg/ml; 8.75 and 3.54 μg/ml; and 13.89 and 4.25 μg/ml, respectively for Enro-C and Enro-R. C_max /MIC₉₀ ratios were 6.17 and 2.46, 8.75 and 3.54, and 13.89 and 4.25 for Enro-C and Enro-R, respectively. Monte Carlo simulations based on C_max /MIC₉₀  = 10 indicate that only Enro-C₁₅ and Enro-C₂₀ may be useful to treat leptospirosis in cows, predicting a success rate ≥95% when MIC₅₀  = 0.5 μg/ml, and ≥80% when MIC₉₀  = 1.0 μg/ml. Although Enro-C₁₅ and Enro-C₂₀ may be useful to treat leptospirosis in cattle, clinical trials are necessary to confirm this proposal.

Rational Combinations of Polymyxins with Other Antibiotics

Combinations of antimicrobial agents are often used in the management of infectious diseases. Antimicrobial agents used as part of combination therapy are often selected empirically. As regrowth and the emergence of polymyxin (either colistin or polymyxin B) resistance has been observed with polymyxin monotherapy, polymyxin combination therapy has been suggested as a possible means by which to increase antimicrobial activity and reduce the development of resistance. This chapter provides an overview of preclinical and clinical investigations of CMS/colistin and polymyxin B combination therapy. In vitro data and animal model data suggests a potential clinical benefit with many drug combinations containing clinically achievable concentrations of polymyxins, even when resistance to one or more of the drugs in combination is present and including antibiotics normally inactive against Gram-negative organisms. The growing body of data on the emergence of polymyxin resistance with monotherapy lends theoretical support to a benefit with combination therapy. Benefits include enhanced bacterial killing and a suppression of polymyxin resistant subpopulations. However, the complexity of the critically ill patient population, and high rates of treatment failure and death irrespective of infection-related outcome make demonstrating a potential benefit for polymyxin combinations extremely challenging. Polymyxin combination therapy in the clinic remains a heavily debated and controversial topic. When combinations are selected, optimizing the dosage regimens for the polymyxin and the combinatorial agent is critical to ensure that the benefits outweigh the risk of the development of toxicity. Importantly, patient characteristics, pharmacokinetics, the site of infection, pathogen and resistance mechanism must be taken into account to define optimal and rational polymyxin combination regimens in the clinic.

Technologies for Measuring Pharmacokinetic Profiles

The creation of a pharmacokinetic (PK) curve, which follows the plasma concentration of an administered drug as a function of time, is a critical aspect of the drug development process and includes such information as the drug's bioavailability, clearance, and elimination half-life. Prior to a drug of interest gaining clearance for use in human clinical trials, research is performed during the preclinical stages to establish drug safety and dosing metrics from data obtained from the PK studies. Both in vivo animal models and in vitro platforms have limitations in predicting human reaction to a drug due to differences in species and associated simplifications, respectively. As a result, in silico experiments using computer simulation have been implemented to accurately predict PK parameters in human studies. This review assesses these three approaches (in vitro, in vivo, and in silico) when establishing PK parameters and evaluates the potential for in silico studies to be the future gold standard of PK preclinical studies.

Sputum Active Polymyxin Lipopeptides: Activity against Cystic Fibrosis Pseudomonas aeruginosa Isolates and Their Interactions with Sputum Biomolecules

The mucoid biofilm mode of growth of Pseudomonas aeruginosa (P. aeruginosa) in the lungs of cystic fibrosis patients makes eradication of infections with antibiotic therapy very difficult. The lipopeptide antibiotics polymyxin B and colistin are currently the last-resort therapies for infections caused by multidrug-resistant P. aeruginosa. In the present study, we investigated the antibacterial activity of a series of polymyxin lipopeptides (polymyxin B, colistin, FADDI-003, octapeptin A₃, and polymyxin A₂) against a panel of polymyxin-susceptible and polymyxin-resistant P. aeruginosa cystic fibrosis isolates grown under planktonic or biofilm conditions in artificial sputum and their interactions with sputum component biomolecules. In sputum media under planktonic conditions, the lipopeptides FADDI-003 and octapeptin A₃ displayed very promising activity against the polymyxin-resistant isolate FADDI-PA066 (polymyxin B minimum inhibitory concentration (MIC) = 32 mg/L), while retaining their activity against the polymyxin-sensitive strains FADDI-PA021 (polymyxin B MIC = 1 mg/L) and FADDI-PA020 (polymyxin B MIC = 2 mg/L). Polymyxin A₂ was only effective against the polymyxin-sensitive isolates. However, under biofilm growth conditions, the hydrophobic lipopeptide FADDI-003 was inactive compared to the more hydrophilic lipopeptides, octapeptin A₃, polymyxin A₂, polymyxin B, and colistin. Transmission electron micrographs revealed octapeptin A₃ caused reduction in the cell numbers in biofilm as well as biofilm disruption/“antibiofilm” activity. We therefore assessed the interactions of the lipopeptides with the component sputum biomolecules, mucin, deoxyribonucleic acid (DNA), surfactant, F-actin, lipopolysaccharide, and phospholipids. We observed the general trend that sputum biomolecules reduce lipopeptide antibacterial activity. Collectively, our data suggests that, in the airways, lipopeptide binding to component sputum biomolecules may reduce antibacterial efficacy and is dependent on the physicochemical properties of the lipopeptide.

Microfluidic Module for Real-Time Generation of Complex Multimolecule Temporal Concentration Profiles

We designed a microfluidic module that generates complex and dynamic concentration profiles of multiple molecules over a large concentration range using pulse-width modulation (PWM). Our PWM module can combine up to six different inputs and select among three downstream mixing channels, as required by the application. The module can produce concentrations with a dynamic range of three decades. We created complex, temporal concentration profiles of two molecules, with each concentration independently controllable, and show that the PWM module can execute rapid concentration changes as well as long-time scale pharmacokinetic profiles. Concentration profiles were generated for molecules with molecular weights ranging from 560 Da to 150 kDa. Our PWM module produces robust and precise concentration profiles under a variety of operating conditions, making it ideal for integration with existing microfluidic devices for advanced cell and pharmacokinetic studies.

Microtechnology-Based Multi-Organ Models

Drugs affect the human body through absorption, distribution, metabolism, and elimination (ADME) processes. Due to their importance, the ADME processes need to be studied to determine the efficacy and side effects of drugs. Various in vitro model systems have been developed and used to realize the ADME processes. However, conventional model systems have failed to simulate the ADME processes because they are different from in vivo, which has resulted in a high attrition rate of drugs and a decrease in the productivity of new drug development. Recently, a microtechnology-based in vitro system called "organ-on-a-chip" has been gaining attention, with more realistic cell behavior and physiological reactions, capable of better simulating the in vivo environment. Furthermore, multi-organ-on-a-chip models that can provide information on the interaction between the organs have been developed. The ultimate goal is the development of a "body-on-a-chip", which can act as a whole body model. In this review, we introduce and summarize the current progress in the development of multi-organ models as a foundation for the development of body-on-a-chip.

Animal models in the pharmacokinetic/pharmacodynamic evaluation of antimicrobial agents

Animal infection models in the pharmacokinetic/pharmacodynamic (PK/PD) evaluation of antimicrobial therapy serve an important role in preclinical assessments of new antibiotics, dosing optimization for those that are clinically approved, and setting or confirming susceptibility breakpoints. The goal of animal model studies is to mimic the infectious diseases seen in humans to allow for robust PK/PD studies to find the optimal drug exposures that lead to therapeutic success. The PK/PD index and target drug exposures obtained in validated animal infection models are critical components in optimizing dosing regimen design in order to maximize efficacy while minimize the cost and duration of clinical trials. This review outlines the key components in animal infection models which have been used extensively in antibiotic discovery and development including PK/PD analyses.

Pharmacokinetic and Pharmacodynamic Principles of Anti-infective Dosing

PURPOSE

An understanding of the pharmacokinetic (PK) and pharmacodynamic (PD) principles that determine response to antimicrobial therapy can provide the clinician with better-informed dosing regimens. Factors influential on antibiotic disposition and clinical outcome are presented, with a focus on the primary site of infection. Techniques to better understand antibiotic PK and optimize PD are acknowledged.

METHODS

PubMed (inception-April 2016) was reviewed for relevant publications assessing antimicrobial exposures within different anatomic locations and clinical outcomes for various infection sites.

FINDINGS

A limited literature base indicates variable penetration of antibiotics to different target sites of infection, with drug solubility and extent of protein binding providing significant PK influences in addition to the major clearing pathway of the agent. PD indices derived from in vitro studies and animal models determine the optimal magnitude and frequency of dosing regimens for patients. PK/PD modeling and simulation has been shown an efficient means of assessing these PD endpoints against a variety of PK determinants, clarifying the unique effects of infection site and patient characteristics to inform the adequacy of a given antibiotic regimen.

IMPLICATIONS

Appreciation of the PK properties of an antibiotic and its PD measure of efficacy can maximize the utility of these life-saving drugs. Unfortunately, clinical data remain limited for a number of infection site-antibiotic exposure relationships. Modeling and simulation can bridge preclinical and patient data for the prescription of optimal antibiotic dosing regimens, consistent with the tenets of personalized medicine.

Single-cell level methods for studying the effect of antibiotics on bacteria during infection

Considerable evidence about phenotypic heterogeneity among bacteria during infection has accumulated during recent years. This heterogeneity has to be considered if the mechanisms of infection and antibiotic action are to be understood, so we need to implement existing and find novel methods to monitor the effects of antibiotics on bacteria at the single-cell level. This review provides an overview of methods by which this aim can be achieved. Fluorescence label-based methods and Raman scattering as a label-free approach are discussed in particular detail. Other label-free methods that can provide single-cell level information, such as impedance spectroscopy and surface plasmon resonance, are briefly summarized. The advantages and disadvantages of these different methods are discussed in light of a challenging in vivo environment.