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.

Application of pharmacokinetic/pharmacodynamic concepts to the development of treatment regimens for sporadic canine urinary tract infections: Challenges and paths forward

Antimicrobial efficacy can be predicted based on infection site exposure to the antimicrobial agent relative to the in vitro susceptibility of the pathogen to that agent. When infections occur in soft tissues (e.g., muscle, blood, and ligaments), exposure at the infection site is generally assumed to reflect an equilibrium between the unbound concentrations in plasma and that in the interstitial fluids. In contrast, for sporadic urinary tract infections (UTIs) in dogs and uncomplicated UTIs in humans, the primary site of infection is the bladder wall. Infection develops when bacteria invade the host bladder urothelium (specifically, the umbrella cells that form the urine-contacting layer of the stratified uroepithelium) within which these bacteria can avoid exposure to host defenses and antimicrobial agents. Traditionally, pathogen susceptibility has been estimated using standardized in vitro tests that measure the minimal concentration that will inhibit pathogen growth (MIC). When using exposure-response relationships during drug development to explore dose optimization, these relationships can either be based upon an assessment of a correlation between clinical outcome, drug exposure at the infection site, and pathogen MIC, or upon benchmark exposure-response relationships (i.e., pharmacokinetic/pharmacodynamic indices) typically used for the various drug classes. When using the latter approach, it is essential that the unbound concentrations at the infection site be considered relative to the MIC within the biological matrix to which the pathogen will be exposed. For soft tissue infections, this typically is the unbound plasma concentrations versus MICs determined in standardized media such as cation-adjusted Mueller Hinton broth, which is how many indices were originally established. However, for UTIs, it is the unbound drug concentrations within the urine versus the MICs in the actual urine biophase that needs to be considered. The importance of these relationships and how they are influenced by drug resistance, resilience, and inoculum are discussed in this review using fluoroquinolones and beta-lactams as examples.

Amoxicillin duration and dose for community-acquired pneumonia in children: the CAP-IT factorial non-inferiority RCT

BACKGROUND

Data are limited regarding the optimal dose and duration of amoxicillin treatment for community-acquired pneumonia in children.

OBJECTIVES

To determine the efficacy, safety and impact on antimicrobial resistance of shorter (3-day) and longer (7-day) treatment with amoxicillin at both a lower and a higher dose at hospital discharge in children with uncomplicated community-acquired pneumonia.

DESIGN

A multicentre randomised double-blind 2 × 2 factorial non-inferiority trial in secondary care in the UK and Ireland.

SETTING

Paediatric emergency departments, paediatric assessment/observation units and inpatient wards.

PARTICIPANTS

Children aged > 6 months, weighing 6-24 kg, with a clinical diagnosis of community-acquired pneumonia, in whom treatment with amoxicillin as the sole antibiotic was planned on discharge.

INTERVENTIONS

Oral amoxicillin syrup at a dose of 35-50 mg/kg/day compared with a dose of 70-90 mg/kg/day, and 3 compared with 7 days' duration. Children were randomised simultaneously to each of the two factorial arms in a 1 : 1 ratio.

MAIN OUTCOME MEASURES

The primary outcome was clinically indicated systemic antibacterial treatment prescribed for respiratory tract infection (including community-acquired pneumonia), other than trial medication, up to 28 days after randomisation. Secondary outcomes included severity and duration of parent/guardian-reported community-acquired pneumonia symptoms, drug-related adverse events (including thrush, skin rashes and diarrhoea), antimicrobial resistance and adherence to trial medication.

RESULTS

A total of 824 children were recruited from 29 hospitals. Ten participants received no trial medication and were excluded. Participants [median age 2.5 (interquartile range 1.6-2.7) years; 52% male] were randomised to either 3 (n = 413) or 7 days (n = 401) of trial medication at either lower (n = 410) or higher (n = 404) doses. There were 51 (12.5%) and 49 (12.5%) primary end points in the 3- and 7-day arms, respectively (difference 0.1%, 90% confidence interval -3.8% to 3.9%) and 51 (12.6%) and 49 (12.4%) primary end points in the low- and high-dose arms, respectively (difference 0.2%, 90% confidence interval -3.7% to 4.0%), both demonstrating non-inferiority. Resolution of cough was faster in the 7-day arm than in the 3-day arm for cough (10 days vs. 12 days) (p = 0.040), with no difference in time to resolution of other symptoms. The type and frequency of adverse events and rate of colonisation by penicillin-non-susceptible pneumococci were comparable between arms.

LIMITATIONS

End-of-treatment swabs were not taken, and 28-day swabs were collected in only 53% of children. We focused on phenotypic penicillin resistance testing in pneumococci in the nasopharynx, which does not describe the global impact on the microflora. Although 21% of children did not attend the final 28-day visit, we obtained data from general practitioners for the primary end point on all but 3% of children.

CONCLUSIONS

Antibiotic retreatment, adverse events and nasopharyngeal colonisation by penicillin-non-susceptible pneumococci were similar with the higher and lower amoxicillin doses and the 3- and 7-day treatments. Time to resolution of cough and sleep disturbance was slightly longer in children taking 3 days' amoxicillin, but time to resolution of all other symptoms was similar in both arms.

FUTURE WORK

Antimicrobial resistance genotypic studies are ongoing, including whole-genome sequencing and shotgun metagenomics, to fully characterise the effect of amoxicillin dose and duration on antimicrobial resistance. The analysis of a randomised substudy comparing parental electronic and paper diary entry is also ongoing.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN76888927, EudraCT 2016-000809-36 and CTA 00316/0246/001-0006.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 60. See the NIHR Journals Library website for further project information.

PK/PD Analysis by Nonlinear Mixed-Effects Modeling of a Marbofloxacin Dose Regimen for Treatment of Goat Mastitis Produced by Coagulase-Negative Staphylococci

Simple Summary

Coagulase-negative staphylococci are main pathogens that produce goat mastitis. Marbofloxacin is a third-generation fluoroquinolone approved to treat mastitis in animals. Since the efficacy of an antimicrobial is related with its concentration in the site of infection, and the latter depends of dose and biological processes that determine the distribution of the antimicrobial in different tissues and secretions, the objectives of this study were to evaluate the efficacy of a dose regimen of marbofloxacin (10 mg/kg/24 h) administered intramuscularly for five days in goats with mastitis induced by coagulase-negative staphylococci, by an evaluation of the concentrations of marbofloxacin achieved in blood and milk over time (called pharmacokinetics), and characterizing the concentration–effect relationship of marbofloxacin against coagulase-negative staphylococci in Mueller Hinton broth and goat milk, by time kill assays, in order to determine the concentrations of marbofloxacin related with an adequate bacterial count reduction (measured by efficacy index AUC/MIC). The proposed dose regimen was adequate for the treatment of goat mastitis produced by coagulase-negative staphylococci, resulting in a microbiological and clinical cure of all animals. The animal model used in this study provided important pharmacokinetic information about the effect of the infection on the pharmacokinetics of marbofloxacin. Pharmacodynamic modeling showed that marbofloxacin concentrations needed for antimicrobial efficacy were higher in goat milk compared with Mueller Hinton broth. Bacterial resistance to antimicrobials is a serious problem, since marbofloxacin is considered a critically important antimicrobial, and its rational and prudent use could extend its utility over time.

Abstract

Coagulase-negative staphylococci are main pathogens that produce goat mastitis. Marbofloxacin is a third-generation fluoroquinolone approved for treat mastitis in animals. The objectives of this study were: (i) to determine the pharmacokinetics of marbofloxacin (10 mg/kg/24 h) in serum and milk administered intramuscularly for five days in goats with mastitis induced by coagulase-negative staphylococci; (ii) to characterize the concentration–effect relationship of marbofloxacin against coagulase-negative staphylococci in Mueller Hinton broth and goat milk; (iii) to determine AUC/MIC cutoff values of marbofloxacin, and (iv) to perform a PK/PD analysis to evaluate the efficacy of the dose regimen for the treatment of goat mastitis produced by coagulase-negative staphylococci. Marbofloxacin presented context-sensitive pharmacokinetics, influenced by the evolution of the disease, which decreased marbofloxacin disposition in serum and milk. Marbofloxacin showed a median (95% CI) fAUC/MIC values for MIC of 0.4 and 0.8 µg/mL of 26.66 (22.26–36.64) and 32.28 (26.57–48.35) related with −2 log₁₀CFU/mL reduction; and 32.26 (24.81–81.50) and 41.39 (29.38–128.01) for −3 log₁₀CFU/mL reduction in Mueller Hinton broth. For milk, −2 log₁₀CFU/mL reduction was achieved with 41.48 (35.29–58.73) and 51.91 (39.09–131.63), and −3 log₁₀CFU/mL reduction with 51.04 (41.6–82.1) and 65.65 (46.68–210.16). The proposed dose regimen was adequate for the treatment of goat mastitis produced by coagulase-negative staphylococci, resulting in microbiological and clinical cure of all animals. The animal model used in this study provided important pharmacokinetic information about the effect of the infection on the pharmacokinetics of marbofloxacin. Pharmacodynamic modeling showed that fAUC/MIC cutoff values were higher in goat milk compared with Mueller Hinton broth.

Modeling of Effective Antimicrobials to Reduce Staphylococcus aureus Virulence Gene Expression Using a Two-Compartment Hollow Fiber Infection Model

Toxins produced by community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) contribute to virulence. We developed a statistical approach to determine an optimum sequence of antimicrobials to treat CA-MRSA infections based on an antimicrobial’s ability to reduce virulence. In an in vitro pharmacodynamic hollow fiber model, expression of six virulence genes (lukSF-PV, sek, seq, ssl8, ear, and lpl10) in CA-MRSA USA300 was measured by RT-PCR at six time points with or without human-simulated, pharmacokinetic dosing of five antimicrobials (clindamycin, minocycline, vancomycin, linezolid, and trimethoprim/sulfamethoxazole (SXT)). Statistical modeling identified the antimicrobial causing the greatest decrease in virulence gene expression at each time-point. The optimum sequence was SXT at T0 and T4, linezolid at T8, and clindamycin at T24–T72 when lukSF-PV was weighted as the most important gene or when all six genes were weighted equally. This changed to SXT at T0–T24, linezolid at T48, and clindamycin at T72 when lukSF-PV was weighted as unimportant. The empirical p-value for each optimum sequence according to the different weights was 0.001, 0.0009, and 0.0018 with 10,000 permutations, respectively, indicating statistical significance. A statistical method integrating data on change in gene expression upon multiple antimicrobial exposures is a promising tool for identifying a sequence of antimicrobials that is effective in sustaining reduced CA-MRSA virulence.

Generating Robust and Informative Nonclinical In Vitro and In Vivo Bacterial Infection Model Efficacy Data To Support Translation to Humans

In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration.

In June 2017, the National Institute of Allergy and Infectious Diseases, part of the National Institutes of Health, organized a workshop entitled “Pharmacokinetics-Pharmacodynamics (PK/PD) for Development of Therapeutics against Bacterial Pathogens.” The aims were to discuss details of various PK/PD models and identify sound practices for deriving and utilizing PK/PD relationships to design optimal dosage regimens for patients. Workshop participants encompassed individuals from academia, industry, and government, including the United States Food and Drug Administration. This and the accompanying review on clinical PK/PD summarize the workshop discussions and recommendations. Nonclinical PK/PD models play a critical role in designing human dosage regimens and are essential tools for drug development. These include in vitro and in vivo efficacy models that provide valuable and complementary information for dose selection and translation from the laboratory to human. It is crucial that studies be designed, conducted, and interpreted appropriately. For antibacterial PK/PD, extensive published data and expertise are available. These have been leveraged to develop recommendations, identify common pitfalls, and describe the applications, strengths, and limitations of various nonclinical infection models and translational approaches. Despite these robust tools and published guidance, characterizing nonclinical PK/PD relationships may not be straightforward, especially for a new drug or new class. Antimicrobial PK/PD is an evolving discipline that needs to adapt to future research and development needs. Open communication between academia, pharmaceutical industry, government, and regulatory bodies is essential to share perspectives and collectively solve future challenges.

Evolutionary epidemiology models to predict the dynamics of antibiotic resistance

The evolution of resistance to antibiotics is a major public health problem and an example of rapid adaptation under natural selection by antibiotics. The dynamics of antibiotic resistance within and between hosts can be understood in the light of mathematical models that describe the epidemiology and evolution of the bacterial population. "Between-host" models describe the spread of resistance in the host community, and in more specific settings such as hospitalized hosts (treated by antibiotics at a high rate), or farm animals. These models make predictions on the best strategies to limit the spread of resistance, such as reducing transmission or adapting the prescription of several antibiotics. Models can be fitted to epidemiological data in the context of intensive care units or hospitals to predict the impact of interventions on resistance. It has proven harder to explain the dynamics of resistance in the community at large, in particular because models often do not reproduce the observed coexistence of drug-sensitive and drug-resistant strains. "Within-host" models describe the evolution of resistance within the treated host. They show that the risk of resistance emergence is maximal at an intermediate antibiotic dose, and some models successfully explain experimental data. New models that include the complex host population structure, the interaction between resistance-determining loci and other loci, or integrating the within- and between-host levels will allow better interpretation of epidemiological and genomic data from common pathogens and better prediction of the evolution of resistance.

Distinguishing Antimicrobial Models with Different Resistance Mechanisms via Population Pharmacodynamic Modeling

Semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) modeling is increasingly used for antimicrobial drug development and optimization of dosage regimens, but systematic simulation-estimation studies to distinguish between competing PD models are lacking. This study compared the ability of static and dynamic in vitro infection models to distinguish between models with different resistance mechanisms and support accurate and precise parameter estimation. Monte Carlo simulations (MCS) were performed for models with one susceptible bacterial population without (M1) or with a resting stage (M2), a one population model with adaptive resistance (M5), models with pre-existing susceptible and resistant populations without (M3) or with (M4) inter-conversion, and a model with two pre-existing populations with adaptive resistance (M6). For each model, 200 datasets of the total bacterial population were simulated over 24h using static antibiotic concentrations (256-fold concentration range) or over 48h under dynamic conditions (dosing every 12h; elimination half-life: 1h). Twelve-hundred random datasets (each containing 20 curves for static or four curves for dynamic conditions) were generated by bootstrapping. Each dataset was estimated by all six models via population PD modeling to compare bias and precision. For M1 and M3, most parameter estimates were unbiased (<10%) and had good imprecision (<30%). However, parameters for adaptive resistance and inter-conversion for M2, M4, M5 and M6 had poor bias and large imprecision under static and dynamic conditions. For datasets that only contained viable counts of the total population, common statistical criteria and diagnostic plots did not support sound identification of the true resistance mechanism. Therefore, it seems advisable to quantify resistant bacteria and characterize their MICs and resistance mechanisms to support extended simulations and translate from in vitro experiments to animal infection models and ultimately patients.

Mathematical models are increasingly used for analysis and interpretation of in vitro efficacy results of antimicrobial drugs. Various models are employed in the scientific literature and it seems that they are equally able to describe the observed data. The aim of the present study was to compare different models in various experimental designs and with different resistance mechanisms of bacteria. For that purpose we have generated experimental data through Monte-Carlo simulations and then used six different mathematical models to analyze these results. We showed that statistical comparison of models did not allow determining which was the true mechanism of resistance, i.e. the one used for the simulation step. Moreover mathematical parameters for bacterial resistance were estimated with bias and with a low precision except for the simpler cases. This suggests that the choice of the mathematical model for data analysis should be guided by experimental characterization of the bacterial mechanism of resistance.

Suppression of Emergence of Resistance in Pathogenic Bacteria: Keeping Our Powder Dry, Part 1

We are in a crisis of bacterial resistance. For economic reasons, most pharmaceutical companies are abandoning antimicrobial discovery efforts, while, in health care itself, infection control and antibiotic stewardship programs have generally failed to prevent the spread of drug-resistant bacteria. At this point, what can be done? The first step has been taken. Governments and international bodies have declared there is a worldwide crisis in antibiotic drug resistance. As discovery efforts begin anew, what more can be done to protect newly developing agents and improve the use of new drugs to suppress resistance emergence? A neglected path has been the use of recent knowledge regarding antibiotic dosing as single agents and in combination to minimize resistance emergence, while also providing sufficient early bacterial kill. In this review, we look at the data for resistance suppression. Approaches include increasing the intensity of therapy to suppress resistant subpopulations; developing concepts of clinical breakpoints to include issues surrounding suppression of resistance; and paying attention to the duration of therapy, which is another important issue for resistance suppression. New understanding of optimizing combination therapy is of interest for difficult-to-treat pathogens like Pseudomonas aeruginosa, Acinetobacter spp., and multidrug-resistant (MDR) Enterobacteriaceae. These lessons need to be applied to our old drugs to preserve them as well and need to be put into national and international antibiotic resistance strategies. As importantly, from a regulatory perspective, new chemical entities should have a corresponding resistance suppression plan at the time of regulatory review. In this way, we can make the best of our current situation and improve future prospects.

Colistin and doripenem combinations against Pseudomonas aeruginosa: profiling the time course of synergistic killing and prevention of resistance

OBJECTIVES

Colistin is an 'old' drug, which is being increasingly utilized due to limited therapeutic options. However, resistance emergence during monotherapy is concerning. Here, our objective was to optimize colistin combinations against Pseudomonas aeruginosa by profiling the time course of synergistic killing and prevention of resistance.

METHODS

Hollow-fibre infection models over 10 days simulated clinically relevant dosage regimens of colistin and doripenem against two heteroresistant P. aeruginosa strains (MIC 1 mg/L) and one resistant (MIC 128 mg/L) strain (inoculum 10(9.3) cfu/mL). New mathematical mechanism-based models (MBMs) were developed using S-ADAPT.

RESULTS

Against heteroresistant P. aeruginosa strains, colistin monotherapy resulted in initial killing (up to 2.64 log10 cfu/mL) within 24 h followed by regrowth. High-intensity combinations involving free steady-state colistin concentrations of 5 mg/L achieved complete eradication (>9.3 log10 killing) within 48 h. These combinations achieved synergy with up to 9.38 log10 greater killing compared with the most active monotherapy. Against the colistin-resistant strain, the combination yielded marked initial synergy with up to 6.11 log10 cfu/mL bacterial reductions within 72 h followed by regrowth. The MBMs quantified total and resistant subpopulations and the proposed synergy between colistin and doripenem.

CONCLUSIONS

Our findings provide insight into optimal antibiotic treatment and may serve as a framework for new drug combinations and combination modelling.

New dosing strategies for an old antibiotic: pharmacodynamics of front-loaded regimens of colistin at simulated pharmacokinetics in patients with kidney or liver disease

Increasing evidence suggests that colistin monotherapy is suboptimal at currently recommended doses. We hypothesized that front-loading provides an improved dosing strategy for polymyxin antibiotics to maximize killing and minimize total exposure. Here, we utilized an in vitro pharmacodynamic model to examine the impact of front-loaded colistin regimens against a high bacterial density (10(8) CFU/ml) of Pseudomonas aeruginosa. The pharmacokinetics were simulated for patients with hepatic (half-life [t1/2] of 3.2 h) or renal (t1/2 of 14.8 h) disease. Front-loaded regimens (n=5) demonstrated improvement in bacterial killing, with reduced overall free drug areas under the concentration-time curve (fAUC) compared to those with traditional dosing regimens (n=14) with various dosing frequencies (every 12 h [q12h] and q24h). In the renal failure simulations, front-loaded regimens at lower exposures (fAUC of 143 mg · h/liter) obtained killing activity similar to that of traditional regimens (fAUC of 268 mg · h/liter), with an ∼97% reduction in the area under the viable count curve over 48 h. In hepatic failure simulations, front-loaded regimens yielded rapid initial killing by up to 7 log10 within 2 h, but considerable regrowth occurred for both front-loaded and traditional regimens. No regimen eradicated the high bacterial inoculum of P. aeruginosa. The current study, which utilizes an in vitro pharmacodynamic infection model, demonstrates the potential benefits of front-loading strategies for polymyxins simulating differential pharmacokinetics in patients with hepatic and renal failure at a range of doses. Our findings may have important clinical implications, as front-loading polymyxins as a part of a combination regimen may be a viable strategy for aggressive treatment of high-bacterial-burden infections.

Aggressive chemotherapy and the selection of drug resistant pathogens

Drug resistant pathogens are one of the key public health challenges of the 21^st century. There is a widespread belief that resistance is best managed by using drugs to rapidly eliminate target pathogens from patients so as to minimize the probability that pathogens acquire resistance de novo. Yet strong drug pressure imposes intense selection in favor of resistance through alleviation of competition with wild-type populations. Aggressive chemotherapy thus generates opposing evolutionary forces which together determine the rate of drug resistance emergence. Identifying treatment regimens which best retard resistance evolution while maximizing health gains and minimizing disease transmission requires empirical analysis of resistance evolution in vivo in conjunction with measures of clinical outcomes and infectiousness. Using rodent malaria in laboratory mice, we found that less aggressive chemotherapeutic regimens substantially reduced the probability of onward transmission of resistance (by >150-fold), without compromising health outcomes. Our experiments suggest that there may be cases where resistance evolution can be managed more effectively with treatment regimens other than those which reduce pathogen burdens as fast as possible.

Drug-resistance is a major public health problem. Conventional wisdom on resistance management is to use aggressive chemotherapy to kill pathogens as rapidly as possible so as to prevent them from acquiring resistance. This is the reason why physicians frequently exhort patients to finish drug courses even after they no longer feel sick. However, this approach is based on the notion that we need only prevent new resistant mutants from arising. We hypothesize that in the situation where such mutants are already present at the time of treatment, more aggressive chemotherapy will select for these the fastest by rapidly killing all sensitive competitors. Here we demonstrate in a rodent malaria model that such selection indeed occurs more intensely following aggressive treatment than following less aggressive treatment, without any benefit to host health or infectivity. This suggests that aggressive chemotherapy will not be the best way to retard resistance evolution in some - perhaps many - circumstances. We suggest that an evidence-based approach across a wide range of infectious diseases is needed to manage resistance evolution.

Dose modulation: a new concept of antibiotic therapy in the critically ill patient?

Considerable evidence has shown that adequate antibiotic therapy is of utmost importance in the critically ill septic patient. However, antibiotic concentration may be insufficient early in infection course. We propose the concept of dose modulation, meaning front-line variability of antibiotic dose, according to patient and microorganism characteristics, followed by its reduction after clinical response and patient recovery. Therefore, dose modulation means concentrating the largest weight of antibiotics at the front-end, when the microbial load is higher and the pharmacokinetic changes poses the highest risk of underdosing and nibbling off antibiotic dose, when the sepsis syndrome is improving, guided by pharmacokinetic and pharmacodynamic data.

Dosing regimen matters: the importance of early intervention and rapid attainment of the pharmacokinetic/pharmacodynamic target

To date, the majority of pharmacokinetic/pharmacodynamic (PK/PD) discussions have focused on PK/PD relationships evaluated at steady-state drug concentrations. However, a concern with reliance upon steady-state drug concentrations is that it ignores events occurring while the pathogen is exposed to intermittent suboptimal systemic drug concentrations prior to the attainment of a steady state. Suboptimal (inadequate) exposure can produce amplification of resistant bacteria. This minireview provides an overview of published evidence supporting the positions that, in most situations, it is the exposure achieved during the first dose that is relevant for determining the therapeutic outcome of an infection, therapeutic intervention should be initiated as soon as possible to minimize the size of the bacterial burden at the infection site, and the duration of drug administration should be kept as brief as clinically appropriate to reduce the risk of selecting for resistant (or phenotypically nonresponsive) microbial strains. To support these recommendations, we briefly discuss data on inoculum effects, persister cells, and the concept of time within some defined mutation selection window.

Mechanisms of resistance and clinical relevance of resistance to β-lactams, glycopeptides, and fluoroquinolones

The widespread use of antibiotics has resulted in a growing problem of antimicrobial resistance in the community and hospital settings. Antimicrobial classes for which resistance has become a major problem include the β-lactams, the glycopeptides, and the fluoroquinolones. In gram-positive bacteria, β-lactam resistance most commonly results from expression of intrinsic low-affinity penicillin-binding proteins. In gram-negative bacteria, expression of acquired β-lactamases presents a particular challenge owing to some natural spectra that include virtually all β-lactam classes. Glycopeptide resistance has been largely restricted to nosocomial Enterococcus faecium strains, the spread of which is promoted by ineffective infection control mechanisms for fecal organisms and the widespread use of colonization-promoting antimicrobials (especially cephalosporins and antianaerobic antibiotics). Fluoroquinolone resistance in community-associated strains of Escherichia coli, many of which also express β-lactamases that confer cephalosporin resistance, is increasingly prevalent. Economic and regulatory forces have served to discourage large pharmaceutical companies from developing new antibiotics, suggesting that the antibiotics currently on the market may be all that will be available for the coming decade. As such, it is critical that we devise, test, and implement antimicrobial stewardship strategies that are effective at constraining and, ideally, reducing resistance in human pathogenic bacteria.

Comorbidity in Atopic Dermatitis

The negative impact of atopic dermatitis (AD) often extends beyond the skin. Children with AD experience increased rates of infectious, mental health, and allergic diseases compared to their non-atopic peers. The mechanisms underlying these associations remain elusive. New insights from genetic and epidermal research pinpoint the skin barrier as a primary initiator of AD. Epicutaneous sensitization represents an intriguing new model which links a disrupted skin barrier to the later development of IgE-mediated diseases in patients with AD. Recent epidemiological studies have identified new comorbidities linked to AD as well, including several mental health disorders and obesity. This manuscript reviews the recent literature regarding both classic and newly described AD comorbidities.

Simulated antibiotic exposures in an in vitro hollow-fiber infection model influence toxin gene expression and production in community-associated methicillin-resistant Staphylococcus aureus strain MW2

Community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) strain MW2 harbors a plethora of toxins to mediate its virulence. However, toxin expression and regulation with simulated clinical antimicrobial exposures are unclear. This study evaluated these relationships using an in vitro pharmacodynamic hollow-fiber infection model. Clinical doses of clindamycin, linezolid, minocycline, trimethoprim-sulfamethoxazole (SXT), and vancomycin were simulated over 72 h against MW2 in the hollow fiber model. Expression levels of lukSF-PV and enterotoxin genes sec4, sek, seq, and sel2 were quantified by real-time PCR. Panton-Valentine leukocidin (PVL) was quantified by enzyme-linked immunosorbent assay (ELISA), and cytotoxicity was determined on polymorphonuclear cells (PMNs). Vancomycin produced the maximum MW2 killing (2.53 log(10) CFU/ml) after the first dose, but the greatest sustained killing over 72 h occurred with linezolid and clindamycin. Vancomycin and minocycline induced gene upregulation from 0 to 8 h, followed by downregulation for the remaining simulation period. Clindamycin decreased gene expression in the first 24 h, followed by moderate increases (2.5-fold) thereafter. Linezolid increased gene expression 11.4- to 200.4-fold but inhibited PVL production (0.6 ± 0.3 versus 5.9 ± 0.2 μg/ml, linezolid versus control at 72 h; P < 0.05). Similar effects on PVL production occurred with clindamycin and minocycline. SXT increased PVL production at 48 h (2.8-fold) and 72 h (4.9-fold) of treatment (P < 0.05), resulting in increased PVL cytotoxicity on PMNs. Linezolid, clindamycin, and minocycline were the most effective agents on decreasing the virulence potential in CA-MRSA, notably after 8 h of treatment. SXT had minimal effects on toxin gene regulation, but it increased production and cytotoxicity of PVL toxin in the model and may enhance virulence when it is used to treat severe infections.

Conserving antibiotics for the future: new ways to use old and new drugs from a pharmacokinetic and pharmacodynamic perspective

There is a growing need to optimize the use of old and new antibiotics to treat serious as well as less serious infections. The topic of how to use pharmacokinetic and pharmacodynamic (PK/PD) knowledge to conserve antibiotics for the future was elaborated on in a workshop of the conference (The conference "The Global Need for Effective Antibiotics - moving towards concerted action", ReAct, Uppsala, Sweden, 2010). The optimization of dosing regimens is accomplished by choosing the dose and schedule that results in the antimicrobial exposure that will achieve the microbiological and clinical outcome desired while simultaneously suppressing emergence of resistance. PK/PD of antimicrobial agents describe how the therapeutic drug effect is dependent on the potency of a drug against a microorganism and the exposure (the concentration of antimicrobial available for effect over time). The description and modeling of these relationships quantitatively then allow for a rational approach to dose optimization and several strategies to that purpose are described. These strategies include not only the dosing regimen itself but also the duration of therapy, preventing collateral damage through inappropriate use and the application of PK/PD in drug development. Furthermore, PK/PD relationships of older antibiotics need to be urgently established. The need for global harmonization of breakpoints is also suggested and would add efficacy to antibiotic therapy. For each of the strategies, a number of priority actions are provided.

Chemotherapy, within-host ecology and the fitness of drug-resistant malaria parasites

A major determinant of the rate at which drug-resistant malaria parasites spread through a population is the ecology of resistant and sensitive parasites sharing the same host. Drug treatment can significantly alter this ecology by removing the drug-sensitive parasites, leading to competitive release of resistant parasites. Here, we test the hypothesis that the spread of resistance can be slowed by reducing drug treatment and hence restricting competitive release. Using the rodent malaria model Plasmodium chabaudi, we found that low-dose chemotherapy did reduce competitive release. A higher drug dose regimen exerted stronger positive selection on resistant parasites for no detectable clinical gain. We estimated instantaneous selection coefficients throughout the course of replicate infections to analyze the temporal pattern of the strength and direction of within-host selection. The strength of selection on resistance varied through the course of infections, even in untreated infections, but increased immediately following drug treatment, particularly in the high-dose groups. Resistance remained under positive selection for much longer than expected from the half life of the drug. Although there are many differences between mice and people, our data do raise the question whether the aggressive treatment regimens aimed at complete parasite clearance are the best resistance-management strategies for humans.

In vitro synergism of ciprofloxacin and cefotaxime against nalidixic acid-resistant Salmonella enterica serotypes Paratyphi A and Paratyphi B

Paratyphoid fever is considered an emerging systemic intracellular infection caused by Salmonella enterica serotypes Paratyphi A, B, and C. We performed in vitro time-kill studies on three clinical isolates of nalidixic acid-resistant Salmonella serotype Paratyphi (NARSP) with different concentrations of ciprofloxacin and cefotaxime to identify combinations of antibiotics with synergistic activity against paratyphoid fever. Furthermore, we identify the frequency of mutations to ciprofloxacin, cefotaxime, and rifampin resistance and also sequenced the gyrA, gyrB, parC, and parE genes to identify the cause of resistance in NARSP. When the activity of ciprofloxacin at 0.75x MIC (0.012 to 0.38 microg/ml) with cefotaxime at the MIC (0.125 to 0.25 microg/ml) against all three NARSP isolates was investigated, synergy was observed at 24 h, and the bacterial counts were reduced by >3 log(10) CFU/ml. This synergy was elongated for up to 72 h in two out of three isolates. When ciprofloxacin at 0.75x MIC (0.012 to 0.38 microg/ml) was combined with cefotaxime at 2x MIC (0.25 to 0.50 microg/ml), synergy was prolonged for up to 72 h in all three isolates. Both Salmonella serotype Paratyphi A isolates carried single mutations in codon 83 of the gyrA gene and codon 84 of the parC gene that were responsible for their reduced susceptibility to ciprofloxacin, while no mutations were found in the gyrB or parE gene. The ciprofloxacin-plus-cefotaxime regimen was very effective in reducing the bacterial counts at 24 h for all three isolates, and this combination therapy may be helpful in reducing the chance of the emergence of fluoroquinolone-resistant mutants in patients with severe paratyphoid fever.

Impact of different carbapenems and regimens of administration on resistance emergence for three isogenic Pseudomonas aeruginosa strains with differing mechanisms of resistance

We compared drugs (imipenem and doripenem), doses (500 mg and 1 g), and infusion times (0.5 and 1.0 [imipenem], 1.0 and 4.0 h [doripenem]) in our hollow-fiber model, examining cell kill and resistance suppression for three isogenic strains of Pseudomonas aeruginosa PAO1. The experiments ran for 10 days. Serial samples were taken for total organism and resistant subpopulation counts. Drug concentrations were determined by high-pressure liquid chromatography-tandem mass spectrometry (LC/MS/MS). Free time above the MIC (time > MIC) was calculated using ADAPT II. Time to resistance emergence was examined with Cox modeling. Cell kill and resistance emergence differences were explained, in the main, by differences in potency (MIC) between doripenem and imipenem. Prolonged infusion increased free drug time > MIC and improved cell kill. For resistance suppression, the 1-g, 4-h infusion was able to completely suppress resistance for the full period of observation for the wild-type isolate. For the mutants, control was ultimately lost, but in all cases, this was the best regimen. Doripenem gave longer free time > MIC than imipenem and, therefore, better cell kill and resistance suppression. For the wild-type organism, the 1-g, 4-h infusion regimen is preferred. For organisms with resistance mutations, larger doses or addition of a second drug should be studied.

Antimicrobial drug resistance

This chapter provides an overview of our current understanding of the mechanisms associated with the development of antimicrobial drug resistance, international differences in definitions of resistance, ongoing efforts to track shifts in drug susceptibility, and factors that can influence the selection of therapeutic intervention. The latter presents a matrix of complex variables that includes the mechanism of drug action, the pharmacokinetics (PK) of the antimicrobial agent in the targeted patient population, the pharmacodynamics (PD) of the bacterial response to the antimicrobial agent, the PK/PD relationship that will influence dose selection, and the integrity of the host immune system. Finally, the differences between bacterial tolerance and bacterial resistance are considered, and the potential for non-traditional anti-infective therapies is discussed.

In vitro activity of ceftaroline against methicillin-resistant Staphylococcus aureus and heterogeneous vancomycin-intermediate S. aureus in a hollow fiber model

Ceftaroline is a broad-spectrum injectable cephalosporin exhibiting bactericidal activity against a variety of bacteria, including methicillin-resistant Staphylococcus aureus (MRSA). Using a two-compartment in vitro pharmacokinetic/pharmacodynamic (PK/PD) model, we evaluated the activity of ceftaroline at 600 mg every 8 h (q8h) and q12h in comparison with that of vancomycin at 1,000 mg q12h over a 72-h time period against six clinical MRSA isolates, including two heterogeneous vancomycin-intermediate S. aureus (hVISA) isolates. The MIC and minimum bactericidal concentration ranged between 0.125 to 2 and 0.5 to 2 microg/ml for ceftaroline and vancomycin, respectively. In the PK/PD model, ceftaroline was superior to vancomycin against all isolates (P < 0.05), except one to which it was equivalent. No difference in activity was observed between both q8 and q12h dosing regimens of ceftaroline. Bacterial regrowth was observed after 32 h for two isolates treated with ceftaroline. This regrowth was uncorrelated to resistance, instability of the drug, or tolerance. However, subpopulations with higher MICs to ceftaroline were found by population analysis for these two isolates. Finally, and in contrast to ceftaroline, MIC elevations up to 8 to 12 microg/ml were observed with vancomycin for the hVISA isolates. In conclusion, in addition to a lower potential to select resistant mutants, ceftaroline demonstrated activity equal to or greater than vancomycin against MRSA isolates. Although further in vitro and in vivo investigations are warranted, ceftaroline appears to be a promising alternative for the treatment of MRSA infections.

Pharmacokinetics and pharmacodynamics of antimicrobial drugs

BACKGROUND

Antimicrobial drugs exhibit different characteristics in their correlation between antimicrobial drug concentrations and effects on microorganisms. These correlations have been studied using different approaches including in vitro analyses with constant and fluctuating concentrations and in vivo analyses involving animals and humans. Mathematical analysis includes correlation of pharmacokinetic-pharmacodynamic (PK-PD) indices to an outcome parameter. Further insight can be gained by mechanism-based modelling of antimicrobial drug effects.

METHODS AND RESULTS

This review aims to provide an overview on the various approaches used to analyse antimicrobial pharmacodynamics, to discuss the limitations of these approaches, to indicate recent developments and to summarise the current knowledge on PK-PD target values as derived from human studies.

CONCLUSION

It is expected that PK-PD analysis of antimicrobial drug effects will lead to a more efficient and possibly also less toxic antimicrobial drug therapy.