In vitro pharmacodynamic models to determine the effect of antibacterial drugs

PK/PD models in antibacterial development

There is an urgent need for novel antibiotics to treat life-threatening infections caused by bacterial 'superbugs'. Validated in vitro pharmacokinetic/pharmacodynamic (PK/PD) and animal infection models have been employed to identify the most predictive PK/PD indices and serve as key tools in the antibiotic development process. The results obtained can be utilized for optimizing study designs in order to minimize the cost and duration of clinical trials. This review outlines the key in vitro PK/PD and animal infection models which have been extensively used in antibiotic discovery and development. These models have shown great potential in accelerating drug development programs and will continue to make significant contributions to antibiotic development.

Pharmacokinetic-pharmacodynamic modeling of antibacterial drugs

Pharmacokinetic-pharmacodynamic (PKPD) modeling and simulation has evolved as an important tool for rational drug development and drug use, where developed models characterize both the typical trends in the data and quantify the variability in relationships between dose, concentration, and desired effects and side effects. In parallel, rapid emergence of antibiotic-resistant bacteria imposes new challenges on modern health care. Models that can characterize bacterial growth, bacterial killing by antibiotics and immune system, and selection of resistance can provide valuable information on the interactions between antibiotics, bacteria, and host. Simulations from developed models allow for outcome predictions of untested scenarios, improved study designs, and optimized dosing regimens. Today, much quantitative information on antibiotic PKPD is thrown away by summarizing data into variables with limited possibilities for extrapolation to different dosing regimens and study populations. In vitro studies allow for flexible study designs and valuable information on time courses of antibiotic drug action. Such experiments have formed the basis for development of a variety of PKPD models that primarily differ in how antibiotic drug exposure induces amplification of resistant bacteria. The models have shown promise for efficacy predictions in patients, but few PKPD models describe time courses of antibiotic drug effects in animals and patients. We promote more extensive use of modeling and simulation to speed up development of new antibiotics and promising antibiotic drug combinations. This review summarizes the value of PKPD modeling and provides an overview of the characteristics of available PKPD models of antibiotics based on in vitro, animal, and patient data.

In vitro bactericidal activity of enrofloxacin against gyrA mutant and qnr-containing Escherichia coli isolates from animals

The objective of this work was to investigate the bactericidal activity of enrofloxacin against gyrA mutant and qnr-containing Escherichia coli isolates from animals. The minimum inhibitory concentrations (MICs) of gyrA mutant and qnr-containing E coli isolates ranged from 1 µg/ml to 32 µg/ml for enrofloxacin. Time-kill experiments were performed using selected E coli isolates. For the time-kill experiments, the colony counts were determined by plating each diluted sample onto plate count agar and an integrated pharmacokinetic/pharmacodynamics area measure (log ratio area) was applied to the colony-forming units (cfu) data. In general, enrofloxacin exhibited bactericidal activity against all the gyrA mutant E coli isolates at all concentrations greater than four times the MIC. However, the bactericidal activity of enrofloxacin for all the qnr-containing E coli isolates was less dependent on concentration. The results of the present study indicated that the genetic mechanism of resistance might account for the different bactericidal activities of enrofloxacin observed for the gyrA mutant and the qnr-containing E coli isolates. Therefore, in addition to MIC assays, genetic mechanism-based pharmacodynamic models should be used to provide accurate predictions of the effects of drugs on resistant bacteria.

Pharmacokinetics and pharmacodynamics of nemonoxacin against Streptococcus pneumoniae in an in vitro infection model

The aim of this paper was to investigate the pharmacokinetics (PK) and pharmacodynamics (PD) of nemonoxacin, a novel nonfluorinated quinolone, against Streptococcus pneumoniae in vitro. A modified infection model was used to simulate the pharmacokinetics of nemonoxacin following scaling of single oral doses and multiple oral dosing. Four S. pneumoniae strains with different penicillin sensitivities were selected, and the drug efficacy was quantified by the change in log colony counts within 24 h. A sigmoid maximum-effect (Emax) model was used to analyze the relationship between PK/PD parameters and drug effect. Analysis indicated that the killing pattern of nemonoxacin shows a dualism which is mainly concentration dependent when the MIC is low and that the better PK/PD index should be the area under the concentration-time curve for the free, unbound fraction of the drug divided by the MIC (fAUC0-24/MIC), which means that giving the total daily amount of drug as one dose is appropriate under those conditions. When the MIC is high, the time (T) dependency is important and the valid PK/PD index should be the cumulative percentage of a 24-h period in which the drug concentration exceeds the MIC under steady-state pharmacokinetic conditions (f%T>MIC), which means that to split the maximum daily dose into several separate doses will benefit the eradication of the bacteria. To obtain a 3-log10-unit decrease, the target values of fAUC0-24/MIC and f%T>MIC are 47.05 and 53.4%, respectively.

Effect of low-intensity focused ultrasound on the middle ear in a mouse model of acute otitis media

We hypothesized that low-intensity focused ultrasound (LIFU) increases vessel permeability and antibacterial drug activity in the mouse middle ear. We determined appropriate settings by applying LIFU to mouse ears with the external auditory canal filled with normal saline and performed histologic and immunohistologic examination. Acute otitis media was induced in mice with nontypable Haemophilus influenzae, and they were given ampicillin (50, 10, or 2 mg/kg) intraperitoneally once daily for 3 days with or without LIFU (1.0 W/cm(2), 20% duty cycle, 30 s). In the LIFU(+) groups receiving the 2- and 10-mg/kg doses, viable bacteria counts, number of inflammatory cells and IL-1β and TNF-α levels in middle ear effusion were significantly lower than in the LIFU(-) groups on the same doses. Severity of AOM also tended to be reduced more in the LIFU(+) groups than in the LIFU(-) groups. LIFU application with antibiotics may be effective for middle ear infection.

Evaluation of antimicrobial activity against Mycoplasma mycoides subsp. mycoides Small Colony using an in vitro dynamic dilution pharmacokinetic/pharmacodynamic model

The objectives of this study were to assess the activity of oxytetracycline (OTC), danofloxacin and tulathromycin against Mycoplasma mycoides subsp. mycoides Small Colony, the causative agent of contagious bovine pleuropneumonia, in an in vitro dynamic concentration model and to determine the concentration and/or time dependence of such activity. Time-kill assays that simulated elimination of antimicrobials from the body were performed. Initial antimicrobial concentrations corresponded to various multiples of the MIC and cultures were diluted in a stepwise fashion with either drug-free or drug-containing artificial medium to mimic administration by single-release bolus or infusion, respectively. Where appropriate, data were fitted to sigmoidal E(max) models. OTC produced no change in mycoplasma titre from the initial inoculum size, regardless of the concentration or means of drug exposure. Both danofloxacin and tulathromycin resulted in a decrease in mycoplasma titre but neither was bactericidal (99.9 % kill) over 12 h. A greater antimycoplasmal effect, defined as the change in log(10) (c.f.u. ml(-1)) over 12 h, was achieved when danofloxacin was administered as a single-release bolus, suggesting concentration-dependent activity, whereas the antimycoplasmal effect of tulathromycin was comparable following administration by single-release bolus or infusion, owing to its long half-life.

Pharmacodynamics of antimicrobials against Mycoplasma mycoides mycoides small colony, the causative agent of contagious bovine pleuropneumonia

BACKGROUND

Mycoplasma mycoides subspecies mycoides Small Colony (MmmSC) is the causative agent of Contagious Bovine Pleuropneumonia (CBPP), a disease of substantial economic importance in sub-Saharan Africa. Failure of vaccination to curtail spread of this disease has led to calls for evaluation of the role of antimicrobials in CBPP control. Three major classes of antimicrobial are effective against mycoplasmas, namely tetracyclines, fluoroquinolones and macrolides. Therefore, the objectives of this study were to determine the effector kinetics of oxytetracycline, danofloxacin and tulathromycin against two MmmSC field strains in artificial medium and adult bovine serum.

METHODS

Minimum inhibitory concentrations (MIC) were determined for oxytetracycline, danofloxacin and tulathromycin against MmmSC strains B237 and Tan8 using a macrodilution technique, and time-kill curves were constructed for various multiples of the MIC over a 24 hour period in artificial medium and serum. Data were fitted to sigmoid E(max) models to obtain 24 hour-area under curve/MIC ratios for mycoplasmastasis and, where appropriate, for mycoplasmacidal activity and virtual mycoplasmal elimination.

RESULTS

Minimum inhibitory concentrations against B237 were 20-fold higher, 2-fold higher and approximately 330-fold lower in serum than in artificial medium for oxytetracycline, danofloxacin and tulathromycin, respectively. Such differences were mirrored in experiments using Tan8. Oxytetracycline was mycoplasmastatic against both strains in both matrices. Danofloxacin elicited mycoplasmacidal activity against B237 and virtual elimination of Tan8; similar maximum antimycoplasmal effects were observed in artificial medium and serum. Tulathromycin effected virtual elimination of B237 but was mycoplasmastatic against Tan8 in artificial medium. However, this drug was mycoplasmastatic against both strains in the more physiologically relevant matrix of serum.

CONCLUSIONS

Oxytetracycline, danofloxacin and tulathromycin are all suitable candidates for further investigation as potential treatments for CBPP. This study also highlights the importance of testing drug activity in biological matrices as well as artificial media.

Combination antibiotic therapy for empiric and definitive treatment of gram-negative infections: insights from the Society of Infectious Diseases Pharmacists

The widespread emergence of antibiotic-resistant gram-negative organisms has compromised the utility of current treatment options for severe infections caused by these pathogens. The rate of gram-negative multidrug resistance is worsening, threatening the effectiveness of newer broad-spectrum antibiotic agents. Infections associated with multidrug-resistant Pseudomonas aeruginosa, Acinetobacter baumannii, and Enterobacteriaceae are having a substantial impact on hospital costs and mortality rates. The potential for these resistant gram-negative nosocomial pathogens must always be a primary consideration when selecting antibiotic therapy for critically ill patients. Empiric combination therapy directed at gram-negative pathogens is a logical approach for patients with suspected health care-associated infections, particularly those with risk factors for infections caused by multidrug-resistant pathogens. Although in vitro synergy tests have shown potential benefits of continued combination therapy, convincing clinical data that demonstrate a need for combination therapy once susceptibilities are known are lacking. Thus, deescalation to a single agent once susceptibilities are known is recommended for most patients and pathogens. Use of polymyxins, often in combination with other antimicrobials, may be necessary for salvage therapy.

Optimizing dosage to prevent emergence of resistance - lessons from in vitro models

The widespread emergence of resistance to antimicrobial agents has taken mammoth dimension and warrants immediate steps to minimize it. Pharmacokinetics/pharmacodynamics of antimicrobial agents, differences among bacterial species, and time-dependent changes in the bacterial population are important factors involved in the development of drug resistance. The key to minimizing resistance lies in understanding how these factors affect resistance emergence and incorporating them in dosing regimen design. In vitro models have proven to be a valuable tool to study these factors and their contribution in resistance emergence. This review summarizes the key factors implicated in resistance development and the lessons learnt from in vitro studies optimizing antimicrobial dosing to prevent resistance emergence.

Pharmacokinetic/pharmacodynamic (PK/PD) indices of antibiotics predicted by a semimechanistic PKPD model: a step toward model-based dose optimization

A pharmacokinetic-pharmacodynamic (PKPD) model that characterizes the full time course of in vitro time-kill curve experiments of antibacterial drugs was here evaluated in its capacity to predict the previously determined PK/PD indices. Six drugs (benzylpenicillin, cefuroxime, erythromycin, gentamicin, moxifloxacin, and vancomycin), representing a broad selection of mechanisms of action and PK and PD characteristics, were investigated. For each drug, a dose fractionation study was simulated, using a wide range of total daily doses given as intermittent doses (dosing intervals of 4, 8, 12, or 24 h) or as a constant drug exposure. The time course of the drug concentration (PK model) as well as the bacterial response to drug exposure (in vitro PKPD model) was predicted. Nonlinear least-squares regression analyses determined the PK/PD index (the maximal unbound drug concentration [fC(max)]/MIC, the area under the unbound drug concentration-time curve [fAUC]/MIC, or the percentage of a 24-h time period that the unbound drug concentration exceeds the MIC [fT(>MIC)]) that was most predictive of the effect. The in silico predictions based on the in vitro PKPD model identified the previously determined PK/PD indices, with fT(>MIC) being the best predictor of the effect for β-lactams and fAUC/MIC being the best predictor for the four remaining evaluated drugs. The selection and magnitude of the PK/PD index were, however, shown to be sensitive to differences in PK in subpopulations, uncertainty in MICs, and investigated dosing intervals. In comparison with the use of the PK/PD indices, a model-based approach, where the full time course of effect can be predicted, has a lower sensitivity to study design and allows for PK differences in subpopulations to be considered directly. This study supports the use of PKPD models built from in vitro time-kill curves in the development of optimal dosing regimens for antibacterial drugs.

In vitro pharmacokinetic/pharmacodynamic models in anti-infective drug development: focus on TB

For rapid anti-tuberculosis (TB) drug development in vitro pharmacokinetic/pharmacodynamic (PK/PD) models are useful in evaluating the direct interaction between the drug and the bacteria, thereby guiding the selection of candidate compounds and the optimization of their dosing regimens. Utilizing in vivo drug-clearance profiles from animal and/or human studies and simulating them in an in vitro PK/PD model allows the in-depth characterization of antibiotic activity of new and existing antibacterials by generating time–kill data. These data capture the dynamic interplay between mycobacterial growth and changing drug concentration as encountered during prolonged drug therapy. This review focuses on important PK/PD parameters relevant to anti-TB drug development, provides an overview of in vitro PK/PD models used to evaluate the efficacy of agents against mycobacteria and discusses the related mathematical modeling approaches of time–kill data. Overall, it provides an introduction to in vitro PK/PD models and their application as critical tools in evaluating anti-TB drugs.

PK-PD modeling of β-lactam antibiotics: in vitro or in vivo models?

A modified E(max)-pharmacokinetic-pharmacodynamic (PK-PD) model was previously proposed in literature for describing the antimicrobial activity of β-lactam antibiotics based on in vitro experiments. However, bacteria behave differently in vitro and in vivo. Thus, the aims of this study were to model the killing effect of piperacillin (PIP) against Escherichia coli on immunocompromised infected rats using this model and to compare the parameters obtained in vitro and in vivo for the same bacteria/drug combination. The PK-PD parameters determined in vitro and in vivo were as follows: generation rate constant of 1.30 ± 0.10 and 0.76 ± 0.20 h(-1), maximum killing effect of 3.11 ± 0.27 and 1.38 ± 0.20 h(-1) and concentration to produce 50% of the maximum effect of 5.44 ± 0.03 and 1.31 ± 0.27 μg ml(-1), respectively. The comparison between the in vitro and in vivo parameters was not straightforward and had to take into consideration the intrinsic differences of the models involved. So far, the main application of the PK-PD model evaluated is for the comparison of different antimicrobial agent's potency and efficacy, under equivalent conditions.

Predicting in vitro antibacterial efficacy across experimental designs with a semimechanistic pharmacokinetic-pharmacodynamic model

We have previously described a general semimechanistic pharmacokinetic-pharmacodynamic (PKPD) model that successfully characterized the time course of antibacterial effects seen in bacterial cultures when exposed to static concentrations of five antibacterial agents of different classes. In this PKPD model, the total bacterial population was divided into two subpopulations, one growing drug-susceptible population and one resting drug-insensitive population. The drug effect was included as an increase in the killing rate of the drug-susceptible bacteria with a maximum-effect (E(max)) model. The aim of the present study was to evaluate the ability of this PKPD model to describe and predict data from in vitro experiments with dynamic concentration-time profiles. Dynamic time-kill curve experiments were performed by using an in vitro kinetic system, where cultures of Streptococcus pyogenes were exposed to benzylpenicillin, cefuroxime, erythromycin, moxifloxacin, or vancomycin using different starting concentrations (2 and 16 times the MIC) and elimination conditions (human half-life, reduced half-life, and constant concentrations). The PKPD model was applied, and the observations for the static as well as dynamic experiments were compared to model predictions based on parameter estimation using (i) static data, (ii) dynamic data, and (iii) combined static and dynamic data. Differences in experimental settings between static and dynamic experiments did not affect the growth kinetics of the bacteria significantly. With parameter reestimation, the structure of our previously proposed PKPD model could well characterize the bacterial growth and killing kinetics when exposed to dynamic concentrations with different elimination rates of all five investigated antibiotics. Furthermore, the model with parameter estimates based on data from only the static time-kill curve experiments could predict the majority of the time-kill curves from the dynamic experiments reasonably well. Adding data from dynamic experiments in the estimation improved the model fit for cefuroxime and vancomycin, indicating some differences in sensitivity to experimental conditions among the antibiotics studied.