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

Exploring the Use of C-Reactive Protein to Estimate the Pharmacodynamics of Vancomycin

BACKGROUND

C-reactive protein (CRP) pharmacodynamic (PD) models have the potential to provide adjunctive methods for predicting the individual exposure response to antimicrobial therapy. We investigated CRP PD linked to a vancomycin pharmacokinetic (PK) model using routinely collected data from noncritical care adults in secondary care.

METHODS

Patients receiving intermittent intravenous vancomycin therapy in secondary care were identified. A 2-compartment vancomycin PK model was linked to a previously described PD model describing CRP response. PK and PD parameters were estimated using a Non-Parametric Adaptive Grid technique. Exposure-response relationships were explored with vancomycin area-under-the-concentration-time-curve (AUC) and EC50 (concentration of drug that causes a half maximal effect) using the index, AUC:EC50, fitted to CRP data using a sigmoidal Emax model.

RESULTS

Twenty-nine individuals were included. Median age was 62 (21-97) years. Fifteen (52%) patients were microbiology confirmed. PK and PD models were adequately fitted (r 0.83 and 0.82, respectively). There was a wide variation observed in individual Bayesian posterior EC50 estimates (6.95-48.55 mg/L), with mean (SD) AUC:EC50 of 31.46 (29.22). AUC:EC50 was fitted to terminal CRP with AUC:EC50 >19 associated with lower CRP value at 96-120 hours of therapy (100 mg/L versus 44 mg/L; P < 0.01).

CONCLUSIONS

The use of AUC:EC50 has the potential to provide in vivo organism and host response data as an adjunct for in vitro minimum inhibitory concentration data, which is currently used as the gold standard PD index for vancomycin therapy. This index can be estimated using routinely collected clinical data. Future work must investigate the role of AUC:EC50 in a prospective cohort and explore linkage with direct patient outcomes.

Pharmacokinetics of Penicillin G in Preterm and Term Neonates

Group B streptococci are common causative agents of early-onset neonatal sepsis (EOS). Pharmacokinetic (PK) data for penicillin G have been described for extremely preterm neonates but have been poorly described for late-preterm and term neonates. Thus, evidence-based dosing recommendations are lacking. We describe the PK of penicillin G in neonates with a gestational age (GA) of ≥32 weeks and a postnatal age of <72 h. Penicillin G was administered intravenously at a dose of 25,000 or 50,000 IU/kg of body weight every 12 h (q12h). At steady state, PK blood samples were collected prior to and at 5 min, 1 h, 3 h, 8 h, and 12 h after injection. Noncompartmental PK analysis was performed with WinNonlin software. With those data in combination with data from neonates with a GA of ≤28 weeks, we developed a population PK model using NONMEM software and performed probability of target attainment (PTA) simulations. In total, 16 neonates with a GA of ≥32 weeks were included in noncompartmental analysis. The median volume of distribution (V) was 0.50 liters/kg (interquartile range, 0.42 to 0.57 liters/kg), the median clearance (CL) was 0.21 liters/h (interquartile range, 0.16 to 0.29 liters/kg), and the median half-life was 3.6 h (interquartile range, 3.2 to 4.3 h). In the population PK analysis that included 35 neonates, a two-compartment model best described the data. The final parameter estimates were 10.3 liters/70 kg and 29.8 liters/70 kg for V of the central and peripheral compartments, respectively, and 13.2 liters/h/70 kg for CL. Considering the fraction of unbound penicillin G to be 40%, the PTA of an unbound drug concentration that exceeds the MIC for 40% of the dosing interval was >90% for MICs of ≤2 mg/liter with doses of 25,000 IU/kg q12h. In neonates, regardless of GA, the PK parameters of penicillin G were similar. The dose of 25,000 IU/kg q12h is suggested for treatment of group B streptococcal EOS diagnosed within the first 72 h of life. (This study was registered with the EU Clinical Trials Register under EudraCT number 2012-002836-97.).

Simulation-Based Exploration of Quorum Sensing Triggered Resistance of Biofilms to Antibiotics

We present a mathematical model of biofilm response to antibiotics, controlled by a quorum sensing system that confers increased resistance. The model is a highly nonlinear system of partial differential equations that we investigate in computer simulations. Our results suggest that an adaptive, quorum sensing-controlled, mechanism to switch between modes of fast growth with little protection and protective modes of slow growth may confer benefits to biofilm populations. It enhances the formation of micro-niches in the inner regions of the biofilm in which bacteria are not easily reached by antibiotics. Whereas quorum sensing inhibitors can delay the onset of increased resistance, their advantage is lost after up-regulation. This emphasizes the importance of timing for treatment of biofilms with antibiotics.

Amikacin Pharmacokinetic-Pharmacodynamic Analysis in Pediatric Cancer Patients

We performed pharmacokinetic-pharmacodynamic (PK-PD) and simulation analyses to evaluate a standard amikacin dose of 15 mg/kg once daily in children with cancer and to determine an optimal dosing strategy. A population pharmacokinetic model was developed from clinical data collected in 34 pediatric patients and used in a simulation study to predict the population probability of various dosing regimens to achieve accepted safety (steady-state unbound trough plasma concentration [fCmin] of <10 mg/liter)- and efficacy (free, unbound plasma concentration-to-MIC ratio [fCmax/MIC] of ≥8)-linked targets. In addition, an adaptive resistance PD (ARPD) model of Pseudomonas aeruginosa was built based on literature time-kill curve data and linked to the PK model to perform PK-ARPD simulations and compare results with those of the probability approach. Using the probability approach, an amikacin dose of 60 mg/kg administered once daily is expected to achieve the target fCmax/MIC in 80% of pediatric patients weighing 8 to 70 kg with a 97.5% probability, and almost all patients were predicted to have fCmin of <10 mg/liter. However, PK-ARPD simulation predicted that 60 mg/kg/day is unlikely to suppress bacterial resistance with repeated dosing. Furthermore, PK-ARPD simulation suggested that amikacin at 90 mg/kg, given in two divided doses (45 mg/kg twice a day), is expected to hit safety and efficacy targets and is associated with a lower rate of bacterial resistance. The disagreement between the two methods is due to the inability of the probability approach to predict development of drug resistance with repeated dosing. This originates from the use of PK-PD indices based on the MIC that neglects measurement errors, ignores the time course dynamic nature of bacterial growth and killing, and incorrectly assumes the MIC to be constant during treatment.

Quantitative Analysis of Gentamicin Exposure in Neonates and Infants Calls into Question Its Current Dosing Recommendations

Optimal dosing of gentamicin in neonates is still a matter of debate despite its common use. We identified gentamicin dosing regimens from eight international guidelines and seven Swiss neonatal intensive care units. The dose per administration, the dosing interval, the total daily dose, and the demographic characteristics between guidelines were compared. There was considerable variability with respect to dose (4 to 6 mg/kg), dosing interval (24 h to 48 h), total daily dose (2.5 to 6 mg/kg/day), and patient demographic characteristics that were used to calculate individualized dosing regimens. A model-based simulation study in 1071 neonates was performed to determine the achievement of efficacious peak gentamicin concentrations according to predefined MICs (Cmax/MIC ≥ 10) and safe trough concentrations (Cmin ≤ 2 mg/liter) with recommended dosing regimens. MIC targets of 0.5 and 1 mg/liter were used. Dosing optimization was performed giving priority to the first day of treatment and with the goal of simplifying dosing. Current gentamicin neonatal guidelines allow to achieve effective peak concentrations for MICs ≤ 0.5 mg/liter but not higher. Model-based simulations indicate that to attain peak gentamicin concentrations of ≥10 mg/liter, a dose of 7.5 mg/kg should be administered using an extended dosing interval regimen. Trough concentrations of ≤2 mg/liter can be maintained with a dosing interval of 36 to 48 h in neonates according to gestational and postnatal age. For treatment beyond 3 days, therapeutic drug monitoring is advised to maintain adequate serum concentrations.

Differential Activity of the Combination of Vancomycin and Amikacin on Planktonic vs. Biofilm-Growing Staphylococcus aureus Bacteria in a Hollow Fiber Infection Model

Combining currently available antibiotics to optimize their use is a promising strategy to reduce treatment failures against biofilm-associated infections. Nevertheless, most assays of such combinations have been performed in vitro on planktonic bacteria exposed to constant concentrations of antibiotics over only 24 h and the synergistic effects obtained under these conditions do not necessarily predict the behavior of chronic clinical infections associated with biofilms. To improve the predictivity of in vitro combination assays for bacterial biofilms, we first adapted a previously described Hollow-fiber (HF) infection model by allowing a Staphylococcus aureus biofilm to form before drug exposure. We then mimicked different concentration profiles of amikacin and vancomycin, similar to the free plasma concentration profiles that would be observed in patients treated daily over 5 days. We assessed the ability of the two drugs, alone or in combination, to reduce planktonic and biofilm-embedded bacterial populations, and to prevent the selection of resistance within these populations. Although neither amikacin nor vancomycin exhibited any bactericidal activity on S. aureus in monotherapy, the combination had a synergistic effect and significantly reduced the planktonic bacterial population by -3.0 to -6.0 log₁₀ CFU/mL. In parallel, no obvious advantage of the combination, as compared to amikacin alone, was demonstrated on biofilm-embedded bacteria for which the addition of vancomycin to amikacin only conferred a further maximum reduction of 0.3 log₁₀ CFU/mL. No resistance to vancomycin was ever found whereas a few bacteria less-susceptible to amikacin were systematically detected before treatment. These resistant bacteria, which were rapidly amplified by exposure to amikacin alone, could be maintained at a low level in the biofilm population and even suppressed in the planktonic population by adding vancomycin. In conclusion, by adapting the HF model, we were able to demonstrate the different bactericidal activities of the vancomycin and amikacin combination on planktonic and biofilm-embedded bacterial populations, suggesting that, for biofilm-associated infections, the efficacy of this combination would not be much greater than with amikacin monotherapy. However, adding vancomycin could reduce possible resistance to amikacin and provide a relevant strategy to prevent the selection of antibiotic-resistant bacteria during treatments.

Mechanism-Based Pharmacokinetic/Pharmacodynamic Modeling of Aerosolized Colistin in a Mouse Lung Infection Model

Optimized dosage regimens of aerosolized colistin (as colistin methanesulfonate [CMS]) are urgently required to maximize bacterial killing against multidrug-resistant Gram-negative bacteria while minimizing toxicity. This study aimed to develop a mechanism-based pharmacokinetic (PK)/pharmacodynamic (PD) model (MBM) for aerosolized colistin based upon PK/PD data in neutropenic infected mice and to perform a deterministic simulation with the PK of aerosolized colistin (as CMS) in critically ill patients. In vivo time-kill experiments were carried out with three different strains of Pseudomonas aeruginosa An MBM was developed in S-ADAPT and evaluated by assessing its ability to predict the PK/PD index associated with efficacy in mice. A deterministic simulation with human PK data was undertaken to predict the efficacy of current dosage regimens of aerosolized colistin in critically ill patients. In the final MBM, the total bacterial population for each isolate consisted of colistin-susceptible and -resistant subpopulations. The antimicrobial efficacy of aerosolized colistin was best described by a sigmoidal E_max model whereby colistin enhanced the rate of bacterial death. Deterministic simulation with human PK data predicted that an inhalational dosage regimen of 60 mg colistin base activity (CBA) every 12 h is needed to achieve a ≥2-log₁₀ bacterial reduction (as the number of CFU per lung) in critically ill patients at 24 h after commencement of inhaled therapy. In conclusion, the developed MBM is a useful tool for optimizing inhalational dosage regimens of colistin. Clinical studies are warranted to validate and refine our MBM for aerosolized colistin.

Modeling the Emergence of Antibiotic Resistance in the Environment: an Analytical Solution for the Minimum Selection Concentration

Environmental antibiotic risk management requires an understanding of how subinhibitory antibiotic concentrations contribute to the spread of resistance. We develop a simple model of competition between sensitive and resistant bacterial strains to predict the minimum selection concentration (MSC), the lowest level of antibiotic at which resistant bacteria are selected. We present an analytical solution for the MSC based on the routinely measured MIC, the selection coefficient (sc) that expresses fitness differences between strains, the intrinsic net growth rate, and the shape of the bacterial growth dose-response curve with antibiotic or metal exposure (the Hill coefficient [κ]). We calibrated the model by optimizing the Hill coefficient to fit previously reported experimental growth rate difference data. The model fit varied among nine compound-taxon combinations examined but predicted the experimentally observed MSC/MIC ratio well (R² ≥ 0.95). The shape of the antibiotic response curve varied among compounds (0.7 ≤ κ ≤ 10.5), with the steepest curve being found for the aminoglycosides streptomycin and kanamycin. The model was sensitive to this antibiotic response curve shape and to the sc, indicating the importance of fitness differences between strains for determining the MSC. The MSC can be >1 order of magnitude lower than the MIC, typically by the factor sc^κ This study provides an initial quantitative depiction and a framework for a research agenda to examine the growing evidence of selection for resistant bacterial communities at low environmental antibiotic concentrations.

Concentrations of Cefuroxime in Brain Tissue of Neurointensive Care Patients

Effective concentrations of antibiotics in brain tissue are essential for antimicrobial therapy of brain infections. However, data concerning cerebral penetration properties of antibiotics for treatment or prophylaxis of central nervous system infections are rare. Six patients suffering subarachnoid hemorrhage and requiring cerebral microdialysis for neurochemical monitoring were included in this study. Free interstitial concentrations of cefuroxime after intravenous application of 1,500 mg were measured by microdialysis in brain tissue, as well as in plasma at steady-state (n = 6) or after single-dose administration (n = 1). At steady state, free area under the concentration-time curve from 0 to 24 h (AUC_0-24) values of 389.0 ± 210.3 mg/liter·h and 131.4 ± 72.8 mg/liter·h were achieved for plasma and brain, respectively, resulting in a brain tissue penetration ratio (AUC_0-24 brain/AUC_{0-24 free plasma}) of 0.33 ± 0.1. Plasma and brain tissue concentrations at individual time points correlated well (R = 0.59, P = 0.001). At steady-state time over MIC (t>MIC) values of >40% of dosing interval were achieved up to an MIC of 16 mg/liter for plasma and 4 mg/liter for brain tissue. Although MIC₉₀ values could not be achieved in brain tissue for relevant bacteria, current dosing strategies of cefuroxime might be sufficient to treat pathogens with MIC values up to 4 mg/liter. The activity of cefuroxime in brain tissue might be overestimated when relying exclusively on plasma levels. Although currently insufficient data after single dose administration exist, lower brain-plasma ratios observed after the first dose might warrant a loading dose for treatment and perioperative prophylaxis.

Protein-inspired antibiotics active against vancomycin- and daptomycin-resistant bacteria

The public health threat posed by a looming ‘post-antibiotic’ era necessitates new approaches to antibiotic discovery. Drug development has typically avoided exploitation of membrane-binding properties, in contrast to nature’s control of biological pathways via modulation of membrane-associated proteins and membrane lipid composition. Here, we describe the rejuvenation of the glycopeptide antibiotic vancomycin via selective targeting of bacterial membranes. Peptide libraries based on positively charged electrostatic effector sequences are ligated to N-terminal lipophilic membrane-insertive elements and then conjugated to vancomycin. These modified lipoglycopeptides, the ‘vancapticins’, possess enhanced membrane affinity and activity against methicillin-resistant Staphylococcus aureus (MRSA) and other Gram-positive bacteria, and retain activity against glycopeptide-resistant strains. Optimised antibiotics show in vivo efficacy in multiple models of bacterial infection. This membrane-targeting strategy has potential to ‘revitalise’ antibiotics that have lost effectiveness against recalcitrant bacteria, or enhance the activity of other intravenous-administered drugs that target membrane-associated receptors.

The antibiotic vancomycin inhibits bacterial cell wall synthesis by binding to a membrane-associated precursor. Here, Blaskovich et al. synthesize vancomycin derivatives containing lipophilic peptide moieties that enhance membrane affinity and in vivo activities against glycopeptide-resistant strains.

Semi-mechanistic pharmacokinetic-pharmacodynamic modelling of antibiotic drug combinations

BACKGROUND

Deriving suitable dosing regimens for antibiotic combination therapy poses several challenges as the drug interaction can be highly complex, the traditional pharmacokinetic-pharmacodynamic (PKPD) index methodology cannot be applied straightforwardly, and exploring all possible dose combinations is unfeasible. Therefore, semi-mechanistic PKPD models developed based on in vitro single and combination experiments can be valuable to suggest suitable combination dosing regimens.

AIMS

To outline how the interaction between two antibiotics has been characterized in semi-mechanistic PKPD models. We also explain how such models can be applied to support dosing regimens and design future studies.

SOURCES

PubMed search for published semi-mechanistic PKPD models of antibiotic drug combinations.

CONTENT

Thirteen publications were identified where ten had applied subpopulation synergy to characterize the combined effect, i.e. independent killing rates for each drug and bacterial subpopulation. We report the various types of interaction functions that have been used to describe the combined drug effects and that characterized potential deviations from additivity under the PKPD model. Simulations from the models had commonly been performed to compare single versus combined dosing regimens and/or to propose improved dosing regimens.

IMPLICATIONS

Semi-mechanistic PKPD models allow for integration of knowledge on the interaction between antibiotics for various PK and PD profiles, and can account for associated variability within the population as well as parameter uncertainty. Decisions on suitable combination regimens can thereby be facilitated. We find the application of semi-mechanistic PKPD models to be essential for efficient development of antibiotic combination regimens that optimize bacterial killing and/or suppress resistance development.

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling as tools to personalize gentamicin therapy

Population pharmacokinetic modelling, Monte Carlo simulation and semi-mechanistic pharmacodynamic modelling are all tools that can be applied to personalize gentamicin therapy. This review summarizes and evaluates literature knowledge on the population pharmacokinetics and pharmacodynamics of gentamicin and identifies areas where further research is required to successfully individualize gentamicin therapy using modelling and simulation techniques. Thirty-five studies have developed a population pharmacokinetic model of gentamicin and 15 studies have made dosing recommendations based on Monte Carlo simulation. Variability in gentamicin clearance was most commonly related to renal function in adults and body weight and age in paediatrics. Nine studies have related aminoglycoside exposure indices to clinical outcomes. Most commonly, efficacy has been linked to a Cmax/MIC ≥7-10 and a AUC24/MIC ≥70-100. No study to date has shown a relationship between predicted achievement of exposure targets and actual clinical success. Five studies have developed a semi-mechanistic pharmacokinetic/pharmacodynamic model to predict bacteria killing and regrowth following gentamicin exposure and one study has developed a deterministic model of aminoglycoside nephrotoxicity. More complex semi-mechanistic models are required that consider the immune response, use of multiple antibiotics, the severity of illness, and both efficacy and toxicity. As our understanding grows, dosing of gentamicin based on sound pharmacokinetic/pharmacodynamic principles should be applied more commonly in clinical practice.

Biofilm formation and antibiotic susceptibility in dispersed cells versus planktonic cells from clinical, industry and environmental origins

We examined the cell-surface physicochemical properties, the biofilm formation capability and the antibiotic susceptibility in dispersed cells (from an artificial biofilm of alginate beads) and compared with their planktonic (free-swimming) counterparts. The strains used were from different origins, such as clinical (Acinetobacter baumannii AB4), cosmetic industry (Klebsiella oxytoca EU213, Pseudomonas aeruginosa EU190), and environmental (Halomonas venusta MAT28). In general, dispersed cells adhered better to surfaces (measured as the "biofilm index") and had a greater hydrophobicity [measured as the microbial affinity to solvents (MATS)] than planktonic cells. The susceptibility to two antibiotics (ciprofloxacin and tetracycline) of dispersed cells was higher compared with that of their planktonic counterparts (tested by the "bactericidal index"). Dispersed and planktonic cells exhibited differences in cell permeability, especially in efflux pump activity, which could be related to the differences observed in susceptibility to antibiotics. At 1 h of biofilm formation in microtiter plates, dispersed cells treated with therapeutic concentration of ciprofloxacin yielded a lower biofilm index than the control dispersed cells without ciprofloxacin. With respect to the planktonic cells, the biofilm index was similar with and without the ciprofloxacin treatment. In both cases there were a reduction of the number of bacteria measured as viable count of the supernatant. The lower biofilm formation in dispersed cells with ciprofloxacin treatment may be due to a significant increase of biofilm disruption with respect to the biofilm from planktonic cells. From a clinical point of view, biofilms formed on medical devices such as catheters, cells that can be related to an infection were the dispersed cells. Our results showed that early treatment with ciprofloxacin of dispersed cells could diminishe bacterial dispersion and facilitate the partial elimination of the new biofilm formed.

Translational Pharmacometric Evaluation of Typical Antibiotic Broad-Spectrum Combination Therapies Against Staphylococcus Aureus Exploiting In Vitro Information

Broad‐spectrum antibiotic combination therapy is frequently applied due to increasing resistance development of infective pathogens. The objective of the present study was to evaluate two common empiric broad‐spectrum combination therapies consisting of either linezolid (LZD) or vancomycin (VAN) combined with meropenem (MER) against Staphylococcus aureus (S. aureus) as the most frequent causative pathogen of severe infections. A semimechanistic pharmacokinetic‐pharmacodynamic (PK‐PD) model mimicking a simplified bacterial life‐cycle of S. aureus was developed upon time‐kill curve data to describe the effects of LZD, VAN, and MER alone and in dual combinations. The PK‐PD model was successfully (i) evaluated with external data from two clinical S. aureus isolates and further drug combinations and (ii) challenged to predict common clinical PK‐PD indices and breakpoints. Finally, clinical trial simulations were performed that revealed that the combination of VAN‐MER might be favorable over LZD‐MER due to an unfavorable antagonistic interaction between LZD and MER.

Dosage Optimization of Nemolizumab Using Population Pharmacokinetic and Pharmacokinetic-Pharmacodynamic Modeling and Simulation

Nemolizumab is a humanized anti-interleukin-31 receptor A monoclonal antibody for treating atopic dermatitis, and it especially improves pruritus. The objective of the simulation study was to optimize the dose regimen using a flat dose. The serum nemolizumab concentration and pruritus visual analog scale as an efficacy end point were modeled using the population analysis approach in 299 patients with atopic dermatitis who received placebo or doses between 0.1 and 3 mg/kg as a single dose once every 4 weeks or 2 mg/kg once every 8 weeks. A 1-compartment model with first-order absorption was employed as the pharmacokinetic model. An indirect turnover model with an inhibition component was employed as the main part of the pharmacokinetic-pharmacodynamic model. The models well described the observations. Therefore, simulations with several dose regimens were performed to optimize the dose regimen including a flat dose. The simulated area under the concentration-time curve at a steady state around 75 mg in the every-4-week regimen corresponds to that associated with the dose range of 0.5 to 2 mg/kg in the 4-week regimen. The simulated pruritus visual analog scale also showed a similar tendency. These simulation results support dose optimization during the clinical development program of nemolizumab.

Necessity of Bumped Kinase Inhibitor Gastrointestinal Exposure in Treating Cryptosporidium Infection

There is a substantial need for novel therapeutics to combat the widespread impact caused by Crytosporidium infection. However, there is a lack of knowledge as to which drug pharmacokinetic (PK) characteristics are key to generate an in vivo response, specifically whether systemic drug exposure is crucial for in vivo efficacy. To identify which PK properties are correlated with in vivo efficacy, we generated physiologically based PK models to simulate systemic and gastrointestinal drug concentrations for a series of bumped kinase inhibitors (BKIs) that have nearly identical in vitro potency against Cryptosporidium but display divergent PK properties. When BKI concentrations were used to predict in vivo efficacy with a neonatal model of Cryptosporidium infection, these concentrations in the large intestine were the sole predictors of the observed in vivo efficacy. The significance of large intestinal BKI exposure for predicting in vivo efficacy was further supported with an adult mouse model of Cryptosporidium infection. This study suggests that drug exposure in the large intestine is essential for generating a superior in vivo response, and that physiologically based PK models can assist in the prioritization of leading preclinical drug candidates for in vivo testing.

Prediction of marbofloxacin dosage for the pig pneumonia pathogens Actinobacillus pleuropneumoniae and Pasteurella multocida by pharmacokinetic/pharmacodynamic modelling

Background

Bacterial pneumonia in pigs occurs widely and requires antimicrobial therapy. It is commonly caused by the pathogens Actinobacillus pleuropneumoniae and Pasteurella multocida. Marbofloxacin is an antimicrobial drug of the fluoroquinolone class, licensed for use against these organisms in the pig. In recent years there have been major developments in dosage schedule design, based on integration and modelling of pharmacokinetic (PK) and pharmacodynamic (PD) data, with the objective of optimising efficacy and minimising the emergence of resistance. From in vitro time-kill curves in pig serum, PK/PD breakpoint Area under the curve (AUC) _24h /minimum inhibitory concentration (MIC) values were determined and used in conjunction with published PK, serum protein binding data and MIC distributions to predict dosages based on Monte Carlo simulation (MCS).

Results

For three levels of inhibition of growth, bacteriostasis and 3 and 4log₁₀ reductions in bacterial count, mean AUC_24h/MIC values were 20.9, 45.2 and 71.7 h, respectively, for P. multocida and 32.4, 48.7 and 55.5 h for A. pleuropneumoniae. Based on these breakpoint values, doses for each pathogen were predicted for several clinical scenarios: (1) bacteriostatic and bactericidal levels of kill; (2) 50 and 90% target attainment rates (TAR); and (3) single dosing and daily dosing at steady state. MCS for 90% TAR predicted single doses to achieve bacteriostatic and bactericidal actions over 48 h of 0.44 and 0.95 mg/kg (P. multocida) and 0.28 and 0.66 mg/kg (A. pleuropneumoniae). For daily doses at steady state, and 90% TAR bacteriostatic and bactericidal actions, dosages of 0.28 and 0.59 mg/kg (P. multocida) and 0.22 and 0.39 mg/kg (A. pleuropneumoniae) were required for pigs aged 12 weeks. Doses were also predicted for pigs aged 16 and 27 weeks.

Conclusions

PK/PD modelling with MCS approaches to dose determination demonstrates the possibility of tailoring clinical dose rates to a range of bacterial kill end-points.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-017-1128-y) contains supplementary material, which is available to authorized users.

Impact of growth matrix on pharmacodynamics of antimicrobial drugs for pig pneumonia pathogens

Background

The most widely used measure of potency of antimicrobial drugs is Minimum Inhibitory Concentration (MIC). MIC is usually determined under standardised conditions in broths formulated to optimise bacterial growth on a species-by-species basis. This ensures comparability of data between laboratories. However, differences in values of MIC may arise between broths of differing chemical composition and for some drug classes major differences occur between broths and biological fluids such as serum and inflammatory exudate. Such differences must be taken into account, when breakpoint PK/PD indices are derived and used to predict dosages for clinical use. There is therefore interest in comparing MIC values in several broths and, in particular, in comparing broth values with those generated in serum. For the pig pneumonia pathogens, Actinobacillus pleuropneumoniae and Pasteurella multocida, MICs were determined for three drugs, florfenicol, oxytetracycline and marbofloxacin, in five broths [Mueller Hinton Broth (MHB), cation-adjusted Mueller Hinton Broth (CAMHB), Columbia Broth supplemented with NAD (CB), Brain Heart Infusion Broth (BHI) and Tryptic Soy Broth (TSB)] and in pig serum.

Results

For each drug, similar MIC values were obtained in all broths, with one exception, marbofloxacin having similar MICs for three broths and 4–5-fold higher MICs for two broths. In contrast, for both organisms, quantitative differences between broth and pig serum MICs were obtained after correction of MICs for drug binding to serum protein (fu serum MIC). Potency was greater (fu serum MIC lower) in serum than in broths for marbofloxacin and florfenicol for both organisms. For oxytetracycline fu serum:broth MIC ratios were 6.30:1 (P. multocida) and 0.35:1 (A. pleuropneumoniae), so that potency of this drug was reduced for the former species and increased for the latter species. The chemical composition of pig serum and broths was compared; major matrix differences in 14 constituents did not account for MIC differences. Bacterial growth rates were compared in broths and pig serum in the absence of drugs; it was concluded that broth/serum MIC differences might be due to differing growth rates in some but not all instances.

Conclusions

For all organisms and all drugs investigated in this study, it is suggested that broth MICs should be adjusted by an appropriate scaling factor when used to determine pharmacokinetic/pharmacodynamic breakpoints for dosage prediction.

Pharmacokinetic/pharmacodynamic integration and modelling of florfenicol for the pig pneumonia pathogens Actinobacillus pleuropneumoniae and Pasteurella multocida

Pharmacokinetic-pharmacodynamic (PK/PD) integration and modelling were used to predict dosage schedules for florfenicol for two pig pneumonia pathogens, Actinobacillus pleuropneumoniae and Pasteurella multocida. Pharmacokinetic data were pooled for two bioequivalent products, pioneer and generic formulations, administered intramuscularly to pigs at a dose rate of 15 mg/kg. Antibacterial potency was determined in vitro as minimum inhibitory concentration (MIC) and Mutant Prevention Concentration in broth and pig serum, for six isolates of each organism. For both organisms and for both serum and broth MICs, average concentration:MIC ratios over 48 h were similar and exceeded 2.5:1 and times greater than MIC exceeded 35 h. From in vitro time-kill curves, PK/PD modelling established serum breakpoint values for the index AUC_24h/MIC for three levels of inhibition of growth, bacteriostasis and 3 and 4log₁₀ reductions in bacterial count; means were 25.7, 40.2 and 47.0 h, respectively, for P. multocida and 24.6, 43.8 and 58.6 h for A. pleuropneumoniae. Using these PK and PD data, together with literature MIC distributions, doses for each pathogen were predicted for: (1) bacteriostatic and bactericidal levels of kill; (2) for 50 and 90% target attainment rates (TAR); and (3) for single dosing and daily dosing at steady state. Monte Carlo simulations for 90% TAR predicted single doses to achieve bacteriostatic and bactericidal actions over 48 h of 14.4 and 22.2 mg/kg (P. multocida) and 44.7 and 86.6 mg/kg (A. pleuropneumoniae). For daily doses at steady state, and 90% TAR bacteriostatic and bactericidal actions, dosages of 6.2 and 9.6 mg/kg (P. multocida) and 18.2 and 35.2 mg/kg (A. pleuropneumoniae) were required. PK/PD integration and modelling approaches to dose determination indicate the possibility of tailoring dose to a range of end-points.

Pharmacokinetic/pharmacodynamic integration and modelling of oxytetracycline for the porcine pneumonia pathogens Actinobacillus pleuropneumoniae and Pasteurella multocida

Pharmacokinetic–pharmacodynamic (PK/PD) integration and modelling were used to predict dosage schedules of oxytetracycline for two pig pneumonia pathogens, Actinobacillus pleuropneumoniae and Pasteurella multocida. Minimum inhibitory concentration (MIC) and mutant prevention concentration (MPC) were determined in broth and porcine serum. PK/PD integration established ratios of average concentration over 48 h (C_av0–48 h)/MIC of 5.87 and 0.27 μg/mL (P. multocida) and 0.70 and 0.85 μg/mL (A. pleuropneumoniae) for broth and serum MICs, respectively. PK/PD modelling of in vitro time–kill curves established broth and serum breakpoint values for area under curve (AUC_0–24 h)/MIC for three levels of inhibition of growth, bacteriostasis and 3 and 4 log₁₀ reductions in bacterial count. Doses were then predicted for each pathogen, based on Monte Carlo simulations, for: (i) bacteriostatic and bactericidal levels of kill; (ii) 50% and 90% target attainment rates (TAR); and (iii) single dosing and daily dosing at steady‐state. For 90% TAR, predicted daily doses at steady‐state for bactericidal actions were 1123 mg/kg (P. multocida) and 43 mg/kg (A. pleuropneumoniae) based on serum MICs. Lower TARs were predicted from broth MIC data; corresponding dose estimates were 95 mg/kg (P. multocida) and 34 mg/kg (A. pleuropneumoniae).

Using Chemical Reaction Kinetics to Predict Optimal Antibiotic Treatment Strategies

Identifying optimal dosing of antibiotics has proven challenging-some antibiotics are most effective when they are administered periodically at high doses, while others work best when minimizing concentration fluctuations. Mechanistic explanations for why antibiotics differ in their optimal dosing are lacking, limiting our ability to predict optimal therapy and leading to long and costly experiments. We use mathematical models that describe both bacterial growth and intracellular antibiotic-target binding to investigate the effects of fluctuating antibiotic concentrations on individual bacterial cells and bacterial populations. We show that physicochemical parameters, e.g. the rate of drug transmembrane diffusion and the antibiotic-target complex half-life are sufficient to explain which treatment strategy is most effective. If the drug-target complex dissociates rapidly, the antibiotic must be kept constantly at a concentration that prevents bacterial replication. If antibiotics cross bacterial cell envelopes slowly to reach their target, there is a delay in the onset of action that may be reduced by increasing initial antibiotic concentration. Finally, slow drug-target dissociation and slow diffusion out of cells act to prolong antibiotic effects, thereby allowing for less frequent dosing. Our model can be used as a tool in the rational design of treatment for bacterial infections. It is easily adaptable to other biological systems, e.g. HIV, malaria and cancer, where the effects of physiological fluctuations of drug concentration are also poorly understood.

Optimization of linezolid treatment regimens for Gram-positive bacterial infections based on pharmacokinetic/pharmacodynamic analysis

AIM

To optimize linezolid treatment regimens for Gram-positive bacterial infections based on pharmacokinetic/pharmacodynamic analysis.

MATERIALS & METHODS

The minimum inhibitory concentration (MIC) distribution of 572 Gram-positive strains from patients with clinically confirmed infections was analyzed. Using the Monte Carlo simulation method, the cumulative fraction of response and probability of target attainment were determined for linezolid regimens of 600 mg q.12h and q.8h Results: Linezolid dosage of 600 mg q.12h yielded >90% cumulative fraction of response and probability of target attainment for staphylococcal infections with an MIC of ≤1 mg/l, enterococcal infections with higher MIC values required 600 mg q.8h.

CONCLUSION

Linezolid 600 mg q.12h is still the clinically recommended empirical dosage for Gram-positive bacterial infections. However, as bacterial MICs increase, 600 mg q.8h may be required to achieve better efficacy.

Mathematical model on Alzheimer's disease

Background

Alzheimer disease (AD) is a progressive neurodegenerative disease that destroys memory and cognitive skills. AD is characterized by the presence of two types of neuropathological hallmarks: extracellular plaques consisting of amyloid β-peptides and intracellular neurofibrillary tangles of hyperphosphorylated tau proteins. The disease affects 5 million people in the United States and 44 million world-wide. Currently there is no drug that can cure, stop or even slow the progression of the disease. If no cure is found, by 2050 the number of alzheimer’s patients in the U.S. will reach 15 million and the cost of caring for them will exceed $ 1 trillion annually.

Results

The present paper develops a mathematical model of AD that includes neurons, astrocytes, microglias and peripheral macrophages, as well as amyloid β aggregation and hyperphosphorylated tau proteins. The model is represented by a system of partial differential equations. The model is used to simulate the effect of drugs that either failed in clinical trials, or are currently in clinical trials.

Conclusions

Based on these simulations it is suggested that combined therapy with TNF- α inhibitor and anti amyloid β could yield significant efficacy in slowing the progression of AD.

Translational PK/PD of anti-infective therapeutics

Translational PK/PD modeling has emerged as a critical technique for quantitative analysis of the relationship between dose, exposure and response of antibiotics. By combining model components for pharmacokinetics, bacterial growth kinetics and concentration-dependent drug effects, these models are able to quantitatively capture and simulate the complex interplay between antibiotic, bacterium and host organism. Fine-tuning of these basic model structures allows to further account for complicating factors such as resistance development, combination therapy, or host responses. With this tool set at hand, mechanism-based PK/PD modeling and simulation allows to develop optimal dosing regimens for novel and established antibiotics for maximum efficacy and minimal resistance development.

Activity of cefquinome against extended-spectrum β-lactamase-producing Klebsiella pneumoniae in neutropenic mouse thigh model

Increasing prevalence of extended-spectrum β-lactamase (ESBL)-producing Klebsiella pneumoniae (K. pneumoniae) is of clinical concern. The objective of our study was to examine the in vivo activity of cefquinome against ESBL-producing K. pneumoniae strain using a neutropenic mouse thigh infection model. Cefquinome kinetics and protein binding in infected neutropenic mice were measured by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Dose-fractionation studies over a 24-h dose range of 2.5-320 mg/kg were administered every 3, 6, 12, or 24 h. The percentage of the dosing interval that the free-drug serum levels exceed the MIC (%fT > MIC) was the PK-PD index that best correlated with cefquinome efficacy (R²  = 86%). Using a sigmoid E_max model, the magnitudes of %fT > MIC producing net bacterial stasis, a 1-log₁₀ kill and a 2-log₁₀ kill over 24 h, were estimated to be 20.07%, 29.57%, and 55.12%, respectively. These studies suggest that optimal cefquinome PK/PD targets are not achieved in pigs, sheep, and cattle at current recommended doses (1˜2 mg/kg). Further studies with higher doses in the target species are needed to ensure therapeutic concentration, if cefquinome is used for treatment of K. pneumoniae infection.

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.

A multistate tuberculosis pharmacometric model: a framework for studying anti-tubercular drug effects in vitro

OBJECTIVES

Mycobacterium tuberculosis can exist in different states in vitro, which can be denoted as fast multiplying, slow multiplying and non-multiplying. Characterizing the natural growth of M. tuberculosis could provide a framework for accurate characterization of drug effects on the different bacterial states.

METHODS

The natural growth data of M. tuberculosis H37Rv used in this study consisted of viability defined as cfu versus time based on data from an in vitro hypoxia system. External validation of the natural growth model was conducted using data representing the rate of incorporation of radiolabelled methionine into proteins by the bacteria. Rifampicin time-kill curves from log-phase (0.25-16 mg/L) and stationary-phase (0.5-64 mg/L) cultures were used to assess the model's ability to describe drug effects by evaluating different linear and non-linear exposure-response relationships.

RESULTS

The final pharmacometric model consisted of a three-compartment differential equation system representing fast-, slow- and non-multiplying bacteria. Model predictions correlated well with the external data (R(2) = 0.98). The rifampicin effects on log-phase and stationary-phase cultures were separately and simultaneously described by including the drug effect on the different bacterial states. The predicted reduction in log10 cfu after 14 days and at 0.5 mg/L was 2.2 and 0.8 in the log-phase and stationary-phase systems, respectively.

CONCLUSIONS

The model provides predictions of the change in bacterial numbers for the different bacterial states with and without drug effect and could thus be used as a framework for studying anti-tubercular drug effects in vitro.

A pharmacokinetic-pharmacodynamic (PKPD) model based on in vitro time-kill data predicts the in vivo PK/PD index of colistin

OBJECTIVES

For antibiotics, extensive animal PKPD studies are often performed to evaluate the PK/PD driver for subsequent use when recommending dosing regimens. The aim of this work was to evaluate a PKPD model, developed based on in vitro time-kill data for colistin, in predicting the relationships between PK/PD indices and the bacterial killing previously observed in mice.

METHODS

An in silico PKPD model for Pseudomonas aeruginosa exposed to colistin was previously developed based on static in vitro time-kill data. The model was here applied to perform an in silico replication of an in vivo study where the effect of colistin on P. aeruginosa was studied in the thigh infection model. Concentration-time profiles of unbound colistin were predicted and used as input to drive the bacterial killing in the PKPD model. The predicted bacterial count at 24 h was related to each of the PK/PD indices and the results were compared with reported observations in vivo.

RESULTS

The model was found to adequately predict in vivo results from mice; both in terms of which PK/PD index best correlates to effect (fAUC/MIC) as well as the magnitude needed for a 2 log kill. The fAUC/MIC needed to achieve a 2 log reduction in bacterial counts after 24 h was here predicted to be 9 compared with 31 previously reported in vivo.

CONCLUSIONS

This study provides further support that PKPD models based on longitudinal data can be a useful tool to make drug development more efficient within the infectious diseases area.

Effects of Implant-Associated Osteomyelitis on Cefuroxime Bone Pharmacokinetics: Assessment in a Porcine Model

BACKGROUND

The prolonged antibiotic therapy that is often needed for successful management of osteomyelitis may be related to incomplete penetration of antibiotics into the target site. The objective of this study was to assess the effects of implant-associated osteomyelitis on cefuroxime penetration into bone.

METHODS

Implant-associated osteomyelitis using a Staphylococcus aureus strain was induced in the right tibia in ten pigs. After five days and following administration of 1500 mg of cefuroxime, measurements of cefuroxime were obtained using microdialysis for eight hours in the implant-related bone cavity, in the adjacent infected cancellous bone and infected subcutaneous tissue, and in healthy cancellous bone and subcutaneous tissue in the contralateral leg. Measurements of the corresponding free plasma concentrations were also obtained. The extent of the infection was assessed by postmortem computed tomography (CT) scans and cultures of blood, swabs, and bone specimens.

RESULTS

Bone destruction was found in the implant cavities. No structural bone changes in the adjacent infected cancellous bone were visible on CT scans. S. aureus was grown on culture of specimens from all implant cavities and from eight of ten swabs and seven of ten bone samples from the infected bone. The areas under the concentration-time curves for the different tissues differed significantly, with the lowest area under the curve found in the implant cavity (analysis of variance; p < 0.001). Although not as notable as for the implant cavity, cefuroxime penetration into infected cancellous bone was incomplete but comparable with that in healthy bone. Despite poorer tissue penetration, slightly increased time with concentrations above the minimal inhibitory concentration (MIC) was achieved in the implant cavity up to MICs of 2 mg/L compared with the other tissues, but the time was shorter for higher MICs.

CONCLUSIONS

Cefuroxime penetration into infected cancellous bone was incomplete but comparable with that in healthy bone. The destructive bone processes associated with acute osteomyelitis reduced cefuroxime penetration further.

CLINICAL RELEVANCE

These findings support the general clinical perception that fast diagnosis and early initiation of antibiotics before the development of implant-associated cavities is important in nonsurgical management of acute osteomyelitis.

Pharmacokinetics of single-dose cefuroxime in porcine intervertebral disc and vertebral cancellous bone determined by microdialysis

BACKGROUND

Pyogenic spondylodiscitis is associated with prolonged antimicrobial therapy and high relapse rates. Nevertheless, tissue pharmacokinetic studies of relevant antimicrobials in both prophylactic and therapeutic situations are still sparse. Previous approaches based on bone biopsy and discectomy exhibit important methodological limitations.

PURPOSE

The objective of this study was to assess the C3-C4 intervertebral disc (IVD), C3 vertebral body cancellous bone, and subcutaneous adipose tissue (SCT) pharmacokinetics of cefuroxime by use of microdialysis in a large animal model.

STUDY DESIGN

This was a single-dose, dense sampling large animal study of cefuroxime spine penetration.

METHODS

Ten female pigs were assigned to receive 1,500 mg of cefuroxime intravenously over 15 minutes. Measurements of cefuroxime were obtained from plasma, SCT, vertebral cancellous bone, and IVD for 8 hours thereafter. Microdialysis was applied for sampling in solid tissues.

RESULTS

For both IVD and vertebral cancellous bone, the area under the concentration curve from zero to the last measured value (AUC(0-last)) was significantly lower than that of free plasma. As estimated by the ratio of tissue AUC(0-last) to plasma AUC(0-last), tissue penetration (95% confidence interval) of cefuroxime was significantly incomplete for the IVD 0.78 (0.57; 0.99), whereas for vertebral cancellous bone 0.78 (0.51; 1.04) and SCT 0.94 (0.73; 1.15) it was not. The penetration of cefuroxime from plasma to the IVD was delayed, and the maximal concentration and the elimination of cefuroxime were also reduced compared with both SCT and vertebral cancellous bone. Because of this delay in elimination of cefuroxime, the time with concentrations above the minimal inhibitory concentration (T(>MIC)) was significantly longer in the IVD compared with the remaining compartments up to MICs of 6 µg/mL.

CONCLUSIONS

Microdialysis was successfully applied for serial assessment of the concentration of cefuroxime in the IVD and the vertebral cancellous bone. Penetration of cefuroxime from plasma to IVD was found to be incomplete and delayed, but because of a prolonged elimination, superior T(>MIC) was found in the IVD up to MICs of 6 µg/mL.

Application of PK/PD Modeling in Veterinary Field: Dose Optimization and Drug Resistance Prediction

Among veterinary drugs, antibiotics are frequently used. The true mean of antibiotic treatment is to administer dose of drug that will have enough high possibility of attaining the preferred curative effect, with adequately low chance of concentration associated toxicity. Rising of antibacterial resistance and lack of novel antibiotic is a global crisis; therefore there is an urgent need to overcome this problem. Inappropriate antibiotic selection, group treatment, and suboptimal dosing are mostly responsible for the mentioned problem. One approach to minimizing the antibacterial resistance is to optimize the dosage regimen. PK/PD model is important realm to be used for that purpose from several years. PK/PD model describes the relationship between drug potency, microorganism exposed to drug, and the effect observed. Proper use of the most modern PK/PD modeling approaches in veterinary medicine can optimize the dosage for patient, which in turn reduce toxicity and reduce the emergence of resistance. The aim of this review is to look at the existing state and application of PK/PD in veterinary medicine based on in vitro, in vivo, healthy, and disease model.

Simulation-Based Evaluation of PK/PD Indices for Meropenem Across Patient Groups and Experimental Designs

PURPOSE

Antibiotic dose predictions based on PK/PD indices rely on that the index type and magnitude is insensitive to the pharmacokinetics (PK), the dosing regimen, and bacterial susceptibility. In this work we perform simulations to challenge these assumptions for meropenem and Pseudomonas aeruginosa.

METHODS

A published murine dose fractionation study was replicated in silico. The sensitivity of the PK/PD index towards experimental design, drug susceptibility, uncertainty in MIC and different PK profiles was evaluated.

RESULTS

The previous murine study data were well replicated with fT > MIC selected as the best predictor. However, for increased dosing frequencies fAUC/MIC was found to be more predictive and the magnitude of the index was sensitive to drug susceptibility. With human PK fT > MIC and fAUC/MIC had similar predictive capacities with preference for fT > MIC when short t1/2 and fAUC/MIC when long t1/2.

CONCLUSIONS

A longitudinal PKPD model based on in vitro data successfully predicted a previous in vivo study of meropenem. The type and magnitude of the PK/PD index were sensitive to the experimental design, the MIC and the PK. Therefore, it may be preferable to perform simulations for dose selection based on an integrated PK-PKPD model rather than using a fixed PK/PD index target.

Gentamicin dosing strategy in patients with end-stage renal disease receiving haemodialysis: evaluation using a semi-mechanistic pharmacokinetic/pharmacodynamic model

OBJECTIVES

Gentamicin is widely used in end-stage renal disease (ESRD) patients for the treatment of infections. The goal of this study was to find the most reasonable dosing regimen for gentamicin in ESRD patients receiving haemodialysis.

METHODS

The in vitro antimicrobial activity of gentamicin was evaluated by static and dynamic time-kill experiments against three bacterial strains of MSSA, MRSA and Pseudomonas aeruginosa. A semi-mechanistic pharmacokinetic/pharmacodynamic (PK/PD) model was established afterwards, allowing the characterization of the antibacterial effect of gentamicin in the human body. The model was utilized to assess dosing regimens of gentamicin in ESRD patients receiving haemodialysis, taking both efficacy and safety into account.

RESULTS

The PK/PD model was capable of describing the bacterial response to gentamicin exposure in all three strains. Simulation based on the PK/PD model showed that pre-dialysis and post-dialysis dosing would bring comparable benefit to the ESRD patient regardless of whether the PK/PD target (fCmax/MIC >8-fold) was achieved, while the post-dialysis dosing resulted in a significantly lower trough concentration. The result of simulated dose fractionation demonstrated that both fCmax/MIC and fAUC(0-24)/MIC are strong predictors of drug effectiveness, but the PK/PD model would provide a more precise prediction of antibacterial activity as well as valuable information on dose selection in ESRD patients receiving haemodialysis.

CONCLUSIONS

Our study supports the original FDA label with regard to the dosing regimen of gentamicin in ESRD patients, which offers adequate clinical benefit as well as an acceptable safety profile.

Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model

One critical approach to preclinical evaluation of anti-tuberculosis (anti-TB) drugs is the study of correlations between drug exposure and efficacy in animal TB infection models. While such pharmacokinetic/pharmacodynamic (PK/PD) studies are useful for the identification of optimal clinical dosing regimens, they are resource intensive and are not routinely performed. A mathematical model capable of simulating the PK/PD properties of drug therapy for experimental TB offers a way to mitigate some of the practical obstacles to determining the PK/PD index that best correlates with efficacy. Here, we present a preliminary physiologically based PK/PD model of rifampin therapy in a mouse TB infection model. The computational framework integrates whole-body rifampin PKs, cell population dynamics for the host immune response to Mycobacterium tuberculosis infection, drug-bacteria interactions, and a Bayesian method for parameter estimation. As an initial application, we calibrated the model to a set of available rifampin PK/PD data and simulated a separate dose fractionation experiment for bacterial killing kinetics in the lungs of TB-infected mice. The simulation results qualitatively agreed with the experimentally observed PK/PD correlations, including the identification of area under the concentration-time curve as best correlating with efficacy. This single-drug framework is aimed toward extension to multiple anti-TB drugs in order to facilitate development of optimal combination regimens.

Applications of physiologically based pharmacokinetic modeling for the optimization of anti-infective therapies

INTRODUCTION

The pharmacokinetic properties of anti-infective drugs are a determinant part of treatment success. Pathogen replication is inhibited if adequate drug levels are achieved in target sites, whereas excessive drug concentrations linked to toxicity are to be avoided. Anti-infective distribution can be predicted by integrating in vitro drug properties and mathematical descriptions of human anatomy in physiologically based pharmacokinetic models. This method reduces the need for animal and human studies and is used increasingly in drug development and simulation of clinical scenario such as, for instance, drug-drug interactions, dose optimization, novel formulations and pharmacokinetics in special populations.

AREAS COVERED

We have assessed the relevance of physiologically based pharmacokinetic modeling in the anti-infective research field, giving an overview of mechanisms involved in model design and have suggested strategies for future applications of physiologically based pharmacokinetic models.

EXPERT OPINION

Physiologically based pharmacokinetic modeling provides a powerful tool in anti-infective optimization, and there is now no doubt that both industry and regulatory bodies have recognized the importance of this technology. It should be acknowledged, however, that major challenges remain to be addressed and that information detailing disease group physiology and anti-infective pharmacodynamics is required if a personalized medicine approach is to be achieved.

Mutant prevention concentration, pharmacokinetic-pharmacodynamic integration, and modeling of enrofloxacin data established in diseased buffalo calves

The pharmacokinetic-pharmacodynamic (PK/PD) modeling of enrofloxacin data using mutant prevention concentration (MPC) of enrofloxacin was conducted in febrile buffalo calves to optimize dosage regimen and to prevent the emergence of antimicrobial resistance. The serum peak concentration (Cmax ), terminal half-life (t1/2 K10) , apparent volume of distribution (Vd(area) /F), and mean residence time (MRT) of enrofloxacin were 1.40 ± 0.27 μg/mL, 7.96 ± 0.86 h, 7.74 ± 1.26 L/kg, and 11.57 ± 1.01 h, respectively, following drug administration at dosage 12 mg/kg by intramuscular route. The minimum inhibitory concentration (MIC), minimum bactericidal concentration, and MPC of enrofloxacin against Pasteurella multocida were 0.055, 0.060, and 1.45 μg/mL, respectively. Modeling of ex vivo growth inhibition data to the sigmoid Emax equation provided AUC24 h /MIC values to produce effects of bacteriostatic (33 h), bactericidal (39 h), and bacterial eradication (41 h). The estimated daily dosage of enrofloxacin in febrile buffalo calves was 3.5 and 8.4 mg/kg against P. multocida/pathogens having MIC90 ≤0.125 and 0.30 μg/mL, respectively, based on the determined AUC24 h /MIC values by modeling PK/PD data. The lipopolysaccharide-induced fever had no direct effect on the antibacterial activity of the enrofloxacin and alterations in PK of the drug, and its metabolite will be beneficial for its use to treat infectious diseases caused by sensitive pathogens in buffalo species. In addition, in vitro MPC data in conjunction with in vivo PK data indicated that clinically it would be easier to eradicate less susceptible strains of P. multocida in diseased calves.

Pyridodiazepine amines are selective therapeutic agents for helicobacter pylori by suppressing growth through inhibition of glutamate racemase but are predicted to require continuous elevated levels in plasma to achieve clinical efficacy

A pyridodiazepine amine inhibitor of Helicobacter pylori glutamate racemase (MurI) was characterized. The compound was selectively active against H. pylori, and growth suppression was shown to be mediated through the inhibition of MurI by several methods. In killing kinetics experiments, the compound showed concentration-independent activity, with about a 2-log loss of viability in 24 h. A demonstration of efficacy in a mouse infection model was attempted but not achieved, and this was attributed to the failure to attain extended exposure levels above the MIC for >95% of the time. This index and magnitude were derived from pharmacokinetic-pharmacodynamic (PK-PD) studies with amoxicillin, another inhibitor of peptidoglycan biosynthesis that showed slow killing kinetics similar to those of the pyridodiazepine amines. These studies indicate that MurI and other enzymes involved in peptidoglycan biosynthesis may be less desirable targets for monotherapy directed against H. pylori if once-a-day dosing is required.

Treatment option for sepsis in children in the era of antibiotic resistance

Sepsis caused by multidrug-resistant microorganisms is one of the most serious infectious diseases of childhood and poses significant challenges for pediatricians involved in management of critically ill children. This review discusses the use of pharmacokinetic/dynamic principles (i.e., prolonged infusion of β-lactams and vancomycin, once-daily administration of aminoglycosides and rationale of therapeutic drug monitoring) when prescribing antibiotics to critically ill patients. The potential of 'old' agents (i.e., colistin, fosfomycin) and newly approved antibiotics is critically reviewed. The pros and cons of combination antibacterial therapy are discussed and finally suggestions for the treatment of sepsis caused by multidrug-resistant organisms are provided.