Population pharmacokinetics and target attainment analysis of moxifloxacin in patients with diabetic foot infections

Population pharmacokinetics of antibacterial agents in the older population: a literature review

INTRODUCTION

Older individuals face an elevated risk of developing bacterial infections. The optimal use of antibacterial agents in this population is challenging because of age-related physiological alterations, changes in pharmacokinetics (PK) and pharmacodynamics (PD), and the presence of multiple underlying diseases. Therefore, population pharmacokinetics (PPK) studies are of great importance for optimizing individual treatments and prompt identification of potential risk factors.

AREA COVERED

Our search involved keywords such as 'elderly,' 'old people,' and 'geriatric,' combined with 'population pharmacokinetics' and 'antibacterial agents.' This comprehensive search yielded 11 categories encompassing 28 antibacterial drugs, including vancomycin, ceftriaxone, meropenem, and linezolid. Out of 127 studies identified, 26 (20.5%) were associated with vancomycin, 14 (11%) with meropenem, and 14 (11%) with piperacillin. Other antibacterial agents were administered less frequently.

EXPERT OPINION

PPK studies are invaluable for elucidating the characteristics and relevant factors affecting the PK of antibacterial agents in the older population. Further research is warranted to develop and validate PPK models for antibacterial agents in this vulnerable population.

Patients with Obesity Should be Recognised as a Special Patient Population During Drug Development of Antibacterial and Antifungal Agents; A Call to Action

Individuals with obesity are at increased risk of developing infectious diseases. Timely administration of an effective dose of an antimicrobial agent is paramount to safeguard optimal therapy. For this purpose, special patient populations at risk for altered exposure such as renal or hepatic impairment are studied during drug development. Strikingly, there is no such evaluation in individuals with obesity despite a potential influence on exposure and a global obesity prevalence of 13 %. Optimal clinical decision making in patients with obesity is impossible without prior study of the drug of interest in this population. This statement is strengthened by an evaluation of 19 antimicrobial agents that showed tremendous variability in the influence of weight on clearance. In contrast to patient with renal or hepatic impairment who are mainly at risk of overexposure, individuals with obesity can be at risk of both under- and overexposure. Gaining knowledge on the influence of body weight on clearance during early phases of drug development may allow for optimisation of other phases of research, potentially increasing success rate of the drug, and can provide clinicians with vital information as soon as the drug reaches the market. Antimicrobial therapy should be tailored to obesity-related (patho)physiological changes and to reach this goal, obese individuals should be studied during drug development.

Colistin Dosing Regimens against Pseudomonas aeruginosa in Critically Ill Patients: An Application of Monte Carlo Simulation

Our aims are to assess various colistin dosing regimens against Pseudomonas aeruginosa (P. aeruginosa) infection in critically ill patients and to propose an appropriate regimen based on microbiological data. A Monte Carlo simulation was performed using the published colistin’s pharmacokinetic parameters of critically ill patients, the published pharmacodynamic target from a mouse thigh infection model, and the minimum inhibitory concentration (MIC) results from a Vietnamese hospital. The probability of target attainment (PTA) of 80% and cumulative fraction of response (CFR) of 90% were used to evaluate the efficacy of each regimen. Of 121 P. aeruginosa laboratory datasets, the carbapenem-resistant P. aeruginosa (CRPA) and the colistin-resistant P. aeruginosa rates were 29.8% and 0.8%, respectively. MIC_50,90 were both 0.5 mg/L. The simulated results showed that at MIC of 2 mg/L, most regimens could not reach the PTA target, particularly in patients with normal renal function (Creatinine clearance (CrCl) ≥ 80 mL/min). At MIC of 0.5 mg/L and 1 mg/L, current recommendations still worked well. On the basis of these results, aside from lung infection, our study recommends three regimens against P. aeruginosa infection at MIC of 0.5 mg/L, 1 mg/L, and 2 mg/L. In conclusion, higher total daily doses and fractionated colistin dosing regimens could be the strategy for difficult-to-acquire PTA cases, while a less aggressive dose might be appropriate for empirical treatment in settings with low MIC_50/90.

Is Moxifloxacin a Treatment Option for Pancreatic Infections? A Pharmacometric Analysis of Serum and Pancreatic Juice

Postoperative local infection is a major complication after pancreatic surgery. The aim of this prospective clinical trial was to assess the potential of moxifloxacin (MXF) to treat pancreatic infections from a pharmacokinetic (PK)/pharmacodynamic (PD) perspective. The PK of MXF in serum and pancreatic juice, via an inserted tube in the pancreatic duct, was determined in 19 patients up to day 7 after pancreatoduodenectomy. PK data in both specimens was analyzed with NONMEM 7.3. Intraoperative swipes were performed for microbiological examination. PK/PD target attainment was assessed in both matrices using unbound area under the plasma concentration-time curve/minimum inhibitory concentration (MIC) targets of ≥30 and ≥100, for gram-positive and gram-negative pathogens, respectively. A 2-compartment population PK model in which the measurements in pancreatic juice were assigned to a scaled peripheral compartment best described the PK in both specimens simultaneously. Median (10th-90th percentile) area under the plasma concentration-time curve values after the third dose were 28.9 mg · h/L (18.6-42.0) in serum and 55.8 mg · h/L (23.7-81.4) in pancreatic juice. Target attainment rate for the intraoperatively isolated bacterial strains was ≥0.88 after the third MXF dose. For gram-negatives, high probability of target attainment ≥0.84 was observed in serum for MIC ≤ 0.125 mg/L and in pancreatic juice for MIC ≤ 0.25 mg/L. For gram-positives, the probability of target attainment was 0.84-1 in serum for MIC ≤ 0.5 mg/L and in pancreatic juice for MIC ≤ 1 mg/L. In conclusion, penetration of MXF into pancreatic juice was substantial. The PK/PD analysis indicated that treatment of pancreatic infections by isolates with MIC ≤ 0.25 mg/L (gram-negative) and ≤1 mg/L (gram-positive) should be evaluated in further studies.

Use of microdialysis for the assessment of fluoroquinolone pharmacokinetics in the clinical practice

Antibacterial drugs, including fluoroquinolones, can exert their therapeutic action only with adequate penetration at the infection site. Multiple factors, such as rate of protein binding, drug liposolubility and organ blood-flow all influence ability of antibiotics to penetrate target tissues. Microdialysis is an in vivo sampling technique that has been successfully applied to measure the distribution of fluoroquinolones in the interstitial fluid of different tissues both in animal studies and clinical setting. Tissue concentrations need to be interpreted within the context of the pathogenesis and causative agents implicated in infections. Integration of microdialysis -derived tissue pharmacokinetics with pharmacodynamic data offers crucial information for correlating exposure with antibacterial effect. This review explores these concepts and provides an overview of tissue concentrations of fluoroquinolones derived from microdialysis studies and explores the therapeutic implications of fluoroquinolone distribution at various target tissues.

Bacterial resistance and failure of clinical cure could be produced by oxidative stress in patients with diabetes or cardiovascular diseases during fluoroquinolone therapy

Fluoroquinolone agents are used widely for the treatment of infectious diseases which are a common cause of deaths around the world. The level of oxidative stress in patients taking fluoroquinolone antibiotics has not been considered a factor to reduce the clinical efficacy of this kind of drugs. Patients with diabetes and/or cardiovascular diseases present abnormal levels of oxidative stress in the blood stream. In this regards, our hypothesis supposes that patients with diabetes and/or cardiovascular disease suffering a bacterial disease could experience a therapeutic failure and bacterial resistance when treated with fluoroquinolones. The crucial mechanism could be an inefficient blood distribution of the drug via red blood cell dysfunction induced by oxidative stress that might reduce the pharmacokinetic-pharmacodinamic ratios. In this way, we review the scientific information to support our hypothesis alongside possible implications. Additionally, this work exhibits the urgent need of studies considering these conditions for quinolone agents.

Decreased protein binding of moxifloxacin in patients with sepsis?

The mean (SD) unbound fraction of moxifloxacin in plasma from patients with severe sepsis or septic shock was determined by ultrafiltration to 85.5±3.0% (range 81.9 and 91.6%) indicating a decreased protein binding of moxifloxacin in this population compared with the value of 58-60% provided in the Summary of Product Characteristics. However, previous investigations neglected the influence of pH and temperature on the protein binding of moxifloxacin. Maintaining physiological conditions (pH 7.4, 37°C) - as in the present study - the unbound fraction of moxifloxacin in plasma from healthy volunteers was 84%. In contrast, the unbound fraction of moxifloxacin was 77% at 4°C and 66-68% in unbuffered plasma or at pH 8.5 in fair agreement with previously published data. PK/PD parameters e.g. fAUC/MIC or ratios between interstitial fluid and free plasma concentrations, which were obtained assuming a protein binding rate of moxifloxacin of 40% or more, should be revised.

What about confidence intervals? A word of caution when interpreting PTA simulations

OBJECTIVES

In the field of antimicrobial chemotherapy, readers are increasingly confronted with population pharmacokinetic models and the ensuing simulation results with the purpose to improve the efficiency of currently used therapeutic regimens. One such type of analysis is Monte Carlo (MC) simulations in support of dose selection. At the moment, results of these MC simulations consist of predictions for the typical individual/population only. The uncertainty associated with the parameters, from which the simulations are derived, is completely ignored. Here, we highlight the importance of and the need to include parameter uncertainty in PTA simulations.

METHODS

Using MC simulation with parameter uncertainty, we estimated CIs around PTA curves. The added benefit of this approach was illustrated using, on the one hand, a population pharmacokinetic model developed in-house for a β-lactam antibiotic and, on the other hand, results from a previously published PTA analysis.

RESULTS

Our examples illustrate that proper clinical decision-making requires more than the typical PTA curve. Therefore, authors should be encouraged to provide an estimate of the uncertainty along with their simulations and to take this into account when interpreting the results. We feel that CIs around PTA curves provide this information in a comprehensive manner without requiring advanced knowledge on the underlying modelling approaches from the reader.

CONCLUSIONS

We believe that this approach should be advocated by all stakeholders in antibiotic stewardship programmes to safeguard the quality of clinical decision-making in the future.

Drug-drug interactions between moxifloxacin and rifampicin based on pharmacokinetics in vivo in rats

Moxifloxacin and rifampicin are all the first-line options for the treatment of active tuberculosis, which are often combined for the treatment of multidrug resistance pulmonary tuberculosis in clinic. However, the potential drug-drug interactions between moxifloxacin and rifampicin were unknown. The aim of this study was to investigate the drug-drug interactions between moxifloxacin and rifampicin based on their pharmacokinetics in vivo after oral administration of the single drug and both drugs, and reveal their mutual effects on their pharmacokinetics. Eighteen male Sprague-Dawley rats were randomly assigned to three groups: moxifloxacin group, rifampicin group and moxifloxacin + rifampicin group. Plasma concentrations of moxifloxacin and rifampicin were determined using LC-MS at the designated time points after drug administration, and the main pharmacokinetic parameters were calculated. In addition, effects of moxifloxacin and rifampicin on their metabolic rate and absorption were investigated using rat liver microsome incubation systems and Caco-2 cell transwell model. The main pharmacokinetic parameters of moxifloxacin including Tmax , Cmax , t1/2 and AUC(0-t) increased more in the moxifloxacin + rifampicin group than in the moxifloxacin group, but the difference was not significant (p > 0.05). However, the pharmacokinetic parameters of rifampicin, including peak concentration, area under the concentration-time curve, half-life and the area under the first moment plasma concentration-time curve, increased significantly (p < 0.05) compared with the rifampicin group, and the time to peak concentration decreased significantly (p < 0.05). The mean residence time of rifampicin also increased in moxifloxacin + rifampicin group compared with the rifampicin group, but the difference was not significant (p > 0.05). The rat liver microsome incubation experiment indicated that moxifloxacin could increase the metabolic rate of rifampicin from 23.7 to 38.7 min. However, the Caco-2 cell transwell experiment showed that moxifloxacin could not affect the absorption rate of rifampicin. These changes could enhance the drug efficacy, but they could also cause drug accumulation, which might induce adverse effect, so it was suggested that the drug dosage should be adjusted and the drug concentration in plasma should be monitored if moxifloxacin and rifampicin are co-administered. Copyright © 2016 John Wiley & Sons, Ltd.