Linezolid is an antibiotic used to treat infections caused by drug-resistant gram-positive organisms, including vancomycin-resistant Enterococcus faecium, multi-drug resistant Streptococcus pneumoniae, and methicillin-resistant Staphylococcus aureus. The adverse effects of linezolid can include thrombocytopenia and neuropathy, which are more prevalent with higher exposures and longer treatment durations. Although linezolid is traditionally administered at a standard 600 mg dose every 12 hours, the resulting exposure can vary greatly between patients and can lead to treatment failure or toxicity. The efficacy and toxicity of linezolid are determined by the exposure achieved in the patient; numerous clinical and population pharmacokinetics (popPK) studies have identified threshold measurements for both parameters. Several special populations with an increased need for linezolid dose adjustments have also been identified. Therapeutic Drug Monitoring (TDM) is a clinical strategy that assesses the response of an individual patient and helps adjust the dosing regimen to maximize efficacy while minimizing toxicity. Adaptive feedback control and model-informed precision dosing are additional strategies that use Bayesian algorithms and PK models to predict patient-specific drug exposure. TDM is a very useful tool for patient populations with sparse clinical data or known alterations in pharmacokinetics, including children, patients with renal insufficiency or those receiving renal replacement therapy, and patients taking co-medications known to interact with linezolid. As part of the clinical workflow, clinicians can use TDM with the thresholds summarized from the current literature to improve linezolid dosing for patients and maximize the probability of treatment success.

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Polymyxin B is used as an antibiotic of last resort for patients with multidrug-resistant Gram-negative bacterial infections; however, it carries a significant risk of nephrotoxicity. Herein we present a polymyxin B therapeutic window based on target area under the concentration-time curve (AUC) values and an adaptive feedback control algorithm (algorithm) which allows for the personalization of polymyxin B dosing. The upper bound of this therapeutic window was determined through a pharmacometric meta-analysis of polymyxin B nephrotoxicity data, and the lower bound was derived from murine thigh infection pharmacokinetic (PK)/pharmacodynamic (PD) studies. A previously developed polymyxin B population pharmacokinetic model was used as the backbone for the algorithm. Monte Carlo simulations (MCS) were performed to evaluate the performance of the algorithm using different sparse PK sampling strategies. The results of the nephrotoxicity meta-analysis showed that nephrotoxicity rate was significantly correlated with polymyxin B exposure. Based on this analysis and previously reported murine PK/PD studies, the target AUC0–24 (AUC from 0 to 24 h) window was determined to be 50 to 100 mg · h/liter. MCS showed that with standard polymyxin B dosing without adaptive feedback control, only 71% of simulated subjects achieved AUC values within this window. Using a single PK sample collected at 24 h and the algorithm, personalized dosing regimens could be computed, which resulted in >95% of simulated subjects achieving AUC0–24 values within the target window. Target attainment further increased when more samples were used. Our algorithm increases the probability of target attainment by using as few as one pharmacokinetic sample and enables precise, personalized dosing in a vulnerable patient population.

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

Stenotrophomonas maltophilia is a non-fermenting, Gram-negative bacillus that has emerged as an opportunistic nosocomial pathogen. Its intrinsic multidrug resistance makes treating infections caused by S. maltophilia a great clinical challenge. Clinical management is further complicated by its molecular heterogeneity that is reflected in the uneven distribution of antibiotic resistance and virulence determinants among different strains, the shortcomings of available antimicrobial susceptibility tests and the lack of standardized breakpoints for the handful of antibiotics with in vitro activity against this microorganism. Herein, we provide an update on the most recent literature concerning these issues, emphasizing the impact they have on clinical management of S. maltophilia infections.

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f Administering polymyxin antibiotics in a traditional fashion may be ineffective against Gram-negative ESKAPE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter species) pathogens. Here, we explored increasing the dose intensity of polymyxin B against two strains of Acinetobacter baumannii in the hollow-fiber infection model. The following dosage regimens were simulated for polymyxin B (t 1/2 ‫؍‬ 8 h): nonloading dose (1.43 mg/kg of body weight every 12 h [q12h]), loading dose (2.22 mg/kg q12h for 1 dose and then 1.43 mg/kg q12h), front-loading dose (3.33 mg/kg q12h for 1 dose followed by 1.43 mg/kg q12h), burst (5.53 mg/kg for 1 dose), and supraburst (18.4 mg/kg for 1 dose). Against both A. baumannii isolates, a rapid initial decline in the total population was observed within the first 6 h of polymyxin exposure, whereby greater polymyxin B exposure resulted in greater maximal killing of ؊1.25, ؊1.43, ؊2.84, ؊2.84, and ؊3.40 log 10 CFU/ml within the first 6 h. Unexpectedly, we observed a paradoxical effect whereby higher polymyxin B exposures dramatically increased resistant subpopulations that grew on agar containing up to 10 mg/liter of polymyxin B over 336 h. High drug exposure also proliferated polymyxin-dependent growth. A cost-benefit pharmacokinetic/pharmacodynamic relationship between 24-h killing and 336-h resistance was explored. The intersecting point, where the benefit of bacterial killing was equal to the cost of resistance, was an fAUC 0 -24 (area under the concentration-time curve from 0 to 24 h for the free, unbound fraction of drug) of 38.5 mg · h/liter for polymyxin B. Increasing the dose intensity of polymyxin B resulted in amplification of resistance, highlighting the need to utilize polymyxins as part of a combination against high-bacterial-density A. baumannii infections.T he polymyxin antibiotics have emerged as a last line of defense for the treatment of Gram-negative strains resistant to all other currently available antibiotics (1-3). Polymyxin B and colistin are often the only available agents with activity against these Gram-negative superbugs (4, 5). Even more worrisome is the first report of plasmid-mediated polymyxin resistance in Escherichia coli, which could be transferred to other Gram-negative strains (6). Furthermore, current dosage regimens for both polymyxin B and colistin result in polymyxin plasma concentrations that are suboptimal in a significant proportion of patients (7-10). In vitro and animal studies clearly demonstrate that antibiotic resistance is amplified during exposure to suboptimal polymyxin concentrations, especially against polymyxin-heteroresistant strains that are frequently isolated in Acinetobacter baumannii (11)(12)(13)(14).Administering nontraditional, high-intensity polymyxin regimens may be a strategy to maximize bacterial killing while minimizing resistance and potential toxicity. We have previously determined that front-loading colistin resulted in greater bacteri...