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Background: Continuous infusion of meropenem has been proposed to increase target attainment in critically ill patients, although stability might limit its practical use. This study investigated the impact of meropenem degradation and infusion bag changes on the concentration-time profiles and bacterial growth and killing of P. aeruginosa given different continuous-infusion solutions., Methods: A semi-mechanistic pharmacokinetic-pharmacodynamic (PK-PD) model quantifying meropenem concentrations (C MEM ) and bacterial counts of a resistant P. aeruginosa strain (ARU552, MIC = 16 mg/L) over 24 h was used to translate in vitro antibiotic effects to patients with severe infections. Concentration-dependent drug degradation of saline infusion solutions was considered using an additional compartment in the population PK model. C MEM , fT >MIC (time that concentrations exceed the MIC) and total bacterial load (B TOT ) after 24 h were simulated for different scenarios (n = 144), considering low- and high-dose regimens (3000/6000 mg/day±loading dose), clinically relevant infusion solutions (20/40/50 mg/mL), different intervals of infusion bag changes (every 8/24 h, q8/24 h), and varied renal function (creatinine clearance 40/80/120 mL/min) and MIC values (8/16 mg/L)., Results: Highest deviations between changing infusion bags q8h and q24h were observed for 50 mg/mL solutions and scenarios with C MEM_24 h close to the MIC, with differences (Δ) in C MEM_24 h up to 4.9 mg/L, ΔfT >MIC ≤65.7%, and ΔB TOT_24h ≤1.1 log10 CFU/mL, thus affecting conclusions on whether bacteriostasis was reached., Conclusions: In summary, this study indicated that for continuous infusion of meropenem, eight-hourly infusion bag changes improved PK/PD target attainment and might be beneficial particularly for high meropenem concentrations of saline infusion solutions and for plasma concentrations in close proximity to the MIC., Competing Interests: Declaration of competing interest None associated with the present work., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

The AIDA randomized clinical trial found no significant difference in clinical failure or survival between colistin monotherapy and colistin-meropenem combination therapy in carbapenem-resistant Gram-negative infections. The aim of this reverse translational study was to integrate all individual preclinical and clinical pharmacokinetic-pharmacodynamic (PKPD) data from the AIDA trial in a pharmacometric framework to explore whether individualized predictions of bacterial burden were associated with the trial outcomes. The compiled dataset included for each of the 207 patients was (i) information on the infecting Acinetobacter baumannii isolate (minimum inhibitory concentration, checkerboard assay data, and fitness in a murine model), (ii) colistin plasma concentrations and colistin and meropenem dosing history, and (iii) disease scores and demographics. The individual information was integrated into PKPD models, and the predicted change in bacterial count at 24 h for each patient, as well as patient characteristics, was correlated with clinical outcomes using logistic regression. The in vivo fitness was the most important factor for change in bacterial count. A model-predicted growth at 24 h of ≥2-log 10 (164/207) correlated positively with clinical failure (adjusted odds ratio, aOR = 2.01). The aOR for one unit increase of other significant predictors were 1.24 for SOFA score, 1.19 for Charlson comorbidity index, and 1.01 for age. This study exemplifies how preclinical and clinical anti-infective PKPD data can be integrated through pharmacodynamic modeling and identify patient- and pathogen-specific factors related to clinical outcomes - an approach that may improve understanding of study outcomes., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Co-administering a low dose of colistin (CST) with ciprofloxacin (CIP) may improve the antibacterial effect against resistant Escherichia coli, offering an acceptable benefit-risk balance. This study aimed to quantify the interaction between ciprofloxacin and colistin in an in silico pharmacokinetic-pharmacodynamic model from in vitro static time-kill experiments (using strains with minimum inhibitory concentrations, MIC CIP 0.023-1 mg/L and MIC CST 0.5-0.75 mg/L). It was also sought to demonstrate an approach of simulating concentrations at the site of infection with population pharmacokinetic and whole-body physiologically based pharmacokinetic models to explore the clinical value of the combination when facing more resistant strains (using extrapolated strains with lower susceptibility). The combined effect in the final model was described as the sum of individual drug effects with a change in drug potency: for ciprofloxacin, concentration at half maximum killing rate (EC 50 ) in combination was 160% of the EC 50 in monodrug experiments, while for colistin, the change in EC 50 was strain-dependent from 54.1% to 119%. The benefit of co-administrating a lower-than-commonly-administrated colistin dose with ciprofloxacin in terms of drug effect in comparison to either monotherapy was predicted in simulated bloodstream infections and pyelonephritis. The study illustrates the value of pharmacokinetic-pharmacodynamic modelling and simulation in streamlining rational development of antibiotic combinations., (© 2024. The Author(s).)

Appropriate antibiotic dosing to ensure early and sufficient target attainment is crucial for improving clinical outcome in critically ill patients. Parametric survival analysis is a preferred modeling method to quantify time-varying antibiotic exposure - response effects, whereas bias may be introduced in hazard functions and survival functions when competing events occur. This study investigated predictors of in-hospital mortality in critically ill patients treated with meropenem by pharmacometric multistate modeling. A multistate model comprising five states (ongoing meropenem treatment, other antibiotic treatment, antibiotic treatment termination, discharge, and death) was developed to capture the transitions in a cohort of 577 critically ill patients treated with meropenem. Various factors were investigated as potential predictors of the transitions, including patient demographics, creatinine clearance calculated by Cockcroft-Gault equation (CLCR CG ), time that unbound concentrations exceed the minimum inhibitory concentration (fT >MIC ), and microbiology-related measures. The probabilities to transit to other states from ongoing meropenem treatment increased over time. A 10 mL/min decrease in CLCR CG was found to elevate the hazard of transitioning from states of ongoing meropenem treatment and antibiotic treatment termination to the death state by 18%. The attainment of 100% fT >MIC significantly increased the transition rate from ongoing meropenem treatment to antibiotic treatment termination (by 9.7%), and was associated with improved survival outcome. The multistate model prospectively assessed predictors of death and can serve as a useful tool for survival analysis in different infection scenarios, particularly when competing risks are present., (© 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Antibiotic resistance presents an incessant threat to our drug armamentarium that necessitates novel approaches to therapy. Over the past several decades, investigation of pharmacokinetic and pharmacodynamic (PKPD) principles has substantially improved our understanding of the relationships between the antibiotic, pathogen, and infected patient. However, crucial gaps in our understanding of the pharmacology of antibacterials and their optimal use in the care of patients continue to exist; simply attaining antibiotic exposures that are considered adequate based on traditional targets can still result in treatment being unsuccessful and resistance proliferation for some infections. It is this salient paradox that points to key future directions for research in antibiotic therapeutics. This Personal View discusses six priority areas for antibiotic pharmacology research: (1) antibiotic-pathogen interactions, (2) antibiotic targets for combination therapy, (3) mechanistic models that describe the time-course of treatment response, (4) understanding and modelling of host response to infection, (5) personalised medicine through therapeutic drug management, and (6) application of these principles to support development of novel therapies. Innovative approaches that enhance our understanding of antibiotic pharmacology and facilitate more accurate predictions of treatment success, coupled with traditional pharmacology research, can be applied at the population level and to individual patients to improve outcomes., Competing Interests: Declaration of interests There was no funding to support this Personal View. JL and RLN licensed their new-generation polymyxin molecules to Qpex Biopharma. JL received grant support, a seminar honorarium, and consultation fees from Northern Antibiotics, Qpex Biopharma, Healthcare Pharmaceuticals, Genentech, and DanDi Bioscience. JBB received research consulting fees from MicuRx Pharmaceuticals and Lupin Pharmaceuticals. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Pharmacokinetic/pharmacodynamic (PKPD) models have emerged as valuable tools for the characterization and translation of antibiotic effects, and consequently for drug development and therapy. In contrast to traditional PKPD concepts for antibiotics such as minimum inhibitory concentration and PKPD indices, PKPD models enable description of the continuous, often species- or population-dependent time course of antimicrobial effects, commonly considering mechanistic pathogen- and drug-related knowledge. This review presents a comprehensive overview of previously published PKPD models describing repeated measurements of antibiotic effects. A literature review was conducted to identify PKPD models based on: (i) antibiotic compounds; (ii) Gram-positive or Gram-negative pathogens; and (iii) in-vitro or in-vivo longitudinal colony-forming unit data. In total, 132 publications were identified that were released between 1963 and 2021, including models based on exposure to single antibiotics (n=92) and drug combinations (n=40), as well as different experimental settings (e.g. static/traditional dynamic/hollow-fibre/animal time-kill models, n=90/27/32/11). An interactive, fully searchable table summarizes the details of each model, namely variants and mechanistic elements of PKPD submodels capturing observed bacterial growth, regrowth, drug effects and interactions. Furthermore, the review highlights the main purposes of PKPD model development, including the translation of preclinical PKPD to clinical settings, and the assessment of varied dosing regimens and patient characteristics for their impact on clinical antibiotic effects. In summary, this comprehensive overview of PKPD models will assist in identifying PKPD modelling strategies to describe growth, killing, regrowth and interaction patterns for pathogen-antibiotic combinations over time, and ultimately facilitate model-informed antibiotic translation, dosing and drug development., Competing Interests: Declaration of competing interests None declared., (Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: Flucloxacillin is a β-lactam penicillin commonly used in the treatment of bone and soft tissue infections. In a recent porcine study, we found surprisingly low time for which the free concentration was maintained above the minimal inhibitory concentration (fT>MIC) in bone and soft tissue, following flucloxacillin oral (PO) and intravenous (IV) administration at 1g every 6h (q6h). In addition to plasma, sampling was obtained from subcutaneous tissue, knee joint, cancellous bone and cortical bone, using microdialysis. To identify flucloxacillin dosing regimens that result in theoretically therapeutic concentrations, we developed a population pharmacokinetic (PK) model for the porcine data, and combined it with a human flucloxacillin population PK model for simulations., Methods: A four-compartment model was developed, and various dosing regimens and modes of administration were simulated. Predicted concentrations were compared to %fT>MIC (0.5 mg/L and 2 mg/L)., Results: Continuous infusion (CI) resulted in higher %fT>MIC compared to intermittent administration. For intermittent IV dosing (4, 8 and 12g/24h), fT>MIC (0.5 mg/L) was ≥70% in plasma, and ranged between 42-96% in the sampled tissue in a typical individual. By applying CI, 4g/day was sufficient to achieve ≥98% fT>MIC (0.5 mg/L) in all sampled tissues. For MIC 2 mg/L, ≥50% fT>MIC was only achieved in plasma at CI 8 and 12g/24h and IV 3g q6h., Conclusions: To reach efficacious flucloxacillin bone and tissue concentrations, dose increment or continuous infusion needs to be considered., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: Mortality among patients with carbapenem-resistant Acinetobacter baumannii (CRAB) infections varies between studies. We examined whether in vivo fitness of CRAB strains is associated with clinical outcomes in patients with CRAB infections., Methods: Isolates were collected from patients enrolled in the AIDA trial with hospital-acquired pneumonia, bloodstream infections and/or urinary tract infections caused by CRAB. The primary outcome was 14-day clinical failure, defined as failure to meet all criteria: alive; haemodynamically stable; improved or stable Sequential Organ Failure Assessment (SOFA) score; improved or stable oxygenation; and microbiological cure of bacteraemia. The secondary outcome was 14-day mortality. We tested in vivo growth using a neutropenic murine thigh infection model. Fitness was defined based on the CFU count 24 hours after injection of an inoculum of 10 5  CFU. We used mixed-effects logistic regression to test the association between fitness and the two outcomes., Results: The sample included 266 patients; 215 (80.8%) experienced clinical failure. CRAB fitness ranged from 5.23 to 10.08 log CFU/g. The odds of clinical failure increased by 62% for every 1-log CFU/g increase in fitness (OR 1.62, 95% CI 1.04-2.52). After adjusting for age, Charlson score, SOFA score and acquisition in the intensive care unit, fitness remained significant (adjusted OR 1.63, 95% CI 1.03-2.59). CRAB fitness had a similar effect on 14-day mortailty, although the association was not statistically significant (OR 1.56, 95% CI 0.95-2.57). It became significant after adjusting for age, Charlson score, SOFA score and recent surgery (adjusted OR 1.88, 95% CI 1.09-3.25)., Conclusions: In vivo CRAB fitness was associated with clinical failure in patients with CRAB infection., (Copyright © 2021 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Background: The clinical-stage drug candidate EBL-1003 (apramycin) represents a distinct new subclass of aminoglycoside antibiotics for the treatment of drug-resistant infections. It has demonstrated best-in-class coverage of resistant isolates, and preclinical efficacy in lung infection models. However, preclinical evidence for its utility in other disease indications has yet to be provided. Here we studied the therapeutic potential of EBL-1003 in the treatment of complicated urinary tract infection and acute pyelonephritis (cUTI/AP)., Methods: A combination of data-base mining, antimicrobial susceptibility testing, time-kill experiments, and four murine infection models was used in a comprehensive assessment of the microbiological coverage and efficacy of EBL-1003 against Gram-negative uropathogens. The pharmacokinetics and renal toxicology of EBL-1003 in rats was studied to assess the therapeutic window of EBL-1003 in the treatment of cUTI/AP., Findings: EBL-1003 demonstrated broad-spectrum activity and rapid multi-log CFU reduction against a phenotypic variety of bacterial uropathogens including aminoglycoside-resistant clinical isolates. The basicity of amines in the apramycin molecule suggested a higher increase in positive charge at urinary pH when compared to gentamicin or amikacin, resulting in sustained drug uptake and bactericidal activity, and consequently in potent efficacy in mouse infection models. Renal pharmacokinetics, biomarkers for toxicity, and kidney histopathology in adult rats all indicated a significantly lower nephrotoxicity of EBL-1003 than of gentamicin., Interpretation: This study provides preclinical proof-of-concept for the efficacy of EBL-1003 in cUTI/AP. Similar efficacy but lower nephrotoxicity of EBL-1003 in comparison to gentamicin may thus translate into a higher safety margin and a wider therapeutic window in the treatment of cUTI/API., Funding: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section., Competing Interests: Declaration of Competing Interest Authors ECB, DC, and SNH are co-founders of and shareholders in Juvabis AG. All other authors declare no conflict of interest., (Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objectives: Novel therapeutics are urgently required for the treatment of carbapenem-resistant Acinetobacter baumannii (CRAB) causing critical infections with high mortality. Here we assessed the therapeutic potential of the clinical-stage drug candidate EBL-1003 (crystalline free base of apramycin) in the treatment of CRAB lung infections., Methods: The genotypic and phenotypic susceptibility of CRAB clinical isolates to aminoglycosides and colistin was assessed by database mining and broth microdilution. The therapeutic potential was assessed by target attainment simulations on the basis of time-kill kinetics, a murine lung infection model, comparative pharmacokinetic analysis in plasma, epithelial lining fluid (ELF) and lung tissue, and pharmacokinetic/pharmacodynamic (PKPD) modelling., Results: Resistance gene annotations of 5451 CRAB genomes deposited in the National Database of Antibiotic Resistant Organisms (NDARO) suggested >99.9% of genotypic susceptibility to apramycin. Low susceptibility to standard-of-care aminoglycosides and high susceptibility to EBL-1003 were confirmed by antimicrobial susceptibility testing of 100 A. baumannii isolates. Time-kill experiments and a mouse lung infection model with the extremely drug-resistant CRAB strain AR Bank #0282 resulted in rapid 4-log CFU reduction both in vitro and in vivo. A single dose of 125 mg/kg EBL-1003 in CRAB-infected mice resulted in an AUC of 339 h × μg/mL in plasma and 299 h × μg/mL in ELF, suggesting a lung penetration of 88%. PKPD simulations suggested a previously predicted dose of 30 mg/kg in patients (creatinine clearance (CLCr) = 80 mL/min) to result in >99% probability of -2 log target attainment for MICs up to 16 μg/mL., Conclusions: This study provides proof of concept for the efficacy of EBL-1003 in the treatment of CRAB lung infections. Broad in vitro coverage, rapid killing, potent in vivo efficacy, and a high probability of target attainment render EBL-1003 a strong therapeutic candidate for a priority pathogen for which treatment options are very limited., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Apramycin represents a subclass of aminoglycoside antibiotics that has been shown to evade almost all mechanisms of clinically relevant aminoglycoside resistance. Model-informed drug development may facilitate its transition from preclinical to clinical phase. This study explored the potential of pharmacokinetic/pharmacodynamic (PK/PD) modeling to maximize the use of in vitro time-kill and in vivo preclinical data for prediction of a human efficacious dose (HED) for apramycin. PK model parameters of apramycin from four different species (mouse, rat, guinea pig, and dog) were allometrically scaled to humans. A semimechanistic PK/PD model was developed from the rich in vitro data on four Escherichia coli strains and subsequently the sparse in vivo efficacy data on the same strains were integrated. An efficacious human dose was predicted from the PK/PD model and compared with the classical PK/PD index methodology and the aminoglycoside dose similarity. One-compartment models described the PK data and human values for clearance and volume of distribution were predicted to 7.07 L/hour and 26.8 L, respectively. The required fAUC/MIC (area under the unbound drug concentration-time curve over MIC ratio) targets for stasis and 1-log kill in the thigh model were 34.5 and 76.2, respectively. The developed PK/PD model predicted the efficacy data well with strain-specific differences in susceptibility, maximum bacterial load, and resistance development. All three dose prediction approaches supported an apramycin daily dose of 30 mg/kg for a typical adult patient. The results indicate that the mechanistic PK/PD modeling approach can be suitable for HED prediction and serves to efficiently integrate all available efficacy data with potential to improve predictive capacity., (© 2020 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Therapeutic drug monitoring (TDM) and model-informed precision dosing (MIPD) have evolved as important tools to inform rational dosing of antibiotics in individual patients with infections. In particular, critically ill patients display altered, highly variable pharmacokinetics and often suffer from infections caused by less susceptible bacteria. Consequently, TDM has been used to individualize dosing in this patient group for many years. More recently, there has been increasing research on the use of MIPD software to streamline the TDM process, which can increase the flexibility and precision of dose individualization but also requires adequate model validation and re-evaluation of existing workflows. In parallel, new minimally invasive and noninvasive technologies such as microneedle-based sensors are being developed, which-together with MIPD software-have the potential to revolutionize how patients are dosed with antibiotics. Nonetheless, carefully designed clinical trials to evaluate the benefit of TDM and MIPD approaches are still sparse, but are critically needed to justify the implementation of TDM and MIPD in clinical practice. The present review summarizes the clinical pharmacology of antibiotics, conventional TDM and MIPD approaches, and evidence of the value of TDM/MIPD for aminoglycosides, beta-lactams, glycopeptides, and linezolid, for which precision dosing approaches have been recommended., (© 2021 The Authors. Clinical Pharmacology & Therapeutics published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Background: Population external validity is the extent to which an experimental study results can be generalized from a specific sample to a defined population. In order to apply the results of a study, we should be able to assess its population external validity. We performed an investigator-initiated randomized controlled trial (RCT) (AIDA study), which compared colistin-meropenem combination therapy to colistin monotherapy in the treatment of patients infected with carbapenem-resistant Gram-negative bacteria. In order to examine the study's population external validity and to substantiate the use of AIDA study results in clinical practice, we performed a concomitant observational trial., Methods: The study was conducted between October 1st, 2013 and January 31st, 2017 (during the RCTs recruitment period) in Greece, Israel and Italy. Patients included in the observational arm of the study have fulfilled clinical and microbiological inclusion criteria but were excluded from the RCT due to receipt of colistin for > 96 h, refusal to participate, or prior inclusion in the RCT. Non-randomized cases were compared to randomized patients. The primary outcome was clinical failure at 14 days of infection onset., Results: Analysis included 701 patients. Patients were infected mainly with Acinetobacter baumannii [78.2% (548/701)]. The most common reason for exclusion was refusal to participate [62% (183/295)]. Non-randomized and randomized patients were similar in most of the demographic and background parameters, though randomized patients showed minor differences towards a more severe infection. Combination therapy was less common in non-randomized patients [31.9% (53/166) vs. 51.2% (208/406), p = 0.000]. Randomized patients received longer treatment of colistin [13 days (IQR 10-16) vs. 8.5 days (IQR 0-15), p = 0.000]. Univariate analysis showed that non-randomized patients were more inclined to clinical failure on day 14 from infection onset [82% (242/295) vs. 75.5% (307/406), p = 0.042]. After adjusting for other variables, non-inclusion was not an independent risk factor for clinical failure at day 14., Conclusion: The similarity between the observational arm and RCT patients has strengthened our confidence in the population external validity of the AIDA trial. Adding an observational arm to intervention studies can help increase the population external validity and improve implementation of study results in clinical practice., Trial Registration: The trial was registered with ClinicalTrials.gov, number NCT01732250 on November 22, 2012.

This mini-review discusses the pharmacodynamics of immune-related biomarkers in the area of bacterial infectious diseases that could be of interest from a pharmacokinetic (PK) and pharmacokinetic/pharmacodynamic (PK/PD) perspective in the evaluation of treatment effects. The host response to an infection is often poorly defined both in preclinical assessments and in clinical practice when it comes to characterisation of PK and PK/PD relationships. Through population modelling, the time courses and variability of immune response variables can be quantified. Incorporation of such biomarker information into PK and PK/PD models may guide the evaluation of individual response to treatment (right antibiotic, more antibiotic, less antibiotic) and when to stop treatment. Furthermore, translation of results from preclinical systems to clinical scenarios may be improved with the incorporation of biomarker information. Potential biomarkers for these purposes are discussed and a few modelling examples are provided., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Objectives: To maximise efficacy and minimise toxicity, special considerations are required for antibiotic prescription in elderly patients. This review aims to provide practical suggestions for the optimal management of antibiotic therapy in elderly patients., Methods: This was a narrative review. A literature search of published articles in the last 15 years on antibiotics and elderly patients was performed using the Cochrane Library and PubMed electronic databases. The three priority areas were identified: (i) pharmacokinetics/pharmacodynamics (PK/PD) for optimising dosage regimens and route of administration; (ii) antibiotic dosages in some special subpopulations; and (iii) treatment considerations relating to different antibiotic classes and their adverse events., Results: Clinicians should understand the altered PK/PD of drugs in this population owing to co-morbid conditions and normal physiological changes associated with ageing. The body of evidence justifies the need for individualised dose selection, especially in patients with impaired renal and liver function. Clinicians should be aware of the major drug-drug interactions commonly observed in the elderly as well as potential side effects., Conclusion: Antibiotic therapy in the elderly requires a comprehensive approach, including strategies to improve appropriate antibiotic prescribing, limit their use for uncomplicated infections and ensure the attainment of an optimal PK/PD target. To this purpose, further studies involving the elderly are needed to better understand the PK of antibiotics. Moreover, it is necessary to assess the role therapeutic drug monitoring in guiding antibiotic therapy in elderly patients in order to evaluate its impact on clinical outcome., (Copyright © 2020. Published by Elsevier Ltd.)

Appropriate dosing of antibiotics is key in the treatment of bacterial infections to ensure clinical efficacy while avoiding toxic drug concentrations and minimizing emergence of resistance. As collection of sufficient clinical evidence is difficult for specific patient populations, infection types and pathogens, market authorization, dosing strategies and recommendations often rely on data obtained from in vitro and animal experiments. The aim of this review is to provide an overview of commonly used preclinical infection models, including their strengths and limitations. In vitro, static and dynamic time-kill experiments are the most frequently used methods for assessing pharmacokinetic/pharmacodynamic (PK/PD) associations. Limitations of in vitro models include the inability to account for the effects of the immune system, and uncertainties in clinically relevant bacterial concentrations, growth conditions and the implications of emerging resistant bacterial populations during experiments. Animal experiments, most commonly murine lung and thigh infections models, are considered a necessary link between in vitro data and the clinical situation. However, there are differences in pathophysiology, immunology, and PK between species. Mathematical modeling in which preclinical data are integrated with human population PK can facilitate translation of preclinical data to the patient's clinical situation. Moreover, PK/PD modeling and simulations can help in the design of clinical trials aiming to establish optimal dosing regimens to improve patient outcomes., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Antibiotic resistance is a major public health threat worldwide, and among others, about 80% of cystic fibrosis patients have chronic Pseudomonas aeruginosa (PA) lung infection resistant to many current antibiotics. Novel treatment strategies are therefore urgently needed. For lung infections, direct delivery of treatments to the site of action in the airway can achieve a higher local concentration with minimal systemic exposure and hence avoid risks of unwanted systemic adverse effects. Previously, a rat preclinical disease model for PA chronic lung infections has been reported. However, the role of this disease model in the development of new treatment has not been thoroughly evaluated. In this study, tobramycin (TOB) was used as a model antibiotic to evaluate the application of this preclinical disease model for PA treatments. The obtained data were used for pharmacokinetic-pharmacodynamic (PKPD) modeling. Plasma samples following pulmonary delivery of TOB via different dosing methods as well as growth and efficacy data from the chronic lung infection disease model following TOB treatments were collected for analysis and modeling. The developed PKPD model incorporates a semimechanistic description on biofilm development in chronic infections to allow the evaluation of drug action on bacteria in different states (i.e., planktonic, biofilm, and latent) and describes the available data from the efficacy study. The PKPD model can be used to support the application of the preclinical lung infection disease model by providing a quantitative description of the drug exposure-response relationship and a mechanistic platform to integrate all available PK and PKPD data with predictive capacity. With the support of appropriate experimental designs, the model can be further extended for other applications to, for instance, study the transition of bacteria between states and describe drug actions on biofilms.

The release of inflammatory bacterial products, such as lipopolysaccharide (LPS)/endotoxin, may be increased upon the administration of antibiotics. An improved quantitative understanding of endotoxin release and its relation to antibiotic exposure and bacterial growth/killing may be gained by an integrated analysis of these processes. The aim of this work was to establish a mathematical model that relates Escherichia coli growth/killing dynamics at various cefuroxime concentrations to endotoxin release in vitro Fifty-two time-kill experiments informed bacterial and endotoxin time courses and included both static (0×, 0.5×, 1×, 2×, 10×, and 50× MIC) and dynamic (0×, 15×, and 30× MIC) cefuroxime concentrations. A model for the antibiotic-bacterium interaction was established, and antibiotic-induced bacterial killing followed a sigmoidal Emax relation to the cefuroxime concentration (MIC-specific 50% effective concentration [EC 50 ], maximum antibiotic-induced killing rate [ E max ] = 3.26 h -1 and γ = 3.37). Endotoxin release was assessed in relation to the bacterial processes of growth, antibiotic-induced bacterial killing, and natural bacterial death and found to be quantitatively related to bacterial growth (0.000292 endotoxin units [EU]/CFU) and antibiotic-induced bacterial killing (0.00636 EU/CFU). Increased release following the administration of a second cefuroxime dose was described by the formation and subsequent antibiotic-induced killing of filaments (0.295 EU/CFU). Release due to growth was instantaneous, while release due to antibiotic-induced killing was delayed (mean transit time of 7.63 h). To conclude, the in vitro release of endotoxin is related to bacterial growth and antibiotic-induced killing, with higher rates of release upon the killing of formed filaments. Endotoxin release over 24 h is lowest when antibiotic exposure rapidly eradicates bacteria, while increased release is predicted to occur when growth and antibiotic-induced killing occur simultaneously., (Copyright © 2020 Thorsted et al.)

Objectives: Piperacillin is a β-lactam antimicrobial frequently used in critically ill patients with acute kidney injury treated with continuous renal replacement therapy (CRRT). However, data regarding piperacillin tissue concentrations in this patient population are limited. A prospective observational study was conducted of free piperacillin concentrations during a single 8-h dosing interval in plasma (8 samples) and subcutaneous tissue (SCT) (13 samples), in 10 patients treated with CRRT following piperacillin 4 g given every 8 h as intermittent administration over 3 min., Methods: A population pharmacokinetic model was developed using NONMEM 7.4.3, to simulate alternative administration modes and dosing regimens. SCT concentrations were obtained using microdialysis. Piperacillin concentrations were compared to the clinical breakpoint minimum inhibitory concentration (MIC) for Pseudomonas aeruginosa (16 mg/l), with evaluation of the following pharmacokinetic/pharmacodynamics targets: 50% fT > 1 × MIC, 100% fT > 1 × MIC, and 100% fT > 4 × MIC., Results: SCT concentrations were generally lower than plasma concentrations. For the target of 50% free time (fT) > 1 × MIC and 100% fT > 1 × MIC, piperacillin 4 g every 8 h resulted in probability of target attainment (PTA) >90% in both plasma and SCT. PTA > 90% for the target of 100% fT > 4 × MIC was only achieved for continuous infusion., Conclusions: Piperacillin 4 g every 8 h is likely to provide sufficient exposure in both plasma and SCT to treat P.aeruginosa infections in critically ill patients on CRRT, given that targets of 50% fT > 1 × MIC or 100% fT > 1 × MIC are adequate. However, if a more aggressive target of 100% fT > 4 × MIC is adopted, continuous infusion is needed., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: The β-lactam antibiotic piperacillin (in combination with tazobactam) is commonly chosen for empirical treatment of suspected bacterial infections. However, pharmacokinetic variability among patient populations and across ages leads to uncertainty when selecting a dosing regimen to achieve an appropriate pharmacodynamic target., Objectives: To guide dosing by establishing a population pharmacokinetic model for unbound piperacillin in febrile children receiving cancer chemotherapy, and to assess pharmacokinetic/pharmacodynamic target attainment (100% fT > 1×MIC and 50% fT > 4×MIC) and resultant exposure, across body weights., Methods: Forty-three children admitted for 89 febrile episodes contributed 482 samples to the pharmacokinetic analysis. The typical doses required for target attainment were compared for various dosing regimens, in particular prolonged infusions, across MICs and body weights., Results: A two-compartment model with inter-fever-episode variability in CL, and body weight included through allometry, described the data. A high CL of 15.4 L/h (70 kg) combined with high glomerular filtration rate (GFR) values indicated rapid elimination and hyperfiltration. The target of 50% fT > 4×MIC was achieved for an MIC of 4.0 mg/L in a typical patient with extended infusions of 2-3 (q6h) or 3-4 (q8h) h, at or below the standard adult dose (75 and 100 mg/kg/dose for q6h and q8h, respectively). Higher doses or continuous infusion were needed to achieve 100% fT > 1×MIC due to the rapid piperacillin elimination., Conclusions: The licensed dose for children with febrile neutropenia (80 mg/kg q6h as a 30 min infusion) performs poorly for attainment of fT>MIC pharmacokinetic/pharmacodynamic targets. Given the population pharmacokinetic profile, feasible dosing regimens with reasonable exposure are continuous infusion (100% fT > 1×MIC) or prolonged infusions (50% fT > 4×MIC)., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Background: We evaluated the association between mortality and colistin resistance in Acinetobacter baumannii infections and the interaction with antibiotic therapy., Methods: This is a secondary analysis of a randomized controlled trial of patients with carbapenem-resistant gram-negative bacterial infections treated with colistin or colistin-meropenem combination. We evaluated patients with infection caused by carbapenem-resistant A. baumannii (CRAB) identified as colistin susceptible (CoS) at the time of treatment and compared patients in which the isolate was confirmed as CoS with those whose isolates were retrospectively identified as colistin resistant (CoR) when tested by broth microdilution (BMD). The primary outcome was 28-day mortality., Results: Data were available for 266 patients (214 CoS and 52 CoR isolates). Patients with CoR isolates had higher baseline functional capacity and lower rates of mechanical ventilation than patients with CoS isolates. All-cause 28-day mortality was 42.3% (22/52) among patients with CoR strains and 52.8% (113/214) among patients with CoS isolates (P = .174). After adjusting for variables associated with mortality, the mortality rate was lower among patients with CoR isolates (odds ratio [OR], 0.285 [95% confidence interval {CI}, .118-.686]). This difference was associated with treatment arm: Mortality rates among patients with CoR isolates were higher in those randomized to colistin-meropenem combination therapy compared to colistin monotherapy (OR, 3.065 [95% CI, 1.021-9.202])., Conclusions: Colistin resistance determined by BMD was associated with lower mortality among patients with severe CRAB infections. Among patients with CoR isolates, colistin monotherapy was associated with a better outcome compared to colistin-meropenem combination therapy., Clinical Trials Registration: NCT01732250., (© The Author(s) 2018. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.)

Background: Data on piperacillin-tazobactam pharmacokinetics and optimal dosing in children with cancer and fever are limited. Our objective was to investigate piperacillin pharmacokinetics and the probability of target attainment (PTA) with standard intermittent administration (IA), and to simulate PTA in other dosing regimens., Procedure: This prospective pharmacokinetic study was conducted from April 2016 to January 2018. Children with cancer receiving empiric piperacillin-tazobactam to treat infections were included. Piperacillin-tazobactam 100 mg/kg was infused over 5 min every 8 hours (IA). An optimized sample schedule provided six blood samples per subject for piperacillin concentration determination. The evaluated targets included: (1) 100% time of free piperacillin concentration above the minimum inhibitory concentration (fT > MIC) and (2) 50% fT > 4× MIC. MIC 50 and MIC 90 were defined based on an intrainstitutional MIC range., Results: A total of 482 piperacillin concentrations were obtained from 43 children (aged 1-18 years) during 89 fever episodes. Standard IA resulted in insufficient target attainment, with significant differences in piperacillin pharmacokinetics for different body weights. Median fT > MIC was 61.2%, 53.5%, and 36.3% for MIC 50 (2.0 mg/L), MIC 90 (4.0 mg/L), and breakpoint for Pseudomonas aeruginosa (16.0 mg/L), respectively. Correspondingly, the median fT > 4× MIC was 43%, 36.3%, and 20.1%. Simulations showed that only continuous infusion reached a PTA of 95% for MIC = 16.0 mg/L, while extended infusion lasting half of the dosing interval reached a PTA of 95% for MIC ≤ 8 mg/L., Conclusions: Our data revealed insufficient PTA with standard IA of piperacillin-tazobactam in children with cancer and fever. Alternative dosing strategies, preferably continuous infusion, are required to ensure adequate PTA., (© 2019 Wiley Periodicals, Inc.)

Antibiotic resistance is a major public health threat worldwide. In particular, about 80% of cystic fibrosis patients have chronic Pseudomonas aeruginosa (PA) lung infection resistant to many current antibiotics. We are therefore developing a novel class of antivirulence agents, quorum sensing inhibitors (QSIs), which inhibit biofilm formation and sensitize PA to antibiotic treatments. For respiratory conditions, targeted delivery to the lung could achieve higher local concentrations with reduced risk of adverse systemic events. In this study, we report the pharmacokinetics of 3 prototype QSIs after pulmonary delivery, and the simultaneous analysis of the drug concentration-time profiles from bronchoalveolar lavage, lung homogenate and plasma samples, using a pharmacometric modeling approach. In addition to facilitating the direct comparison and selection of drug candidates, the developed model was used for dosing simulation studies to predict in vivo exposure following different dosing scenarios. The results show that systemic clearance has limited impact on local drug exposure in the lung after pulmonary delivery. Therefore, we suggest that novel QSIs designed for pulmonary delivery as targeted treatments for respiratory conditions should ideally have a long residence time in the lung for local efficacy with rapid clearance after systemic absorption for reduced risk of systemic adverse events., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Colistin is a polymyxin antibiotic used to treat patients infected with multidrug-resistant Gram-negative bacteria (MDR-GNB). The objective of this work was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model to predict tissue distribution of colistin in rat. The distribution of a drug in a tissue is commonly characterized by its tissue-to-plasma partition coefficient, K p . Colistin and its prodrug, colistin methanesulfonate (CMS) K p priors, were measured experimentally from rat tissue homogenates or predicted in silico. The PK parameters of both compounds were estimated fitting in vivo their plasma concentration-time profiles from six rats receiving an i.v. bolus of CMS. The variability in the data was quantified by applying a nonlinear mixed effect (NLME) modelling approach. A WB-PBPK model was developed assuming a well-stirred and perfusion-limited distribution in tissue compartments. Prior information on tissue distribution of colistin and CMS was investigated following three scenarios: K p was estimated using in silico K p priors (I) or K p was estimated using experimental K p priors (II) or K p was fixed to the experimental values (III). The WB-PBPK model best described colistin and CMS plasma concentration-time profiles in scenario II. Colistin-predicted concentrations in kidneys in scenario II were higher than in other tissues, which was consistent with its large experimental K p prior. This might be explained by a high affinity of colistin for renal parenchyma and active reabsorption into the proximal tubular cells. In contrast, renal accumulation of colistin was not predicted in scenario I. Colistin and CMS clearance estimates were in agreement with published values. The developed model suggests using experimental priors over in silico K p priors for kidneys to provide a better prediction of colistin renal distribution. Such models might serve in drug development for interspecies scaling and investigate the impact of disease state on colistin disposition., (© 2018 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).)

Background: Colistin-carbapenem combinations are synergistic in vitro against carbapenem-resistant Gram-negative bacteria. We aimed to test whether combination therapy improves clinical outcomes for adults with infections caused by carbapenem-resistant or carbapenemase-producing Gram-negative bacteria., Methods: A randomised controlled superiority trial was done in six hospitals in Israel, Greece, and Italy. We included adults with bacteraemia, ventilator-associated pneumonia, hospital-acquired pneumonia, or urosepsis caused by carbapenem-non-susceptible Gram-negative bacteria. Patients were randomly assigned (1:1) centrally, by computer-generated permuted blocks stratified by centre, to intravenous colistin (9-million unit loading dose, followed by 4·5 million units twice per day) or colistin with meropenem (2-g prolonged infusion three times per day). The trial was open-label, with blinded outcome assessment. Treatment success was defined as survival, haemodynamic stability, improved or stable Sequential Organ Failure Assessment score, stable or improved ratio of partial pressure of arterial oxygen to fraction of expired oxygen for patients with pneumonia, and microbiological cure for patients with bacteraemia. The primary outcome was clinical failure, defined as not meeting all success criteria by intention-to-treat analysis, at 14 days after randomisation. This trial is registered at ClinicalTrials.gov, number NCT01732250, and is closed to accrual., Findings: Between Oct 1, 2013, and Dec 31, 2016, we randomly assigned 406 patients to the two treatment groups. Most patients had pneumonia or bacteraemia (355/406, 87%), and most infections were caused by Acinetobacter baumannii (312/406, 77%). No significant difference between colistin monotherapy (156/198, 79%) and combination therapy (152/208, 73%) was observed for clinical failure at 14 days after randomisation (risk difference -5·7%, 95% CI -13·9 to 2·4; risk ratio [RR] 0·93, 95% CI 0·83-1·03). Results were similar among patients with A baumannii infections (RR 0·97, 95% CI 0·87-1·09). Combination therapy increased the incidence of diarrhoea (56 [27%] vs 32 [16%] patients) and decreased the incidence of mild renal failure (37 [30%] of 124 vs 25 [20%] of 125 patients at risk of or with kidney injury)., Interpretation: Combination therapy was not superior to monotherapy. The addition of meropenem to colistin did not improve clinical failure in severe A baumannii infections. The trial was unpowered to specifically address other bacteria., Funding: EU AIDA grant Health-F3-2011-278348., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Predicting competition between antibiotic-susceptible wild-type (WT) and less susceptible mutant (MT) bacteria is valuable for understanding how drug concentrations influence the emergence of resistance. Pharmacokinetic/pharmacodynamic (PK/PD) models predicting the rate and extent of takeover of resistant bacteria during different antibiotic pressures can thus be a valuable tool in improving treatment regimens. The aim of this study was to evaluate a previously developed mechanism-based PK/PD model for its ability to predict in vitro mixed-population experiments with competition between Escherichia coli (E. coli) WT and three well-defined E. coli resistant MTs when exposed to ciprofloxacin. Model predictions for each bacterial strain and ciprofloxacin concentration were made for in vitro static and dynamic time-kill experiments measuring CFU (colony forming units)/mL up to 24 h with concentrations close to or below the minimum inhibitory concentration (MIC), as well as for serial passage experiments with concentrations well below the MIC measuring ratios between the two strains with flow cytometry. The model was found to reasonably well predict the initial bacterial growth and killing of most static and dynamic time-kill competition experiments without need for parameter re-estimation. With parameter re-estimation of growth rates, an adequate fit was also obtained for the 6-day serial passage competition experiments. No bacterial interaction in growth was observed. This study demonstrates the predictive capacity of a PK/PD model and further supports the application of PK/PD modelling for prediction of bacterial kill in different settings, including resistance selection., (Copyright © 2017 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.)

Background: Pharmacokinetic/pharmacodynamic (PKPD) models developed based on data from in vitro time-kill experiments have been suggested to contribute to more efficient drug development programmes and better dosing strategies for antibiotics. However, for satisfactory predictions such models would have to show good extrapolation properties., Objectives: To evaluate if a previously described mechanism-based PKPD model was able also to predict drug efficacy for higher bacterial densities and across bacterial strains., Methods: A PKPD model describing the efficacy of ciprofloxacin on Escherichia coli was evaluated. The predictive performance of the model was evaluated across several experimental conditions with respect to: (i) bacterial start inoculum ranging from the standard of ∼106 cfu/mL up to late stationary-phase cultures; and (ii) efficacy for seven additional strains (three laboratory and four clinical strains), not included during the model development process, based only on information regarding their MIC. Model predictions were performed according to the intended experimental protocol and later compared with observed bacterial counts., Results: The mechanism-based PKPD model structure developed based on data from standard start inoculum experiments was able to accurately describe the inoculum effect. The model successfully predicted the time course of drug efficacy for additional laboratory and clinical strains based on only the MIC values. The model structure was further developed to better describe the stationary phase data., Conclusions: This study supports the use of mechanism-based PKPD models based on preclinical data for predictions of untested scenarios., (© The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Colistin adheres to a range of materials, including plastics in labware. The loss caused by adhesion influences an array of methods detrimentally, including MIC assays and in vitro time-kill experiments. The aim of this study was to characterize the extent and time course of colistin loss in different types of laboratory materials during a simulated time-kill experiment without bacteria or plasma proteins present. Three types of commonly used large test tubes, i.e., soda-lime glass, polypropylene, and polystyrene, were studied, as well as two different polystyrene microplates and low-protein-binding microtubes. The tested concentration range was 0.125 to 8 mg/liter colistin base. Exponential one-phase and two-phase functions were fitted to the data, and the adsorption of colistin to the materials was modeled with the Langmuir adsorption model. In the large test tubes, the measured start concentrations ranged between 44 and 102% of the expected values, and after 24 h, the concentrations ranged between 8 and 90%. The half-lives of colistin loss were 0.9 to 12 h. The maximum binding capacities of the three materials ranged between 0.4 and 1.1 μg/cm 2 , and the equilibrium constants ranged between 0.10 and 0.54 ml/μg. The low-protein-binding microtubes showed start concentrations between 63 and 99% and concentrations at 24 h of between 59 and 90%. In one of the microplates, the start concentrations were below the lower limit of quantification at worst. In conclusion, to minimize the effect of colistin loss due to adsorption, our study indicates that low-protein-binding polypropylene should be used when possible for measuring colistin concentrations in experimental settings, and the results discourage the use of polystyrene. Furthermore, when diluting colistin in protein-free media, the number of dilution steps should be minimized., (Copyright © 2017 American Society for Microbiology.)

Background: In view of the paucity of clinical evidence, in vitro studies are needed to find antibiotic combinations effective against multidrug-resistant Gram-negative bacteria. Interpretation of in vitro effects is usually based on bacterial growth after 24 h in time-kill and checkerboard experiments. However, the clinical relevance of the effects observed in vitro is not established. In this study we explored alternative output parameters to assess the activities of colistin and meropenem against Pseudomonas aeruginosa and Acinetobacter baumannii., Methods: Four strains each of P. aeruginosa and A. baumannii were exposed to colistin and meropenem, alone and in combination, in 8 h dynamic time-kill experiments. Initial (1 h), maximum and 8 h bacterial reductions and the area under the bacterial time-kill curve were evaluated. Checkerboards, interpreted based on fractional inhibitory concentration indices after 24 h, were performed for comparison., Results: In the time-kill experiments, the combination resulted in enhanced 1 h, maximum and 8 h bacterial reductions against 2, 3 and 5 of 8 strains, respectively, as compared to the single drugs. A statistically significant reduction in the area under the time-kill curve was observed for three strains. In contrast, the checkerboards did not identify synergy for any of the strains., Conclusions: Combination effects were frequently found with colistin and meropenem against P. aeruginosa and A. baumannii in time-kill experiments but were not detected with the checkerboard method. We propose that the early dynamics of bacterial killing and growth, which may be of great clinical importance, should be considered in future in vitro combination studies.

Biofilm formation plays an important role in the persistence of pulmonary infections, for example, in cystic fibrosis patients. So far, little is known about the antimicrobial lung disposition in biofilm-associated pneumonia. This study aimed to evaluate, by microdialysis, ciprofloxacin (CIP) penetration into the lungs of healthy and Pseudomonas aeruginosa biofilm-infected rats and to develop a comprehensive model to describe the CIP disposition under both conditions. P. aeruginosa was immobilized into alginate beads and intratracheally inoculated 14 days before CIP administration (20 mg/kg of body weight). Plasma and microdialysate were sampled from different animal groups, and the observations were evaluated by noncompartmental analysis (NCA) and population pharmacokinetic (popPK) analysis. The final model that successfully described all data consisted of an arterial and a venous central compartment and two peripheral distribution compartments, and the disposition in the lung was modeled as a two-compartment model structure linked to the venous compartment. Plasma clearance was approximately 32% lower in infected animals, leading to a significantly higher level of plasma CIP exposure (area under the concentration-time curve from time zero to infinity, 27.3 ± 12.1 μg · h/ml and 13.3 ± 3.5 μg · h/ml in infected and healthy rats, respectively). Despite the plasma exposure, infected animals showed a four times lower tissue concentration/plasma concentration ratio (lung penetration factor = 0.44 and 1.69 in infected and healthy rats, respectively), and lung clearance (CL lung ) was added to the model for these animals (CL lung = 0.643 liters/h/kg) to explain the lower tissue concentrations. Our results indicate that P. aeruginosa biofilm infection reduces the CIP free interstitial lung concentrations and increases plasma exposure, suggesting that plasma concentrations alone are not a good surrogate of lung concentrations., (Copyright © 2017 American Society for Microbiology.)

The purpose of this study was to develop a whole-body physiologically based pharmacokinetic (WB-PBPK) model for ciprofloxacin for ICU patients, based on only plasma concentration data. In a next step, tissue and organ concentration time profiles in patients were predicted using the developed model. The WB-PBPK model was built using a non-linear mixed effects approach based on data from 102 adult intensive care unit patients. Tissue to plasma distribution coefficients (Kp) were available from the literature and used as informative priors. The developed WB-PBPK model successfully characterized both the typical trends and variability of the available ciprofloxacin plasma concentration data. The WB-PBPK model was thereafter combined with a pharmacokinetic-pharmacodynamic (PKPD) model, developed based on in vitro time-kill data of ciprofloxacin and Escherichia coli to illustrate the potential of this type of approach to predict the time-course of bacterial killing at different sites of infection. The predicted unbound concentration-time profile in extracellular tissue was driving the bacterial killing in the PKPD model and the rate and extent of take-over of mutant bacteria in different tissues were explored. The bacterial killing was predicted to be most efficient in lung and kidney, which correspond well to ciprofloxacin's indications pneumonia and urinary tract infections. Furthermore, a function based on available information on bacterial killing by the immune system in vivo was incorporated. This work demonstrates the development and application of a WB-PBPK-PD model to compare killing of bacteria with different antibiotic susceptibility, of value for drug development and the optimal use of antibiotics .

Traditionally, reduced daily doses of colistin methanesulphonate (CMS) in critically ill patients receiving continuous venovenous haemodiafiltration (CVVHDF) have resulted in suboptimal colistin concentrations. The necessity of a loading dose (LD) at treatment initiation has been proposed. A LD of 9 million IU (MU) [ca. 270 mg of colistin base activity (CBA)] was administrated with a maintenance dose of 4.5 MU (ca. 140 mg CBA) every 12 h (q12h) to eight critically ill patients receiving renal replacement therapy. Blood samples were collected immediately before and at different time intervals after the LD and the fourth dose, whilst pre-filter and post-filter blood samples were also collected. CMS and colistin concentrations were determined using an LC-MS/MS assay. Median maximum observed concentrations after the LD were 22.1 mg/L for CMS and 1.55 mg/L for colistin, whereas during maintenance dosing the corresponding values were 12.6 mg/L and 1.72 mg/L, respectively. CVVHDF clearance was determined as 2.98 L/h for colistin, equivalent to 62% of total apparent colistin clearance in CVVHDF patients. Both CMS and colistin were cleared by CVVHDF. Application of a LD of 9 MU CMS resulted in more rapid achievement of the target colistin concentration. Following implementation of a predicted pharmacokinetic model on plasma CMS/colistin concentrations, a LD of 12 MU CMS appears more appropriate, whilst a CMS maintenance dosage of at least 6.5-7.5 MU q12h is suggested in patients undergoing CVVHDF. However, further clinical studies are warranted to assess the safety of a LD of 12 MU CMS in patients receiving CVVHDF., (Copyright © 2016 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.)

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., (© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

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.

Objectives: Combination therapy can be a strategy to ensure effective bacterial killing when treating Pseudomonas aeruginosa, a Gram-negative bacterium with high potential for developing resistance. The aim of this study was to develop a pharmacokinetic/pharmacodynamic (PK/PD) model that describes the in vitro bacterial time-kill curves of colistin and meropenem alone and in combination for one WT and one meropenem-resistant strain of P. aeruginosa., Methods: In vitro time-kill curve experiments were conducted with a P. aeruginosa WT (ATCC 27853) (MICs: meropenem 1 mg/L; colistin 1 mg/L) and a meropenem-resistant type (ARU552) (MICs: meropenem 16 mg/L; colistin 1.5 mg/L). PK/PD models characterizing resistance were fitted to the observed bacterial counts in NONMEM. The final model was applied to predict the bacterial killing of ARU552 for different combination dosages of colistin and meropenem., Results: A model with compartments for growing and resting bacteria, where the bacterial killing by colistin reduced with continued exposure and a small fraction (0.15%) of the start inoculum was resistant to meropenem, characterized the bactericidal effect and resistance development of the two antibiotics. For a typical patient, a loading dose of colistin combined with a high dose of meropenem (2000 mg q8h) was predicted to result in a pronounced kill of the meropenem-resistant strain over 24 h., Conclusions: The developed PK/PD model successfully described the time course of bacterial counts following exposures to colistin and meropenem, alone and in combination, for both strains, and identified a dynamic drug interaction. The study illustrates the application of a PK/PD model and supports high-dose combination therapy of colistin and meropenem to overcome meropenem resistance., (© The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Introduction: The emergence of antibiotic-resistant bacteria has driven renewed interest in older antibacterials, including colistin. Previous studies have shown that colistin is less effective and more toxic than modern antibiotics. In vitro synergy studies and clinical observational studies suggest a benefit of combining colistin with a carbapenem. A randomised controlled study is necessary for clarification., Methods and Analysis: This is a multicentre, investigator-initiated, open-label, randomised controlled superiority 1:1 study comparing colistin monotherapy with colistin-meropenem combination therapy for infections caused by carbapenem-resistant Gram-negative bacteria. The study is being conducted in 6 centres in 3 countries (Italy, Greece and Israel). We include patients with hospital-associated and ventilator-associated pneumonia, bloodstream infections and urosepsis. The primary outcome is treatment success at day 14, defined as survival, haemodynamic stability, stable or improved respiratory status for patients with pneumonia, microbiological cure for patients with bacteraemia and stability or improvement of the Sequential Organ Failure Assessment (SOFA) score. Secondary outcomes include 14-day and 28-day mortality as well as other clinical end points and safety outcomes. A sample size of 360 patients was calculated on the basis of an absolute improvement in clinical success of 15% with combination therapy. Outcomes will be assessed by intention to treat. Serum colistin samples are obtained from all patients to obtain population pharmacokinetic models. Microbiological sampling includes weekly surveillance samples with analysis of resistance mechanisms and synergy. An observational trial is evaluating patients who met eligibility requirements but were not randomised in order to assess generalisability of findings., Ethics and Dissemination: The study was approved by ethics committees at each centre and informed consent will be obtained for all patients. The trial is being performed under the auspices of an independent data and safety monitoring committee and is included in a broad dissemination strategy regarding revival of old antibiotics., Trial Registration Number: NCT01732250 and 2012-004819-31; Pre-results., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Colistin has been revived, in the era of extensively drug-resistant (XDR) Gram-negative infections, as the last-resort treatment in critically ill patients. Recent studies focusing on the optimal dosing strategy of colistin have demonstrated the necessity of a loading dose at treatment initiation (D. Plachouras, M. Karvanen, L. E. Friberg, E. Papadomichelakis, A. Antoniadou, I. Tsangaris, I. Karaiskos, G. Poulakou, F. Kontopidou, A. Armaganidis, O. Cars, and H. Giamarellou, Antimicrob Agents Chemother 53:3430-3436, 2009, http://dx.doi.org/10.1128/AAC.01361-08; A. F. Mohamed, I. Karaiskos, D. Plachouras, M. Karvanen, K. Pontikis, B. Jansson, E. Papadomichelakis, A. Antoniadou, H. Giamarellou, A. Armaganidis, O. Cars, and L. E. Friberg, Antimicrob Agents Chemother 56:4241- 4249, 2012, http://dx.doi.org/10.1128/AAC.06426-11; S. M. Garonzik, J. Li, V. Thamlikitkul, D. L. Paterson, S. Shoham, J. Jacob, F. P. Silveira, A. Forrest, and R. L. Nation, Antimicrob Agents Chemother 55:3284-3294, 2011, http://dx.doi.org/10.1128/AAC.01733-10). In 19 critically ill patients with suspected or microbiologically documented infections caused by XDR Gram-negative strains, a loading dose of 9 MU colistin methanesulfonate (CMS) (∼ 270 mg colistin base activity) was administered with a maintenance dose of 4.5 MU every 12 h, commenced after 24 h. Patients on renal replacement were excluded. CMS infusion was given over 30 min or 1 h. Repeated blood sampling was performed after the loading dose and after the 5th or 6th dose. Colistin concentrations and measured CMS, determined after hydrolization to colistin and including the partially sulfomethylated derivatives, were determined with a liquid chromatography-tandem mass spectrometry assay. Population pharmacokinetic analysis was conducted in NONMEM with the new data combined with data from previous studies. Measured colistimethate concentrations were described by 4 compartments for distribution and removal of sulfomethyl groups, while colistin disposition followed a 1-compartment model. The average observed maximum colistin A plus B concentration was 2.65 mg/liter after the loading dose (maximum time was 8 h). A significantly higher availability of the measured A and B forms of colistimethate and colistin explained the higher-than-expected concentrations in the present study compared to those in previous studies. Creatinine clearance was a time-varying covariate of colistimethate clearance. The incidence of acute renal injury was 20%., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Inter occasion variability (IOV) is of importance to consider in the development of a design where individual pharmacokinetic or pharmacodynamic parameters are of interest. IOV may adversely affect the precision of maximum a posteriori (MAP) estimated individual parameters, yet the influence of inclusion of IOV in optimal design for estimation of individual parameters has not been investigated. In this work two methods of including IOV in the maximum a posteriori Fisher information matrix (FIMMAP) are evaluated: (i) MAP occ-the IOV is included as a fixed effect deviation per occasion and individual, and (ii) POP occ-the IOV is included as an occasion random effect. Sparse sampling schedules were designed for two test models and compared to a scenario where IOV is ignored, either by omitting known IOV (Omit) or by mimicking a situation where unknown IOV has inflated the IIV (Inflate). Accounting for IOV in the FIMMAP markedly affected the designs compared to ignoring IOV and, as evaluated by stochastic simulation and estimation, resulted in superior precision in the individual parameters. In addition MAPocc and POP occ accurately predicted precision and shrinkage. For the investigated designs, the MAP occ method was on average slightly superior to POP occ and was less computationally intensive.

Objectives: In silico pharmacokinetic/pharmacodynamic (PK/PD) models can be developed based on data from in vitro time-kill experiments and can provide valuable information to guide dosing of antibiotics. The aim was to develop a mechanism-based in silico model that can describe in vitro time-kill experiments of Escherichia coli MG1655 WT and six isogenic mutants exposed to ciprofloxacin and to identify relationships that may be used to simplify future characterizations in a similar setting., Methods: In this study, we developed a mechanism-based PK/PD model describing killing kinetics for E. coli following exposure to ciprofloxacin. WT and six well-characterized mutants, with one to four clinically relevant resistance mutations each, were exposed to a wide range of static ciprofloxacin concentrations., Results: The developed model includes susceptible growing bacteria, less susceptible (pre-existing resistant) growing bacteria, non-susceptible non-growing bacteria and non-colony-forming non-growing bacteria. The non-colony-forming state was likely due to formation of filaments and was needed to describe data close to the MIC. A common model structure with different potency for bacterial killing (EC50) for each strain successfully characterized the time-kill curves for both WT and the six E. coli mutants., Conclusions: The model-derived mutant-specific EC50 estimates were highly correlated (r(2) = 0.99) with the experimentally determined MICs, implying that the in vitro time-kill profile of a mutant strain is reasonably well predictable by the MIC alone based on the model., (© The Author 2015. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Objectives: An optimized dosing regimen of the prodrug of colistin, colistin methanesulphonate (CMS), against resistant Pseudomonas aeruginosa is needed to ensure effective bacterial killing. The objectives of this study were to develop a pharmacokinetic (PK)/pharmacodynamic (PD) model that characterizes the time course of the antibacterial activity of colistin against P. aeruginosa in a static in vitro system and to perform simulations of different dosing regimens and dosing algorithms to evaluate the effect of interindividual variability and interoccasion variability in PK on bacterial killing., Methods: Static in vitro time-kill curve experiments were conducted on two different strains of P. aeruginosa (MIC 1 and 1.5 mg/L). Mechanism-based PK/PD models were fitted in NONMEM7 and the final model was combined with a previously developed population PK model of CMS and colistin to perform simulations of variability based on different dosing algorithms., Results: A model with compartments for growing and resting bacteria, with a function allowing the maximal bacterial killing of colistin to reduce upon increasing colistin exposure, characterized both the fast bactericidal effect and the adaptive resistance. The variability in PK was shown to translate into pronounced interoccasion variability in bacterial killing. A flat fixed loading dose was demonstrated to result in less variability than an algorithm based on weight., Conclusions: The developed PK/PD model described the growth, death and resistance development of P. aeruginosa in response to colistin for two different strains. Based on simulations, a flat fixed loading dose followed by an 8 or 12 hourly maintenance dose with an infusion duration of up to 2 h appeared adequate.

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.

This report describes the pharmacokinetics of colistin methanesulfonate (CMS) and colistin in five intensive care unit patients receiving continuous venovenous hemodiafiltration. For CMS, the mean maximum concentration of drug in plasma (C(max)) after the fourth dose was 6.92 mg/liter and total clearance (CL) 8.23 liters/h. For colistin, the mean concentration was 0.92 mg/liter and CL/metabolized fraction (f(m)) 18.91 liters/h. Colistin concentrations were below the current MIC breakpoints, and the area under the concentration-time curve for the free, unbound fraction of the drug over 24 h in the steady state divided by the MIC (fAUC/MIC) was lower than recommended, suggesting that a dosage regimen of 160 mg CMS every 8 h (q8h) is inadequate.

A previous pharmacokinetic study on dosing of colistin methanesulfonate (CMS) at 240 mg (3 million units [MU]) every 8 h indicated that colistin has a long half-life, resulting in insufficient concentrations for the first 12 to 48 h after initiation of treatment. A loading dose would therefore be beneficial. The aim of this study was to evaluate CMS and colistin pharmacokinetics following a 480-mg (6-MU) loading dose in critically ill patients and to explore the bacterial kill following the use of different dosing regimens obtained by predictions from a pharmacokinetic-pharmacodynamic model developed from an in vitro study on Pseudomonas aeruginosa. The unbound fractions of colistin A and colistin B were determined using equilibrium dialysis and considered in the predictions. Ten critically ill patients (6 males; mean age, 54 years; mean creatinine clearance, 82 ml/min) with infections caused by multidrug-resistant Gram-negative bacteria were enrolled in the study. The pharmacokinetic data collected after the first and eighth doses were analyzed simultaneously with the data from the previous study (total, 28 patients) in the NONMEM program. For CMS, a two-compartment model best described the pharmacokinetics, and the half-lives of the two phases were estimated to be 0.026 and 2.2 h, respectively. For colistin, a one-compartment model was sufficient and the estimated half-life was 18.5 h. The unbound fractions of colistin in the patients were 26 to 41% at clinical concentrations. Colistin A, but not colistin B, had a concentration-dependent binding. The predictions suggested that the time to 3-log-unit bacterial kill for a 480-mg loading dose was reduced to half of that for the dose of 240 mg.

Gentamicin is commonly used in the management of neonatal infections. Development of adaptive resistance is typical for aminoglycosides and reduces the antibacterial effect. There is, however, a lack of understanding of how this phenomenon influences the effect of different dosing schedules. The aim was to develop a pharmacokinetic-pharmacodynamic (PKPD) model that describes the time course of the bactericidal activity of gentamicin and its adaptive resistance and to investigate different dosing schedules in preterm and term newborn infants based on the developed model. In vitro time-kill curve experiments were conducted on a strain of Escherichia coli (MIC of 2 mg/liter). The gentamicin exposure was either constant (0.125 to 16 mg/liter) or dynamic (simulated concentration-time profiles in a kinetic system with peak concentrations of 2.0, 3.9, 7.8, and 16 mg/liter given as single doses or as repeated doses every 6, 12, or 24 h). Semimechanistic PKPD models were fitted to the bacterial counts in the NONMEM (nonlinear mixed effects modeling) program. A model with compartments for growing and resting bacteria, with a function allowing the maximal bacterial killing of gentamicin to reduce with exposure, characterized both the fast bactericidal effect and the adaptive resistance. Despite a lower peak concentration, preterm neonates were predicted to have a higher bacterial killing effect than term neonates for the same per-kg dose because of gentamicin's longer half-life. The model supported an extended dosing interval of gentamicin in preterm neonates, and for all neonates, dosing intervals of 36 to 48 h were as effective as a 24-h dosing interval for the same total dose.

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.

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.

An analytical method for quantitation of colistin A and colistin B in plasma and culture medium is described. After protein precipitation with acetonitrile (ACN) containing 0.1% trifluoroacetic acid (TFA), the supernatants were diluted with 0.03% TFA. The compounds were separated on an Ultrasphere C18 column, 4.6 mm x 250 mm, 5 microm particle size with a mobile phase consisting of 25% ACN in 0.03% TFA and detected with tandem mass spectrometry. The instrument was operating in ESI negative ion mode and the precursor-product ion pairs were m/z 1167.7-->1079.6 for colistin A and m/z 1153.7-->1065.6 for colistin B. The lower limit of quantification (LLOQ) for 100 microL plasma was 19.4 and 10.5 ng/mL for colistin A and B, respectively, with CV <6.2% and accuracy <+/-12.6%. For culture medium (50 microL+50 microL plasma), LLOQ was 24.2 and 13.2 ng/mL for colistin A and B, respectively, with CV <11.4% and accuracy <+/-8.1%. The quick sample work-up method allows for determination of colistin A and B in clinical samples without causing hydrolysis of the prodrug colistin methanesulfonate (CMS).