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Objectives: To expand a translational pharmacokinetic-pharmacodynamic (PKPD) modelling approach for assessing the combined effect of polymyxin B and minocycline against Klebsiella pneumoniae., Methods: A PKPD model developed based on in vitro static time-kill experiments of one strain (ARU613) was first translated to characterize that of a more susceptible strain (ARU705), and thereafter to dynamic time-kill experiments (both strains) and to a murine thigh infection model (ARU705 only). The PKPD model was updated stepwise using accumulated data., Results: The same model structure could be used in each translational step, with parameters being re-estimated. Dynamic data were well predicted by static-data-based models. The in vitro - in vivo differences were primarily quantified as a change in polymyxin B effect: a lower killing rate constant in vivo compared to in vitro (concentration of 3 mg/L corresponds to 0.05 /h and 57 /h, respectively), and a slower adaptive resistance rate (the constant in vivo was 2.5% of that in vitro). There was no significant difference in polymyxin B - minocycline interaction functions. Predictions based on both in vitro and in vivo parameters indicated that the combination has a greater-than-monotherapy antibacterial effect in humans, forecasting a reduction of approximately 5 and 2 log 10 CFU/mL at 24 hours, respectively, under combined therapy, while in monotherapy the maximum bacterial load was reached., Conclusions: The study demonstrated the utility of the PKPD modelling approach to understand translation of antibiotic effects across experimental systems and showed a promising antibacterial effect of polymyxin B and minocycline in combination against K. pneumoniae., (Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

In vitro time-kill curve (TKC) experiments are an important part of the pharmacokinetic- pharmacodynamic (PKPD) characterisation of antibiotics. Traditional TKCs use Mueller-Hinton broth (MHB), which lacks specific plasma components that could potentially influence the bacterial growth and killing dynamics, and affect translation to in vivo. This study aimed to evaluate the impact of plasma on the PKPD characterisation of two antibiotics; cefazolin and clindamycin. TKC experiments were conducted in pure MHB, and MHB spiked with 20% and 70% human plasma. Plasma protein binding (PPB) data were available, and a linear model described cefazolin's PPB, while clindamycin's PPB was best described by a second-order polynomial model. PKPD models were developed based on pure MHB and described drug effects using an E max model, with consideration of adaptive resistance for cefazolin. The observed bacterial growth and killing in the plasma-spiked MHB TKC data was insufficiently described when applying the developed PPB and PKPD models. In plasma spiked MHB, a growth delay was observed, estimated to 0.25 h (20% plasma), or 2.90 h (70% plasma) for cefazolin, and 0.64 h (20% plasma), or 1.40 h (70% plasma) for clindamycin. Furthermore, the drug effect was higher than expected in plasma-spiked MHB, with bacterial stasis and/or killing at unbound concentrations below MIC, necessitating drug effect parameter scaling (C 50 for cefazolin, Hill coefficient for clindamycin). The findings highlight significant differences in bacterial growth and killing dynamics between pure MHB and plasma-spiked MHB and exemplify how PKPD modelling may be used to improve the translation of in vitro results., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2025 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Purpose: To investigate the pharmacokinetics (PK) of ceftazidime-avibactam (CAZ-AVI) in critically ill patients undergoing continuous venovenous hemodiafiltration (CVVHDF), and compare with a general phase III trial population., Methods: A prospective PK study was conducted in critically ill patients who received CVVHDF for acute kidney injury, treated with CAZ-AVI (1000/250 mg or 2000/500 mg q8h). Plasma and CVVHDF-circuit samples were collected to determine CAZ-AVI concentrations. Individual PK parameters at steady-state were estimated using non-compartmental analysis. For visual comparison, plasma concentrations from CVVHDF patients were overlaid with simulated data from patients not receiving CVVHDF based on previously developed population PK models., Results: A total of 35 plasma samples and 16 CVVHDF-circuit samples were obtained from four patients, with two patients sampled on two separate occasions. Median total clearance and volume of distribution were 4.54 L/h and 73.2 L for CAZ and 10.5 L/h and 102 L for AVI, respectively. Median contribution of CVVHDF to total clearance was 19.8% for CAZ and 5.3% for AVI. Observed CAZ-AVI PK profiles were generally within the 90% confidence interval of model predictions, but the observed concentrations were notably lower early (0-2 h) and higher later (4-8 h) in the dosing interval, suggesting a higher volume of distribution., Conclusions: These results suggest that the CAZ-AVI dose regimens used in this study can be applicable in critically ill patients undergoing CVVHDF, despite the different shape of the PK profiles observed in this population. Further research with a larger patient cohort is warranted to validate and refine these findings., Competing Interests: Declaration of competing interest H.G. has received speaker honoraria from Pfizer and MSD. I.K. has received speaker honoraria from Pfizer. Menarini and bioMérieux. All other authors declare no conflict of interest., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Objectives: Applying physiologically-based pharmacokinetic (PBPK) modelling in sepsis could help to better understand how PK changes are influenced by drug- and patient-related factors. We aimed to elucidate the influence of sepsis pathophysiology on the PK of meropenem by applying PBPK modelling., Methods: A whole-body meropenem PBPK model was developed and evaluated in healthy individuals, and renally impaired non-septic patients. Sepsis-induced physiological changes in body composition, organ blood flow, kidney function, albumin, and haematocrit were implemented according to a previously proposed PBPK sepsis model. Model performance was evaluated, and a local sensitivity analysis was conducted., Results: The model-predicted PK metrics (AUC, C max , CL, V ss ) were within 1.33-fold-error margin of published data for 87.5% of the simulated profiles in healthy individuals. In sepsis, the model provided good predictions for literature-digitised average plasma and tissue exposure data, where the model-predicted AUC was within 1.33-fold-error margin for 9 out 11 simulated study profiles. Furthermore, the model was applied to individual plasma concentration data from 52 septic patients, where the model-predicted AUC, C max , and CL had a fold-error ratio range of 0.98-1.12, with alignment of the predicted and observed variability. For V ss , the fold-error ratio was 0.81, and the model underpredicted the population variability. CL was sensitive to renal plasma clearance, and kidney volume, whereas V ss was sensitive to the unbound fraction, organ volume fraction of the interstitial compartment, and the organ volume., Conclusions: These findings may be extended to more diverse drug types and support a more mechanistic understanding of the effect of sepsis on drug exposure., Competing Interests: Declaration of competing interests None declared., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Carbapenem-resistant bacteria pose a threat to public health. Characterising the pharmacokinetics-pharmacodynamics (PKPD) of meropenem longitudinally in vivo against resistant bacteria could provide valuable information for development and translation of carbapenem-based therapies., Objectives: To assess the time course of meropenem effects in vivo against strains with high MIC to predict PK/PD indices and expected efficacy in patients using a modelling approach., Methods: A PKPD model was built on longitudinal bacterial count data to describe meropenem effects against six Escherichia coli and Klebsiella pneumoniae strains (MIC values 32-128 mg/L) in a 24 h mouse thigh infection model. The model was used to derive PK/PD indices from simulated studies in mice and to predict the efficacy of different infusion durations with high-dose meropenem (2 g q8 h/q12 h for normal/reduced kidney function) in patients., Results: Data from 592 mice were available for model development. The estimated meropenem concentration-dependent killing rate was not associated with differences in MIC. The fraction of time that unbound concentrations exceeded EC 50 (fT >EC50 , EC 50 = 1.01 mg/L) showed higher correlations than fT >MIC . For all investigated strains, bacteriostasis at 24 h was predicted for prolonged infusions of high-dose meropenem monotherapy in >90% of patients., Conclusions: The developed PKPD model successfully described bacterial growth and meropenem killing over time in the thigh infection model. For the investigated strains, the MIC, determined in vitro, or MIC-based PK/PD indices, did not predict in vivo response. Simulations suggested prolonged infusions of high-dose meropenem to be efficacious in patients infected by the studied strains., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

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.)

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.)

There has been accumulating interest in nebulised colistin methanesulfonate (CMS) for the treatment of ventilator-associated pneumonia (VAP). In this study, pulmonary and systemic pharmacokinetics following nebulisation of CMS at a dose of 3 MIU and 5 MIU, using a vibrating mesh nebuliser, for VAP caused by extensively drug-resistant Gram-negative pathogens was assessed. Blood samples and mini-bronchoalveolar lavage (mini-BAL) was performed post-dose at 1, 4 and 8 h. Concentrations of CMS and formed colistin in mini-BAL and plasma were determined by liquid chromatography-tandem mass spectrometry, and pharmacokinetic analysis was conducted using a population approach. The study population included three groups (n = 10 per group): (A) intravenous CMS and concomitantly nebulised CMS at a dose of 3 MIU (30 min duration); (B) nebulised CMS at a dose of 3 MIU (30 min duration) as monotherapy; and (C) nebulised CMS 5 MIU (45 min duration) as monotherapy. Mean plasma formed colistin concentrations were <1 mg/L following CMS nebulisation as monotherapy (groups B and C). Predicted trough concentrations of formed colistin in the epithelial lining fluid (ELF) following 24-h dosing of 3 MIU and 5 MIU nebulised CMS were 120.4 mg/L and 200.7 mg/L, respectively. The model predicted that concomitant intravenous CMS (group A) had minimal impact on the formed colistin concentration in ELF. This study demonstrated high ELF formed colistin concentrations following nebulised CMS (constantly above colistin MICs), while plasma concentrations were lower than those associated with nephrotoxicity. Our results provide important information for optimisation of nebulised colistin therapy., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

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.)

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.)

Lack of effective treatment for multidrug-resistant Klebsiella pneumoniae (MDR-Kp) necessitates finding and optimising combination therapies of old antibiotics. The aims of this study were to quantify the combined effect of polymyxin B and minocycline by building an in silico semi-mechanistic pharmacokinetic/pharmacodynamic (PKPD) model and to predict bacterial kinetics when exposed to the drugs alone and in combination at clinically achievable unbound drug concentration-time profiles. A clinical K. pneumoniae strain resistant to polymyxin B [minimum inhibitory concentration (MIC) = 16 mg/L] and minocycline (MIC = 16 mg/L) was selected for extensive in vitro static time-kill experiments. The strain was exposed to concentrations of 0.0625-48 × MIC, with seven samples taken per experiment for viable counts during 0-28 h. These observations allowed the development of the PKPD model. The final PKPD model included drug-induced adaptive resistance for both drugs. Both the minocycline-induced bacterial killing and resistance onset rate constants were increased when polymyxin B was co-administered, whereas polymyxin B parameters were unaffected. Predictions at clinically used dosages from the developed PKPD model showed no or limited antibacterial effect with monotherapy, whilst combination therapy kept bacteria below the starting inoculum for >20 h at high dosages [polymyxin B 2.5 mg/kg + 1.5 mg/kg every 12 h (q12h); minocycline 400 mg + 200 mg q12h, loading + maintenance doses]. This study suggests that polymyxin B and minocycline in combination may be of clinical benefit in the treatment of infections by MDR-Kp and for isolates that are non-susceptible to either drug alone., (Copyright © 2020 The Authors. Published by Elsevier B.V. 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.)

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.)