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SUMMARYThe World Health Organisation's 2022 AWaRe Book provides guidance for the use of 39 antibiotics to treat 35 infections in primary healthcare and hospital facilities. We review the evidence underpinning suggested dosing regimens. Few ( n = 18) population pharmacokinetic studies exist for key oral AWaRe antibiotics, largely conducted in homogenous and unrepresentative populations hindering robust estimates of drug exposures. Databases of minimum inhibitory concentration distributions are limited, especially for community pathogen-antibiotic combinations. Minimum inhibitory concentration data sources are not routinely reported and lack regional diversity and community representation. Of studies defining a pharmacodynamic target for ß-lactams ( n = 80), 42 (52.5%) differed from traditionally accepted 30%-50% time above minimum inhibitory concentration targets. Heterogeneity in model systems and pharmacodynamic endpoints is common, and models generally use intravenous ß-lactams. One-size-fits-all pharmacodynamic targets are used for regimen planning despite complexity in drug-pathogen-disease combinations. We present solutions to enable the development of global evidence-based antibiotic dosing guidance that provides adequate treatment in the context of the increasing prevalence of antimicrobial resistance and, moreover, minimizes the emergence of resistance., Competing Interests: A.H. declares consulting work for Pfizer outside the submitted work. M.S. is Chair of the WHO Essential Medicine List Antibiotic Working group. W.H. holds or has held research grants with UKRI, EU, F2G, Spero Therapeutics, Antabio, Pfizer, Bugworks, Phico Therapeutics, BioVersys, Global Antibiotic Research & Development Partnership (GARDP), and NAEJA-RGM. W.H. is or has been a consultant for Appili Therapeutics, F2G, Spero Therapeutics, NAEJA-RGM, Centauri, Pfizer, Phico Therapeutics, Pulmocide, Amplyx, Mundipharma Research, and VenatoRx. W.H. is a member of the Specialist Advisory Committee for GARDP and the Specialty National co-lead for Infectious Diseases for the National Institute of Health Research.

Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human error, and require considerable infrastructure. AIgarMIC streamlines and standardizes MIC measurement and is especially valuable for large-scale surveillance activities. MICs were measured using agar dilution for n = 10 antibiotics against clinical Enterobacterales isolates ( n = 1,086) obtained from a large tertiary hospital microbiology laboratory. Escherichia coli ( n = 827, 76%) was the most common organism. Photographs of agar plates were divided into smaller images covering one inoculation site. A labeled data set of colony images was created and used to train a convolutional neural network to classify images based on whether a bacterial colony was present (first-step model). If growth was present, a second-step model determined whether colony morphology suggested antimicrobial growth inhibition. The ability of the AI to determine MIC was then compared with standard visual determination. The first-step model classified bacterial growth as present/absent with 94.3% accuracy. The second-step model classified colonies as "inhibited" or "good growth" with 88.6% accuracy. For the determination of MIC, the rate of essential agreement was 98.9% (644/651), with a bias of -7.8%, compared with manual annotation. AIgarMIC uses artificial intelligence to automate endpoint assessments for agar dilution and potentially increases throughput without bespoke equipment. AIgarMIC reduces laboratory barriers to generating high-quality MIC data that can be used for large-scale surveillance programs., Importance: This research uses modern artificial intelligence and machine-learning approaches to standardize and automate the interpretation of agar dilution minimum inhibitory concentration testing. Artificial intelligence is currently of significant topical interest to researchers and clinicians. In our manuscript, we demonstrate a use-case in the microbiology laboratory and present validation data for the model's performance against manual interpretation., Competing Interests: A.G. holds a research grant with United Kingdom Research and Innovation (UKRI) for technology described in this manuscript. W.H. and A.G. hold research grants with EPSRC and MRC for technology described in this manuscript. A.H. declares consulting work for Pfizer outside of the submitted work. W.H. holds or has held research grants with UKRI, EU, F2G, Spero Therapeutics, Antabio, Pfizer, Bugworks, Phico Therapeutics, BioVersys, Global Antibiotic Research & Development Partnership (GARDP), and NAEJA- RGM. W.H. is or has been a consultant for Appili Therapeutics, F2G, Spero Therapeutics, NAEJA-RGM, Centauri, Pfizer, Phico Therapeutics, Pulmocide, Amplyx, Mundipharma Research, and VenatoRx. W.H. is a member of the Specialist Advisory Committee for GARDP and the Specialty National co-lead for Infectious Diseases for the National Institute of Health Research. All other authors declare no competing interests.

The proliferation of various forms of artificial intelligence (AI) brings many opportunities to improve health care. AI models can harness complex evolving data, inform and augment human actions, and learn from health outcomes such as morbidity and mortality. The global public health challenge of antimicrobial resistance (AMR) needs large-scale optimisation of antimicrobial use and wider infection care, which could be enabled by carefully constructed AI models. As AI models become increasingly useful and robust, health-care systems remain challenging places for their deployment. An implementation gap exists between the promise of AI models and their use in patient and population care. Here, we outline an adaptive implementation and maintenance framework for AI models to improve antimicrobial use and infection care as a learning system. The roles of AMR problem identification, law and regulation, organisational support, data processing, and AI development, assessment, maintenance, and scalability in the implementation of AMR-targeted AI models are considered., Competing Interests: Declaration of interests AH declares consulting work for Pfizer outside the submitted work. HM received support for research not related to the current manuscript from UK Research and Innovation (UKRI), the Bill and Melinda Gates Foundation, and National Institutes of Health; is on the data safety monitoring board for the IMPROVE trial; is an interview panel member for the Wellcome career development award; and is a council member of the International Society for Infectious Diseases. IB holds a senior investigator award with the National Institute for Health and Care Research, and received personal fees and other fees from AstraZeneca outside the submitted work. WH holds or has held research grants with UKRI, EU, F2G, Spero Therapeutics, Antabio, Pfizer, Bugworks, Phico Therapeutics, BioVersys, Global Antibiotic Research & Development Partnership (GARDP), and NAEJA-RGM; is or has been a consultant for Appili Therapeutics, F2G, Spero Therapeutics, NAEJA-RGM, Centauri, Pfizer, Phico Therapeutics, Pulmocide, Amplyx, Mundipharma Research, and VenatoRx; is a member of the Specialist Advisory Committee for GARDP; and is the Specialty National Co-lead for Infectious Diseases for the National Institute of Health Research. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Objectives: This systematic review focuses on the use of the in vitro hollow fibre infection model (HFIM) for microbial culture. We summarize the direction of the field to date and propose best-practice principles for reporting of the applications., Methods: Searches in six databases (MEDLINE®, EMBASE®, PubMed®, BIOSIS®, SCOPUS® and Cochrane®) up to January 2020 identified 129 studies meeting our inclusion criteria. Two reviewers independently assessed and extracted data from each publication. The quality of reporting of microbiological and technical parameters was analysed., Results: Forty-seven out of 129 (36.4%) studies did not report the minimum pharmacokinetic parameters required in order to replicate the pharmacokinetic profile of HFIM experiments. Fifty-three out of 129 (41.1%) publications did not report the medium used in the HFIM. The overwhelming majority of publications did not perform any technical repeats [107/129 (82.9%)] or biological repeats [97/129 (75.2%)]., Conclusions: This review demonstrates that most publications provide insufficient data to allow for results to be evaluated, thus impairing the reproducibility of HFIM experiments. Therefore, there is a clear need for the development of laboratory standardization and improved reporting of HFIM experiments., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.)

Antimicrobial resistance (particularly through extended-spectrum β-lactamase and aminoglycoside-modifying enzyme production) in neonatal sepsis is a global problem, particularly in low- and middle-income countries, with significant mortality rates. High rates of resistance are reported for the current WHO-recommended first-line antibiotic regimen for neonatal sepsis, i.e., ampicillin and gentamicin. We assessed the utility of fosfomycin and amikacin as a potential alternative regimen to be used in settings of increasingly prevalent antimicrobial resistance. The combination was studied in a 16-arm dose-ranged hollow-fiber infection model (HFIM) experiment. The combination of amikacin and fosfomycin enhanced bactericidal activity and prevented the emergence of resistance, compared to monotherapy with either antibiotic. Modeling of the experimental quantitative outputs and data from checkerboard assays indicated synergy. We further assessed the combination regimen at clinically relevant doses in the HFIM with nine Enterobacterales strains with high fosfomycin and amikacin MICs and demonstrated successful kill to sterilization for 6/9 strains. From these data, we propose a novel combination breakpoint threshold for microbiological success for this antimicrobial combination against Enterobacterales strains, i.e., MIC F × MIC A < 256 (where MIC F and MIC A are the fosfomycin and amikacin MICs, respectively). Monte Carlo simulations predict that a standard fosfomycin-amikacin neonatal regimen would achieve >99% probability of pharmacodynamic success for strains with MICs below this threshold. We conclude that the combination of fosfomycin with amikacin is a viable regimen for the empirical treatment of neonatal sepsis and is suitable for further clinical assessment in a randomized controlled trial.

The high interindividual variability in the pharmacokinetics (PK) of linezolid has been described, which results in an unacceptably high proportion of patients with either suboptimal or potentially toxic concentrations following the administration of a fixed regimen. The aim of this study was to develop a population pharmacokinetic model of linezolid and use this to build and validate alogorithms for individualized dosing. A retrospective pharmacokinetic analysis was performed using data from 338 hospitalized patients (65.4% male, 65.5 [±14.6] years) who underwent routine therapeutic drug monitoring for linezolid. Linezolid concentrations were analyzed by using high-performance liquid chromatography. Population pharmacokinetic modeling was performed using a nonparametric methodology with Pmetrics, and Monte Carlo simulations were employed to calculate the 100% time >MIC after the administration of a fixed regimen of 600 mg administered every 12 h (q12h) intravenously (i.v.). The dose of linezolid needed to achieve a PTA ≥ 90% for all susceptible isolates classified according to EUCAST was estimated to be as high as 2,400 mg q12h, which is 4 times higher than the maximum licensed linezolid dose. The final PK model was then used to construct software for dosage individualization, and the performance of the software was assessed using 10 new patients not used to construct the original population PK model. A three-compartment model with an absorptive compartment with zero-order i.v. input and first-order clearance from the central compartment best described the data. The dose optimization software tracked patients with a high degree of accuracy. The software may be a clinically useful tool to adjust linezolid dosages in real time to achieve prespecified drug exposure targets. A further prospective study is needed to examine the potential clinical utility of individualized therapy., (Copyright © 2021 American Society for Microbiology.)

Background: Therapeutic drug monitoring (TDM) is a tool to personalize and optimize dosing by measuring the drug concentration and subsequently adjusting the dose to reach a target concentration or exposure. The evidence to support TDM is however often ranked as expert opinion. Limitations in study design and sample size have hampered definitive conclusions of the potential added value of TDM., Objectives: We aim to give expert opinion and discuss the main points and limitations of available data from antibiotic TDM trials and emphasize key elements for consideration in design of future clinical studies to quantify the benefits of TDM., Sources: The sources were peer-reviewed publications, guidelines and expert opinions from the field of TDM., Content: This review focuses on key aspects of antimicrobial TDM study design: describing the rationale for a TDM study, assessing the exposure of a drug, assessing susceptibility of pathogens and selecting appropriate clinical endpoints. Moreover we provide guidance on appropriate study design., Implications: This is an overview of different aspects relevant for the conduct of a TDM study. We believe that this paper will help researchers and clinicians to design and conduct high-quality TDM studies., (Copyright © 2020 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.)

Background: Optimal antimicrobial drug exposure in the lung is required for successful treatment outcomes for nosocomial pneumonia. Little is known about the intrapulmonary pharmacokinetics (PK) of meropenem when administered by continuous infusion (CI). The aim of this study was to evaluate the PK of two dosages of meropenem (3 g vs 6 g/day by CI) in the plasma and epithelial lining fluid (ELF) in critically ill patients with nosocomial pneumonia., Methods: Thirty-one patients (81% male, median (IQR) age 72 (22) years) were enrolled in a prospective, randomized, clinical trial. Sixteen patients received 1 g/8 h and 15 2 g/8 h by CI (8 h infusion). Plasma and ELF meropenem concentrations were modeled using a population methodology, and Monte Carlo simulations were performed to estimate the probability of attaining (PTA) a free ELF concentration of 50% of time above MIC (50% fT>MIC), which results in logarithmic killing and the suppression of resistance in experimental models of pneumonia., Results: The median (IQR) of meropenem AUC 0-24 h in the plasma and ELF was 287.6 (190.2) and 84.1 (78.8) mg h/L in the 1 g/8 h group vs 448.1 (231.8) and 163.0 (201.8) mg h/L in the 2 g/8 h group, respectively. The penetration ratio was approximately 30% and was comparable between the dosage groups. In the Monte Carlo simulations, only the highest approved dose of meropenem of 2 g/8 h by CI allowed to achieve an optimal PTA for all isolates with a MIC < 4 mg/L., Conclusions: An increase in the dose of meropenem administered by CI achieved a higher exposure in the plasma and ELF. The use of the highest licensed dose of 6 g/day may be necessary to achieve an optimal coverage in ELF for all susceptible isolates (MIC ≤ 2 mg/L) in patients with conserved renal function. An alternative therapy should be considered when the presence of microorganisms with a MIC greater than 2 mg/L is suspected., Trial Registration: The trial was registered in the European Union Drug Regulating Authorities Clinical Trials Database (EudraCT-no. 2016-002796-10). Registered on 27 December 2016.

Objectives: To identify the pharmacokinetic (PK) and toxicodynamic (TD) relationship for vancomycin-induced kidney injury., Methods: Male Sprague-Dawley rats received intravenous (iv) vancomycin. Doses ranging from 150 mg/kg/day to 400 mg/kg/day were administered as a single or twice-daily injection over 24 h (total protocol duration). Controls received iv saline. Plasma was sampled with up to eight samples in 24 h per rat. Twenty-four hour urine was collected and assayed for kidney injury molecule 1 (KIM-1), osteopontin and clusterin. Vancomycin in plasma was quantified via LC-MS/MS. PK analyses were conducted using Pmetrics for R. PK exposures during the first 24 h (i.e. AUC0-24h, Cmax 0-24h and Cmin 0-24h) were calculated. PK/TD relationships were assessed with Spearman's rank coefficient (rs) and the best-fit mathematical model., Results: PK/TD data were generated from 45 vancomycin-treated and 5 control rats. A two-compartment model fit the data well (Bayesian: observed versus predicted R2 = 0.97). Exposure-response relationships were found between AUC0-24h versus KIM-1 and osteopontin (R2 = 0.61 and 0.66) and Cmax 0-24h versus KIM-1 and osteopontin (R2 = 0.50 and 0.56) using a four-parameter Hill fit. Conversely, Cmin 0-24h was less predictive of KIM-1 and osteopontin (R2 = 0.46 and 0.53). A vancomycin AUC0-24h of 482.2 corresponded to a 90% of maximal rise in KIM-1., Conclusions: Vancomycin-induced kidney injury as defined by urinary biomarkers is driven by vancomycin AUC or Cmax rather than Cmin. Further, an identified PK/TD target AUC0-24h of 482.2 mg·h/L may have direct relevance to human outcomes., (© 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.)

Objectives: To conduct a population pharmacokinetic analysis of continuous-infusion ceftazidime in a retrospective cohort of paediatric HSCT patients who were empirically treated for febrile neutropenia (FN) and who underwent therapeutic drug monitoring of ceftazidime steady-state plasma concentrations (Css) for optimization of drug exposure., Methods: A non-parametric approach with Pmetrics was used for pharmacokinetic analysis and covariate evaluation. Monte Carlo simulations were performed to calculate the PTA of the pharmacodynamic determinant of efficacy (Css/MIC ≥4) against Pseudomonas aeruginosa with continuous-infusion ceftazidime dosages of 1-6 g daily. The Css safety threshold was arbitrarily placed at 100 mg/L and advisable dosages were used., Results: A total of 46 patients with 70 ceftazidime Css values were included. Estimated glomerular filtration rate (eGFR) and body surface area were the covariates associated with drug clearance. At the EUCAST clinical breakpoint of 8 mg/L, simulations showed that continuous-infusion ceftazidime dosages of 4-6 g daily attained optimal PTAs (>90%) across most of 16 different clinical scenarios based on four classes of eGFR (50-145, 145.1-200, 200.1-286 and 286.1-422 mL/min/1.73 m2) and body surface area (0.30-0.64, 0.65-0.88, 0.89-1.34 and 1.35-1.84 m2). In patients with body surface area 0.30-0.64 m2 and eGFR ≤200 mL/min/1.73 m2 the advisable dose of 3 g daily allowed only suboptimal PTAs (<75%). The cumulative fraction of response against MIC distribution of P. aeruginosa was >87%., Conclusions: Continuous-infusion ceftazidime dosages ranging from 3 to 6 g daily according to different classes of eGFR and body surface area may allow optimized empirical treatment of P. aeruginosa infections in paediatric HSCT patients with FN., (© 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: Vancomycin is recommended for ventriculitis. However, penetration into the CNS is relatively poor., Objectives: To investigate the population pharmacokinetics of vancomycin in serum and CSF in critical care patients with proven or suspected CNS infections from neurosurgical procedures., Patients and Methods: This was an observational pharmacokinetic study in critical care patients with proven or suspected CNS infections receiving intravenous vancomycin. Multiple blood and intraventricular CSF samples were collected. Population pharmacokinetic analysis and simulation were undertaken with ADAPT5 and Pmetrics., Results: A total of 187 blood and CSF samples were collected from 21 patients. The median (range) Cmax and Cmin concentrations in serum were 25.67 (10.60-50.78) and 9.60 (4.46-23.56) mg/L, respectively, with a median daily dose of 2500 (500-4000) mg. The corresponding median concentrations in CSF were 0.65 (<0.24-3.83) mg/L and 0.58 (<0.24-3.95) mg/L, respectively. The median AUC0-24 in serum and CSF was 455.09 and 14.10 mg·h/L, respectively. A three-compartment linear population pharmacokinetic model best fitted the observed data. Vancomycin demonstrated poor penetration into CSF, with a median CSF/serum ratio of 3% and high intersubject pharmacokinetic variability of its penetration., Conclusions: Therapeutic drug monitoring in both serum and CSF and higher daily doses may be an option to ensure adequate trough levels and to optimize patient therapy. Novel dosing strategies designed to reduce renal toxicity, such as administration by continuous infusion, should be investigated in further clinical studies to avoid antibiotic underexposure in CSF., (© 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: C-reactive protein (CRP) pharmacodynamic (PD) models have the potential to provide adjunctive methods for predicting the individual exposure response to antimicrobial therapy. We investigated CRP PD linked to a vancomycin pharmacokinetic (PK) model using routinely collected data from noncritical care adults in secondary care., Methods: Patients receiving intermittent intravenous vancomycin therapy in secondary care were identified. A 2-compartment vancomycin PK model was linked to a previously described PD model describing CRP response. PK and PD parameters were estimated using a Non-Parametric Adaptive Grid technique. Exposure-response relationships were explored with vancomycin area-under-the-concentration-time-curve (AUC) and EC50 (concentration of drug that causes a half maximal effect) using the index, AUC:EC50, fitted to CRP data using a sigmoidal Emax model., Results: Twenty-nine individuals were included. Median age was 62 (21-97) years. Fifteen (52%) patients were microbiology confirmed. PK and PD models were adequately fitted (r 0.83 and 0.82, respectively). There was a wide variation observed in individual Bayesian posterior EC50 estimates (6.95-48.55 mg/L), with mean (SD) AUC:EC50 of 31.46 (29.22). AUC:EC50 was fitted to terminal CRP with AUC:EC50 >19 associated with lower CRP value at 96-120 hours of therapy (100 mg/L versus 44 mg/L; P < 0.01)., Conclusions: The use of AUC:EC50 has the potential to provide in vivo organism and host response data as an adjunct for in vitro minimum inhibitory concentration data, which is currently used as the gold standard PD index for vancomycin therapy. This index can be estimated using routinely collected clinical data. Future work must investigate the role of AUC:EC50 in a prospective cohort and explore linkage with direct patient outcomes.

Background: Severe infections of the respiratory tracts of critically ill patients are common and associated with excess morbidity and mortality. Piperacillin is commonly used to treat pulmonary infections in critically ill patients. Adequate antibiotic concentration in the epithelial lining fluid (ELF) of the lung is essential for successful treatment of pulmonary infection., Objectives: To compare piperacillin pharmacokinetics/pharmacodynamics in the serum and ELF of healthy volunteers and critically ill patients., Methods: Piperacillin concentrations in the serum and ELF of healthy volunteers and critically ill patients were compared using population methodologies., Results: Median piperacillin exposure was significantly higher in the serum and the ELF of critically ill patients compared with healthy volunteers. The IQR for serum piperacillin exposure in critically ill patients was six times greater than for healthy volunteers. The IQR for piperacillin exposure in the ELF of critically ill patients was four times greater than for healthy volunteers. The median pulmonary piperacillin penetration ratio was 0.31 in healthy volunteers and 0.54 in critically ill patients., Conclusions: Greater variability in serum and ELF piperacillin concentrations is observed in critically ill patients compared with healthy adult subjects and must be considered in the development of dosage regimens. Pulmonary penetration of antimicrobial agents should be studied in critically ill patients, as well as healthy volunteers, during drug development to ensure appropriate dosing of patients with pneumonia.

Sub-optimal exposure to antimicrobial therapy is associated with poor patient outcomes and the development of antimicrobial resistance. Mechanisms for optimizing the concentration of a drug within the individual patient are under development. However, several barriers remain in realizing true individualization of therapy. These include problems with plasma drug sampling, availability of appropriate assays, and current mechanisms for dose adjustment. Biosensor technology offers a means of providing real-time monitoring of antimicrobials in a minimally invasive fashion. We report the potential for using microneedle biosensor technology as part of closed-loop control systems for the optimization of antimicrobial therapy in individual patients.

Objectives: The overall study aim was to identify the relevant preclinical teicoplanin pharmacokinetic (PK)/pharmacodynamic (PD) indices to predict efficacy and suppression of resistance in MRSA infection., Methods: A hollow-fibre infection model and a neutropenic murine thigh infection model were developed. The PK/PD data generated were modelled using a non-parametric population modelling approach with Pmetrics. The posterior Bayesian estimates derived were used to study the exposure-effect relationships. Monte Carlo simulations from previously developed population PK models in adults and children were conducted to explore the probability of target attainment (PTA) for teicoplanin dosage regimens against the current EUCAST WT susceptibility range., Results: There was a concentration-dependent activity of teicoplanin in both the in vitro and in vivo models. A total in vivo AUC/MIC of 610.4 (total AUC of 305.2 mg·h/L) for an MRSA strain with an MIC of 0.5 mg/L was needed for efficacy (2 log10 cell kill) against a total bacterial population. A total AUC/MIC ratio of ∼1500 (total AUC of ∼750 mg·h/L) was needed to suppress the emergence of resistance. The PTA analyses showed that adult and paediatric patients receiving a standard regimen were only successfully treated for the in vivo bactericidal target if the MIC was ≤0.125 mg/L in adults and ≤0.064 mg/L in children., Conclusions: This study improves our understanding of teicoplanin PD against MRSA and defines an in vivo AUC/MIC target for efficacy and suppression of resistance. Additional studies are needed to further corroborate the PK/PD index in a variety of infection models and in patients., (© 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.)

The aim of this study was to develop a population pharmacokinetic (PK) model for teicoplanin across childhood age ranges to be used as Bayesian prior information in the software constructed for individualized therapy. We developed a nonparametric population model fitted to PK data from neonates, infants, and older children. We then implemented this model in the BestDose multiple-model Bayesian adaptive control algorithm to show its clinical utility. It was used to predict the dosages required to achieve optimal teicoplanin predose targets (15 mg/liter) from day 3 of therapy. We performed individual simulations for an infant and a child from the original population, who provided early first dosing interval concentration-time data. An allometric model that used weight as a measure of size and that also incorporated renal function using the estimated glomerular filtration rate (eGFR), or the ratio of postnatal age (PNA) to serum creatinine concentration (SCr) for infants <3 months old, best described the data. The median population PK parameters were as follows: elimination rate constant (Ke) = 0.03 · (wt/70) -0.25 · Renal (h -1 ); V = 19.5 · (wt/70) (liters); Renal = eGFR 0.07 (ml/min/1.73 m 2 ), or Renal = PNA/SCr (μmol/liter). Increased teicoplanin dosages and alternative administration techniques (extended infusions and fractionated multiple dosing) were required in order to achieve the targets safely by day 3 in simulated cases. The software was able to predict individual measured concentrations and the dosages and administration techniques required to achieve the desired target concentrations early in therapy. Prospective evaluation is now needed in order to ensure that this individualized teicoplanin therapy approach is applicable in the clinical setting. (This study has been registered in the European Union Clinical Trials Register under EudraCT no. 2012-005738-12.)., (Copyright © 2017 Ramos-Martín et al.)

Objectives: To assess the population pharmacokinetics (popPK) of daptomycin at the conventional dose of 6 mg/kg/day in a cohort of oncohaematological patients., Methods: Patients underwent serial blood sampling on day 3 of therapy (before dosing and at 0, 0.5, 1, 2, 3, 5, 7, 9 and 12 h after dosing) to assess the pharmacokinetic profile of daptomycin. PopPK and Monte Carlo simulation were performed to define the probability of target attainment (PTA) with 6, 8, 10 and 12 mg/kg/day of the pharmacokinetic/pharmacodynamic target of AUC 24 /MIC >1081., Results: Thirty patients were recruited. A two-compartment open model with first-order intravenous input and first-order elimination was developed. Estimated creatinine clearance (CL CR ), serum albumin concentration (Alb) and presence of AML were covariates included in the final model. Monte Carlo simulation showed that the conventional 6 mg/kg/day dose resulted in optimal PTAs (≥80%) in the presence of pathogens with an MIC up to 0.5 mg/L only in patients with CL CR 50-100 mL/min/1.73 m 2 , Alb 26-45 g/L and a haematological diagnosis other than AML. Conversely, higher dosages, up to 12 mg/kg/day, were needed to achieve this goal in the presence of pathogens with an MIC of 0.25-0.5 mg/L in all of the other tested scenarios. In patients with CL CR 101-150 mL/min/1.73 m 2 and Alb 15-25 g/L, suboptimal PTAs (<60%) were predicted even with 12 mg/kg/day dosing ., Conclusions: Our study provides a strong rationale for considering daptomycin dosages of ≥ 8 mg/kg/day in several clinical scenarios for oncohaematological patients. In some of these scenarios therapeutic drug monitoring could be a useful adjunct for optimized care., (© 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.)

The broad-spectrum activity of fosfomycin, including against multidrug-resistant (MDR) strains, has led to renewed interest in its use in recent years. Neonatal sepsis remains a substantial cause of morbidity and mortality at a global level, with evidence that MDR bacteria play an increasing role. The evidence for use of fosfomycin in neonatal subjects is limited. We summarise current knowledge of the pharmacokinetics and clinical outcomes for the use of fosfomycin in neonatal sepsis and issues specific to neonatal physiology. While fosfomycin has a broad range of coverage, we evaluate the extent to which it may be effective against MDR bacteria in a neonatal setting, in light of recent evidence suggesting it to be most effective when administered in combination with other antibiotics. Given the urgency of clinical demand for treatment of MDR bacterial sepsis, we outline directions for further work, including the need for future clinical trials in this at-risk population.

A retrospective study was conducted in a large sample of acutely hospitalized older patients who underwent therapeutic drug monitoring during levofloxacin treatment. The aim was to assess the population pharmacokinetics (popPK) and pharmacodynamics of levofloxacin among older patients. PopPK and Monte Carlo simulation were performed to define the permissible doses in older patients according to various degrees of renal function. Classification and regression tree (CART) analysis was used to detect the cutoff 24-hour area under the concentration-time curve (AUC 24 )/MIC ratio that best correlated with the clinical outcome. The probability of target attainment (PTA) of this value was calculated against different pathogens. A total of 168 patients were included, and 330 trough and 239 peak concentrations were used for the popPK analysis. Creatinine clearance (CrCL) was the only covariate that improved the model fit (levofloxacin CL = 0.399 + 0.051 × CrCL CKD-EPI [creatinine clearance estimated by means of the chronic kidney disease epidemiology]). Drug doses ranged between 500 mg every 48 h and 500 mg every 12 h in relation to different renal functions. The identified cutoff AUC 24 /MIC ratio (≥95.7) was the only covariate that correlated with a favorable clinical outcome in multivariate regression analysis (odds ratio [OR], 20.85; 95% confidence interval [CI], 1.56 to 186.73). PTAs were optimal (>80%) against Escherichia coli and Haemophilus influenzae , borderline against Staphylococcus aureus , and suboptimal against Pseudomonas aeruginosa The levofloxacin doses defined in our study may be effective for the treatment of infections due to bacterial pathogens, with an MIC of ≤0.5 mg/liter in older patients with various degrees of renal function, while minimizing the toxicity risk. Conversely, the addition of another active antimicrobial should be considered whenever treating infections caused by less susceptible pathogens., (Copyright © 2017 American Society for Microbiology.)

Objectives: There is uncertainty about the optimal teicoplanin regimens for neonates. The study aim was to determine the population pharmacokinetics (PK) of teicoplanin in neonates, evaluate currently recommended regimens and explore the exposure-effect relationships., Methods: An open-label PK study was conducted. Neonates from 26 to 44 weeks post-menstrual age were recruited (n = 18). The teicoplanin regimen was a 16 mg/kg loading dose, followed by 8 mg/kg once daily. Therapeutic drug monitoring and dose adjustment were not conducted. A standard two-compartment PK model was developed, followed by models that incorporated weight. A PK/pharmacodynamic (PD) model with C-reactive protein serial measurements as the PD input was fitted to the data. Monte Carlo simulations (n = 5000) were performed using Pmetrics. The AUCs at steady state and the proportion of patients achieving the recommended drug exposures (i.e. C min >15 mg/L) were determined. The study was registered in the European Clinical Trials Database Registry (EudraCT: 2012-005738-12)., Results: The PK allometric model best accounted for the observed data. The PK parameters medians were: clearance = 0.435 × (weight/70) 0.75 (L/h); volume = 0.765 (L); K cp  = 1.3 (h -1 ); and K pc  = 0.629 (h -1 ). The individual time-course of C-reactive protein was well described using the Bayesian posterior estimates for each patient. The simulated median AUC 96-120 was 302.3 mg·h/L and the median C min at 120 h was 12.9 mg/L; 38.8% of patients attained a C min >15 mg/L by 120 h., Conclusions: Teicoplanin population PK is highly variable in neonates, weight being the best descriptor of PK variability. A low percentage of neonates were able to achieve C min >15 mg/L. The routine use of therapeutic drug monitoring and improved knowledge on the PD of teicoplanin is required., (© 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.)

Background: Ventriculitis is a complication of temporary intraventricular drains. The limited penetration of meropenem into the cerebrospinal fluid (CSF) is well known. However, ventricular CSF pharmacokinetic data in patients with ventriculitis are lacking. The aim of this study was to evaluate meropenem pharmacokinetics in the serum and CSF of neurocritical care patients with proven or suspected ventriculitis., Methods: We conducted an observational pharmacokinetic study of neurocritical care patients with proven or suspected ventriculitis receiving meropenem. Multiple blood and CSF samples were taken and were described using nonparametric pharmacokinetic modelling with Pmetrics., Results: In total, 21 patients (median age 52 years, median weight 76 kg) were included. The median (range) of peak and trough concentrations in serum were 20.16 (4.40-69.00) mg/L and 2.54 (0.00-31.40) mg/L, respectively. The corresponding peak and trough concentrations in CSF were 1.20 (0.00-6.20) mg/L and 1.28 (0.00-4.10) mg/L, respectively, with a median CSF/serum ratio (range) of 0.09 (0.03-0.16). Median creatinine clearance ranged from 60.7 to 217.6 ml/minute (median 122.5 ml/minute). A three-compartment linear population pharmacokinetic model was most appropriate. No covariate relationships could be supported for any of the model parameters. Meropenem demonstrated poor penetration into CSF, with a median CSF/serum ratio of 9 % and high interindividual pharmacokinetic variability., Conclusions: Administration of higher-than-standard doses of meropenem and therapeutic drug monitoring in both serum and CSF should be considered to individualise meropenem dosing in neurocritical care patients with ventriculitis.

Objectives: CoNS are the most common cause of neonatal late-onset sepsis. Information on the vancomycin pharmacokinetics/pharmacodynamics against CoNS is limited. The aim of this study was to characterize vancomycin pharmacokinetic/pharmacodynamic relationships for CoNS and investigate neonatal optimal dosage regimens., Methods: A hollow fibre and a novel rabbit model of neonatal central line-associated bloodstream CoNS infections were developed. The results were then bridged to neonates by use of population pharmacokinetic techniques and Monte Carlo simulations., Results: There was a dose-dependent reduction in the total bacterial population and C-reactive protein levels. The AUC/MIC and Cmax/MIC ratios were strongly linked with total and mutant resistant cell kill. Maximal amplification of resistance was observed in vitro at an fAUC/MIC of 200 mg · h/L. Simulations predicted that neonates <29 weeks post-menstrual age are underdosed with standard regimens with respect to older age groups., Conclusions: The AUC/MIC and Cmax/MIC ratios are the pharmacodynamic indices that best explain total and resistant cell kill in CoNS infection. This suggests that less-fractionated regimens are appropriate for clinical use and continuous infusions may be associated with increased risk of emergence of antimicrobial resistance. This study has provided the pharmacodynamic evidence to inform an optimized neonatal dosage regimen to take into a randomized controlled trial., (© 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.)

We are in a crisis of bacterial resistance. For economic reasons, most pharmaceutical companies are abandoning antimicrobial discovery efforts, while, in health care itself, infection control and antibiotic stewardship programs have generally failed to prevent the spread of drug-resistant bacteria. At this point, what can be done? The first step has been taken. Governments and international bodies have declared there is a worldwide crisis in antibiotic drug resistance. As discovery efforts begin anew, what more can be done to protect newly developing agents and improve the use of new drugs to suppress resistance emergence? A neglected path has been the use of recent knowledge regarding antibiotic dosing as single agents and in combination to minimize resistance emergence, while also providing sufficient early bacterial kill. In this review, we look at the data for resistance suppression. Approaches include increasing the intensity of therapy to suppress resistant subpopulations; developing concepts of clinical breakpoints to include issues surrounding suppression of resistance; and paying attention to the duration of therapy, which is another important issue for resistance suppression. New understanding of optimizing combination therapy is of interest for difficult-to-treat pathogens like Pseudomonas aeruginosa, Acinetobacter spp., and multidrug-resistant (MDR) Enterobacteriaceae. These lessons need to be applied to our old drugs as well to preserve them and to be put into national and international antibiotic resistance strategies. As importantly, from a regulatory perspective, new chemical entities should have a resistance suppression plan at the time of regulatory review. In this way, we can make the best of our current situation and improve future prospects., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

We are in a crisis of bacterial resistance. For economic reasons, most pharmaceutical companies are abandoning antimicrobial discovery efforts, while, in health care itself, infection control and antibiotic stewardship programs have generally failed to prevent the spread of drug-resistant bacteria. At this point, what can be done? The first step has been taken. Governments and international bodies have declared there is a worldwide crisis in antibiotic drug resistance. As discovery efforts begin anew, what more can be done to protect newly developing agents and improve the use of new drugs to suppress resistance emergence? A neglected path has been the use of recent knowledge regarding antibiotic dosing as single agents and in combination to minimize resistance emergence, while also providing sufficient early bacterial kill. In this review, we look at the data for resistance suppression. Approaches include increasing the intensity of therapy to suppress resistant subpopulations; developing concepts of clinical breakpoints to include issues surrounding suppression of resistance; and paying attention to the duration of therapy, which is another important issue for resistance suppression. New understanding of optimizing combination therapy is of interest for difficult-to-treat pathogens like Pseudomonas aeruginosa, Acinetobacter spp., and multidrug-resistant (MDR) Enterobacteriaceae. These lessons need to be applied to our old drugs to preserve them as well and need to be put into national and international antibiotic resistance strategies. As importantly, from a regulatory perspective, new chemical entities should have a corresponding resistance suppression plan at the time of regulatory review. In this way, we can make the best of our current situation and improve future prospects., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)

Teicoplanin is frequently administered to treat Gram-positive infections in pediatric patients. However, not enough is known about the pharmacokinetics (PK) of teicoplanin in children to justify the optimal dosing regimen. The aim of this study was to determine the population PK of teicoplanin in children and evaluate the current dosage regimens. A PK hospital-based study was conducted. Current dosage recommendations were used for children up to 16 years of age. Thirty-nine children were recruited. Serum samples were collected at the first dose interval (1, 3, 6, and 24 h) and at steady state. A standard 2-compartment PK model was developed, followed by structural models that incorporated weight. Weight was allowed to affect clearance (CL) using linear and allometric scaling terms. The linear model best accounted for the observed data and was subsequently chosen for Monte Carlo simulations. The PK parameter medians/means (standard deviation [SD]) were as follows: CL, [0.019/0.023 (0.01)] × weight liters/h/kg of body weight; volume, 2.282/4.138 liters (4.14 liters); first-order rate constant from the central to peripheral compartment (Kcp), 0.474/3.876 h(-1) (8.16 h(-1)); and first-order rate constant from peripheral to central compartment (Kpc), 0.292/3.994 h(-1) (8.93 h(-1)). The percentage of patients with a minimum concentration of drug in serum (Cmin) of <10 mg/liter was 53.85%. The median/mean (SD) total population area under the concentration-time curve (AUC) was 619/527.05 mg · h/liter (166.03 mg · h/liter). Based on Monte Carlo simulations, only 30.04% (median AUC, 507.04 mg · h/liter), 44.88% (494.1 mg · h/liter), and 60.54% (452.03 mg · h/liter) of patients weighing 50, 25, and 10 kg, respectively, attained trough concentrations of >10 mg/liter by day 4 of treatment. The teicoplanin population PK is highly variable in children, with a wider AUC distribution spread than for adults. Therapeutic drug monitoring should be a routine requirement to minimize suboptimal concentrations. (This trial has been registered in the European Clinical Trials Database Registry [EudraCT] under registration number 2012-005738-12.)., (Copyright © 2014, American Society for Microbiology. All Rights Reserved.)

Pulmonary infections in critically ill patients are common and are associated with high morbidity and mortality. Piperacillin-tazobactam is a frequently used therapy in critically ill patients with pulmonary infection. Antibiotic concentrations in the lung reflect target-site antibiotic concentrations in patients with pneumonia. The aim of this study was to assess the plasma and intrapulmonary pharmacokinetics (PK) of piperacillin-tazobactam in critically ill patients administered standard piperacillin-tazobactam regimens. A population PK model was developed to describe plasma and intrapulmonary piperacillin and tazobactam concentrations. The probability of piperacillin exposures reaching pharmacodynamic end points and the impact of pulmonary permeability on piperacillin and tazobactam pulmonary penetration was explored. The median piperacillin and tazobactam pulmonary penetration ratios were 49.3 and 121.2%, respectively. Pulmonary piperacillin and tazobactam concentrations were unpredictable and negatively correlated with pulmonary permeability. Current piperacillin-tazobactam regimens may be insufficient to treat pneumonia caused by piperacillin-tazobactam-susceptible organisms in some critically ill patients.

The pharmacokinetics (PK) of antimicrobial agents administered to critically ill patients exhibit marked variability. This variability results from pathophysiological changes that occur in critically ill patients. Changes in volume of distribution, clearance, and tissue penetration all affect the drug concentrations at the site of infection. PK-pharmacodynamic indices (fCmax:MIC; AUC0-24:MIC; fT>MIC; fCmin:MIC) for both antimicrobial effect and suppression of emergence of resistance are described for many antimicrobial drugs. Changing the regimen by which antimicrobial drugs are delivered can help overcome the PK variability and optimise target attainment. This will deliver optimised antimicrobial chemotherapy to individual critically ill patients. Delivery of β-lactams antimicrobial agents by infusions, rather than bolus dosing, is effective at increasing the duration of the dosing interval that the drug concentration is above the MIC. Therapeutic drug monitoring, utilising population PK mathematical models with Bayesian estimation, can also be used to optimise regimens following measurement of plasma drug concentrations. Clinical trials are required to establish if patient outcomes can be improved by implementing these techniques., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Piperacillin-tazobactam is frequently used for empirical and targeted therapy of infections in critically ill patients. Considerable pharmacokinetic (PK) variability is observed in critically ill patients. By estimating an individual's PK, dosage optimization Bayesian estimation techniques can be used to calculate the appropriate piperacillin regimen to achieve desired drug exposure targets. The aim of this study was to establish a population PK model for piperacillin in critically ill patients and then analyze the performance of the model in the dose optimization software program BestDose. Linear, with estimated creatinine clearance and weight as covariates, Michaelis-Menten (MM) and parallel linear/MM structural models were fitted to the data from 146 critically ill patients with nosocomial infection. Piperacillin concentrations measured in the first dosing interval, from each of 8 additional individuals, combined with the population model were embedded into the dose optimization software. The impact of the number of observations was assessed. Precision was assessed by (i) the predicted piperacillin dosage and by (ii) linear regression of the observed-versus-predicted piperacillin concentrations from the second 24 h of treatment. We found that a linear clearance model with creatinine clearance and weight as covariates for drug clearance and volume of distribution, respectively, best described the observed data. When there were at least two observed piperacillin concentrations, the dose optimization software predicted a mean piperacillin dosage of 4.02 g in the 8 patients administered piperacillin doses of 4.00 g. Linear regression of the observed-versus-predicted piperacillin concentrations for 8 individuals after 24 h of piperacillin dosing demonstrated an r(2) of >0.89. In conclusion, for most critically ill patients, individualized piperacillin regimens delivering a target serum piperacillin concentration is achievable. Further validation of the dosage optimization software in a clinical trial is required., (Copyright © 2014 Felton et al.)

Management of nosocomial pneumonia is frequently complicated by bacterial resistance. Extended infusions of beta-lactams are increasingly being used to improve clinical outcomes. However, the impact of this strategy on the emergence of antimicrobial resistance is not known. A hollow-fiber infection model with Pseudomonas aeruginosa (PAO1) was used. Pharmacokinetic (PK) profiles of piperacillin-tazobactam similar to those in humans were simulated over 5 days. Three dosages of piperacillin-tazobactam were administered over 0.5 h or 4 h, with redosing every 8 h. Two initial bacterial densities were investigated (∼10(4) CFU/ml and ∼10(7) CFU/ml). The time courses of the total bacterial population and the resistant subpopulation were determined. All data were described using a mathematical model, which was then used to define the relationship between drug concentrations, bacterial killing, and emergence of piperacillin resistance. There was logarithmic growth in controls in the initial 24 h, reaching a plateau of ∼9 log10 CFU/ml. Bacterial killing following administration of piperacillin via bolus dosing and that after extended infusions were similar. For the lower initial bacterial density, trough total plasma piperacillin concentration/MIC ratios of 3.4 and 10.4 for bolus and extended-infusion regimens, respectively, were able to suppress the emergence of piperacillin resistance. For the higher initial bacterial density, all regimens were associated with progressive growth of a resistant subpopulation. A stratified approach, according to bacterial density, is required to treat patients with nosocomial pneumonia. Antimicrobial monotherapy may be sufficient for some patients. However, for patients with a high bacterial burden, alternative therapeutic strategies are required to maximize bacterial killing and prevent antimicrobial resistance.

While extended infusions of piperacillin-tazobactam (TZP) are increasingly used in practice, the effect of infusion on the pharmacokinetic (PK) profile of TZP has not been widely assessed. To assess its effect on the pharmacokinetic profile of TZP, seven serum samples were collected from 11 hospitalized patients who received 3.375 g TZP intravenously for 4 h every 8 h. Population pharmacokinetic models were fit to the PK data utilizing first-order, Michaelis-Menten (MM), and parallel first-order/MM clearance. A population PK model with first-order clearance was fit to the tazobactam PK data. Monte Carlo simulations (MCSs) were used to determine the most effective administration schedule to ensure that free piperacillin concentrations were above the MIC for at least 50% of the dosing interval (50% fT>MIC) and to quantify the extent of the nonlinear clearance. The model incorporating parallel linear/MM clearance best fit the piperacillin PK data. The MCSs demonstrated that approximately 50% of the administered piperacillin is cleared by the nonlinear clearance mechanism. The results of the MCSs also revealed that more intensive TZP extended infusion dosing schemes (3.375 to 4.5 g intravenously [3-h infusion] every 6 h) than those commonly used in clinical practice were needed to maximize the 50% fT>MIC for MICs of ≥8 mg/liter. This study suggests that extended infusion of TZP is the most effective method of administration for patients with nosocomial infections. Due to the hyperclearance nature of the hospitalized patient populations studied, more intensive TZP dosing regimens may be needed to maximize fT>MIC in certain hospitalized populations.