Impact of continuous-infusion meropenem degradation and infusion bag changes on bacterial killing of Pseudomonas aeruginosa based on model-informed translation.

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 (CMEM) 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. CMEM, fT>MIC (time that concentrations exceed the MIC) and total bacterial load (BTOT) 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 CMEM_24h close to the MIC, with differences (Δ) in CMEM_24h up to 4.9 mg/L, ΔfT>MIC≤65.7%, and ΔBTOT_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.

Distribution of Bevacizumab into the Cerebrospinal Fluid of Children and Adolescents with Recurrent Brain Tumors.

BACKGROUND: To date, evidence has been lacking regarding bevacizumab pharmacokinetics in the cerebrospinal fluid (CSF). OBJECTIVE: This study assessed the penetration of bevacizumab, as part of a metronomic antiangiogenic treatment regimen, into the CSF of children, adolescents, and young adults with recurrent brain tumors. PATIENTS AND METHODS: Serum and CSF concentrations, malignant cells, and vascular endothelial growth factor A (VEGF-A) were analyzed in 12 patients (5-27 years) following 10 mg/kg bevacizumab intravenous biweekly administration (EudraCT number 2009-013024-23). A population pharmacokinetic model including body weight, albumin, and tumor type as influential factors was extended to quantify the CSF penetration of bevacizumab. RESULTS: Apart from in serum (minimum concentration/maximum concentration [Cmin/Cmax] 77.0-305/267-612 mg/L, median 144/417 mg/L), bevacizumab could be quantified in the CSF (0.01-2.26 mg/L, median 0.35 mg/L). The CSF/serum ratio was 0.16 and highly variable between patients. Malignant cells could be detected in CSF before initiation of treatment in five of 12 patients; after treatment, the CSF was cleared in all patients. VEGF-A was detected in three patients before treatment (mean ± SD: 20 ± 11 pg/mL), and was still measurable in one of these patients despite treatment (16 pg/mL). CONCLUSIONS: This pharmacokinetic pilot study indicated penetration of bevacizumab into the CSF in a population of children, adolescents, and young adults with recurrent brain tumors.

Best Practice for Therapeutic Drug Monitoring of Infliximab: Position Statement from the International Association of Therapeutic Drug Monitoring and Clinical Toxicology.

BACKGROUND: Infliximab, an anti-tumor necrosis factor monoclonal antibody, has revolutionized the pharmacological management of immune-mediated inflammatory diseases (IMIDs). This position statement critically reviews and examines existing data on therapeutic drug monitoring (TDM) of infliximab in patients with IMIDs. It provides a practical guide on implementing TDM in current clinical practices and outlines priority areas for future research. METHODS: The endorsing TDM of Biologics and Pharmacometrics Committees of the International Association of TDM and Clinical Toxicology collaborated to create this position statement. RESULTS: Accumulating data support the evidence for TDM of infliximab in the treatment of inflammatory bowel diseases, with limited investigation in other IMIDs. A universal approach to TDM may not fully realize the benefits of improving therapeutic outcomes. Patients at risk for increased infliximab clearance, particularly with a proactive strategy, stand to gain the most from TDM. Personalized exposure targets based on therapeutic goals, patient phenotype, and infliximab administration route are recommended. Rapid assays and home sampling strategies offer flexibility for point-of-care TDM. Ongoing studies on model-informed precision dosing in inflammatory bowel disease will help assess the additional value of precision dosing software tools. Patient education and empowerment, and electronic health record-integrated TDM solutions will facilitate routine TDM implementation. Although optimization of therapeutic effectiveness is a primary focus, the cost-reducing potential of TDM also merits consideration. CONCLUSIONS: Successful implementation of TDM for infliximab necessitates interdisciplinary collaboration among clinicians, hospital pharmacists, and (quantitative) clinical pharmacologists to ensure an efficient research trajectory.

Pharmacokinetics of isavuconazole at different target sites in healthy volunteers after single and multiple intravenous infusions.

BACKGROUND: Invasive aspergillosis is a severe fungal infection that affects multiple organ systems including the CNS and the lungs. Isavuconazole, a novel triazole antifungal agent, has demonstrated promising activity against Aspergillus spp. However, data on the penetration of isavuconazole into the CNS and ELF and intracellular accumulation remain limited. MATERIALS AND METHODS: We conducted a prospective single-centre pharmacokinetic (PK) study in 12 healthy volunteers. Subjects received seven doses of 200 mg isavuconazole to achieve an assumed steady-state. After the first and final infusion, plasma sampling was conducted over 8 and 12 h, respectively. All subjects underwent one lumbar puncture and bronchoalveolar lavage, at either 2, 6 or 12 h post-infusion of the final dose. PBMCs were collected in six subjects from blood to determine intracellular isavuconazole concentrations at 6, 8 or 12 h. The AUC/MIC was calculated for an MIC value of 1 mg/L, which marks the EUCAST susceptibility breakpoint for Aspergillus fumigatus and Aspergillus flavus. RESULTS: C max and AUC0-24h of isavuconazole in plasma under assumed steady-state conditions were 6.57 ±â€Š1.68 mg/L (mean ±â€ŠSD) and 106 ±â€Š32.1 h·mg/L, respectively. The average concentrations measured in CSF, ELF and in PBMCs were 0.07 ±â€Š0.03, 0.94 ±â€Š0.46 and 27.1 ±â€Š17.8 mg/L, respectively. The AUC/MIC in plasma, CSF, ELF and in PBMCs under steady-state conditions were 106 ±â€Š32.1, 1.68 ±â€Š0.72, 22.6 ±â€Š11.0 and 650 ±â€Š426 mg·h/L, respectively. CONCLUSION: Isavuconazole demonstrated moderate penetration into ELF, low penetrability into CSF and high accumulation in PBMCs. Current dosing regimens resulted in sufficient plasma exposure in all subjects to treat isolates with MICs ≤ 1 mg/L.

Integrative model-based comparison of target site-specific antimicrobial effects: A case study with ceftaroline and lefamulin.

OBJECTIVE: Predictions of antimicrobial effects typically rely on plasma-based pharmacokinetic-pharmacodynamic (PK-PD) targets, ignoring target-site concentrations and potential differences in tissue penetration between antibiotics. In this study, we applied PK-PD modelling to compare target site-specific effects of antibiotics by integrating clinical microdialysis data, in vitro time-kill curves, and antimicrobial susceptibility distributions. As a case study, we compared the effect of lefamulin and ceftaroline against methicillin-resistant Staphylococcus aureus (MRSA) at soft-tissue concentrations. METHODS: A population PK model describing lefamulin concentrations in plasma, subcutaneous adipose and muscle tissue was developed. For ceftaroline, a similar previously reported PK model was adopted. In vitro time-kill experiments were performed with six MRSA isolates and a PD model was developed to describe bacterial growth and antimicrobial effects. The clinical PK and in vitro PD models were linked to compare antimicrobial effects of ceftaroline and lefamulin at the different target sites. RESULTS: Considering minimum inhibitory concentration (MIC) distributions and standard dosages, ceftaroline showed superior anti-MRSA effects compared to lefamulin both at plasma and soft-tissue concentrations. Looking at the individual antibiotics, lefamulin effects were highest at soft-tissue concentrations, while ceftaroline effects were highest at plasma concentrations, emphasising the importance of considering target-site PK-PD in antibiotic treatment optimisation. CONCLUSION: Given standard dosing regimens, ceftaroline appeared more effective than lefamulin against MRSA at soft-tissue concentrations. The PK-PD model-based approach applied in this study could be used to compare or explore the potential of antibiotics for specific indications or in populations with unique target-site PK.

Impact of Key Components of Intensified Ceftaroline Dosing on Pharmacokinetic/Pharmacodynamic Target Attainment.

BACKGROUND AND OBJECTIVE: Ceftaroline fosamil is a ß-lactam antibiotic approved as a 600 mg twice daily dose (≤1 h infusion, 'standard dosing') or a 600 mg thrice daily dose (2 h infusion) to treat complicated skin and soft tissue infections caused by Staphylococcus aureus (minimum inhibitory concentration [MIC] 2-4 mg/L). We sought to systematically evaluate the relative impact of the three key components of the intensified dosing regimen (i.e. shortened dosing interval, prolonged infusion duration and increased total daily dose [TDD]) on the pharmacokinetic/pharmacodynamic (PK/PD) target attainment given different grades of bacterial susceptibility. METHODS: A population PK model was developed using data from 12 healthy volunteers (EudraCT-2012-005134-11) receiving standard or intensified dosing. PK/PD target attainment (ƒT>MIC = 35% and 100%) after 24 h was compared following systematically varied combinations of the (1) dosing interval (every 12 h [q12h]→ every 8 h [q8h]); (2) infusion duration (1 h→2 h); and (3) individual and total daily dose (400→900 mg, i.e. TDD 1200→1800 mg), as well as for varying susceptibility of S. aureus (MIC 0.032-8 mg/L). RESULTS: A two-compartment model with linear elimination adequately described ceftaroline concentrations (n = 274). The relevance of the dosing components dosing interval/infusion duration/TDD for ƒT>MIC systematically changed with pathogen susceptibility. For susceptible pathogens with MIC ≤1 mg/L, shortened dosing intervals appeared as the main driver of the improved target attainment associated with the intensified dosing regimen, followed by increased TDD and infusion duration. For less susceptible pathogens, the advantage of q8h dosing and 2 h infusions declined, and increased TDD improved ƒT>MIC the most. CONCLUSION: The analysis calls to mind consideration of dose increases when prolonging the infusion duration in the case of low bacterial susceptibility.

Multistate modeling for survival analysis in critically ill patients treated with meropenem.

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 (CLCRCG ), 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 CLCRCG 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.

Towards model-informed precision dosing of piperacillin: multicenter systematic external evaluation of pharmacokinetic models in critically ill adults with a focus on Bayesian forecasting.

PURPOSE: Inadequate piperacillin (PIP) exposure in intensive care unit (ICU) patients threatens therapeutic success. Model-informed precision dosing (MIPD) might be promising to individualize dosing; however, the transferability of published models to external populations is uncertain. This study aimed to externally evaluate the available PIP population pharmacokinetic (PopPK) models. METHODS: A multicenter dataset of 561 ICU patients (11 centers/3654 concentrations) was used for the evaluation of 24 identified models. Model performance was investigated for a priori (A) predictions, i.e., considering dosing records and patient characteristics only, and for Bayesian forecasting, i.e., additionally including the first (B1) or first and second (B2) therapeutic drug monitoring (TDM) samples per patient. Median relative prediction error (MPE) [%] and median absolute relative prediction error (MAPE) [%] were calculated to quantify accuracy and precision. RESULTS: The evaluation revealed a large inter-model variability (A: MPE - 135.6-78.3% and MAPE 35.7-135.6%). Integration of TDM data improved all model predictions (B1/B2 relative improvement vs. A: |MPE|median_all_models 45.1/67.5%; MAPEmedian_all_models 29/39%). The model by Kim et al. was identified to be most appropriate for the total dataset (A/B1/B2: MPE - 9.8/- 5.9/- 0.9%; MAPE 37/27.3/23.7%), Udy et al. performed best in patients receiving intermittent infusion, and Klastrup et al. best predicted patients receiving continuous infusion. Additional evaluations stratified by sex and renal replacement therapy revealed further promising models. CONCLUSION: The predictive performance of published PIP models in ICU patients varied considerably, highlighting the relevance of appropriate model selection for MIPD. Our differentiated external evaluation identified specific models suitable for clinical use, especially in combination with TDM.

Model-Informed Translation of In Vitro Effects of Short-, Prolonged- and Continuous-Infusion Meropenem against Pseudomonas aeruginosa to Clinical Settings.

Pharmacokinetic-pharmacodynamic (PKPD) models have met increasing interest as tools to identify potential efficacious antibiotic dosing regimens in vitro and in vivo. We sought to investigate the impact of diversely shaped clinical pharmacokinetic profiles of meropenem on the growth/killing patterns of Pseudomonas aeruginosa (ARU552, MIC = 16 mg/L) over time using a semi-mechanistic PKPD model and a PK/PD index-based approach. Bacterial growth/killing were driven by the PK profiles of six patient populations (infected adults, burns, critically ill, neurosurgery, obese patients) given varied pathogen features (e.g., EC50, growth rate, inoculum), patient characteristics (e.g., creatinine clearance), and ten dosing regimens (including two dose levels and 0.5-h, 3-h and continuous-infusion regimens). Conclusions regarding the most favourable dosing regimen depended on the assessment of (i) the total bacterial load or fT>MIC (time that unbound concentrations exceed the minimum inhibitory concentration); (ii) the median or P0.95 profile of the population; and (iii) 8 h or 24 h time points. Continuous infusion plus loading dose as well as 3-h infusions (3-h infusions: e.g., for scenarios associated with low meropenem concentrations, P0.95 profiles, and MIC ≥ 16 mg/L) appeared superior to standard 0.5-h infusions at 24 h. The developed platform can serve to identify promising strategies of efficacious dosing for clinical trials.

Pharmacokinetic/pharmacodynamic models for time courses of antibiotic effects.

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.

Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety.

PURPOSE: Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity. METHODS: Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CLSN-38: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m2 (-30%)). Study power was assessed given diverse scenarios (n = 50-400 patients/arm, parallel/crossover, varying magnitude of CLSN-38, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing. RESULTS: The magnitude of CLSN-38 reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (<0.5·109 cells/L) after PGx-based versus standard dosing. To achieve >80% power with traditional statistical analysis (χ2/McNemar's test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (n = 100/15 given parallel/crossover design) to obtain the same statistical power. CONCLUSIONS: The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies.

From Therapeutic Drug Monitoring to Model-Informed Precision Dosing for Antibiotics.

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.

Development of a dosing algorithm for meropenem in critically ill patients based on a population pharmacokinetic/pharmacodynamic analysis.

Effective antibiotic dosing is vital for therapeutic success in critically ill patients. This work aimed to develop an algorithm to identify appropriate meropenem dosing in critically ill patients. Population pharmacokinetic (PK) modelling was performed in NONMEM®7.3 based on densely sampled meropenem serum samples (npatients = 48; nsamples = 1376) and included a systematic analysis of 27 pre-selected covariates to identify factors influencing meropenem exposure. Using Monte Carlo simulations newly considering the uncertainty of PK parameter estimates, standard meropenem dosing was evaluated with respect to attainment of the pharmacokinetic/pharmacodynamic (PK/PD) target and was compared with alternative infusion regimens (short-term, prolonged, continuous; daily dose, 2000-6000 mg). Subsequently, a dosing algorithm was developed to identify appropriate dosing regimens. The two-compartment population PK model included three factors influencing meropenem pharmacokinetics: the Cockcroft-Gault creatinine clearance (CLCRCG) on meropenem clearance; and body weight and albumin on the central and peripheral volume of distribution, respectively; of these, only CLCRCG was identified as a vital influencing factor on PK/PD target attainment. A three-level dosing algorithm was developed (considering PK parameter uncertainty), suggesting dosing regimens depending on renal function and the level (L) of knowledge about the infecting pathogen (L1, pathogen unknown; L2, pathogen known; L3(-MIC), pathogen and susceptibility known; L3(+MIC), MIC known). Whereas patients with higher CLCRCG and lower pathogen susceptibility required mainly intensified dosing regimens, lower than standard doses appeared sufficient for highly susceptible pathogens. In conclusion, a versatile meropenem dosing algorithm for critically ill patients is proposed, indicating appropriate dosing regimens based on patient- and pathogen-specific information.

Development of a dosing nomogram for continuous-infusion meropenem in critically ill patients based on a validated population pharmacokinetic model.

Background: Optimal antibiotic exposure is a vital but challenging prerequisite for achieving clinical success in ICU patients. Objectives: To develop and externally validate a population pharmacokinetic model for continuous-infusion meropenem in critically ill patients and to establish a nomogram based on a routinely available marker of renal function. Methods: A population pharmacokinetic model was developed in NONMEM® 7.3 based on steady-state meropenem concentrations (CSS) collected during therapeutic drug monitoring. Different serum creatinine-based markers of renal function were compared for their influence on meropenem clearance (the Cockcroft-Gault creatinine clearance CLCRCG, the CLCR bedside estimate according to Jelliffe, the Chronic Kidney Disease Epidemiology Collaboration equation and the four-variable Modification of Diet in Renal Disease equation). After validation of the pharmacokinetic model with independent data, a dosing nomogram was developed, relating renal function to the daily doses required to achieve selected target concentrations (4/8/16 mg/L) in 90% of the patients. Probability of target attainment was determined for efficacy (CSS ≥8 mg/L) and potentially increased likelihood of adverse drug reactions (CSS >32 mg/L). Results: In total, 433 plasma concentrations (3.20-48.0 mg/L) from 195 patients (median/P0.05 - P0.95 at baseline: weight 77.0/55.0-114 kg, CLCRCG 63.0/19.6-168 mL/min) were used for model building. We found that CLCRCG best described meropenem clearance (CL = 7.71 L/h, CLCRCG = 80 mL/min). The developed model was successfully validated with external data (n = 171, 73 patients). According to the nomogram, daily doses of 910/1480/2050/2800/3940 mg were required to reach a target CSS = 8 mg/L in 90% of patients with CLCRCG = 20/50/80/120/180 mL/min, respectively. A low probability of adverse drug reactions (<0.5%) was associated with these doses. Conclusions: A dosing nomogram was developed for continuous-infusion meropenem based on renal function in a critically ill population.

Role of renal function in risk assessment of target non-attainment after standard dosing of meropenem in critically ill patients: a prospective observational study.

BACKGROUND: Severe bacterial infections remain a major challenge in intensive care units because of their high prevalence and mortality. Adequate antibiotic exposure has been associated with clinical success in critically ill patients. The objective of this study was to investigate the target attainment of standard meropenem dosing in a heterogeneous critically ill population, to quantify the impact of the full renal function spectrum on meropenem exposure and target attainment, and ultimately to translate the findings into a tool for practical application. METHODS: A prospective observational single-centre study was performed with critically ill patients with severe infections receiving standard dosing of meropenem. Serial blood samples were drawn over 4 study days to determine meropenem serum concentrations. Renal function was assessed by creatinine clearance according to the Cockcroft and Gault equation (CLCRCG). Variability in meropenem serum concentrations was quantified at the middle and end of each monitored dosing interval. The attainment of two pharmacokinetic/pharmacodynamic targets (100%T>MIC, 50%T>4×MIC) was evaluated for minimum inhibitory concentration (MIC) values of 2 mg/L and 8 mg/L and standard meropenem dosing (1000 mg, 30-minute infusion, every 8 h). Furthermore, we assessed the impact of CLCRCG on meropenem concentrations and target attainment and developed a tool for risk assessment of target non-attainment. RESULTS: Large inter- and intra-patient variability in meropenem concentrations was observed in the critically ill population (n = 48). Attainment of the target 100%T>MIC was merely 48.4% and 20.6%, given MIC values of 2 mg/L and 8 mg/L, respectively, and similar for the target 50%T>4×MIC. A hyperbolic relationship between CLCRCG (25-255 ml/minute) and meropenem serum concentrations at the end of the dosing interval (C8h) was derived. For infections with pathogens of MIC 2 mg/L, mild renal impairment up to augmented renal function was identified as a risk factor for target non-attainment (for MIC 8 mg/L, additionally, moderate renal impairment). CONCLUSIONS: The investigated standard meropenem dosing regimen appeared to result in insufficient meropenem exposure in a considerable fraction of critically ill patients. An easy- and free-to-use tool (the MeroRisk Calculator) for assessing the risk of target non-attainment for a given renal function and MIC value was developed. TRIAL REGISTRATION: Clinicaltrials.gov, NCT01793012 . Registered on 24 January 2013.

Pharmacokinetics of doripenem in plasma and epithelial lining fluid (ELF): comparison of two dosage regimens.

PURPOSE: In 2014, FDA released a warning for prescription of doripenem for ventilator-associated bacterial pneumonia due to unsatisfactory clinical cure rates. The present study explores if the observed lack of efficacy might be explained by insufficient target site pharmacokinetics in intensive care patients after two different infusion schemes. METHODS: Plasma and bronchoalveolar lavage sampling was performed in 16 intubated patients with pneumonia receiving doripenem either as 1-h or as 4-h infusion. Doripenem concentrations were measured at steady state in plasma over 8 h, bronchoalvoelar lavage was performed in each patient once either after 0 h, 2 h, 4 h or 6 h. RESULTS: In plasma, mean values of Cmax, Tmax and AUC0-8 were 16.87 mg/L, 0.69 h and 52.98 mg/L×h after 1 h of infusion, and 12.94 mg/L, 3.21 h and 70.64 mg/L×h after 4 h of infusion, respectively. While the later tmax in plasma was with delay mirrored in the lung, for ELF, much lower concentrations were observed (Cmax, Tmax and AUC0-8 after 1-h infusion of 4.6 mg/L, 2 h and 15.3 mg/L×h and after 4-h infusion 6.9 mg/L, 4 h and 14.8 mg/L×h). CONCLUSION: The difference in plasma pharmacokinetics after 1-h and 4-h infusion reflects in the concentration versus time profile in the lung, but concentration at the target site was not only considerably lower but also subject to high inter-individual variability. We hypothesise that insufficient concentrations at the target site might have contributed to the previously described lack of clinical efficacy and confirmed the demand for assessment of target site pharmacokinetics in larger patient collectives.