Systematic Evaluation of Pharmacokinetic Models for Model-Informed Precision Dosing of Meropenem in Critically Ill Patients Undergoing Continuous Renal Replacement Therapy.

The altered pharmacokinetics of renally cleared drugs such as meropenem in critically ill patients receiving continuous renal replacement therapy (CRRT) might impact target attainment. Model-informed precision dosing (MIPD) is applied to individualize meropenem dosing. However, most population pharmacokinetic (PopPK) models developed to date have not yet been evaluated for MIPD. Eight PopPK models based on adult CRRT patients were identified in a systematic literature research and encoded in NONMEM 7.4. A data set of 73 CRRT patients from two different study centers was used to evaluate the predictive performance of the models using simulation and prediction-based diagnostics for i) a priori dosing based on patient characteristics only and ii) Bayesian dosing by including the first measured trough concentration. Median prediction error (MPE) for accuracy within |20%| (95% confidence intervals including zero) and median absolute prediction error (MAPE) for precision ≤ 30% were considered clinically acceptable. For a priori dosing, most models (n = 5) showed accuracy and precision MPE within |20%| and MAPE <35%. The integration of the first measured meropenem concentration improved the predictive performance of all models (median MAPE decreased from 35.4 to 25.0%; median MPE decreased from 21.8 to 4.6%). The best predictive performance for intermittent infusion was observed for the O'Jeanson model, including residual diuresis as covariate (a priori and Bayesian dosing MPE within |2%|, MAPE <30%). Our study revealed the O'Jeanson model as the best-predicting model for intermittent infusion. However, most of the selected PopPK models are suitable for MIPD in CRRT patients when one therapeutic drug monitoring sample is available.

Combination of Pharmacokinetic and Pathogen Susceptibility Information To Optimize Meropenem Treatment of Gram-Negative Infections in Critically Ill Patients.

Meropenem is one of the most frequently used antibiotics to treat life-threatening infections in critically ill patients. This study aimed to develop a meropenem dosing algorithm for the treatment of Gram-negative infections based on intensive care unit (ICU)-specific resistance data. Antimicrobial susceptibility testing of Gram-negative bacteria obtained from critically ill patients was carried out from 2016 to 2020 at a tertiary care hospital. Based on the observed MIC distribution, stochastic simulations (n = 1,000) of an evaluated pharmacokinetic meropenem model, and a defined pharmacokinetic/pharmacodynamic target (100%T>4×MIC while minimum concentrations were <44.5 mg/L), dosing recommendations for patients with varying renal function were derived. Pathogen-specific MIC distributions were used to calculate the cumulative fraction of response (CFR), and the overall MIC distribution was used to calculate the local pathogen-independent mean fraction of response (LPIFR) for the investigated dosing regimens. A CFR/LPIFR of >90% was considered adequate. The observed MIC distribution significantly differed from the EUCAST database. Based on the 6,520 MIC values included, a three-level dosing algorithm was developed. If the pathogen causing the infection is unknown (level 1), known (level 2), known to be neither Pseudomonas aeruginosa nor Acinetobacter baumannii, or classified as susceptible (level 3), a continuous infusion of 1.5 g daily reached sufficient target attainment independent of renal function. In all other cases, dosing needs to be adjusted based on renal function. ICU-specific susceptibility data should be assessed regularly and integrated into dosing decisions. The presented workflow may serve as a blueprint for other antimicrobial settings.

Target Site Pharmacokinetics of Meropenem: Measurement in Human Explanted Lung Tissue by Bronchoalveolar Lavage, Microdialysis, and Homogenized Lung Tissue.

Pneumonia is one of the most common infections in intensive care patients, and it is often treated with beta-lactam antibiotics. Even if therapeutic drug monitoring in blood is available, it is unclear whether sufficient concentrations are reached at the target site: the lung. The present study was initiated to fill this knowledge gap. Various compartments from 10 patients' explanted lungs were subjected to laboratory analysis. Meropenem was quantified in serum, bronchoalveolar lavage (BAL) fluid, microdialysate, and homogenized lung tissue with isotope dilution liquid chromatography tandem mass spectrometry (ID-LC-MS/MS). BAL fluid represents diluted epithelial lining fluid (ELF), and microdialysate represents interstitial fluid (IF). Differences between target site and blood concentrations were investigated. The median meropenem concentration in blood, ELF, IF, and tissue were 26.8, 18.0, 12.1, and 9.1 mg/liter, respectively. A total of 37.5% of the target site ELF and IF meropenem concentrations were below the clinical EUCAST breakpoint of 8 mg/liter. The median ELF/serum quotient was 61.8% (interquartile range [IQR], 24.8% to 87.6%), the median IF/serum quotient was 35.4% (IQR, 23.8% to 54.3%), and the median tissue/serum quotient was 34.2% (IQR, 28.3% to 38.2%). We observed a substantial interindividual variability between the blood and the compartments (ELF and IF), whereas the intraindividual variability was relatively low. Target site measurement in different lung compartments was feasible and successfully applied in a clinical setting. A relevant amount of 37.5% of the target site concentrations were below the clinical EUCAST breakpoint, indicating subtherapeutic dosing in high-risk patients receiving perioperative antibiotic prophylaxis in lung transplantation. (This study has been registered at ClinicalTrials.gov under identifier NCT03970265.).

CYP2D6 phenotype explains reported yohimbine concentrations in four severe acute intoxications.

The indole alkaloid yohimbine is an alpha-2 receptor antagonist used for its sympathomimetic effects. Several cases of yohimbine intoxication have been reported and the most recent one involved four individuals taking a yohimbine-containing drug powder. All individuals developed severe intoxication symptoms and were admitted to the hospital. Even though all individuals were assumed to have taken the same dose of the drug powder, toxicology analyses revealed yohimbine blood concentrations of 249-5631 ng/mL, amounting to a 22-fold difference. The reason for this high variability remained to be elucidated. We used recently reported knowledge on the metabolism of yohimbine together with state-of-the art nonlinear mixed-effects modelling and simulation and show that a patient's cytochrome P450 2D6 (CYP2D6) phenotype can explain the large differences observed in the measured concentration after intake of the same yohimbine dose. Our findings can be used both for the identification of safe doses in therapeutic use of yohimbine and for an explanation of individual cases of overdosing.

Addressing the ADME Challenges of Compound Loss in a PDMS-Based Gut-on-Chip Microphysiological System.

Microphysiological systems (MPSs) are promising in vitro technologies for physiologically relevant predictions of the human absorption, distribution, metabolism, and excretion (ADME) properties of drug candidates. However, polydimethylsiloxane (PDMS), a common material used in MPSs, can both adsorb and absorb small molecules, thereby compromising experimental results. This study aimed to evaluate the feasibility of using the PDMS-based Emulate gut-on-chip to determine the first-pass intestinal drug clearance. In cell-free PDMS organ-chips, we assessed the loss of 17 drugs, among which testosterone was selected as a model compound for further study based on its substantial ad- and absorptions to organ chips and its extensive first-pass intestinal metabolism with well-characterized metabolites. A gut-on-chip model consisting of epithelial Caco-2 cells and primary human umbilical vein endothelial cells (HUVECs) was established. The barrier integrity of the model was tested with reference compounds and inhibition of drug efflux. Concentration-time profiles of testosterone were measured in cell-free organ chips and in gut-on-chip models. A method to deduce the metabolic clearance was provided. Our results demonstrate that metabolic clearance can be determined with PDMS-based MPSs despite substantial compound loss to the chip. Overall, this study offers a practical protocol to experimentally assess ADME properties in PDMS-based MPSs.

Results from a Joined Prospective Study to Evaluate the Sensitivity of the In Vivo Dog QT Assay in Line with the ICH E14/S7B Q&A Best Practices.

The ICH E14/S7B Q&As highlighted the need for best practices concerning the design, execution, analysis, interpretation, and reporting of the in vivo non-rodent QT assay as a component of the integrated risk assessment to potentially support a TQT waiver or substitute. We conducted a dog telemetry study to assess the effects on QTc of six reference compounds (five positive and one negative) previously evaluated by Darpo et al. (2015) in humans. The sensitivity of the assay to detect QTc increases was determined, and exposure-response analysis was performed, as done in clinical practice. By-timepoint analysis showed QTc prolongation induced by moxifloxacin, dofetilide, dolasetron, ondansetron, and quinine within human relevant plasma exposures ranges. Moreover, a hysteresis was observed for quinine. As expected, levocetirizine showed no statistically significant effect on QTc across a range of exposure, well exceeding the therapeutic Cmax. Power analyses confirmed the study ability to detect statistically significant QTc changes of less than 10 milliseconds with 80% probability, even with a sample size as low as n = 4 animals. Finally, concentration-QTc modeling enabled to predict the minimal plasma concentration needed to detect a 10 milliseconds QTc prolongation, including for quinine. The comparison with clinical available data supported the relevance of dogs under these experimental conditions as a robust translational predictor of drug-induced QTc prolongation in humans as a key pillar of the integrated risk assessment.

Does the cytokine adsorber CytoSorb® reduce vancomycin exposure in critically ill patients with sepsis or septic shock? a prospective observational study.

BACKGROUND: Hemadsorption of cytokines is used in critically ill patients with sepsis or septic shock. Concerns have been raised that the cytokine adsorber CytoSorb® unintentionally adsorbs vancomycin. This study aimed to quantify vancomycin elimination by CytoSorb®. METHODS: Critically ill patients with sepsis or septic shock receiving continuous renal replacement therapy and CytoSorb® treatment during a prospective observational study were included in the analysis. Vancomycin pharmacokinetics was characterized using population pharmacokinetic modeling. Adsorption of vancomycin by the CytoSorb® was investigated as linear or saturable process. The final model was used to derive dosing recommendations based on stochastic simulations. RESULTS: 20 CytoSorb® treatments in 7 patients (160 serum samples/24 during CytoSorb®-treatment, all continuous infusion) were included in the study. A classical one-compartment model, including effluent flow rate of the continuous hemodialysis as linear covariate on clearance, best described the measured concentrations (without CytoSorb®). Significant adsorption with a linear decrease during CytoSorb® treatment was identified (p < 0.0001) and revealed a maximum increase in vancomycin clearance of 291% (initially after CytoSorb® installation) and a maximum adsorption capacity of 572 mg. For a representative patient of our cohort a reduction of the area under the curve (AUC) by 93 mg/L*24 h during CytoSorb® treatment was observed. The additional administration of 500 mg vancomycin over 2 h during CytoSorb® attenuated the effect and revealed a negligible reduction of the AUC by 4 mg/L*24 h. CONCLUSION: We recommend the infusion of 500 mg vancomycin over 2 h during CytoSorb® treatment to avoid subtherapeutic concentrations. Trial registration NCT03985605. Registered 14 June 2019, https://clinicaltrials.gov/ct2/show/NCT03985605.

Evaluation of a Meropenem and Piperacillin Monitoring Program in Intensive Care Unit Patients Calls for the Regular Assessment of Empirical Targets and Easy-to-Use Dosing Decision Tools.

The drug concentrations targeted in meropenem and piperacillin/tazobactam therapy also depend on the susceptibility of the pathogen. Yet, the pathogen is often unknown, and antibiotic therapy is guided by empirical targets. To reliably achieve the targeted concentrations, dosing needs to be adjusted for renal function. We aimed to evaluate a meropenem and piperacillin/tazobactam monitoring program in intensive care unit (ICU) patients by assessing (i) the adequacy of locally selected empirical targets, (ii) if dosing is adequately adjusted for renal function and individual target, and (iii) if dosing is adjusted in target attainment (TA) failure. In a prospective, observational clinical trial of drug concentrations, relevant patient characteristics and microbiological data (pathogen, minimum inhibitory concentration (MIC)) for patients receiving meropenem or piperacillin/tazobactam treatment were collected. If the MIC value was available, a target range of 1-5 × MIC was selected for minimum drug concentrations of both drugs. If the MIC value was not available, 8-40 mg/L and 16-80 mg/L were selected as empirical target ranges for meropenem and piperacillin, respectively. A total of 356 meropenem and 216 piperacillin samples were collected from 108 and 96 ICU patients, respectively. The vast majority of observed MIC values was lower than the empirical target (meropenem: 90.0%, piperacillin: 93.9%), suggesting empirical target value reductions. TA was found to be low (meropenem: 35.7%, piperacillin 50.5%) with the lowest TA for severely impaired renal function (meropenem: 13.9%, piperacillin: 29.2%), and observed drug concentrations did not significantly differ between patients with different targets, indicating dosing was not adequately adjusted for renal function or target. Dosing adjustments were rare for both drugs (meropenem: 6.13%, piperacillin: 4.78%) and for meropenem irrespective of TA, revealing that concentration monitoring alone was insufficient to guide dosing adjustment. Empirical targets should regularly be assessed and adjusted based on local susceptibility data. To improve TA, scientific knowledge should be translated into easy-to-use dosing strategies guiding antibiotic dosing.

Development of a Model-Informed Dosing Tool to Optimise Initial Antibiotic Dosing-A Translational Example for Intensive Care Units.

The prevalence and mortality rates of severe infections are high in intensive care units (ICUs). At the same time, the high pharmacokinetic variability observed in ICU patients increases the risk of inadequate antibiotic drug exposure. Therefore, dosing tailored to specific patient characteristics has a high potential to improve outcomes in this vulnerable patient population. This study aimed to develop a tabular dosing decision tool for initial therapy of meropenem integrating hospital-specific, thus far unexploited pathogen susceptibility information. An appropriate meropenem pharmacokinetic model was selected from the literature and evaluated using clinical data. Probability of target attainment (PTA) analysis was conducted for clinically interesting dosing regimens. To inform dosing prior to pathogen identification, the local pathogen-independent mean fraction of response (LPIFR) was calculated based on the observed minimum inhibitory concentrations distribution in the hospital. A simple, tabular, model-informed dosing decision tool was developed for initial meropenem therapy. Dosing recommendations achieving PTA > 90% or LPIFR > 90% for patients with different creatinine clearances were integrated. Based on the experiences during the development process, a generalised workflow for the development of tabular dosing decision tools was derived. The proposed workflow can support the development of model-informed dosing tools for initial therapy of various drugs and hospital-specific conditions.

Evaluation of the MeroRisk Calculator, A User-Friendly Tool to Predict the Risk of Meropenem Target Non-Attainment in Critically Ill Patients.

BACKGROUND: The MeroRisk-calculator, an easy-to-use tool to determine the risk of meropenem target non-attainment after standard dosing (1000 mg; q8h), uses a patient's creatinine clearance and the minimum inhibitory concentration (MIC) of the pathogen. In clinical practice, however, the MIC is rarely available. The objectives were to evaluate the MeroRisk-calculator and to extend risk assessment by including general pathogen sensitivity data. METHODS: Using a clinical routine dataset (155 patients, 891 samples), a direct data-based evaluation was not feasible. Thus, in step 1, the performance of a pharmacokinetic model was determined for predicting the measured concentrations. In step 2, the PK model was used for a model-based evaluation of the MeroRisk-calculator: risk of target non-attainment was calculated using the PK model and agreement with the MeroRisk-calculator was determined by a visual and statistical (Lin's concordance correlation coefficient (CCC)) analysis for MIC values 0.125-16 mg/L. The MeroRisk-calculator was extended to include risk assessment based on EUCAST-MIC distributions and cumulative-fraction-of-response analysis. RESULTS: Step 1 showed a negligible bias of the PK model to underpredict concentrations (-0.84 mg/L). Step 2 revealed a high level of agreement between risk of target non-attainment predictions for creatinine clearances >50 mL/min (CCC = 0.990), but considerable deviations for patients <50 mL/min. For 27% of EUCAST-listed pathogens the median cumulative-fraction-of-response for the observed patients receiving standard dosing was < 90%. CONCLUSIONS: The MeroRisk-calculator was successfully evaluated: For patients with maintained renal function it allows a reliable and user-friendly risk assessment. The integration of pathogen-based risk assessment substantially increases the applicability of the tool.