Population Pharmacokinetic Analysis of Vancomycin in Patients with Solid or Hematological Malignancy in Relation to the Quick Sequential Organ Failure Assessment Scores.

BACKGROUND AND OBJECTIVE: It remains unclear whether sepsis in patients with malignancy interferes with the predictive performance of the dose-estimation formulas. The quick sequential organ failure assessment (qSOFA) score can help identify patients with poor outcomes because of sepsis-associated organ damage. Vancomycin, an important antibiotic, treats systemic infections (sepsis) caused by methicillin-resistant Staphylococcus aureus. We aimed to clarify whether including the qSOFA score in a standard population pharmacokinetic (PopPK) assessment may improve the predictive performance of vancomycin doses in patients with malignancy. METHODS: This was a retrospective, observational study. Serum vancomycin concentration-time datasets were obtained from the therapeutic drug monitoring records of St. Luke's International Hospital (Tokyo, Japan) from January 2011 to August 2016. Clinical and laboratory data of the relevant patients were retrieved from electronic health records. PopPK analysis was performed using the NONMEM program, which includes creatinine clearance (CLCr), blood neutrophil counts, qSOFA scores, and type of malignancy as covariates. We examined the validity of the final PopPK model using bootstrapping, goodness-of-fit plots, and prediction-corrected visual predictive checks. RESULTS: Six hundred and eight blood samples were obtained from 325 patients. In the final PopPK model, the CLCr and qSOFA scores were selected as covariates of systemic vancomycin clearance (p < 0.05): the population mean value was 2.8 (L/h). Regardless of the CLCr, a qSOFA score of greater than 1 was associated with an approximately 10% reduction in vancomycin clearance. CONCLUSIONS: qSOFA scores might be an additional covariate to CLCr for estimating vancomycin concentrations with a PopPK model in patients with malignancy.

Correlation of Calculated Vancomycin Trough Concentrations and Exposure: A Monte Carlo Simulation.

BACKGROUND: Current recommendations are to dose vancomycin to target 24-hour area under the curve (AUC) of 400-600 mg·h/L to optimize efficacy and safety. Limited data support AUC monitoring, and some centers continue to use trough concentrations. A target of 10-20 mg/L has been proposed to reduce nephrotoxicity risk. OBJECTIVE: To use previously published pharmacokinetic equations in a Monte Carlo simulation relating AUC exposure to trough concentrations when targeting an AUC between 400 and 600 mg·h/L. METHODS: Previously published pharmacokinetic data were used as input parameters for a Monte Carlo simulation using previously published formulae to correlate AUC to simulated trough concentrations. Pharmacokinetic parameters were assumed to occur in a normal distribution pattern. We excluded irrelevant simulated cases. Maintenance doses of 15 mg/kg were rounded to the nearest 250 mg. Calculated trough concentrations for AUCs of both 400 and 600 mg·h/L were evaluated in each simulation. RESULTS: A total of 10 000 Monte Carlo simulations were performed. Targeting an AUC of 400 mg·h/L resulted in a mean trough concentration of 10.3 ± 0.8 mg/L. Targeting an AUC of 600 mg·h/L resulted in a mean trough concentration of 15.4 ± 1.2 mg/L. CONCLUSION AND RELEVANCE: We demonstrate that a lower trough concentration range may be supported by an AUC of 400-600 mg·h/L, which may reduce risk and rates of nephrotoxicity without compromising previously established efficacious target trough concentrations.

Optimization of Vancomycin Initial Dose in Term and Preterm Neonates by Machine Learning.

INTRODUCTION: Vancomycin is one of the antibiotics most used in neonates. Continuous infusion has many advantages over intermittent infusions, but no consensus has been achieved regarding the optimal initial dose. The objectives of this study were: to develop a Machine learning (ML) algorithm based on pharmacokinetic profiles obtained by Monte Carlo simulations using a population pharmacokinetic model (POPPK) from the literature, in order to derive the best vancomycin initial dose in preterm and term neonates, and to compare ML performances with those of an literature equation (LE) derived from a POPPK previously published. MATERIALS AND METHODS: The parameters of a previously published POPPK model of vancomycin in children and neonates were used in the mrgsolve R package to simulate 1900 PK profiles. ML algorithms were developed from these simulations using Xgboost, GLMNET and MARS in parallel, benchmarked and used to calculate the ML first dose. Performances were evaluated in a second simulation set and in an external set of 82 real patients and compared to those of a LE. RESULTS: The Xgboost algorithm yielded numerically best performances and target attainment rates: 46.9% in the second simulation set of 400-600 AUC/MIC ratio vs. 41.4% for the LE model (p = 0.0018); and 35.3% vs. 28% in real patients (p = 0.401), respectively). The Xgboost model resulted in less AUC/MIC > 600, thus decreasing the risk of nephrotoxicity. CONCLUSION: The Xgboost algorithm developed to estimate the initial dose of vancomycin in term or preterm infants has better performances than a previous validated LE and should be evaluated prospectively.

Predictive Performance of Pharmacokinetic Model-Based Virtual Trials of Vancomycin in Neonates: Mathematics Matches Clinical Observation.

BACKGROUND AND OBJECTIVE: Vancomycin is frequently used to treat Gram-positive bacterial infections in neonates. However, there is still no consensus on the optimal initial dosing regimen. This study aimed to assess the performance of pharmacokinetic model-based virtual trials to predict the dose-exposure relationship of vancomycin in neonates. METHODS: The PubMed database was searched for clinical trials of vancomycin in neonates that reported the percentage of target attainment. Monte Carlo simulations were performed using nonlinear mixed-effect modeling to predict the dose-exposure relationship, and the differences in outcomes between virtual trials and real-world data in clinical studies were calculated. RESULTS: A total of 11 studies with 14 dosing groups were identified from the literature to evaluate dose-exposure relationships. For the ten dosing groups where the surrogate marker for exposure was the trough concentration, the mean ± standard deviation (SD) for the target attainment between original studies and virtual trials was 3.0 ± 7.3%. Deviations between - 10 and 10% accounted for 80% of the included dosing groups. For the other four dosing groups where the surrogate marker for exposure was concentration during continuous infusion, all deviations were between - 10 and 10%, and the mean ± SD value was 2.9 ± 4.5%. CONCLUSION: The pharmacokinetic model-based virtual trials of vancomycin exhibited good predictive performance for dose-exposure relationships in neonates. These results might be used to assist the optimization of dosing regimens in neonatal practice, avoiding the need for trial and error.

Population Pharmacokinetics and Dosing Optimization of Vancomycin in Pediatric Liver Transplant Recipients.

Methicillin-resistant Staphylococcus aureus infections are a significant cause of morbidity and mortality in pediatric liver transplant (LT) recipients. Physiological changes following LT may affect vancomycin pharmacokinetics; however, appropriate dosing to achieve sufficient drug exposure (i.e., 24-h area under the concentration-time curve [AUC24]/MIC ≥ 400) in pediatric LT recipients has not been reported. This retrospective pharmacokinetics study of LT recipients aged <18 years utilized data on patient characteristics with vancomycin concentrations and dosing information obtained from electronic medical records. Population pharmacokinetics analysis was conducted by nonlinear mixed-effects modeling with the Phoenix NLME software. Potential covariates were screened with univariate and multivariate analysis. Monte Carlo simulations were performed using the final model to explore appropriate dosing. The study included 270 pharmacokinetics profiles encompassing 1,158 concentrations measured in 161 patients. The median age was 13.3 (interquartile range, 7.6 to 53.5) months, serum creatinine (sCr) was 0.16 (0.12 to 0.23) mg/dl, and days from LT (DFLT) was 17 (6 to 31). Multivariate analysis demonstrated that lower sCr and shorter DFLT were associated with higher clearance. By post hoc estimation, the average clearance and volume of distribution were 0.18 liters/h/kg and 1.01 liters/kg, respectively. The Monte Carlo simulations revealed that only 16% of patients achieved an AUC24/MIC of ≥400 with the assumed vancomycin MIC of 1 µg/ml. DFLT and sCr were significant covariates for vancomycin clearance in pediatric LT recipients. Standard vancomycin dosing may be insufficient, and higher or more frequent dosing may be required to achieve an AUC24/MIC of ≥400 in pediatric LT recipients with normal renal function. IMPORTANCE We evaluated vancomycin pharmacokinetics in pediatric LT recipients and developed a population pharmacokinetics model by considering various factors that might account for alterations in vancomycin pharmacokinetics. Our analyses revealed that lower serum creatinine levels and a shorter duration from the day of LT were associated with higher vancomycin clearance and led to subtherapeutic drug exposure. We also performed Monte Carlo simulations to determine the appropriate dosing strategy in pediatric LT recipients, which revealed that a standard vancomycin dosing might be insufficient and that higher or more frequent dosing might be necessary to achieve an AUC24/MIC of ≥400 in pediatric LT recipients with normal renal function. To the best of our knowledge, this is the first study to assess vancomycin pharmacokinetics in pediatric LT recipients by population pharmacokinetics analysis.

Population Pharmacokinetics and Dose Optimization of Vancomycin in Critically Ill Children.

BACKGROUND AND OBJECTIVE: Critically ill children may exhibit varied vancomycin pharmacokinetic parameters mainly due to altered protein binding, extracellular volume, and renal elimination. The objective of this study was to assess the pharmacokinetics of vancomycin in critically ill children and determine the optimum dose regimen. METHODS: This was a cross-sectional study of critically ill children admitted to a pediatric intensive care unit. They received vancomycin dose of 15 mg/kg every 8 h for mild infections or every 6 h if infection was moderate or severe. A nonlinear mixed-effects modeling approach was applied in estimating pharmacokinetic parameters using Monolix 2019R2®. We performed Monte Carlo simulations to assess and optimize the dosing regimen using Simulx®. We used the ratio of the area under the concentration-time curve up to 24 h to minimum inhibitory concentration (AUC0-24/MIC) ≥ 400 as the pharmacokinetic-pharmacodynamic target. RESULTS: Fifty-eight critically ill children with 145 concentrations were included in the present study. A one-compartment pharmacokinetic model with linear elimination described the concentration-time profile well. The estimated median (95% confidence intervals) volume of distribution (Vd) was 13.3 (10.8-16.5) l and clearance (CL) was 1.23 (1.03-1.45) l/h. Creatinine clearance significantly affected the CL of vancomycin. Monte Carlo simulations revealed that a dose of either 15 mg/kg 6 hourly or 20 mg/kg 8 hourly was likely to result into most critically ill children attaining the vancomycin lead pharmacokinetic-pharmacodynamic target. CONCLUSION: We established pharmacokinetic parameters of vancomycin for critically ill children. We also observed that the current dosing regimen practiced in the intensive care unit was inadequate for achieving the pharmacokinetic-pharmacodynamic target. We recommend vancomycin dose escalation in critically ill pediatric patients from 15 mg/kg 8 hourly (current dosing regimen) to either 6 hourly or 20 mg/kg 8 hourly with intense therapeutic drug monitoring for adverse effects.

Optimization of dosing regimens of vancomycin, teicoplanin, linezolid and daptomycin against methicillin-resistant Staphylococcus aureus in neutropenic patients with cancer by Monte Carlo simulations.

The objective of this study was to evaluate the efficacy of various dosing regimens of vancomycin, teicoplanin, linezolid and daptomycin against methicillin-resistant Staphylococcus aureus (MRSA) in neutropenic patients with cancer. Monte Carlo simulations were conducted using pharmacokinetic parameters and pharmacodynamic data to determine cumulative fraction of response (CFRs) in terms of area under the concentration-time curve/minimum inhibition concentration target. Currently clinical standard dosing regimens of vancomycin, teicoplanin, linezolid and daptomycin were insufficient to provide expected CFRs against MRSA for neutropenic patients with cancer. The high dosing regimens of vancomycin (3500 mg/d), teicoplanin (800 mg/d) and daptomycin (8 mg/kg/d) could provide CFRs of ≥ 80%, showing a higher treatment success. However, the majority of CFRs with linezolid simulated dosing regimens reached < 80% against MRSA. Therefore, a strategy of high dosages of vancomycin, teicoplanin and daptomycin may be needed to attain optimal therapeutic efficacy against MRSA in neutropenic patients with cancer.

Understanding the Role of Pharmacometrics-Based Clinical Decision Support Systems in Pediatric Patient Management: A Case Study Using Lyv Software.

Pharmacometrics could play a key role in shifting pediatric pharmacotherapy from dosing for an average patient to individualizing dosing. Clinicians can have these quantitative tools at their disposal without requiring significant training through the development of clinical decision support systems with easy-to-use interfaces that have a back-end analysis engine or pharmacometric model that uses extensive electronic health record data to predict an individualized dose for each patient. There has been increased development of these clinical decision support systems recently, and for these tools to make the proper breakthrough into clinical practice, it is of utmost importance to perform rigorous testing to ensure adequate predictive performance. In this article, we walk through the components of a decision support tool and the testing required to determine its robustness using an example of a decision support tool we developed for vancomycin dosing in pediatrics.

Establishment of a population pharmacokinetics model of vancomycin in 94 infants with septicemia and its application in individualized therapy.

BACKGROUND: We aim to develop a population pharmacokinetics (PopPK) model of vancomycin for the treatment of septicemia in infants younger than one year. Factors influence of the PK was investigated to optimize vancomycin dosing regimen. METHODS: The nonlinear mixed effects modelling software (NONMEM) was used to develop the PopPK model of vancomycin. The stability and predictive ability of the final model were assessed by using normalized prediction distribution errors (NPDE) and bootstrap methods. The final model was subjected to Monte Carlo simulation in order to determine the optimal dose. RESULTS: A total of 205 trough and peak concentrations in 94 infants (0-1 year of age) with septicemia were analyzed. The interindividual variability of the PK parameter was described by the exponential model. Residual error was better described by the proportional model than the mixed proportional and addition models. Serum creatinine concentration and body weight are the major factors that affect the PK parameters of vancomycin. The clearance was shown to be higher when ceftriaxone was co-treated. More than two model evaluation methods showed better stability than the base model, with superior predictive performance, which can develop individualized dosing regimens for clinical reference. Through prediction of final model, the trough concentration was more likely < 5 mg/L when a routine dose of 10 mg/kg is administered every 6 h to 3-9-month-old infants. Therefore, the dose should be increased in the treatment of infant septicemia. CONCLUSIONS: The stable and effective PopPK model of vancomycin in Chinese infants with septicemia was established. This model has satisfactory predictive ability for clinically individualized dosing regimens in this vulnerable population.

Exploring the possible targeting strategies of liposomes against methicillin-resistant Staphylococcus aureus (MRSA).

Multi antibiotic-resistant bacterial infections are on the rise due to the overuse of antibiotics. Methicillin-resistant Staphylococcus aureus (MRSA) is one of the pathogens listed under the category of serious threats where vancomycin remains the mainstay treatment despite the availability of various antibacterial agents. Recently, decreased susceptibility to vancomycin from clinical isolates of MRSA has been reported and has drawn worldwide attention as it is often difficult to overcome and leads to increased medical costs, mortality, and longer hospital stays. Development of antibiotic delivery systems is often necessary to improve bioavailability and biodistribution, in order to reduce antibiotic resistance and increase the lifespan of antibiotics. Liposome entrapment has been used as a method to allow higher drug dosing apart from reducing toxicity associated with drugs. The surface of the liposomes can also be designed and enhanced with drug-release properties, active targeting, and stealth effects to prevent recognition by the mononuclear phagocyte system, thus enhancing its circulation time. The present review aimed to highlight the possible targeting strategies of liposomes against MRSA bacteremia systemically while investigating the magnitude of this effect on the minimum inhibitory concentration level.

[Assessment of Renal Function and Simulation Using Serum Cystatin-C in an Elderly Patient with Uncontrollable Plasma Vancomycin Levels Due to Muscular Dystrophy: A Case Report].

Herein, we describe a case of an elderly patient with muscular dystrophy for whom control of the plasma vancomycin (VCM) concentration proved difficult when he developed a catheter-related bloodstream infection. The pharmacist initially carried out therapeutic drug monitoring using an estimate of the creatinine clearance (CLcr) level, which was based on the serum creatinine (SCr) and serum cystatin-C (CysC) levels, but was ultimately unable to control the plasma VCM concentration. Therefore, the plasma VCM concentration was predicted ex post facto using population pharmacokinetic parameters as a covariate; that is, directly including the glomerular filtration rate (GFRCysC) estimated from the CysC level, which is not affected by the muscle mass. As a result, the estimated VCM concentration was closer to the actual concentration than that predicted using CLcr. Furthermore, the results of examining the predictive accuracy according to the assessment of renal function at the time of initial VCM administration suggested that estimation of the trough concentration using GFRCysC might be useful in elderly patients with muscular dystrophy.

Determination of vancomycin exposure target and individualised dosing recommendations for neonates: model-informed precision dosing.

INTRODUCTION: Few studies incorporating population pharmacokinetic/pharmacodynamic (Pop-PK/PD) modelling have been conducted to quantify the exposure target of vancomycin in neonates. A retrospective observational cohort study was undertaken in neonates to determine this target and dosing recommendations (chictr.org.cn, ChiCTR1900027919). METHODS: A Pop-PK model was developed to estimate PK parameters. Causalities between acute kidney injury (AKI) occurrence and vancomycin use were verified using Naranjo criteria. Thresholds of vancomycin exposure in predicting AKI or efficacy were identified via classification and regression tree analysis. Associations between exposure thresholds and clinical outcomes, including AKI and efficacy, were analysed by logistic regression. Dosing recommendations were designed using Monte Carlo simulations based on the optimised exposure target. RESULTS: Pop-PK modelling included 182 neonates with 411 observations. On covariate analysis, neonatal physiological maturation, renal function and concomitant use of vasoactive agents (VAS) significantly affected vancomycin PK. Seven cases of vancomycin-induced AKI were detected. Area under the concentration-time curve from 0-24 hours (AUC0-24) ≥ 485 mg•h/L was an independent risk factor for AKI after adjusting for VAS co-administration. The clinical efficacy of vancomycin was analysed in 42 patients with blood culture-proven staphylococcal sepsis. AUC0-24 to minimum inhibitory concentration (AUC0-24/MIC) ≥ 234 was the only significant predictor of clinical effectiveness. Monte Carlo simulations indicated that regimens in Neonatal Formulary 7 and Red Book (2018) were unsuitable for all neonates. CONCLUSION: An AUC0-24 of 240-480 (assuming MIC = 1 mg/L) is a recommended exposure target of vancomycin in neonates. Model-informed dosing regimens are valuable in clinical practice.

Evaluation and Development of Vancomycin Dosing Schemes to Meet New AUC/MIC Targets in Intermittent Hemodialysis Using Monte Carlo Simulation Techniques.

Published vancomycin dosing recommendations for patients receiving maintenance hemodialysis were not designed to meet newly recommended 24-hour area under the curve/minimum inhibitory concentration (AUC24h /MIC) pharmacokinetic/pharmacodynamic targets. The aims of this study were to predict pharmacokinetic/pharmacodynamic target attainment rates with a commonly used vancomycin regimen and to design a new dosing scheme incorporating therapeutic drug monitoring (TDM) to maximize target attainment in patients receiving vancomycin and hemodialysis with high- or low-flux hemodialyzers. Vancomycin pharmacokinetic- and dialysis-specific parameters were incorporated into Monte Carlo simulations (MCS). A commonly used vancomycin regimen was modeled to determine its likelihood of attaining AUC24h /MIC targets for 1 week of thrice-weekly hemodialysis treatments. MCS was then used to develop optimal initial vancomycin dosing for patients receiving intradialytic or postdialytic vancomycin administration with either high- or low-flux hemodialyzers. Finally, a new MCS model incorporating TDM was built to further optimize the probability of pharmacokinetic/pharmacodynamic target attainment. Traditional vancomycin dosing methods are unlikely to meet AUC24h /MIC targets. Vancomycin doses necessary to attain AUC24h /MIC targets are significantly influenced by hemodialyzer permeability and whether vancomycin is administered intradialytically or after hemodialysis. Depending on dialyzer type and whether vancomycin is administered during or after hemodialysis, loading doses of 25 to 35 mg/kg followed by maintenance doses of 7.5 to 15 mg/kg are necessary to reach minimum AUC24h /MIC targets in 90% of virtual patients. For a 3-day interdialytic period, a 30% higher maintenance dose is required to maintain target attainment. Dosing based on a single vancomycin serum concentration obtained prior to the second dialysis session greatly enhances the probability of target attainment.

Cost-benefit analysis comparing trough, two-level AUC and Bayesian AUC dosing for vancomycin.

OBJECTIVES: Area under the time-concentration curve (AUC) -guided dosing provides better estimates of exposure than vancomycin trough concentrations. Though clinical benefits have been reported, the costs of AUC-guided dosing are uncertain. The objective of this study was to quantify the costs of single-sample Bayesian or two-sample AUC strategies versus trough-guided dosing. METHODS: A cost-benefit analysis from the institutional perspective was conducted using a decision tree to model the probabilities and costs of acute kidney injury (AKI) associated with vancomycin administered over 48 hours up to 21+ days. Costs included vancomycin concentrations, Bayesian software and AKI hospitalization costs, and probabilities were obtained from primary literature. Robustness was assessed via both one-way and probabilistic sensitivity analyses. RESULTS: In the base-case model, two-sample AUC versus trough dosing saved an average of US$ 846 per patient encounter, and single-sample Bayesian AUC versus trough dosing saved an average of US$ 2065 per patient encounter. This translates into annual cost-savings of US$ 846 810 and US$ 2 065 720 for two-sample and single-sample Bayesian methods versus trough dosing, respectively, assuming 1000 vancomycin-treated patients per year. Assuming a budget of US$ 100 000 per year for Bayesian software, an institution would need to treat ≥41 patients with vancomycin for at least 48 hours to break even. CONCLUSIONS: There are significant institutional cost benefits using two-sample AUC or single-sample Bayesian methods over trough dosing, even after accounting for the annual costs of Bayesian programs. The potential to decrease rates of AKI, improve clinical outcomes and reduce costs to the institution strongly warrants consideration of improved dosing methods for vancomycin.

Development, Evaluation, and Pharmacokinetic Assessment of Polymeric Microarray Patches for Transdermal Delivery of Vancomycin Hydrochloride.

Methicillin-resistant Staphylococcus aureus (MRSA) can cause harmful and potentially deadly infections. Vancomycin remains the first-line antibiotic treatment for MRSA-derived infections. Nevertheless, as a peptide drug, it is poorly absorbed when administered orally because of its high molecular weight and low permeability in the gastrointestinal tract and is therefore administered intravenously for the treatment of systemic diseases. In order to circumvent some of the many drawbacks associated with intravenous injection, other routes of drug delivery should be investigated. One of the strategies which has been employed to enhance transdermal drug delivery is based on microarray patches (MAPs). This work, for the first time, describes successful transdermal delivery of vancomycin hydrochloride (VCL) using dissolving MAPs (DMAPs) and hydrogel-forming MAPs (HFMAPs). VCL was formulated into DMAPs and reservoirs [film dosage forms, lyophilized wafers, and compressed tablets (CSTs)] using excipients such as poly(vinyl pyrrolidone), poly(vinyl alcohol), sodium hyaluronate, d-sorbitol, and glycerol. In this study, HFMAPs were manufactured using aqueous blends containing poly(methylvinyl ether-co-maleic acid) cross-linked by esterification with poly(ethylene glycol). The VCL-loaded CSTs (60% w/w VCL) were the most promising reservoirs to be integrated with HFMAPs based on the physicochemical evaluations performed. Both HFMAPs and DMAPs successfully delivered VCL in ex vivo studies with the percentage of drug that permeated across the neonatal porcine skin recorded at 46.39 ± 8.04 and 7.99 ± 0.98%, respectively. In in vivo studies, the area under the plasma concentration time curve from time zero to infinity (AUC0-∞) values of 162.04 ± 61.84 and 61.01 ± 28.50 µg h/mL were achieved following the application of HFMAPs and DMAPs, respectively. In comparison, the AUC0-∞ of HFMAPs was significantly greater than that of the oral administration control group, which showed an AUC0-∞ of 30.50 ± 9.18 µg h/mL (p < 0.05). This work demonstrates that transdermal delivery of VCL is feasible using DMAPs and HFMAPs and could prove effective in the treatment of infectious diseases caused by MRSA, such as skin and soft tissue infections, lymphatic-related infections, and neonatal sepsis.

Population Pharmacokinetics and Pharmacodynamics of Norvancomycin in Children With Malignant Hematological Disease.

Knowledge of pharmacokinetic (PK) behavior of norvancomycin (NVCM) in pediatric patients is lacking, which leads to empirical therapy in clinical practice. This study developed a population PK model of children aged 0-15 years; 112 opportunistic samples in total from 90 children were analyzed. The stability and prediction of the final model were evaluated by goodness-of-fit plots, nonparametric bootstrap, visual predictive check, and normalized prediction distribution errors. The PKs of NVCM in children was described by a 2-compartment model with first-order elimination along with body weight and estimated glomerular filtration rate as significant covariates on clearance. The population typical values of the PK parameters were as follows: clearance 0.12 L/kg/h, central compartment distribution volume 0.17 L/kg, peripheral compartment distribution volume 0.38 L/kg, and intercompartmental clearance 0.35 L/kg/h. Logistic analysis showed that the ratio of area under the concentration-time curve over 24 hours (AUC0-24 ) to minimum inhibitory concentration (MIC) had the strongest correlation with clinical efficacy, and at least 80% clinical efficiency could be achieved when AUC0-24 /MIC ≥ 221.06 was defined as the target. Monte Carlo simulation results suggested that a higher dose was required for this pediatric population in order to reach the target. The dosing regimen was optimized based on the final model. A population PK model of NVCM was first characterized in children with hematologic malignancy, and an evidence-based approach for NVCM dosage individualization was provided.

Vancomycin population pharmacokinetics and dosing recommendations in haematologic malignancy with augmented renal clearance children.

WHAT IS KNOWN AND OBJECTIVES: Augmented renal clearance (ARC) is characterized by enhanced renal clearance, which leads to insufficient vancomycin exposure and treatment failure. In haematologic malignancy patients, determination of optimal vancomycin dosage is essential because of high stake of life-threatening bacterial infection and increased clearance. The aim of this study was to describe vancomycin pharmacokinetic parameters in haematologic malignancy with augmented renal clearance children and define the appropriate dosing regimen to achieve an AUC0-24h /MIC ≥400. METHODS: Hematologic malignancy with ARC children was enrolled in this retrospective study. The vancomycin PPK model was established by non-linear mixed-effects modelling programme. Goodness-of-fit (GOF) plots, non-parametric bootstrap, normalized prediction distribution error (NPDE) and visual predictive checks (VPCs) were carried out for internal evaluation of the final model. Monte Carlo simulation method was used to stimulate the optimal dosage regimens. RESULTS: Fifty-three patients with 106 samples were included. A one-compartment model with first-order elimination was developed, and the final model was as follows: CL (L/h) = 6.32×（WT/70）0.75  × e0.0467 ; V(L) = 39.6×(WT/70), where WT denotes weight (kg). The internal validation of the model showed a good prediction performance. Monte Carlo simulation results showed that when MIC was 0.5 mg/L or 1 mg/L, the recommended doses to achieve a target of AUC0-24h /MIC ≥400 were 25 to 40 and 50 to 75 mg/kg/d, respectively. With decreasing weight, the recommended dosage to achieve an AUC0-24h /MIC ≥400 increased. WHAT IS NEW AND CONCLUSION: A one-compartment vancomycin PPK model was established in haematologic malignancy with augmented renal clearance children with weight with allometric scaling as a significant covariate. When MIC was 1 mg/L, current recommended paediatric dosages were insufficient in haematologic malignancy with augmented renal clearance children and should be increased.

Influence of venovenous extracorporeal membrane oxygenation on pharmacokinetics of vancomycin in lung transplant recipients.

WHAT IS KNOWN AND OBJECTIVE: The influence of venovenous extracorporeal membrane oxygenation (VV-ECMO) on the population pharmacokinetics (PPK) of vancomycin in recipients after lung transplantation (LTx) is unknown. We investigated whether VV-ECMO influences vancomycin PPK and determined optimal recommended dosage for patients after LTx. METHODS: We tested vancomycin serum concentration and calculated PPK parameters using NONMEM. To check for any potential influence of ECMO on vancomycin PK, we compared ECMO patients with a non-ECMO patient control group, and patients before and after ECMO weaning as self-control to analysed changes in vancomycin PK. Monte Carlo dosing simulation was conducted to explore vancomycin dosing regimens. RESULTS: Nineteen ECMO and 6 non-ECMO lung transplant recipients were enrolled. Vancomycin serum concentrations did not significantly differ between patients with and without ECMO support. Comparison of separate vancomycin population pharmacokinetic models showed that ECMO patients had smaller peripheral compartment volume of distribution (V2 ) [Estimate (relative standard error, RSE, %) 19.7 (12) vs. 22 (17) L, P = .003] than non-ECMO patients. For treatment of methicillin-resistant Staphylococcus aureus (MRSA) infections with MIC ≤ 0.5 µg/mL, venous infusion of 400 mg vancomycin every 8 hours was recommended. For MRSA infection with MIC ≤ 1 µg/mL, the proposed dosage was 600 mg every 8 hours. WHAT IS NEW AND CONCLUSION: Venovenous extracorporeal membrane oxygenation slightly alters vancomycin PK but does not significantly impact vancomycin serum concentration in patients after LTx. Dose adjustment is not necessary for VV-ECMO support. Specific vancomycin dosing regimens with lower nephrotoxicity may benefit LTx recipients with VV-ECMO.

Pharmacokinetic Assessment of Pre- and Post-Oxygenator Vancomycin Concentrations in Extracorporeal Membrane Oxygenation: A Prospective Observational Study.

BACKGROUND: Extracorporeal membrane oxygenation (ECMO) is a form of cardiopulmonary life support frequently utilized in catastrophic lung and or cardiac failure. Patients on ECMO often receive vancomycin therapy for treatment or prophylaxis against Gram-positive organisms. It is unclear if ECMO affects vancomycin pharmacokinetics, thus we modeled the pharmacokinetic behavior of vancomycin according to ECMO-specific variables. METHODS: Adult patients receiving vancomycin and Veno-Arterial-ECMO between 12/1/2016 and 10/1/2017 were prospectively enrolled. Extracorporeal membrane oxygenation settings and four sets of pre- and post-oxygenator vancomycin concentrations were collected for each patient. Compartmental models were built and assessed ECMO flow rates on vancomycin clearance and potential circuit sequestration. Bayesian posterior concentrations of the pre- and post-oxygenator concentrations were obtained for each patient, and summary pharmacokinetic parameters were calculated. Simulations were performed from the final model for efficacy and toxicity predictions. RESULTS: Eight patients contributed 64 serum concentrations. Patients were a median (interquartile range) age of 58.5 years (50.8-62.3) with a calculated creatinine clearance of 39 mL/min (29.5-62.5) and ECMO flow rates of 3980 mL/min (interquartile range = 3493.75-4132.5). A three-compartment model best fit the data (Bayesian: plasma pre-oxygenation R2 = 0.99, post-oxygenation R2 = 0.99). Vancomycin clearance was not impacted by ECMO flow rate (p = 0.7). Simulations demonstrated that vancomycin 1 g twice daily was rarely sufficient for minimum inhibitory concentrations > 0.5 mg/L. Doses ≥ 1.5 g twice daily often exceeded toxicity thresholds for exposure. CONCLUSIONS: Extracorporeal membrane oxygenation flow rates did not influence vancomycin clearance between flow rates of 3500 and 5000 mL/min and vancomycin was not sequestered in ECMO. Common vancomycin regimens resulted in suboptimal efficacy and/or excessive toxicity. Individual therapeutic drug monitoring is recommended for patients on ECMO.

Assessment of Vancomycin Pharmacokinetics and Dose Regimen Optimisation in Preterm Neonates.

BACKGROUND: The pharmacokinetics of vancomycin, a drug used for the treatment of methicillin-resistant Staphylococcus aureus (MRSA), varies between paediatric and adult patients. OBJECTIVE: The objective of this study was to assess the pharmacokinetics of vancomycin in preterm neonates and determine the optimum dose regimen. METHODS: This was a randomised double-blind study of preterm neonates admitted to neonatal intensive care units. They all received vancomycin 15 mg/kg every 12 h. Blood was sampled just before administration of the third, sixth and ninth vancomycin dose. Pharmacokinetic parameters were estimated using a Bayesian approach implemented in Monolix 2018R2 software. Covariates assessed included postmenstrual age, current weight, creatinine clearance, albumin, gestational age, body surface area and current age. We used Monte Carlo simulations for dose regimen optimisation targeting area under the concentration-time curve up to 24 h (AUC0-24h) of ≥ 400 mg × h/L. RESULTS: In total, 19 preterm neonates were enrolled in the study with a median age of 14 (3-58) days. A one-compartment model with linear elimination best described the pharmacokinetics of vancomycin. Volume of distribution and clearance was 0.88 L and 0.1 L/h, respectively, for a typical neonate weighing 1.48 kg. Simulation of the current dose regimen showed that 27.5% of the neonates would achieve the target AUC0-24h of ≥ 400 mg × h/L, and 70.7% of the neonates would achieve it with 12 mg/kg every 8 h. CONCLUSION: The majority of the neonates were under dosed. Vancomycin 12 mg/kg should be administered every 8 h over 1 h infusion to improve the likelihood of achieving the AUC0-24h target of ≥ 400 mg × h/L. This target is considered optimal for MRSA infections, where the vancomycin minimum inhibitory concentration is ≤ 1 µg/mL.