Innovative approaches to optimizing the delivery of vancomycin in individual patients

Determination of a vancomycin nephrotoxicity threshold and assessment of target attainment in hematology patients

An area-under-the-curve (AUC24)-based approach is recommended to guide vancomycin therapeutic drug monitoring (TDM), yet trough concentrations are still commonly used despite associated risks. A definitive toxicity target is lacking, which is important for hematology patients who have a higher risk of nephrotoxicity. The aims were to (1) assess the impact of trough-based TDM on acute kidney injury (AKI) incidence, (2) establish a vancomycin nephrotoxicity threshold, and (3) evaluate the proportion of hematology patients achieving vancomycin therapeutic targets. Retrospective data was collected from 100 adult patients with a hematological malignancy or aplastic anemia who received vancomycin between April 2020 and January 2021. AKI occurrence was determined based on serum creatinine concentrations, and individual pharmacokinetic parameters were estimated using a Bayesian approach. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of pharmacokinetic indices to predict AKI occurrence. The proportion of patients who achieved target vancomycin exposure was evaluated based on an AUC24/MIC ≥400 and the determined toxicity threshold. The incidence of AKI was 37%. ROC curve analysis indicated a maximum AUC24 of 644 mg.h/L over the treatment period was an important predictor of AKI. By Day 4 of treatment, 29% of treatment courses had supratherapeutic vancomycin exposure, with only 62% of courses achieving AUC24 targets. The identified toxicity threshold supports an AUC24 target range of 400-650 mg.h/L, assuming an MIC of 1 mg/L, to optimize vancomycin efficacy and minimize toxicity. This study highlights high rates of AKI in this population and emphasizes the importance of transitioning from trough-based TDM to an AUC-based approach to improve clinical outcomes.

Determining steady-state trough range in vancomycin drug dosing using machine learning

BACKGROUND

Vancomycin is a renally eliminated, nephrotoxic, glycopeptide antibiotic with a narrow therapeutic window, widely used in intensive care units (ICU). We aimed to predict the risk of inappropriate vancomycin trough levels and appropriate dosing for each ICU patient.

METHODS

Observed vancomycin trough levels were categorized into sub-therapeutic, therapeutic, and supra-therapeutic levels to train and compare different classification models. We included adult ICU patients (≥ 18 years) with at least one vancomycin concentration measurement during hospitalization at Mayo Clinic, Rochester, MN, from January 2007 to December 2017.

RESULT

The final cohort consisted of 5337 vancomycin courses. The XGBoost models outperformed other machine learning models with the AUC-ROC of 0.85 and 0.83, specificity of 53% and 47%, and sensitivity of 94% and 94% for sub- and supra-therapeutic categories, respectively. Kinetic estimated glomerular filtration rate and other creatinine-based measurements, vancomycin regimen (dose and interval), comorbidities, body mass index, age, sex, and blood pressure were among the most important variables in the models.

CONCLUSION

We developed models to assess the risk of sub- and supra-therapeutic vancomycin trough levels to improve the accuracy of drug dosing in critically ill patients.

Optimization of Vancomycin Initial Dosing Regimen in Neonates Using an Externally Evaluated Population Pharmacokinetic Model

BACKGROUND

Vancomycin therapeutic monitoring guidelines were revised in March 2020, and a population pharmacokinetics-guided Bayesian approach to estimate the 24-hour area under the concentration-time curve to the minimum inhibitory concentration ratio has since been recommended instead of trough concentrations. To comply with these latest guidelines, we evaluated published population pharmacokinetic models of vancomycin using an external dataset of neonatal patients and selected the most predictive model to develop a new initial dosing regimen.

METHODS

The models were identified from the literature and tested using a retrospective dataset of Canadian neonates. Their predictive performance was assessed using prediction- and simulation-based diagnostics. Monte Carlo simulations were performed to develop the initial dosing regimen with the highest probability of therapeutic target attainment.

RESULTS

A total of 144 vancomycin concentrations were derived from 63 neonates in the external population. Five of the 28 models retained for evaluation were found predictive with a bias of 15% and an imprecision of 30%. Overall, the Grimsley and Thomson model performed best, with a bias of -0.8% and an imprecision of 20.9%; therefore, it was applied in the simulations. A novel initial dosing regimen of 15 mg/kg, followed by 11 mg/kg every 8 hours should favor therapeutic target attainment.

CONCLUSIONS

A predictive population pharmacokinetic model of vancomycin was identified after an external evaluation and used to recommend a novel initial dosing regimen. The implementation of these model-based tools may guide physicians in selecting the most appropriate initial vancomycin dose, leading to improved clinical outcomes.

In Vitro Performance of a Long-Range Surface Plasmon Hydrogel Aptasensor for Continuous and Real-Time Vancomycin Measurement in Human Serum

This study investigated the suitability of surface modification for a long-range surface plasmon (LRSP) aptasensor using two different hydrogels, aiming at real-time monitoring of vancomycin (VCM) in undiluted serum and blood. Three different layer structures were formed on a gold surface of LRSP sensor chip using poly[2-methacryloyloxyethyl phosphorylcholine (MPC)-co-N-methacryloyl-(L)-tyrosinemethylester (MAT)] (PMM) and poly[MPC-co-2-ethylhexyl methacrylate (EHMA)-co-MAT] (PMEM). The peptide aptamer for VCM was immobilized in PMM and PMEM via MAT. Among four differently prepared sensor chips, the LRSP hydrogel aptasensor with PMM, referred to as the PMM hydrogel, exhibited the highest sensor output and superior antifouling properties. Following the optimization of the PMM hydrogel preparation conditions, the shelf life of the PMM hydrogel was determined to exceed 2 weeks, and the same sensor chip could be used for 102 days without significant performance deterioration. The PMM hydrogel was then applied for VCM measurement in undiluted serum in vitro, where it demonstrated a limit of detection of 0.098 μM and a dynamic range of 0.18-100 μM, covering the therapeutic range. Additionally, the PMM hydrogel enabled the continuous measurement of various VCM concentrations in serum without rinsing and showed a concentration-dependent output in undiluted blood. These findings underscore the potential of the PMM hydrogel for real-time and direct monitoring of VCM in body fluids.

Evaluation of the appropriateness of vancomycin therapeutic drug monitoring in the intensive care unit with a clinical pharmacy approach, a cross-sectional study

OBJECTIVES

Vancomycin, a glycopeptide antibiotic has antibacterial activity against Gram-positive bacteria and is frequently used in the intensive care unit (ICU). Inappropriate therapeutic drug monitoring (TDM) of vancomycin is a common problem encountered in hospital daily practice. The aim of this study was to evaluate the appropriateness of vancomycin trough-guided TDM in patients treated in the ICU using a clinical pharmacy approach.

METHODS

The study was conducted retrospectively in patients over 18 years old who had at least one vancomycin trough level and who had received intravenous (IV) vancomycin for ≥3 days between 1 November 2020 and 1 April 2022. The study included 137 patients. Patient demographics and relevant vancomycin TDM data were collected from medical records. The appropriateness of TDM was evaluated according to the criteria established based on the monitoring recommendations specified in consensus guidelines for therapeutic drug monitoring of vancomycin published by the American Society of Health-System Pharmacists (ASHP) in 2009 and 2020.

RESULTS

Of a total of 238 vancomycin trough levels measured in patients, 32.4% were collected at an inappropriate time. When patients were evaluated in terms of TDM appropriateness according to vancomycin level ranges (<10 µg/mL, 10-20 µg/mL and >20 µg/mL), we found the appropriate TDM was significantly higher in the therapeutic range (10-20 µg/mL) (p <0.001). Of the total 238 vancomycin trough concentrations taken from patients, 77 (32.4%) were measured at an inappropriate time. This caused dose withholding, wrong adjustments and therapy failure. The total TDM appropriateness of vancomycin was significantly higher in the therapeutic range defined as 10-20 µg/mL when evaluated based on 'TDM appropriateness criteria' (p <0.001).

CONCLUSION

Our study shows that appropriate vancomycin TDM increases the likelihood of achieving target trough concentrations. Involvement of clinical pharmacists in TDM management may prevent the development of adverse reactions by ensuring appropriate sampling time and appropriate interpretation of vancomycin levels.

Is It Still Beneficial to Monitor the Trough Concentration of Vancomycin? A Quantitative Meta-Analysis of Nephrotoxicity and Efficacy

This study conducted a quantitative meta-analysis to investigate the association of vancomycin indicators, particularly area under the curve over 24 h (AUC24) and trough concentrations (Ctrough), and their relationship with both nephrotoxicity and efficacy. Literature research was performed in PubMed and Web of Science on vancomycin nephrotoxicity and efficacy in adult inpatients. Vancomycin Ctrough, AUC24, AUC24/minimum inhibitory concentration (MIC), nephrotoxicity evaluation and treatment outcomes were extracted. Logistic regression and Emax models were conducted, stratified by evaluation criterion for nephrotoxicity and primary outcomes for efficacy. Among 100 publications on nephrotoxicity, 29 focused on AUC24 and 97 on Ctrough, while of 74 publications on efficacy, 27 reported AUC24/MIC and 68 reported Ctrough. The logistic regression analysis indicated a significant association between nephrotoxicity and vancomycin Ctrough (odds ratio = 2.193; 95% CI 1.582-3.442, p < 0.001). The receiver operating characteristic curve had an area of 0.90, with a cut-off point of 14.55 mg/L. Additionally, 92.3% of the groups with a mean AUC24 within 400-600 mg·h/L showed a mean Ctrough of 10-20 mg/L. However, a subtle, non-statistically significant association was observed between the AUC24 and nephrotoxicity, as well as between AUC24/MIC and Ctrough concerning treatment outcomes. Our findings suggest that monitoring vancomycin Ctrough remains a beneficial and valuable approach to proactively identifying patients at risk of nephrotoxicity, particularly when Ctrough exceeds 15 mg/L. Ctrough can serve as a surrogate for AUC24 to some extent. However, no definitive cut-off values were identified for AUC24 concerning nephrotoxicity or for Ctrough and AUC24/MIC regarding efficacy.

Innovative Vancomycin-Loaded Hydrogel-Based Systems - New Opportunities for the Antibiotic Therapy

Purpose

Surgical site infections pose a significant challenge for medical services. Systemic antibiotics may be insufficient in preventing bacterial biofilm development. With the local administration of antibiotics, it is easier to minimize possible complications, achieve drugs' higher concentration at the injured site, as well as provide their more sustained release. Therefore, the main objective of the proposed herein studies was the fabrication and characterization of innovative hydrogel-based composites for local vancomycin (VAN) therapy.

Methods

Presented systems are composed of ionically gelled chitosan particles loaded with vancomycin, embedded into biomimetic collagen/chitosan/hyaluronic acid-based hydrogels crosslinked with genipin and freeze-dried to serve in a flake/disc-like form. VAN-loaded carriers were characterized for their size, stability, and encapsulation efficiency (EE) using dynamic light scattering technique, zeta potential measurements, and UV-Vis spectroscopy, respectively. The synthesized composites were tested in terms of their physicochemical and biological features.

Results

Spherical structures with sizes of about 200 nm and encapsulation efficiencies reaching values of approximately 60% were obtained. It was found that the resulting particles exhibit stability over time. The antibacterial activity of the developed materials against Staphylococcus aureus was established. Moreover, in vitro cell culture study revealed that the surfaces of all prepared systems are biocompatible as they supported the proliferation and adhesion of the model MG-63 cells. In addition, we have demonstrated significantly prolonged VAN release while minimizing the initial burst effect for the composites compared to bare nanoparticles and verified their desired physicochemical features during swellability, and degradation experiments.

Conclusion

It is expected that the developed herein system will enable direct delivery of the antibiotic at an exposed to infections surgical site, providing drugs sustained release and thus will reduce the risk of systemic toxicity. This strategy would both inhibit biofilm formation and accelerate the healing process.

Clinical benefits of therapeutic drug monitoring of vancomycin therapy in patients with postoperative intracerebral hemorrhage: a retrospective cohort study

OBJECTIVE

The objective of this study was to investigate the clinical efficacy and safety of conducting therapeutic drug monitoring (TDM) of vancomycin in patients with postoperative intracerebral haemorrhage.

METHODS

We conducted a retrospective analysis of 435 patients who experienced postoperative cerebral haemorrhage and were treated with vancomycin in the Department of Neurosurgery of Inner Mongolia Autonomous Region People's Hospital from January 2017 to December 2021. Patients were then matched using the propensity score matching method in a ratio of 1:1. Ninety-two pairs of cases were successfully matched, and the data before and after performing vancomycin TDM were analysed.

RESULTS

After PSM, the baseline data of the two groups were balanced. There were no significant differences in the 14-day mortality and length of hospital stay (p>0.05) between the two groups. Compared with the non-TDM group, the TDM group had a higher proportion of patients with normal white blood cells (83.7% vs 56.5%, p=0.000), neutrophil count (57.6% vs 25.0%, p=0.000) and attaining desirable reductions of 80% in procalcitonin (65.2% vs 10.9%, p=0.000) and C-reactive protein (78.3% vs 41.3%, p=0.000) levels. At US$15.82 per additional TDM, TDM significantly promoted patient outcomes, as seen in improvements in the proportion of patients attaining desirable levels of white blood cells, neutrophil count, procalcitonin and C-reactive protein.

CONCLUSIONS

Vancomycin TDM is a safe and effective approach for the treatment of patients with postoperative intracerebral haemorrhage. The empirical use of TDM of vancomycin significantly improved normal values of white blood cells and neutrophil count, achieved desirable reductions of 80% in procalcitonin and C-reactive protein, and reduced nephrotoxicity in patients with postoperative intracerebral haemorrhage.

MALDI-TOF MS combined with AUC method for tigecycline susceptibility testing in Escherichia coli

Objectives

The wide spread of tet(X4) gene orthologues in the environment, food, poultry and humans is causing serious tigecycline resistance. Consequently, developing a fast and universal method to detect tigecycline resistance has become increasingly important.

Methods

During 2019-2022, 116 Escherichia coli isolates were obtained from nine provinces in China. All isolates were tested for their susceptibility to antimicrobial agents by the microdilution broth method and for the tet(X4) gene by PCR. Ten tet(X4)-positive E. coli isolates were used to confirm certain conditions, including the optimal incubation time, the optimal concentration of tigecycline, and the cut-off of the relative growth (RG) value.

Results

The optimal time and concentration of tigecycline for separation of susceptible and resistant isolates was 2 h and 4 mg/L, and the RG cut-off value was 0.4. We validated whether the experiment was feasible using 116 isolates of E. coli. The method yielded a susceptibility of 94.9% (95% CI: 81.4%-99.1%) and a specificity of 96.1% (95% CI: 88.3%-99.0%).

Conclusions

This research has shown that this optical antimicrobial susceptibility testing method can rapidly differentiate between susceptible and resistant phenotypes in isolates of E. coli. In the same range as the current gold-standard methods, the clinical turnaround time is reduced from 48 h to 2.5 h. The above results suggest that the method has splendid specificity and operationality.

One-Step Detection of Vancomycin in Whole Blood Using the Lateral Flow Immunoassay

Vancomycin (VAN) is an effective antibiotic against Gram-positive bacteria and the first-line therapy to prevent and treat methicillin-resistant Staphylococcus aureus (MRSA) and severe infections. However, low concentrations of VAN can result in resistant strains. High doses of VAN can cause nephrotoxicity and ototoxicity; thus, VAN is a representative drug for which drug monitoring is recommended. Several methods have been proposed to detect VAN. Among them, lateral flow immunoassays (LFIAs) have advantages, such as simple and user-friendly operation, low sample volume requirement, and cost effectiveness. In this study, we developed an LFIA capable of rapid on-site detection such that the VAN concentration in plasma could be monitored within 20 min by a one-step detection process using whole blood without plasma separation. VAN can be detected in whole blood over a wide range of concentrations (20-10,000 ng/mL), and the LFIA reported here has a detection limit of 18 ng/mL. The applicability of the developed LFIA compared to the results of measuring VAN with a commercial enzyme-linked immunosorbent assay kit showed a satisfactory correlation (Spearman's rho, ρ = 0.891). Therefore, the developed LFIA enables rapid and wide-range VAN detection in whole blood and can aid in drug monitoring to evaluate patients' responses to treatment.

Time-Dependent Differences in Vancomycin Sensitivity of Macrophages Underlie Vancomycin-Induced Acute Kidney Injury

Although vancomycin (VCM)-frequently used to treat drug-resistant bacterial infections-often induces acute kidney injury (AKI), discontinuation of the drug is the only effective treatment; therefore, analysis of effective avoidance methods is urgently needed. Here, we report the differences in the induction of AKI by VCM in 1/2-nephrectomized mice depending on the time of administration. Despite the lack of difference in the accumulation of VCM in the kidney between the light (ZT2) and dark (ZT14) phases, the expression of AKI markers due to VCM was observed only in the ZT2 treatment. Genomic analysis of the kidney suggested that the time of administration was involved in VCM-induced changes in monocyte and macrophage activity, and VCM had time-dependent effects on renal macrophage abundance, ATP activity, and interleukin (IL)-1β expression. Furthermore, the depletion of macrophages with clodronate abolished the induction of IL-1β and AKI marker expression by VCM administration at ZT2. This study provides evidence of the need for time-dependent pharmacodynamic considerations in the prevention of VCM-induced AKI as well as the potential for macrophage-targeted AKI therapy. SIGNIFICANCE STATEMENT: There is a time of administration at which vancomycin (VCM)-induced renal injury is more and less likely to occur, and macrophages are involved in this difference. Therefore, there is a need for time-dependent pharmacodynamic considerations in the prevention of VCM-induced acute kidney injury as well as the potential for macrophage-targeted acute kidney injury therapy.

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.

Feasibility of individualised patient modelling for continuous vancomycin infusions in outpatient antimicrobial therapy, a retrospective study

BACKGROUND

The area under the curve (AUC) to minimum inhibitory concentration (MIC) ratio is proposed as a therapeutic drug-monitoring parameter for dosing vancomycin continuous infusion in methicillin-resistant Staphylococcus aureus (MRSA) infection. Individualised pharmacokinetic-pharmacodynamic (PK/PD) calculation of AUC24 may better represent therapeutic dosing than current Therapeutic Drug Monitoring (TDM) practices, targeting a Steady State Concentration of 15-25 mg/L.

AIM

To compare real world TDM practice to theoretical, individualised, PK/PD target parameters utilising Bayesian predictions to steady state concentrations (Css) for outpatients on continuous vancomycin infusions.

METHOD

A retrospective single centre study was conducted at a tertiary hospital on adult patients, enrolled in an outpatient parenteral antimicrobial therapy (OPAT) program, receiving vancomycin infusions for MRSA infection. Retrospective Bayesian dosing was modelled to target PK/PD parameters and compared to real world data.

RESULTS

Fifteen patients were evaluated with 53% (8/15) achieved target CSS during hospitalisation, and 83% (13/15) as outpatient. Median Bayesian AUC/MIC was 613 mg.h/L with CSS 25 mg/L. Patients suffering an Acute Kidney Injury (33%) had higher AUC0-24/MIC values. Retrospective Bayesian modelling demonstrated on median 250 mg/24 h lower doses than that administered was required (R2 = 0.81) which achieved AUC24/MIC median 444.8 (range 405-460) mg.h/L and CSS 18.8 (range 16.8-20.4) mg/L.

CONCLUSION

Bayesian modelling could assist in obtaining more timely target parameters at lower doses for patients receiving continuous vancomycin infusion as part of an OPAT program, which may beget fewer adverse effects. Utilisation of personalised predictive modelling may optimise vancomycin prescribing, achieving earlier target concentrations as compared to empiric dosing regimens.

Mid-dosing interval concentration is important for polymyxin B exposure and acute kidney injury in critically ill patients

This study aimed to evaluate the association between polymyxin B (PMB) exposure and acute kidney injury (AKI) and analyze the risk factors for PMB-induced AKI in critically ill patients. Plasma concentrations of PMB were determined using an ultraperformance liquid chromatography-tandem mass spectrometer in intensive care unit patients who were administered PMB. Univariate and multivariate analyses were conducted to identify risk factors. A receiver operating characteristic curve was constructed to assess the discriminant power of the factors and to identify the cutoff value for AKI. The white blood cell count and estimated area under the concentration-time curve (AUC) of patients administered PMB were independent risk factors for PMB-induced AKI, where AUC were calculated using a first-order pharmacokinetic equation based on the mid-dosing interval concentration (C1/2t ) and peak concentration. The area under the receiver operating characteristic curve of the final model was 0.805 (95% confidence interval, 0.690-0.921). The cutoff value for the combined predictor was 0.57. Alternatively, when using C1/2t , which was strongly correlated with AUC, as the only independent risk factor, the analysis showed that the 3.47 μg/ml threshold provides favorable differentiation between the AKI and non-AKI groups. These results provide insightful information for therapeutic drug monitoring-guiding PMB dosing in clinical practice.

Population pharmacokinetics of vancomycin in patients with diabetic foot infection: a comparison of five models

Purpose

This study aimed to compare individual pharmacokinetic (PK) parameters of vancomycin with predicted values from five population PK models in patients with diabetic foot infections (DFIs).

Methods

Patients with a diagnosis of DFI and an estimated glomerular filtration rate (eGFR) ≥ 30 mL/min were included in the study. Individual PK data was carried on by collecting three vancomycin serum concentrations in a steady-state condition. Five published population-based nomograms were assumed to predict PK parameters. Optimal vancomycin exposure was considered as a trough level of 15-20 mg/L or the area under the curve over 24 h/minimum inhibitory concentration (AUC24/MIC) ≥ 400.

Results

A total of 48 samples from 16 patients were analyzed. There was a statistically significant difference between the volume of distribution (Vd) obtained from population methods and the individual estimations (P ≤ 0.001 in Ambrose and Burton, P = 0.010 and 0.006 in Bauer and Burton revised models, respectively). AUC/MIC ≥ 400 was achieved in 68.7% of patients while 50% had a trough level of less than 15 mg/L.

Conclusions

Vancomycin PK parameters, particularly individualized Vd, may not be predictable by population nomograms in patients with DFI and stable renal function. Moreover, the weak correlation between AUC24 values and trough concentrations underlines the starting practice of vancomycin AUC24-based monitoring and dosing in the clinical setting.

Pharmacokinetics and therapeutic target attainment of vancomycin in pediatric post-liver transplant patients

INTRODUCTION

Vancomycin is widely prescribed to treat or prevent Gram-positive infections in pediatric liver transplant recipients. The objective of this prospective cohort study is to describe vancomycin pharmacokinetics and to evaluate the therapeutic target attainment after initial dose regimen.

MATERIALS AND METHODS

Patients with previous renal injury were excluded. Vancomycin therapy started with 40‒60 mg/kg/day. The pharmacokinetic parameters were assessed using two steady-state blood samples and the first-order kinetic equations. Therapeutic target was defined as vancomycin 24-hour Area Under the Curve/Minimum Inhibitory Concentration (AUC/MIC) ≥ 400 and < 600.

RESULTS

Sixteen patients were included. The found vancomycin clearance, half-life, and volume of distribution were, respectively: 2.1 (1.3‒2.8) mL/kg/min, 3.3 (2.7‒4.4) hours, and 0.7 (0.5‒0.9) L/kg. With the initial dose, only 6 (37 %) patients reached the therapeutic target against Gram-positive pathogens with MIC 1 mg/L. After individual dose adjustments, all patients reached the target. The correlation between trough levels and AUC was low (R2 = 0.5).

CONCLUSIONS

Pediatric patients with preserved renal function after liver transplantation have an increased volume of distribution for vancomycin, and most patients present subtherapeutic levels after the standard initial dosing regimen. With the vancomycin AUC-guided monitoring and dosing, it is possible to improve therapeutic target attainment.

Comparison of Vancomycin Trough-Based and 24-Hour Area Under the Curve Over Minimum Inhibitory Concentration (AUC/MIC)-Based Therapeutic Drug Monitoring in Pediatric Patients

OBJECTIVES

Vancomycin 24-hour area under the curve over minimum inhibitory concentration (AUC/MIC) monitoring has been recommended over trough-based monitoring in pediatric patients. This study compared the proportion of target attainment between vancomycin AUC/MIC and trough-based methods, and identified risk factors for subtherapeutic initial extrapolated targets.

METHODS

This was a retrospective, observational study conducted at KK Women's and Children's Hospital (KKH), Singapore. Patients aged 1 month to 18 years with stable renal function who received intravenous vancomycin between January 2014 and October 2017, with at least 2 vancomycin serum concentrations obtained after the first dose of vancomycin, were included. Using a pharmacokinetic software, namely Adult and Pediatric Kinetics (APK), initial extrapolated steady-state troughs and 24-hour AUC were determined by using a one-compartmental model. Statistical tests included Wilcoxon rank sum test, McNemar test, logistic regression, and classification and regression tree (CART) analysis.

RESULTS

Of the 82 pediatric patients included, a significantly larger proportion of patients achieved therapeutic targets when the AUC/MIC-based method (24, 29.3%) was used than with the trough-based method (9, 11.0%; p < 0.01). Patients with estimated glomerular filtration rate (eGFR) ≥60 mL/min/1.73 m2 or with age <13 years had an increased risk of obtaining subtherapeutic targets. However, empiric vancomycin doses of 60 mg/kg/day would be sufficient to achieve serum therapeutic targets, using the AUC/MIC-based method.

CONCLUSION

The AUC/MIC-based vancomycin monitoring may be preferred because a larger proportion of patients could achieve initial therapeutic targets. Future prospective studies with larger sample size will be required to determine the optimal vancomycin strategy for pediatric patients.

Treatment implications of augmented renal clearance in a critically ill COVID-19 patient: A case report

Augmented renal clearance (ARC) is a pathophysiological phenomenon that can occur in critically ill patients, leading to enhanced renal function. It is defined as a creatinine clearance of >130 mL/min/1.73 m2 . ARC can lead to subtherapeutic levels of renally cleared drugs and subsequent treatment failure. In COVID-19, it has only been described in the literature in a few cases. We present the case of a 38-year-old critically ill patient with COVID-19 who developed ARC with an initial clearance of 226 mL/min/1.73 m2 , persisting for 30 days. He required high doses of sedatives and neuromuscular blocking agents, as well as increased doses of vancomycin and dalteparin, to reach adequate serum levels. This case emphasizes the importance for clinicians to consider ARC in the dosing of all renally cleared drugs, including antibiotics, low molecular weight heparins, and sedatives, to prevent subtherapeutic drug levels and treatment failure.

Population Pharmacokinetics of Vancomycin in Patients Receiving Hemodialysis in a Malian and a French Center and Simulation of the Optimal Loading Dose

PURPOSE

Vancomycin dosing remains challenging in patients receiving intermittent hemodialysis, especially in developing countries, where access to therapeutic drug monitoring and model-based dose adjustment services is limited. The objectives of this study were to describe vancomycin population PK in patients receiving hemodialysis in a Malian and French center and examine the optimal loading dose of vancomycin in this setting.

METHODS

Population pharmacokinetic analysis was conducted using Pmetrics in 31 Malian and 27 French hemodialysis patients, having a total of 309 vancomycin plasma concentrations. Structural and covariate analyses were based on goodness-of-fit criteria. The final model was used to perform simulations of the vancomycin loading dose, targeting a daily area under the concentration-time curve (AUC) of 400-600 mg.h/L or trough concentration of 15-20 mg/L at 48 hours.

RESULTS

After 48 hours of therapy, 68% of Malian and 63% of French patients exhibited a daily AUC of <400. The final model was a 2-compartment model, with hemodialysis influencing vancomycin elimination and age influencing the vancomycin volume distribution. Younger Malian patients exhibited a lower distribution volume than French patients. Dosing simulation suggested that loading doses of 1500, 2000, and 2500 mg would be required to minimize underexposure in patients aged 30, 50, and 70 years, respectively.

CONCLUSIONS

In this study, a low AUC was frequently observed in hemodialysis patients in Mali and France after a standard vancomycin loading dose. A larger dose is necessary to achieve the currently recommended AUC target. However, the proposed dosing algorithm requires further clinical evaluation.

Impact of model-informed precision dosing on achievement of vancomycin exposure targets in pediatric patients with cystic fibrosis

BACKGROUND

Vancomycin is commonly used to treat acute pulmonary exacerbations in pediatric patients with cystic fibrosis (CF) and a history of methicillin-resistant Staphylococcus aureus. Optimizing vancomycin exposure during therapy is essential and area under-the-curve (AUC)-guided dosing is now recommended. Model-informed precision dosing (MIPD) utilizing Bayesian forecasting is a powerful approach that can support AUC-guided dose individualization. The objective of the current study was to examine the impact of implementing an AUC-guided dose individualization approach supported via a MIPD clinical decision support (CDS) tool on vancomycin exposure, target attainment rate, and safety in pediatric patients with CF treated with vancomycin during clinical care.

METHODS

A retrospective chart review was performed in patients with CF at a single children's hospital comparing pre- and post-implementation of a MIPD approach for vancomycin supported by a cloud-based, CDS tool integrated into the electronic health record (EHR). In the pre-MIPD period, vancomycin starting doses of 60 mg/kg/day (<13 years) or 45 mg/kg/day (≥13 years) were used. Dose adjustment was guided by therapeutic drug monitoring (TDM) with a target trough 10-20 mg/L. In the post-MIPD period, starting dose and dose adjustment were based on the MIPD CDS tool predictions with a target 24 h AUC (AUC24 ) 400-600 mg*h/L. Exposure and target achievement rates were retrospectively calculated and compared. Rates of acute kidney injury (AKI) were also compared.

RESULTS

Overall, 23 patient courses were included in the pre-MIPD period and 21 patient courses in the post-MIPD period. In the post-MIPD period, an individualized MIPD starting dose resulted in 71% of patients achieving target AUC24 compared to 39% in the pre-MIPD period (p < 0.05). After the first TDM and dose adjustment, target AUC24 achievement was also higher post-MIPD versus pre-MIPD (86% vs. 57%; p < 0.05). AKI rates were low and similar between periods (pre-MIPD 8.7% vs. post-MIPD 9.5%; p = 0.9).

CONCLUSION

An MIPD approach implemented within a cloud-based, EHR-integrated CDS tool safely supported vancomycin AUC-guided dosing and resulted in high rates of target achievement.

Vancomycin dosing in high-intensity continuous renal replacement therapy: A retrospective cohort study

INTRODUCTION

An inverse relationship exists between vancomycin serum concentrations and the intensity of continuous renal replacement therapy (CRRT), reflected through the dialysate flow rate (DFR). There remains a lack of evidence to guide initial vancomycin dosing in the setting of high-intensity CRRT (i.e., DFR >30 mL/kg/h). Additionally, recommendations for pharmacokinetic monitoring of vancomycin have transitioned from a trough-based to area under the curve (AUC)-based dosing strategy to optimize efficacy and safety. Therefore, an improved understanding of the impact of CRRT intensity on AUC/MIC (minimum inhibitory concentration) has the potential to enhance vancomycin dosing in this patient population.

OBJECTIVES

The goal of this study is to evaluate current vancomycin dosing strategies and achievement of pharmacokinetic targets in patients on high-intensity CRRT.

METHODS

This was a single-center, retrospective cohort study of adult critically ill patients admitted to Houston Methodist Hospital between May 2019 and October 2021 and received vancomycin therapy while on high-intensity CRRT. High-intensity CRRT was defined by a DFR that was both ≥3 L/h and >30 mL/kg/h. Depending on the initial vancomycin dosing strategy, patients were stratified into either the traditional (15 mg/kg/day) or enhanced (≥15 mg/kg/day) dosing group. The primary outcome was the percent of patients who attained steady-state AUC24 /MIC ≥400 mg*h/L at the first obtained vancomycin level in the enhanced group compared with the traditional group.

RESULTS

A total of 125 patients were included in the final analysis, 56 in the traditional and 69 in the enhanced dosing group. The primary end point occurred in 74% and 54% of patients in the enhanced and traditional dosing groups, respectively (p = 0.029). Therapeutic vancomycin trough levels (10-20 μg/mL) were more commonly achieved in the enhanced dosing group compared with the traditional dosing group (66.7% vs. 45%, p = 0.013). As DFR rose, increasingly higher doses of vancomycin, up to 27 mg/kg/day, were required to achieve the therapeutic targets.

CONCLUSION

This is the first study to evaluate the influence of variable CRRT intensities on vancomycin AUC/MIC. Our findings suggest that vancomycin doses of ≥15 mg/kg/day are needed to achieve early therapeutic targets in patients on high-intensity CRRT.

The Significance of Bayesian Pharmacokinetics in Dosing for Critically Ill Patients: A Primer for Clinicians Using Vancomycin as an Example

Antibiotic use is becoming increasingly challenging with the emergence of multidrug-resistant organisms. Pharmacokinetic (PK) alterations result from complex pathophysiologic changes in some patient populations, particularly those with critical illness. Therefore, antibiotic dose individualization in such populations is warranted. Recently, there have been advances in dose optimization strategies to improve the utilization of existing antibiotics. Bayesian-based dosing is one of the novel approaches that could help clinicians achieve target concentrations in a greater percentage of their patients earlier during therapy. This review summarizes the advantages and disadvantages of current approaches to antibiotic dosing, with a focus on critically ill patients, and discusses the use of Bayesian methods to optimize vancomycin dosing. The Bayesian method of antibiotic dosing was developed to provide more precise predictions of drug concentrations and target achievement early in therapy. It has benefits such as the incorporation of personalized PK/PD parameters, improved predictive abilities, and improved patient outcomes. Recent vancomycin dosing guidelines emphasize the importance of using the Bayesian method. The Bayesian method is able to achieve appropriate antibiotic dosing prior to the patient reaching the steady state, allowing the patient to receive the right drug at the right dose earlier in therapy.

Screening of hub inflammatory bowel disease biomarkers and identification of immune-related functions based on basement membrane genes

BACKGROUND

Inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), is a chronic, inflammatory, and autoimmune disease, but its specific etiology and pathogenesis are still unclear. This study aimed to better discover the causative basement membrane (BM) genes of their subtypes and their associations.

METHODS

The differential expression of BM genes between CD and UC was analyzed and validated by downloading relevant datasets from the GEO database. We divided the samples into 3 groups for comparative analysis. Construction of PPI networks, enrichment of differential gene functions, screening of Lasso regression models, validation of ROC curves, nomogram for disease prediction and other analytical methods were used. The immune cell infiltration was further explored by ssGSEA analysis, the immune correlates of hub BM genes were found, and finally, the hub central genes were screened by machine learning.

RESULTS

We obtained 6 candidate hub BM genes related to cellular immune infiltration in the CD and UC groups, respectively, and further screened the central hub genes ADAMTS17 and ADAMTS9 through machine learning. And in the ROC curve models, AUC > 0.7, indicating that this characteristic gene has a more accurate predictive effect on IBD. We also found that the pathogenicity-related BM genes of the CD and UC groups were mainly concentrated in the ADAMTS family (ADAMTS17 and ADAMTS9). Addition there are some differences between the two subtypes, and the central different hub BM genes are SPARC, POSTN, and ADAMTS2.

CONCLUSIONS

In the current study, we provided a nomogram model of CD and UC composed of BM genes, identified central hub genes, and clarified the similarities and differences between CD and UC. This will have potential value for preclinical, clinical, and translational guidance and differential research in IBD.

Model-Informed Precision Dosing Software Tools for Dosage Regimen Individualization: A Scoping Review

BACKGROUND

Pharmacokinetic nomograms, equations, and software are considered the main tools available for Therapeutic Drug Monitoring (TDM). Model-informed precision dosing (MIPD) is an advanced discipline of TDM that allows dose individualization, and requires a software for knowledge integration and statistical calculations. Due to its precision and extensive applicability, the use of these software is widespread in clinical practice. However, the currently available evidence on these tools remains scarce.

OBJECTIVES

To review and summarize the available evidence on MIPD software tools to facilitate its identification, evaluation, and selection by users.

METHODS

An electronic literature search was conducted in MEDLINE, EMBASE, OpenAIRE, and BASE before July 2022. The PRISMA-ScR was applied. The main inclusion criteria were studies focused on developing software for use in clinical practice, research, or modelling.

RESULTS

Twenty-eight software were classified as MIPD software. Ten are currently unavailable. The remaining 18 software were described in depth. It is noteworthy that all MIPD software used Bayesian statistical methods to estimate drug exposure and all provided a population model by default, except NONMEN.

CONCLUSIONS

Pharmacokinetic software have become relevant tools for TDM. MIPD software have been compared, facilitating its selection for use in clinical practice. However, it would be interesting to standardize the quality and validate the software tools.

Contemporary pharmacologic treatments of MRSA for hospitalized adults: rationale for vancomycin versus non-vancomycin therapies as first line agents

INTRODUCTION

Methicillin-resistant Staphylococcus aureus (MRSA) remains an important pathogen in the hospital setting and causes significant morbidity and mortality each year. Since the initial discovery over 60 years ago, vancomycin has remained a first-line treatment for many different types of MRSA infections. However, significant concerns related to target attainment and nephrotoxicity have spurred efforts to develop more effective agents in the last two decades.

AREAS COVERED

Newer anti-MRSA antibiotics that have been approved since 2000 include linezolid, daptomycin, and ceftaroline. As clinical evidence has accumulated, these newer agents have become more frequently used, and some are now recommended as co-first-line options (along with vancomycin) in clinical practice guidelines. For this review, a scoping review of the literature was conducted to support our findings and recommendations.

EXPERT OPINION

Vancomycin remains an important standard of care for MRSA infections but is limited with respect to nephrotoxicity and rapid target attainment. Newer agents such as linezolid, daptomycin, and ceftaroline have specific indications for treating different types of MRSA infections; however, newer agents also have unique attributes which require consideration during therapy.

Evaluation of Real-World Vancomycin Dosing and Attainment of Therapeutic Drug Monitoring Targets

In 2020, the Infectious Diseases Society of America (IDSA) recommended a change in vancomycin therapeutic drug monitoring from trough-based to AUC/MIC-based to optimize vancomycin's efficacy and reduce nephrotoxicity. Many hospitals have not implemented this change due to barriers such as the cost of AUC/MIC software and lack of provider familiarity. The purpose of this study was to determine the rate of AUC/MIC ratio target attainment using current trough-based vancomycin dosing practices at a city hospital. The rates of acute kidney injury (AKI) were also evaluated. Vancomycin orders were reviewed retrospectively to determine the expected AUC/MIC ratios using first-order pharmacokinetic equations over a 7-month period. Orders were excluded if they were written for a one-time dose, for individuals less than 18 years of age, or for those on hemodialysis. A total of 305 vancomycin orders were included in this review. Overall, 27.9% (85/305) of vancomycin orders attained the AUC/MIC ratio target of 400-600 mg·h/L as recommended by the guidelines. Nearly 35% (106/305) achieved AUC/MIC ratios below 400 mg·h/L and 37.4% (114/305) achieved AUC/MIC ratios above 600 mg·h/L. Orders for obese patients were significantly more likely to have below the target AUC/MIC ratios (68% vs. 23.9%, X² 48.48, p < 0.00001) and non-obese patients were significantly more likely to have above the target AUC/MIC ratios (45.7% vs. 12%, X² 27.36, p < 0.00001). The overall rate of acute kidney injury observed was 2.6%. Most vancomycin orders did not attain therapeutic drug monitoring targets, reflecting the ongoing clinical challenge of optimizing vancomycin doses and implementing new guideline recommendations.

Altered Pharmacokinetics Parameters of Vancomycin in Patients with Hematological Malignancy with Febrile Neutropenia, a Bayesian Software Estimation

The pharmacokinetics of vancomycin vary significantly between specific groups of patients, such as critically ill patients and patients with hematological malignancy (HM) with febrile neutropenia (FN). Recent evidence suggests that the use of the usual standard dose of antibiotics in patients with FN may not offer adequate exposure due to pharmacokinetic variability (PK). Therefore, the purpose of this study is to assess the effect of FN on AUC_0-24 as a key parameter for vancomycin monitoring, as well as to determine which vancomycin PK parameters are affected by the presence of FN using Bayesian software PrecisePK in HM with FN. This study was carried out in King Abdulaziz Medical City. All adult patients who were admitted to the Princess Norah Oncology Center PNOC between 1 January and 2017 and 31 December 2020, hospitalized and received vancomycin with a steady-state trough concentration measured before the fourth dose, were included. During the trial period, 297 patients received vancomycin during their stay at the oncology center, 217 of them meeting the inclusion criteria. Pharmacokinetic parameters were estimated for the neutropenic and non-FN patients using the precise PK Bayesian platform. The result showed that there was a significant difference (p < 0.05) in vancomycin clearance Cl_van, the volume of distribution at a steady-state V_dss, the volume of distribution for peripheral compartment V_dp, half-life for the elimination phase t½_β, and the first-order rate constant for the elimination process β in FN compared to non-FN patients. Furthermore, AUC_0-24 was lower for FN patients compared to non-FN patients, p < 0.05. FN has a significant effect on the PK parameters of vancomycin and AUC_0-24, which may require specific consideration during the treatment initiation.

Accuracy of 4 Free Online Dosing Calculators in Predicting the Vancomycin Area Under the Concentration-Time Curve Calculated Using a 2-Point Pharmacokinetic Approach

BACKGROUND

Free online adaptive vancomycin dosing calculators are available to estimate area under the concentration-time curve (AUC), but the accuracy of predicting vancomycin AUC using these calculators compared with using a 2-point pharmacokinetic approach has not been described.

OBJECTIVE

To evaluate the accuracy of calculator-predicted AUC (cpAUC) using 4 free online calculators compared with reference AUC (rAUC), and to assess pharmacists' impressions of the ease of use.

METHODS

Vancomycin AUC was estimated using (1) the reference method via the Sawchuk-Zaske method and linear-logarithmic trapezoidal rule using 2 steady-state postdistributional vancomycin serum concentrations and (2) 4 free online vancomycin dosing calculators including ClinCalc, VancoPK, TDMx, and DMC. Accuracy was calculated by dividing cpAUC by rAUC. Ease of cpAUC estimation was determined by using a 10-point Likert scale.

RESULTS

All 4 calculators had a median cpAUC accuracy ranging from 89% to 110%. Concordance between cpAUC and rAUC determinations of AUC <400 and > 600 mg·h/L occurred 63.3% to 71.4% and 74.5% to 78.6% of the time, respectively. Pharmacist investigators agreed that ClinCalc and VancoPK calculators were easiest to use.

CONCLUSION AND RELEVANCE

cpAUC accuracy varied among the 4 calculators, but all consistently identified patients with an rAUC <400 mg·h/L and an rAUC > 600 mg·h/L at comparable frequencies. All 4 calculators demonstrated some imprecision based on their wide 95% CIs and potential inaccuracies in predicting an rAUC <400 mg·h/L or an rAUC > 600 mg·h/L. Clin Calc and VancoPK were most user friendly based on our pharmacists' impressions.

Predicting the Area under the Plasma Concentration-Time Curve (AUC) for First Dose Vancomycin Using First-Order Pharmacokinetic Equations

To treat critically ill patients, early achievement of the target area under the plasma concentration-time curve/minimum inhibitory concentration (AUC/MIC) in the first 24 h is recommended. However, accurately calculating the AUC before steady state is an obstacle to this goal. A first-order pharmacokinetic equation to calculate vancomycin AUC after a first dose of vancomycin has never been studied. We sought to estimate AUC using two first-order pharmacokinetic equations, with different paired concentration time points, and to compare these to the actual first dose vancomycin AUC calculated by the linear-log trapezoid rule as a reference. The equations were validated using two independent intensive first dose vancomycin concentration time data sets, one from 10 adults and another from 14 children with severe infection. The equation with compensation for the alpha distribution phase using a first vancomycin serum concentration from 60 to 90 min and the second concentration from 240 to 300 min after the completed infusion showed good agreement and low bias of calculated AUC, with mean differences <5% and Lin's correlation coefficient >0.96. Moreover, it gave an excellent correlation with Pearson's r > 0.96. Estimating the first dose vancomycin AUC calculated using this first-order pharmacokinetic equation is both reliable and reproducible in clinical practice settings.

Development of a Therapeutic Drug Monitoring Strategy for the Optimization of Vincristine Treatment in Pediatric Oncology Populations in Africa

BACKGROUND

Recent studies have reported ethnic differences in vincristine exposure and outcomes such as toxicity. This resulted in the hypothesis of subtherapeutic dosing in African children. To optimize individual treatment, a strategy to identify subtherapeutic exposure using therapeutic drug monitoring is essential. The aim of the current study was to develop a strategy for therapeutic drug monitoring of vincristine in African children to meet the following criteria: (1) identify patients with low vincristine exposure with sufficient sensitivity (>70%), (2) determine vincristine exposure with a limited sampling strategy design of 3 samples, and (3) allow all samples to be collected within 4 hours after administration.

METHODS

An in silico simulation study was performed using a previously described population pharmacokinetic model and real-life demographic dataset of Kenyan and Malawian pediatric oncology patients. Two different therapeutic drug monitoring strategies were evaluated: (1) Bayesian approach and (2) pharmacometric nomogram. The sampling design was optimized using the constraints described above. Sensitivity analysis was performed to investigate the influence of missing samples, erroneous sampling times, and different boundaries on the nomogram weight bands.

RESULTS

With the Bayesian approach, 43.3% of the estimated individual exposure values had a prediction error of ≥20% owing to extremely high shrinkage. The Bayesian approach did not improve with alternative sampling designs within sampling constraints. However, the pharmacometric nomogram could identify patients with low vincristine exposure with a sensitivity, specificity, and accuracy of 75.1%, 76.4%, and 75.9%, respectively. The pharmacometric nomogram performed similarly for different weight bands.

CONCLUSIONS

The pharmacometric nomogram was able to identify patients with low vincristine exposure with high sensitivity, with 3 blood samples collected at 1, 1.5, and 4 hours after administration. Missing samples should be avoided, and the 3 scheduled samples should be collected within 15, 5, and 15 minutes of 1, 1.5, and 4 hours after administration, respectively.

Population pharmacokinetics and limited sampling strategies of polymyxin B in critically ill patients

OBJECTIVES

To characterize the pharmacokinetics (PK) of polymyxin B in Chinese critically ill patients. The factors significantly affecting PK parameters are identified, and a limited sampling strategy for therapeutic drug monitoring of polymyxin B is explored.

METHODS

Thirty patients (212 samples) were included in a population PK analysis. A limited sampling strategy was developed using Bayesian estimation, multiple linear regression and modified integral equations. Non-linear mixed-effects models were developed using Phoenix NLME software.

RESULTS

A two-compartment population PK model was used to describe polymyxin B PK. Population estimates of the volumes of central compartment distribution (V) and peripheral compartment distribution (V2), central compartment clearance (CL) and intercompartmental clearance (Q) were 7.857 L, 12.668 L, 1.672 L/h and 7.009 L/h. Continuous renal replacement therapy (CRRT) significantly affected CL, and body weight significantly affected CL and Q. The AUC0-12h of polymyxin B in patients with CRRT was significantly lower than in patients without CRRT. CL and Q increased with increasing body weight. A limited sampling strategy was suggested using a two-sample scheme with plasma at 0.5h and 8h after the end of infusion (C0.5 and C8) for therapeutic drug monitoring in the clinic.

CONCLUSIONS

A dosing regimen should be based on body weight and the application of CRRT. A two-sample strategy for therapeutic drug monitoring could facilitate individualized treatment with polymyxin B in critically ill patients.

Long-range surface plasmon aptasensor for label-free monitoring of vancomycin

Vancomycin (VCM) causes poisoning symptoms at high concentrations; thus, therapeutic drug monitoring is recommended to measure and control blood levels regularly. However, blood analysis at regular intervals does not allow knowing the detailed temporal change in concentration. To address this challenge, we developed a long-range surface plasmon (LRSP) aptasensor for measuring VCM label-free and real-time by combining a sensitive LRSP sensor and a peptide aptamer with a VCM recognition site. First, three different biosensors for VCM were compared. One was prepared by immobilizing the peptide aptamer directly on (Direct-Apt) or via a self-assembled monolayer (SAM) on a gold surface (SAM-Apt). The other used anti-VCM antibodies immobilized on a gold surface via the SAM (SAM-Ab). The Direct-Apt showed larger sensor output to VCM than the other biosensors. The dynamic range for VCM was 0.78-100 μM, including the therapeutic range (6.9-13.8 μM). The Direct-Apt also showed the sensor output only from VCM among four different antibiotics, demonstrating the high selectivity for VCM. The VCM captured by the aptamer could be removed by rinsing with phosphate-buffered saline. The measurement was rapid, with 72- and 77-sec response and recovery times, allowing not only repeated but also real-time measurements. Finally, the Direct-Apt in 20% serum solutions showed comparable sensitivity to VCM in the buffer solution, indicating high capability for real-sample.

Impact of Pharmacist-Led Multidisciplinary Team to Attain Targeted Vancomycin Area under the Curved Monitoring in a Tertiary Care Center in Thailand

Vancomycin Area Under the Curve (AUC) monitoring has been recommended to ensure successful clinical outcomes and minimize the risk of nephrotoxicity, rather than traditional trough concentration. However, vancomycin AUC monitoring by a pharmacist-led multidisciplinary team (PMT) has not been well established in Southeast Asia. This study was conducted at Thammasat University Hospital. Adult patients aged ≥ 18 years who were admitted and received intravenous vancomycin ≥48 h were included. The pre-PMT period (April 2020-September 2020) was defined as a period using traditional trough concentration, while the post-PMT period (October 2020-March 2021) was defined as a period using PMT to monitor vancomycin AUC. The primary outcome was the rate of achievement of the therapeutic target of an AUC/MIC ratio of 400-600. There was a significantly higher rate of achievement of therapeutic target vancomycin AUC during post-PMT period (66.7% vs. 34.3%, p < 0.001). Furthermore, there was a significant improvement in the clinical cure rate (92.4% vs. 69.5%, p < 0.001) and reduction in 30-day ID mortality (2.9% vs. 12.4%, p = 0.017) during the post-PMT period. Our study demonstrates that PMT was effective to help attain a targeted vancomycin AUC, improve the clinical cure rate, and reduce 30-day ID mortality. This intervention should be encouraged to be implemented in Southeast Asia.

Doing More With Less: Pragmatic Implementation of Vancomycin Area-Under-the-Curve (AUC) Monitoring

Universal area-under-the-curve (AUC) guided vancomycin therapeutic drug monitoring (TDM) is resource-intensive, cost-prohibitive, and presents a paradigm shift that leaves institutions with the quandary of defining the preferred and most practical method for TDM. We report a step-by-step quality improvement process using 4 plan-do-study-act (PDSA) cycles to provide a framework for development of a hybrid model of trough and AUC-based vancomycin monitoring. We found trough-based monitoring a pragmatic strategy as a first-tier approach when anticipated use is short-term. AUC-guided monitoring was most impactful and cost-effective when reserved for patients with high-risk for nephrotoxicity. We encourage others to consider quality improvement tools to locally adopt AUC-based monitoring.

Comparison of the mathematical equation and trapezoidal approach for 24 h area under the plasma concentration-time curve calculation in patients who received intravenous vancomycin in an acute care setting

The current recommendation for therapeutic monitoring of vancomycin has recently suggested AUC-guided dosing in patients with serious methicillin-resistant Staphylococcus aureus infections. The study objective was to evaluate mathematical equations and trapezoidal methods for calculating the 24 h area under the plasma vancomycin concentration-time curve (AUC24). The analysis of plasma vancomycin concentrations was performed in 20 adult patients treated with intravenous vancomycin. For each patient, AUC24 was estimated using two methods including, equation and trapezoidal calculation. The AUC24 from two methods was analyzed for correlation. The correlation between the equation and trapezoidal methods was strong. The coefficient of determination (R2 ) values was greater than .99. The two plasma vancomycin concentrations to achieve the highest correlation were concentration at 2.5 to 3 h after starting the infusion and concentration at 1 h before the next dose. Moreover, the AUC24 calculation from trapezoidal and equation methods showed that 19 out of 20 patients (95%) had AUC24 of more than 400 mg·h/L, and more than 50% in this group had AUC24/MIC greater than 600. Of those patients with AUC-trapezoidal >600, 15.38% of patients had trough under 15 mg/L, 15.38% of patients had trough in the range 15 to 20 mg/L and 69.23% of patients had trough more than 20 mg/L. The results of AUC-equation were similar to those of the AUC-trapezoidal method. Our study confirmed that the AUC monitoring is more appropriate than the trough vancomycin concentration. Given these considerations, the AUC-equation method is better and more practical to use in part of a point-of-care treatment, especially in the part of the Bayesian program is not available. The best sampling time point of the peak concentration was 0.5-1 h after 2-h infusion.

Characteristics and calculations of paired vancomycin measurements for determination of 24-h area-under-curve (AUC)

Background

Current pharmacy practice guidelines recommend 24-h area-under-curve (AUC₂₄) targets for use of vancomycin against methicillin-resistant Staphylococcus aureus (MRSA). AUC protocol-specific vancomycin orders were begun recently (2022) at our institution. We reviewed initial AUC protocol-associated data and calculations.

Methods

AUC₂₄ calculations are derived from timed, paired measurements of vancomycin (V1,V2). We retrieved paired (V1,V2) measurements for a 90-day interval. Calculations to obtain AUC₂₄ were performed according to two accepted methods (A, B) that assume first-order kinetics for vancomycin elimination between V1 and V2.

Results

44 (V1,V2) measurement pairs were from among 27 patients. Dosing intervals were 8, 12, or 24 h. The first-order rate constant k was normally distributed (k = 0.096 ± 0.046 1/h); t_1/2 ranged from 3 to 30 h. For target AUC₂₄ = 400-600 h × μg/mL, 55% of calculated AUC₂₄ results were within target. Imprecision for calculated k was predicted to be least when V2 is a trough level. Method B results were greater than Method A results by a factor of 1.07.

Conclusions

45% of AUC₂₄ results indicated need for change in dosage. Recommendations are that average results from A and B methods of calculation should be used, and that V1 and V2 should be as widely separated as possible.

The Bayesian-Based Area under the Curve of Vancomycin by Using a Single Trough Level: An Evaluation of Accuracy and Discordance at Tertiary Care Hospital in KSA

The AUC_0-24 is the most accurate way to track the vancomycin level while the C_min is not an accurate surrogate. Most hospitals in Saudi Arabia are under-practicing the AUC-guided vancomycin dosing and monitoring. No previous work has been conducted to evaluate such practice in the whole kingdom. The current study objective is to calculate the AUC_0-24 using the Bayesian dosing software (PrecisePK), identify the probability of patients who receive the optimum dose of vancomycin, and evaluate the accuracy and precision of the Bayesian platform. This retrospective study was conducted at King Abdulaziz medical city, Jeddah. All adult patients treated with vancomycin were included. Pediatric patients, critically ill patients requiring ICU admission, patients with acute renal failure or undergoing dialysis, and febrile neutropenic patients were excluded. The AUC_0-24 was predicted using the PrecisePK platform based on the Bayesian principle. The two-compartmental model by Rodvold et al. in this platform and patients' dose data were utilized to calculate the AUC_0-24 and trough level. Among 342 patients included in the present study, the mean of the estimated vancomycin AUC_0-24 by the posterior model of PrecisePK was 573 ± 199.6 mg, and the model had a bias of 16.8%, whereas the precision was 2.85 mg/L. The target AUC_0-24 (400 to 600 mg·h/L) and measured trough (10 to 20 mg/L) were documented in 127 (37.1%) and 185 (54%), respectively. Furthermore, the result demonstrated an increase in odds of AUC_0-24 > 600 mg·h/L among trough level 15-20 mg/L group (OR = 13.2, p < 0.05) as compared with trough level 10-14.9 mg/L group. In conclusion, the discordance in the AUC_0-24 ratio and measured trough concentration may jeopardize patient safety, and implantation of the Bayesian approach as a workable alternative to the traditional trough method should be considered.

In Outpatients Receiving Parenteral Vancomycin, Dosing Adjustments Produced by Area Under the Curve-Based and Trough-Based Monitoring Differ Only at the Extremes of the Therapeutic Trough Range

Area under the curve (AUC)-based vancomycin dosing reduces nephrotoxicity but is burdensome. Reviewing 115 adults receiving ≥2 weeks of outpatient vancomycin, we found AUC-based and trough-based dose adjustments discordant only for troughs <12 or >16 mg/L. Selective versus universal outpatient AUC calculation would likely offer similar benefit with reduced workload.

Isavuconazole Pharmacokinetics and Pharmacodynamics in Children

Isavuconazole is a broad-spectrum azole anti-fungal not yet approved in children. We conducted a retrospective, single-center review of isavuconazole use and routine therapeutic drug monitoring in pediatric patients, extracting demographic, dosing, concentration, mortality and hepatoxicity data. We constructed a nonparametric population model using Pmetrics. Of 26 patients, 19 (73%) were male. The mean (SD) age and weight were 12.7 (5.5) years and 50.9 (26.8) kg. Eighty percent received between 9.7 and 10.6 mg/kg per dose. Ten (38%) subjects had proven fungal disease and eight (31%) had probable disease, mostly with Candida and Aspergillus spp. The predicted steady-state isavuconazole concentrations in our patients were similar to previous reports in children and adults, and simulations with the proposed dosing of 10 mg/kg/dose every 8 h for 2 days followed by once daily maintenance matched effective adult exposures. Attributable mortality (5 of 11 deaths) was associated with steady-state daily AUC < 60 mg∗h/L and higher AST/ALT with trough concentrations > 5 mg/L. Neither dose nor trough alone correlated well with AUC, but AUC can be estimated with one sample 10 h after the first maintenance dose or a trough concentration, if combined with a Bayesian approach or a peak and trough without a Bayesian approach.

Comparison of vancomycin area under the concentration-time curve (AUC) using two-point pharmacokinetics versus two open-access online single-concentration vancomycin calculators

WHAT IS KNOWN AND OBJECTIVE

Current vancomycin monitoring guidelines recommend the use of area under the concentration-time curve (AUC₂₄ ) monitoring in patients with serious Methicillin-Resistant Staphylococcus aureus (MRSA) infections by utilizing either a Bayesian approach or first-order analytic equations. Several open-access websites exist that allow estimation of vancomycin AUC₂₄ with the use of a single steady-state concentration. It is uncertain how these open-access calculators perform against guideline-recommended methods. The objective was to compare AUC₂₄ estimates from two online, open-access, single-concentration vancomycin calculators compared with the two-point pharmacokinetic (2PK) method.

METHODS

AUC₂₄ estimates were made using the 2PK reference method and the single-concentration vancomycin calculators, ClinCalc and VancoPK. The AUC₂₄ estimates from the 2PK reference method were compared to the online calculators by assessing bias (median AUC₂₄ difference) and precision (AUC₂₄ difference ± 100 mg*h/L). Clinical precision was also assessed by characterizing the frequency that the 2PK reference method and the online calculators showed clinical disagreement based on the following AUC₂₄ categories: (1) AUC₂₄  < 400 mg*h/L; (2) AUC₂₄ 400-600 mg*h/L and (3) AUC₂₄  > 600 mg*h/L.

RESULTS AND DISCUSSION

A total of 253 patients were included in the study. The AUC₂₄ estimates from the ClinCalc and VancoPK single-concentration vancomycin calculators showed some bias and imprecision, though VancoPK appeared to have less. Clinical disagreement versus the 2PK reference method occurred in 31.2% and 19.4% of AUC₂₄ estimates from the ClinCalc and VancoPK single-concentration vancomycin calculators, suggesting clinical imprecision.

WHAT IS NEW AND CONCLUSION

The AUC₂₄ estimates from single-concentration, online vancomycin calculators showed some bias and imprecision in comparison to the 2PK method. Institutions should validate these online, trough-only calculators relative to a 2PK method in their patient populations prior to adoption as standard-of-care.

An area under the concentration-time curve threshold as a predictor of efficacy and nephrotoxicity for individualizing polymyxin B dosing in patients with carbapenem-resistant gram-negative bacteria

BACKGROUND

Evidence supports therapeutic drug monitoring of polymyxin B, but clinical data for establishing an area under the concentration-time curve across 24 h at steady state (AUC_ss,24 h) threshold are still limited. This study aimed to examine exposure-response/toxicity relationship for polymyxin B to establish an AUC_ss,24 h threshold in a real-world cohort of patients.

METHODS

Using a validated Bayesian approach to estimate AUC_ss,24 h from two samples, AUC_ss,24 h threshold that impacted the risk of polymyxin B-related nephrotoxicity and clinical response were derived by classification and regression tree (CART) analysis and validated by Cox regression analysis and logical regression analysis.

RESULTS

A total of 393 patients were included; acute kidney injury (AKI) was 29.0%, clinical response was 63.4%, and 30-day all-cause mortality was 35.4%. AUC_ss,24 h thresholds for AKI of > 99.4 mg h/L and clinical response of > 45.7 mg h/L were derived by CART analysis. Cox and logical regression analyses showed that AUC_ss,24 h of > 100 mg h/L was a significant predictor of AKI (HR 16.29, 95% CI 8.16-30.25, P < 0.001) and AUC_ss,24 h of ≥ 50 mg h/L (OR 4.39, 95% CI 2.56-7.47, P < 0.001) was independently associated with clinical response. However, these exposures were not associated with mortality. In addition, the correlation between trough concentration (1.2-2.8 mg/L) with outcomes was similar to AUC_ss,24 h.

CONCLUSIONS

For critically ill patients, AUC_ss,24 h threshold of 50-100 mg h/L was associated with decreased nephrotoxicity while assuring clinical efficacy. Therapeutic drug monitoring is recommended for individualizing polymyxin B dosing.

Use of modeling and simulation to predict the influence of triazole antifungal agents on the pharmacokinetics of zanubrutinib and acalabrutinib

Background: Bruton’s tyrosine kinase (BTK) inhibitors are commonly used in the targeted therapy of B-cell malignancies. It is reported that myelosuppression and fungal infections might occur during antitumor therapy of BTK inhibitors, therefore a combination therapy with triazole antifungals is usually required.

Objective: To evaluate the influence of different triazoles (voriconazole, fluconazole, itraconazole) on the pharmacokinetics of BTK inhibitors (zanubrutinib, acalabrutinib) and to quantify the drug-drug interactions (DDIs) between them.

Methods: The physiologically-based pharmacokinetic (PBPK) models were developed based on pharmacokinetic parameters and physicochemical data using Simcyp^® software. These models were validated using clinically observed plasma concentrations data which based on existing published studies. The successfully validated PBPK models were used to evaluate and predict potential DDIs between BTK inhibitors and different triazoles. BTK inhibitors and triazole antifungal agents were simulated by oral administration.

Results: Simulated plasma concentration-time profiles of the zanubrutinib, acalabrutinib, voriconazole, fluconazole, and itraconazole are consistent with the clinically observed profiles which based on existing published studies, respectively. The exposures of BTK inhibitors increase by varying degrees when co-administered with different triazole antifungals. At multiple doses regimen, voriconazole, fluconazole and itraconazole may increase the area under plasma concentration-time curve (AUC) of zanubrutinib by 127%, 81%, and 48%, respectively, and may increase the AUC of acalabrutinib by 326%, 119%, and 264%, respectively.

Conclusion: The PBPK models sufficiently characterized the pharmacokinetics of BTK inhibitors and triazole antifungals, and were used to predict untested clinical scenarios. Voriconazole exhibited the greatest influence on the exposures of BTK inhibitors. The dosage of zanubrutinib or acalabrutinib need to be reduced when co-administered with moderate CYP3A inhibitors.

Vancomycin Area under the Concentration-Time Curve Estimation Using Bayesian Modeling versus First-Order Pharmacokinetic Equations: A Quasi-Experimental Study

Aim: To evaluate the efficiency of Bayesian modeling software and first-order pharmacokinetic (PK) equations to calculate vancomycin area under the concentration-time curve (AUC) estimations. Methods: Unblinded, crossover, quasi-experimental study at a tertiary care hospital for patients receiving intravenous vancomycin. Vancomycin AUC monitoring was compared using Bayesian modeling software or first-order PK equations. The primary endpoint was the time taken to estimate the AUC and determine regimen adjustments. Secondary endpoints included the percentage of vancomycin concentrations usable for AUC calculations and acute kidney injury (AKI). Results: Of the 124 patients screened, 34 patients had usable vancomycin concentrations that led to 44 AUC estimations. Without electronic health record (EHR) integration, the time from assessment to intervention in the Bayesian modeling platform was a median of 9.3 min (quartiles Q₁–Q₃ 7.8–12.4) compared to 6.8 min (Q₁–Q₃ 4.8–8.0) in the PK equations group (p = 0.004). With simulated Bayesian software integration into the EHR, however, the median time was 3.8 min (Q₁–Q₃ 2.3–6.9, p = 0.019). Vancomycin concentrations were usable in 88.2% in the Bayesian group compared to 48.3% in the PK equation group and there were no cases of AKI. Conclusion: Without EHR integration, Bayesian software was more time-consuming to assess vancomycin dosing than PK equations. With simulated integration, however, Bayesian software was more time efficient. In addition, vancomycin concentrations were more likely to be usable for calculations in the Bayesian group.

Trough-Guided Versus AUC/MIC-Guided Vancomycin Monitoring: A Cost Analysis

PURPOSE

Recent vancomycin dosing and monitoring guidelines recommend monitoring vancomycin area under the 24-hour time-concentration curve instead of traditional trough-only monitoring. This study aimed to compare the total costs of vancomycin dosing and monitoring between trough-guided and AUC-guided approaches in a quaternary hospital from Brazil.

METHODS

In this retrospective cohort study, patients were divided into 2 groups according to the monitoring method. Patients with previous renal impairment were excluded. Vancomycin AUC was estimated by using 2 steady-state serum concentrations and first-order kinetics equations. The primary outcome was total cost of vancomycin therapy and monitoring from the hospital perspective, which included costs of cumulative doses, laboratory fees, materials used in blood collection, nursing time for collection, and pharmacist time for result interpretation.

FINDINGS

A total of 68 patients were included in the AUC/MIC-guided monitoring group, and 76 patients were included in the trough-guided monitoring group. There were no significant differences between groups regarding baseline serum creatinine level, duration of vancomycin therapy, and cumulative vancomycin dose. The median (interquartile range) total vancomycin drug and monitoring cost was $298.32 ($153.81-$429.85) for the AUC/MIC-guided group compared with $285.59 ($198.81-$435.57) for the trough-guided group (P = 0.9658).

IMPLICATIONS

Vancomycin AUC estimation using 2 steady-state serum concentrations and first-order kinetics equations is a feasible alternative for limited-resource institutions that intend to transition from a trough approach to AUC/MIC-guided monitoring. (Clin Ther. 2022;44:XXX-XXX) © 2022 Elsevier HS Journals, Inc.

Evaluating the Safety of Trough Versus Area Under the Curve (AUC)-Based Dosing Method of Vancomycin With Concomitant Piperacillin-Tazobactam

Background: Vancomycin and piperacillin-tazobactam (VPT) is a common antibiotic combination used in hospitals, and there has been increasing data indicating that the combination is associated with increased rates of acute kidney injury (AKI). It is unclear if the dosing method of vancomycin would mitigate the risk of AKI seen with VPT. Objective: To observe and compare incidence of AKI in patients on VPT when using the trough-based dosing method versus the area-under-the-curve (AUC)-based dosing method. Methods: This was a multi-center, retrospective, observational study at 3 community hospitals. Adults receiving at least 48 hours of VPT were included. Patients with severe renal dysfunction, pregnant patients, prisoners, and patients with central nervous system infections, or malignancy were excluded. The primary outcome was incidence of AKI as defined by the Infectious Disease Society of America (IDSA) criteria. Results: A total of 300 patients were included in the study; 150 patients in both the trough and AUC groups. A total of 23 patients (15%) in the trough group and 17 patients (11%) in the AUC group met the primary outcome (odds ratio [OR]: 0.7058, 95% confidence interval [CI]: [0.3603, 1.3826], P = .3098). Conclusion and Relevance: The incidence of AKI was lower in the AUC group compared with the trough group; however, this was not significant. The results of our study suggest that there is no difference between incidence of AKI when using trough- or AUC-based dosing in those receiving VPT. Because of the small sample size and retrospective nature of the study, more data are needed.

Assessment of an institutional guideline for vancomycin dosing and identification of predictive factors associated with dose and drug trough levels

OBJECTIVES

To evaluate the effectiveness of an antimicrobial guideline for vancomycin prescribing deployed using electronic prescribing aid and web/phone-based app. To define factors associated with guideline compliance and drug levels, and to investigate if antimicrobial dosing recommendations can be refined using routinely collected electronic healthcare record data.

METHODS

We used data from Oxford University Hospitals between 01-January-2016 and 01-June-2021 and multivariable regression models to investigate factors associated with dosing compliance, drug levels and acute kidney injury (AKI).

RESULTS

3767 patients received intravenous vancomycin for ≥24 h. Compliance with recommended loading and initial maintenance doses reached 84% and 70% respectively; 72% of subsequent maintenance doses were correctly adjusted. However, only 26% first and 32% subsequent levels reached the target range, and for patients with ongoing vancomycin treatment, 55-63% achieved target levels at 5 days. Drug levels were independently higher in older patients. Incidence of AKI was low (5.7%). Model estimates were used to propose updated age, weight and eGFR specific guidelines.

CONCLUSION

Despite good compliance with guidelines for vancomycin dosing, the proportion of drug levels achieving the target range remained suboptimal. Routinely collected electronic data can be used at scale to inform pharmacokinetic studies and could improve vancomycin dosing.

Prediction Accuracy of Area under the Concentration-Time Curve of Vancomycin by Bayesian Approach Using Creatinine-Based Equations of Estimated Kidney Function in Bedridden Elderly Japanese Patients

An administration plan for vancomycin (VCM) in bedridden elderly patients has not been established. This retrospective study aimed to evaluate the prediction accuracy of the area under the concentration-time curve (AUC) of VCM by the Bayesian approach using creatinine-based equations of estimated kidney function in such patients. Kidney function was estimated using the Japanese equation of estimated glomerular filtration rate (eGFR) and the Cockcroft-Gault equation of estimated creatinine clearance (eCCr). eCCr (serum creatinine (SCr) + 0.2) was calculated by substituting the SCr level +0.2 mg/dL into the Cockcroft-Gault equation. For eGFR/0.789, eGFR, eCCr, and eCCr (SCr + 0.2), the AUC values were calculated by the Bayesian approach using the therapeutic drug monitoring (TDM) software, BMs-Pod (ver 8.06) and denoted as AUC_eGFR/0.789, AUC_eGFR, AUC_eCCr, and AUC_{eCCr (SCr + 0.2)} respectively. The reference AUC (AUC_REF) was calculated by applying VCM's peak and trough steady-state concentrations to first-order pharmacokinetic equations. The medians (range) of AUC_eGFR/0.789/AUC_REF, AUC_eGFR/AUC_REF, AUC_eCCr/AUC_REF, and AUC_{eCCr (SCr + 0.2)}/AUC_REF were 0.88 (0.74-0.93), 0.90 (0.79-1.04), 0.92 (0.81-1.07), and 1.00 (0.88-1.11), respectively. Moreover, the percentage of patients within 10% of the AUC_REF, defined as |Bayesian-estimated AUC - AUC_REF| < AUC_REF × 0.1, was the highest (86%) in AUC_{eCCr (SCr + 0.2)}. These results suggest that the Bayesian approach using eCCr (SCr + 0.2) has the highest prediction accuracy for the AUC_REF in bedridden elderly patients. Although further studies are required with more accurate determination methods of the CCr and AUC, our findings highlight the potential of eCCr (SCr + 0.2) for estimating VCM's AUC by the Bayesian approach in such patients.

Optimized sampling to estimate vancomycin drug exposure: Comparison of pharmacometric and equation-based approaches in a simulation-estimation study

Vancomycin dosing should be accompanied by area under the concentration‐time curve (AUC)–guided dosing using model‐informed precision dosing software according to the latest guidelines. Although a peak plus a trough sample is considered the gold standard to determine the AUC, single‐sample strategies might be more economic. Yet, optimal sampling times for AUC determination of vancomycin have not been systematically evaluated. In the present study, automated one‐ or two‐sample strategies were systematically explored to estimate the AUC with a model averaging and a model selection algorithm. Both were compared with a conventional equation‐based approach in a simulation‐estimation study mimicking a heterogenous patient population (n = 6000). The optimal single‐sample timepoints were identified between 2–6.5 h post dose, with varying bias values between −2.9% and 1.0% and an imprecision of 23.3%–24.0% across the population pharmacokinetic approaches. Adding a second sample between 4.5–6.0 h improved the predictive performance (−1.7% to 0.0% bias, 17.6%–18.6% imprecision), although the difference in the two‐sampling strategies were minor. The equation‐based approach was always positively biased and hence inferior to the population pharmacokinetic approaches. In conclusion, the approaches always preferred samples to be drawn early in the profile (<6.5 h), whereas sampling of trough concentrations resulted in a higher imprecision. Furthermore, optimal sampling during the early treatment phase could already give sufficient time to individualize the second dose, which is likely unfeasible using trough sampling.

Does calculation method matter for targeting vancomycin area under the curve?

OBJECTIVES

To assess differences in vancomycin AUC estimates from two common, clinically applied first-order pharmacokinetic equation methods compared with Bayesian estimates.

METHODS

A cohort of patients who received vancomycin and therapeutic drug monitoring was studied. First-order population pharmacokinetic equations were used to guide initial empirical dosing. After receipt of the first dose, patients had peak and trough serum levels drawn and steady-state AUC was estimated using first-order pharmacokinetic equations as standard care. We subsequently created a Bayesian model and used individual Empirical Bayes Estimates to precisely calculate vancomycin AUC24-48, AUC48-72 and AUC72-96 in this cohort. AUC at steady state (AUCSS) differences from the first-order methods were compared numerically and categorically (i.e. below, within or above 400-600 mg·h/L) to Bayesian AUCs, which served as the gold standard.

RESULTS

A total of 65 adult inpatients with 409 plasma samples were included in this analysis. A two-compartment intravenous infusion model with first-order elimination fit the data well. The mean of Bayesian AUC24-48 was not significantly different from AUC estimates from the two first-order pharmacokinetic equation methods (P = 0.68); however, Bayesian AUC48-72 and Bayesian AUC72-96 were both significantly different when compared with both first-order pharmacokinetic equation methods (P < 0.01 for each). At the patient level, categorical classifications of AUC estimates from the two first-order pharmacokinetic equation methods differed from categorizations derived from the Bayesian calculations. Categorical agreement was ∼50% between first-order and Bayesian calculations, with declining categorical agreement observed with longer treatment courses. Differences in categorical agreement between calculation methods could potentially result in different dose recommendations for the patient.

CONCLUSIONS

Bayesian-calculated AUCs between 48-72 and 72-96 h intervals were significantly different from first-order pharmacokinetic method-estimated AUCs at steady state. The various calculation methods resulted in different categorical classification, which could potentially lead to erroneous dosing adjustments in approximately half of the patients.