Individualized Empiric Vancomycin Dosing in Neonates Using a Model-Based Approach

Pharmacokinetic and Pharmacodynamic Approaches to Optimize Antibiotic Use in Neonates

Newborn infants (particularly those born preterm) are frequently exposed to empiric antibiotics at birth, and antibiotics are among the most commonly prescribed medications in neonatal intensive care units. Challenges in optimizing neonatal antibiotic dosing include: technical and ethical barriers to neonatal pharmacoanalytic study design and sampling, difficulty in extrapolating adult and pediatric data due to unique neonatal physiology, and a lack of validated pharmacodynamic targets specific to neonatal populations. In this review, we summarize basic concepts in pharmacokinetics (PK) and pharmacodynamics (PD), describe pharmacometric strategies utilized in contemporary PK/PD analyses, and review the evolution of PK/PD data guiding neonatal dosing among 3 commonly used antibiotics.

A Review of Vancomycin, Gentamicin, and Amikacin Population Pharmacokinetic Models in Neonates and Infants

Population pharmacokinetic (popPK) models are an essential tool when implementing therapeutic drug monitoring (TDM) and to overcome dosing challenges in neonates in clinical practice. Since vancomycin, gentamicin, and amikacin are among the most prescribed antibiotics for the neonatal population, we aimed to characterize the popPK models of these antibiotics and the covariates that may influence the pharmacokinetic parameters in neonates and infants with no previous pathologies. We searched the PubMed, Embase, Web of Science, and Scopus databases and the bibliographies of relevant articles from inception to the beginning of February 2024. The search identified 2064 articles, of which 68 met the inclusion criteria (34 for vancomycin, 21 for gentamicin, 13 for amikacin). A one-compartment popPK model was more frequently used to describe the pharmacokinetics of the three antibiotics (91.2% vancomycin, 76.9% gentamicin, 57.1% amikacin). Pharmacokinetic parameter (mean ± standard deviation) values calculated for a "typical" neonate weighing 3 kg were as follows: clearance (CL) 0.34 ± 0.80 L/h for vancomycin, 0.27 ± 0.49 L/h for gentamicin, and 0.19 ± 0.07 L/h for amikacin; volume of distribution (Vd): 1.75 ± 0.65 L for vancomycin, 1.54 ± 0.53 L for gentamicin, and 1.67 ± 0.27 L for amikacin for one-compartment models. Total body weight, postmenstrual age, and serum creatinine were common predictors (covariates) for describing the variability in CL, whereas only total body weight predominated for Vd. A single universal popPK model for each of the antibiotics reviewed cannot be implemented in the neonatal population because of the significant variability between them. Body weight, renal function, and postmenstrual age are important predictors of CL in the three antibiotics, and total body weight for Vd. TDM represents an essential tool in this population, not only to avoid toxicity but to attain the desired pharmacokinetic/pharmacodynamic index. The characteristics of the neonatal population, coupled with the lack of prospective studies and external validation of most models, indicate a need to continue investigating the pharmacokinetics of these antibiotics in neonates.

Dose optimization of β-lactam antibiotics in children: from population pharmacokinetics to individualized therapy

INTRODUCTION

β-Lactams are the most widely used antibiotics in children. Their optimal dosing is essential to maximize their efficacy, while minimizing the risk for toxicity and the further emergence of antimicrobial resistance. However, most β-lactams were developed and licensed long before regulatory changes mandated pharmacokinetic studies in children. As a result, pediatric dosing practices are poorly harmonized and off-label use remains common today.

AREAS COVERED

β-Lactam pharmacokinetics and dose optimization strategies in pediatrics, including fixed dose regimens, therapeutic drug monitoring, and model-informed precision dosing are reviewed.

EXPERT OPINION/COMMENTARY

Standard pediatric doses can result in subtherapeutic exposure and non-target attainment for specific patient subpopulations (neonates, critically ill children, e.g.). Such patients could benefit greatly from more individualized approaches to dose optimization, beyond a relatively simple dose adaptation based on weight, age, or renal function. In this context, Therapeutic Drug Monitoring (TDM) and Model-Informed Precision Dosing (MIPD) emerge as particularly promising avenues. Obstacles to their implementation include the lack of strong evidence of clinical benefit due to the paucity of randomized clinical trials, of standardized assays for monitoring concentrations, or of adequate markers for renal function. The development of precision medicine tools is urgently needed to individualize therapy in vulnerable pediatric subpopulations.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

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.

Prospective validation of a model-informed precision dosing tool for vancomycin treatment in neonates

We recruited 48 neonates (50 vancomycin treatment episodes) in a prospective study to validate a model-informed precision dosing (MIPD) software. The initial vancomycin dose was based on a population pharmacokinetic model and adjusted every 36-48 h. Compared with a historical control group of 53 neonates (65 episodes), the achievement of a target trough concentration of 10-15 mg/L improved from 37% in the study to 62% in the MIPD group (P = 0.01), with no difference in side effects.

External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese

Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi-center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity.

Bayesian Vancomycin Model Selection for Therapeutic Drug Monitoring in Neonates

BACKGROUND AND OBJECTIVE

Pharmacokinetic models can inform drug dosing of vancomycin in neonates to optimize therapy. However, the model selected needs to describe the intended population to provide appropriate dose recommendations. Our study aims to identify the population pharmacokinetic (PopPK) model(s) with the best performance to predict vancomycin exposure in neonates in our hospital.

METHODS

Relevant published PopPK models for vancomycin in neonates were selected based on demographics and vancomycin dosing strategy. The predictive performance of the models was evaluated in Tucuxi using a local cohort of 69 neonates. Mean absolute error (MAE), relative bias (rBias) and relative root mean square error (rRMSE) were used to quantify the accuracy and precision of the predictive performance of each model for three different approaches: a priori, a posteriori, and Bayesian forecasting for the next course of therapy based on the previous course predictions. A PopPK model was considered clinically acceptable if rBias was between ± 20 and 95% confidence intervals included zero.

RESULTS

A total of 25 PopPK models were identified and nine were considered suitable for further evaluation. The model of De Cock et al. 2014 was the only clinically acceptable model based on a priori [MAE 0.35 mg/L, rBias 0.8 % (95% confidence interval (CI) - 7.5, 9.1%), and rRMSE 8.9%], a posteriori [MAE 0.037 mg/L, rBias - 0.23% (95% CI - 1.3, 0.88%), and rRMSE 6.02%] and Bayesian forecasting for the next courses [MAE 0.89 mg/L, rBias 5.45% (95% CI - 8.2, 19.1%), and rRMSE 38.3%) approaches.

CONCLUSIONS

The De Cock model was selected based on a comprehensive approach of model selection to individualize vancomycin dosing in our neonates.

Population pharmacokinetics of vancomycin in very low birth weight neonates

Introduction

Vancomycin dosing in very low birth weight (VLBW) neonates is challenging. Compared with the general neonatal population, VLBW neonates are less likely to achieve the vancomycin therapeutic targets. Current dosing recommendations are based on studies of the general neonatal population, as only a very limited number of studies have evaluated vancomycin pharmacokinetics in VLBW neonates. The main aim of this study was to develop a vancomycin population pharmacokinetic model to optimize vancomycin dosing in VLBW neonates.

Methods

This multicenter study was conducted at six major hospitals in Saudi Arabia. The study included VLBW neonates who received vancomycin and had at least one vancomycin serum trough concentration measurement at a steady state. We developed a pharmacokinetic model and performed Monte Carlo simulations to develop an optimized dosing regimen for VLBW infants. We evaluated two different targets: AUC_0-24 of 400-600 or 400-800 µg. h/mL. We also estimated the probability of trough concentrations >15 and 20 µg/mL.

Results

In total, we included 236 neonates, 162 in the training dataset, and 74 in the validation dataset. A one-compartment model was used, and the distribution volume was significantly associated only with weight, whereas clearance was significantly associated with weight, postmenstrual age (PMA), and serum creatinine (Scr).

Discussion

We developed dosing regimens for VLBW neonates, considering the probability of achieving vancomycin therapeutic targets, as well as different toxicity thresholds. The dosing regimens were classified according to PMA and Scr. These dosing regimens can be used to optimize the initial dose of vancomycin in VLBW neonates.

Evaluation of Neonatal and Paediatric Vancomycin Pharmacokinetic Models and the Impact of Maturation and Serum Creatinine Covariates in a Large Multicentre Data Set

BACKGROUND AND OBJECTIVE

Infants and neonates present a clinical challenge for dosing drugs with high interindividual variability due to these patients' rapid growth and the interplay between maturation and organ function. Model-informed precision dosing (MIPD), which can account for interindividual variability via patient characteristics and Bayesian forecasting, promises to improve individualized dosing strategies in this complex population. Here, we assess the predictive performance of published population pharmacokinetic models describing vancomycin in neonates and infants, and analyze the robustness of these models in the face of clinical uncertainty surrounding covariate values.

METHODS

The predictive precision and bias of nine pharmacokinetic models were compared in a large multi-site data set (N = 2061 patients, 5794 drug levels, 28 institutions) of patients aged 0-365 days. The robustness of model predictions to errors in serum creatinine measurements and gestational age was assessed by using recorded values or by replacing covariate values with 0.3, 0.5 or 0.8 mg/dL or with 40 weeks, respectively.

RESULTS

Of the nine models, two models (Dao and Jacqz-Aigrain) resulted in predicted concentrations within 2.5 mg/L or 15% of the measured values for at least 60% of population predictions. Within individual models, predictive performance often 2 differed in neonates (0-4 weeks) versus older infants (15-52 weeks). For preterm neonates, imputing gestational age as 40 weeks reduced the accuracy of model predictions. Measured values of serum creatinine improved model predictions compared to using imputed values even in neonates ≤1 week of age.

CONCLUSIONS

Several available pharmacokinetic models are suitable for MIPD in infants and neonates. Availability and accuracy of model covariates for patients will be important for guiding dose decision-making.

Evaluation of vancomycin individualized model-based dosing approach in neonates

BACKGROUND

Vancomycin is commonly used to treat methicillin-resistant staphylococcal infections in neonates. Consensus on its ideal dosing in neonates has not been achieved. Model-based dosing recently has evolved as an important tool to optimize vancomycin initial dosing. The aim of this is to evaluate a population pharmacokinetic model-based approach in achieving the vancomycin therapeutic target of an AUC_0-24 400 as recommended by the recent IDSA treatment guidelines. This model was implemented as a simple Excel calculator to individualize and optimize vancomycin initial dosing in neonates.

METHODS

An Excel calculator was developed using a previously published population pharmacokinetic model in neonates. It was evaluated using retrospectively retrieved data. For each patient, the initial empiric dose was calculated using the proposed Excel model and the most widely used neonatal dosing references. The probability of achieving the target AUC_0-24 of >400 mg h/L using the model-based method was calculated and compared with that of the empiric doses using other references.

RESULTS

This analysis included 225 neonates. The probability of achieving the target AUC_0-24 >400 was 89% using our model-based approach compared with 11%-59% using tertiary neonatal dosing references (p < 0.01 for all comparisons).

CONCLUSION

These innovative personalized dosing calculators are promising to improve vancomycin initial dosing in neonates and are easily applicable in routine practices.

Reappraisal of therapeutic vancomycin trough concentrations with empirical dosing in neonatal infections

BACKGROUND

Vancomycin is commonly used for neonatal sepsis. However, consensus on an empirical neonatal vancomycin regimen remains uncertain. We aimed to reappraise the therapeutic optimum concerning vancomycin trough concentrations with empirical dosing and to evaluate the relationship between trough concentrations and predicted 24-h area under the curve (AUC₂₄).

METHODS

This was a 3-year retrospective study. Neonates who were admitted to the neonatal intensive care unit with available vancomycin trough concentrations were enrolled. Trough levels were obtained before the fourth dose. Achievement of goal trough after implementing the vancomycin dosing regimen was based on the Practical Neonatology Medical Manual, published by the National Taiwan University College of Medicine.

RESULTS

A total of 46 neonates were included for analysis. Coagulase-negative staphylococci were the most commonly identified pathogens of sepsis. Among these patients, 22 achieved goal trough levels of 10-20 mcg/mL. Trough levels of 5-10 or >20 mcg/mL occurred in 13 and 11 patients, respectively. A moderately positive correlation between trough and predicted AUC₂₄ was found in all patients (Spearman's rho = 0.676, p < 0.001). In patients with body weight 1200-2000 g and postnatal age >7 days, the serum creatinine of those with trough levels >20 mcg/mL was significantly higher than those with goal trough levels (0.61 vs. 0.45 mg/dL, p = 0.01). Among those with trough levels >20 mcg/mL, 5 patients received ibuprofen for patent ductus arteriosus closing prior to vancomycin treatment (45%, 5/11), compared to only 3 patients with trough levels <20 mcg/mL (9%, 3/35) (p = 0.013).

CONCLUSION

Only half of the neonates receiving empirical vancomycin regimen achieved goal trough levels of 10-20 mcg/mL. Higher serum creatinine or ibuprofen treatment may increase the risk of overly high trough levels. The vancomycin regimen needs further validation and modification to provide adequate dosing for optimal use in neonates.

Clinical decision support in the neonatal ICU

Clinical Decision Support (CDS) tools help the healthcare team diagnose, monitor, and treat patients more efficiently and consistently by executing clinical practice guidelines and recommendations. As a result, CDS has a direct impact on the delivery and healthcare outcomes. This review covers the fundamental concepts, as well as the infrastructure needed to create a CDS tool and examples of its use in the neonatal setting. This article also serves as a primer on what to think about when proposing the development of a new CDS tool, or when upgrading an existing one. We also highlight important elements that influence CDS development, such as informatics methodologies, data and device interoperability, and regulation.

Use of Antibiotics in Preterm Newborns

Due to complex maturational and physiological changes that characterize neonates and affect their response to pharmacological treatments, neonatal pharmacology is different from children and adults and deserves particular attention. Although preterms are usually considered part of the neonatal population, they have physiological and pharmacological hallmarks different from full-terms and, therefore, need specific considerations. Antibiotics are widely used among preterms. In fact, during their stay in neonatal intensive care units (NICUs), invasive procedures, including central catheters for parental nutrition and ventilators for respiratory support, are often sources of microbes and require antimicrobial treatments. Unfortunately, the majority of drugs administered to neonates are off-label due to the lack of clinical studies conducted on this special population. In fact, physiological and ethical concerns represent a huge limit in performing pharmacokinetic (PK) studies on these subjects, since they limit the number and volume of blood sampling. Therapeutic drug monitoring (TDM) is a useful tool that allows dose adjustments aiming to fit plasma concentrations within the therapeutic range and to reach specific drug target attainment. In this review of the last ten years’ literature, we performed Pubmed research aiming to summarize the PK aspects for the most used antibiotics in preterms.

Uncovering Discrepancies in IV Vancomycin Infusion Records between Pump Logs and EHR Documentation

BACKGROUND

Infusion start time, completion time, and interruptions are the key data points needed in both area under the concentration-time curve (AUC)- and trough-based vancomycin therapeutic drug monitoring (TDM). However, little is known about the accuracy of documented times of drug infusions compared with automated recorded events in the infusion pump system. A traditional approach of direct observations of infusion practice is resource intensive and impractical to scale. We need a new methodology to leverage the infusion pump event logs to understand the prevalence of timestamp discrepancies as documented in the electronic health records (EHRs).

OBJECTIVES

We aimed to analyze timestamp discrepancies between EHR documentation (the information used for clinical decision making) and pump event logs (actual administration process) for vancomycin treatment as it may lead to suboptimal data used for therapeutic decisions.

METHODS

We used process mining to study the conformance between pump event logs and EHR data for a single hospital in the United States from July to December 2016. An algorithm was developed to link records belonging to the same infusions. We analyzed discrepancies in infusion start time, completion time, and interruptions.

RESULTS

Of the 1,858 infusions, 19.1% had infusion start time discrepancy more than ± 10 minutes. Of the 487 infusion interruptions, 2.5% lasted for more than 20 minutes before the infusion resumed. 24.2% (312 of 1,287) of 1-hour infusions and 32% (114 of 359) of 2-hour infusions had over 10-minute completion time discrepancy. We believe those discrepancies are inherent part of the current EHR documentation process commonly found in hospitals, not unique to the care facility under study.

CONCLUSION

We demonstrated pump event logs and EHR data can be utilized to study time discrepancies in infusion administration at scale. Such discrepancy should be further investigated at different hospitals to address the prevalence of the problem and improvement effort.

External Validation of a Vancomycin Population Pharmacokinetic Model and Developing a New Dosage Regimen in Neonates

BACKGROUND AND OBJECTIVE

Vancomycin is the drug of choice in the treatment of MRSA infections. In a published vancomycin population pharmacokinetic study on neonates in Singapore healthcare institutions, it was found that vancomycin clearance was predicted by weight, postmenstrual age, and serum creatinine. The aim of this study was to externally validate the vancomycin population pharmacokinetic model to develop a new dosage regimen in neonates, and to compare this regimen with the existing institutional and NeoFax^® dosage regimens.

METHODS

A retrospective chart review of neonates who received vancomycin therapy and therapeutic drug monitoring was conducted. The median prediction error percentage was calculated to assess bias, while the median absolute prediction error percentage and the root mean squared error percentage were calculated to assess precision. The new dosage regimen was developed using Monte Carlo simulation.

RESULTS

A total of 20 neonates were included in the external validation dataset. Eighteen of them were premature, with a median gestational age of 27.7 (25.9-31.5) weeks and postmenstrual age of 30.5 (27.3-34.3) weeks at the point of vancomycin initiation. No apparent systematic bias was found in the predictions of the model. The external validation performed in the current study found the model to be generally unbiased. Our new vancomycin dosage regimen was able to achieve target trough concentrations and area under the curve (AUC₂₄) at a greater proportion as compared to existing institutional and NeoFax^® dosage regimens.

CONCLUSION

The pharmacokinetic model built in the previous study can be used to conduct reliable population simulations of our Asian neonatal population in Singapore. The new dosage regimen was able to achieve target trough concentrations and AUC₂₄ better than existing institutional and NeoFax^® dosage regimens.

Implementation of Vancomycin Therapeutic Monitoring Guidelines: Focus on Bayesian Estimation Tools in Neonatal and Pediatric Patients

BACKGROUND

The 2020 consensus guidelines for vancomycin therapeutic monitoring recommend using Bayesian estimation targeting the ratio of the area under the curve over 24 hours to minimum inhibitory concentration as an optimal approach to individualize therapy in pediatric patients. To support institutional guideline implementation in children, the objective of this study was to comprehensively assess and compare published population-based pharmacokinetic (PK) vancomycin models and available Bayesian estimation tools, specific to neonatal and pediatric patients.

METHODS

PubMed and Embase databases were searched from January 1994 to December 2020 for studies in which a vancomycin population PK model was developed to determine clearance and volume of distribution in neonatal and pediatric populations. Available Bayesian software programs were identified and assessed from published articles, software program websites, and direct communication with the software company. In the present review, 14 neonatal and 20 pediatric models were included. Six programs (Adult and Pediatric Kinetics, BestDose, DoseMeRx, InsightRx, MwPharm++, and PrecisePK) were evaluated.

RESULTS

Among neonatal models, Frymoyer et al and Capparelli et al used the largest PK samples to generate their models, which were externally validated. Among the pediatric models, Le et al used the largest sample size, with multiple external validations. Of the Bayesian programs, DoseMeRx, InsightRx, and PrecisePK used clinically validated neonatal and pediatric models.

CONCLUSIONS

To optimize vancomycin use in neonatal and pediatric patients, clinicians should focus on selecting a model that best fits their patient population and use Bayesian estimation tools for therapeutic area under the -curve-targeted dosing and monitoring.

Using mathematical modeling to estimate time-independent cancer chemotherapy efficacy parameters

One of the primary cancer treatment modalities is chemotherapy. Unfortunately, traditional anti-cancer drugs are often not selective and cause damage to healthy cells, leading to serious side effects for patients. For this reason more targeted therapeutics and drug delivery methods are being developed. The effectiveness of new treatments is initially determined via in vitro cell viability assays, which determine the IC 50  of the drug. However, these assays are known to result in estimates of IC 50  that depend on the measurement time, possibly resulting in over- or under-estimation of the IC 50 . Here, we test the possibility of using cell growth curves and fitting of mathematical models to determine the IC 50  as well as the maximum efficacy of a drug ( ε max ). We measured cell growth of MCF-7 and HeLa cells in the presence of different concentrations of doxorubicin and fit the data with a logistic growth model that incorporates the effect of the drug. This method leads to measurement time-independent estimates of IC 50  and ε max , but we find that ε max  is not identifiable. Further refinement of this methodology is needed to produce uniquely identifiable parameter estimates.

Open-source maximum a posteriori-bayesian dosing AdDS to current therapeutic drug monitoring: Adapting to the era of individualized therapy

Recent updates in the therapeutic drug monitoring (TDM) guidelines for vancomycin have rekindled interest in maximum a posteriori-Bayesian (MAP-Bayesian) estimation of patient-specific pharmacokinetic parameters. To create a versatile infrastructure for MAP-Bayesian dosing of vancomycin or other drugs, a freely available, R-based software package, Advanced Dosing Solutions (AdDS), was created to facilitate clinical implementation of these improved TDM methods. The objective of this study was to utilize AdDS for pre- and post-processing of data in order to streamline the therapeutic management of vancomycin in healthy and obese veterans. Patients from a local Veteran Affairs hospital were utilized to compare the process of full re-estimation versus Bayesian updating of priors on healthy adult and obese patient populations for use with AdDS. Twenty-four healthy veterans were utilized to train (14/24) and test (10/24) the base pharmacokinetic model of vancomycin while comparing the effects of updated and fully re-estimated priors. This process was repeated with a total of 18 obese veterans for both training (11/18) and testing (7/18). Comparison of MAP objective function between the original and re-estimated models for healthy adults indicated that 78.6% of the subjects in the training and 70.0% of the subjects in the testing datasets had similar or improved predictions by the re-estimated model. For obese veterans, 81.8% of subjects in the training dataset and 85.7% of subjects in the testing dataset had similar or improved predictions. Re-estimation of model parameters provided more significant improvements in objective function compared with Bayesian updating, which may be a useful strategy in cases where sufficient samples and subjects are available. The generation of bespoke regimens based on patient-specific clearance and minimal sampling may improve patient care by addressing fundamental pharmacokinetic differences in healthy and obese veteran populations.

Individualized precision dosing approaches to optimize antimicrobial therapy in pediatric populations

Introduction:Severe infections continue to impose a major burden on critically ill children and mortality rates remain stagnant. Outcomes rely on accurate and timely delivery of antimicrobials achieving target concentrations in infected tissue. Yet, developmental aspects, disease-related variables, and host factors may severely alter antimicrobial pharmacokinetics in pediatrics. The emergence of antimicrobial resistance increases the need for improved treatment approaches.Areas covered:This narrative review explores why optimization of antimicrobial therapy in neonates, infants, children, and adolescents is crucial and summarizes the possible dosing approaches to achieve antimicrobial individualization. Finally, we outline a roadmap toward scientific evidence informing the development and implementation of precision antimicrobial dosing in critically ill children.The literature search was conducted on PubMed using the following keywords: neonate, infant, child, adolescent, pediatrics, antimicrobial, pharmacokinetic, pharmacodynamic target, Bayes dosing software, optimizing, individualizing, personalizing, precision dosing, drug monitoring, validation, attainment, and software implementation. Further articles were sought from the references of the above searched articles.Expert opinion:Recently, technological innovations have emerged that enabled the development of individualized antimicrobial dosing approaches in adults. More work is required in pediatrics to make individualized antimicrobial dosing approaches widely operationalized in this population.

Status Toward the Implementation of Precision Dosing in Children

Precision dosing is progressing beyond the conceptual and proof-of-concept stages toward implementation. As the availability of dosing algorithms, tools, and platforms increases, so do the investment in technology services and actual implementation of clinical services offering these solutions to patients. Nowhere is this needed more than in pediatric populations, which are still reliant on adult drug development and bridging strategies to support dosing, often in the absence of actual dose-finding studies in the target pediatric population. Still, there is more work to be done to ensure that proper governance of these services is maintained, and that sustainability of these early implementations is guided by new science as it evolves and meaningful outcome data to confirm that such services deliver on both clinical and economic return on investment. In addition, the field should ensure that all approaches beyond a therapeutic drug monitoring-driven, pharmacokinetic-centric approach should be considered as the tools and services evolve, especially when pediatric-specific pharmacokinetic/pharmacodyamic and pharmacogenetic data are available and shown to be useful to guide dosing. This review evaluates current pediatric precision dosing efforts, highlighting their utility, longevity, and sustainability and assesses the current process for implementing such approaches examining current barriers that stand in the way of broader implementation and the stakeholders that must engage to ensure its ultimate success.

Low vancomycin trough concentration in neonates and young infants

BACKGROUND

Vancomycin (VCM) is useful for treating methicillin-resistant Staphylococcus aureus. In infants, calibrating the initial VCM dose is difficult, and many regimens have been proposed. For instance, our center uses the VCM regimen recommended for infants in the 2012-13 Nelson's Pediatric Antimicrobial Therapy. Nonetheless, our experience has shown that the initial VCM trough concentrations were frequently off target. We therefore analyzed the data on the initial VCM trough concentration in infant patients at our center.

METHODS

The study subjects were inborn infants born between July 2014 and June 2019 who were given VCM at earlier than day 60 in the neonatal intensive care unit. The primary outcome was the initial VCM trough concentration. The patients were divided into three groups by VCM trough concentration: <10, 10-15, and >15 mg/L. We also estimated VCM trough concentration by one method using Monte Carlo simulation, based on Nelson regimen dosage.

RESULTS

Thirty-three patients were analyzed. The number of patients with <10, 10-15, and >15 mg/L was 24, 4, and 5, respectively. There was no significant difference in clinical characteristics between <10 versus 10-15 and 10-15 versus >15 mg/L. The numbers of patients with <10, 10-15, and >15 mg/L in the simulation were 26, 6, and 1, respectively.

CONCLUSIONS

Most initial VCM trough concentrations were below the target. We could not find any significant clinical characteristics, which affected VCM trough concentration. Increasing the VCM dosage of the Nelson regimen with simulation should therefore be considered.

Vancomycin dosing and therapeutic drug monitoring practices: guidelines versus real-life

Background Correct dosing and therapeutic drug monitoring (TDM) practices are essential when aiming for optimal vancomycin treatment. Objective To assess target attainment after initial dosing and dose adjustments, and to determine compliance to dosing and TDM guidelines. Setting Tertiary care university hospital in Belgium. Method A chart review was performed in 150 patients, ranging from preterm infants to adults, treated intravenously with vancomycin. Patient characteristics, dosing and TDM data were compared to evidence-based hospital guidelines. Main outcome measures Target attainment of vancomycin after initial dosing and dose adjustments. Results Subtherapeutic concentrations were measured in 68% of adults, in 76% of children and in 52% of neonates after treatment initiation. Multiple dose adaptations (median 2, Q1 1-Q3 2) were required for target attainment, whilst more than 20% of children and neonates never reached targeted concentrations. Regarding compliance to the hospital guideline, some points of improvement were identified: omitted dose adjustment in adults with decreased renal function (53%), delayed sampling (16% in adults, 31% in children) and redundant sampling (34% of all samples in adults, 12% in children, 13% in neonates). Conclusion Target attainment for vancomycin with current dosing regimens and TDM is poor in all age groups. Besides, human factors should not be ignored when aiming for optimal treatment. This study reflects an ongoing challenge in clinical practice and highlights the need for optimization of vancomycin dosing strategies and improvement of awareness of all health care professionals involved.

Personalized Dosing of Intravenous Vancomycin Among Critically Ill Neonates in Hong Kong: Harnessing Electronic Health Records to Develop a Web-Based Dosing Interface (Preprint)

Background

Intravenous (IV) vancomycin is used in the treatment of severe infection in neonates. However, its efficacy is compromised by elevated risks of acute kidney injury. The risk is even higher among neonates admitted to the neonatal intensive care unit (NICU), in whom the pharmacokinetics of vancomycin vary widely. Therapeutic drug monitoring is an integral part of vancomycin treatment to balance efficacy against toxicity. It involves individual dose adjustments based on the observed serum vancomycin concentration (VC_s). However, the existing trough-based approach shows poor evidence for clinical benefits. The updated clinical practice guideline recommends population pharmacokinetic (popPK) model–based approaches, targeting area under curve, preferably through the Bayesian approach. Since Bayesian methods cannot be performed manually and require specialized computer programs, there is a need to provide clinicians with a user-friendly interface to facilitate accurate personalized dosing recommendations for vancomycin in critically ill neonates.

Objective

We used medical data from electronic health records (EHRs) to develop a popPK model and subsequently build a web-based interface to perform model-based individual dose optimization of IV vancomycin for NICU patients in local medical institutions.

Methods

Medical data of subjects prescribed IV vancomycin in the NICUs of Prince of Wales Hospital and Queen Elizabeth Hospital in Hong Kong were extracted from EHRs, namely the Clinical Information System, In-Patient Medication Order Entry, and electronic Patient Record. Patient demographics, such as body weight and postmenstrual age (PMA), serum creatinine (SCr), vancomycin administration records, and VC_s were collected. The popPK model employed a 2-compartment infusion model. Various covariate models were tested against body weight, PMA, and SCr, and were evaluated for the best goodness of fit. A previously published web-based dosing interface was adapted to develop the interface in this study.

Results

The final data set included EHR data extracted from 207 subjects, with a total of 689 VC_s measurements. The final model chosen explained 82% of the variability in vancomycin clearance. All parameter estimates were within the bootstrapping CIs. Predictive plots, residual plots, and visual predictive checks demonstrated good model predictability. Model approximations showed that the model-based Bayesian approach consistently promoted a probability of target attainment (PTA) above 75% for all subjects, while only half of the subjects could achieve a PTA over 50% with the trough-based approach. The dosing interface was developed with the capability to optimize individual doses with the model-based empirical or Bayesian approach.

Conclusions

Using EHRs, a satisfactory popPK model was verified and adopted to develop a web-based individual dose optimization interface. The interface is expected to improve treatment outcomes of IV vancomycin for severe infections among critically ill neonates. This study provides the foundation for a cohort study to demonstrate the utility of the new approach compared with previous dosing methods.

Model-Optimized Fluconazole Dose Selection for Critically Ill Patients Improves Early Pharmacodynamic Target Attainment without the Need for Therapeutic Drug Monitoring

Fluconazole has been associated with higher mortality compared with the echinocandins in patients treated for invasive candida infections. Underexposure from current fluconazole dosing regimens may contribute to these worse outcomes, so alternative dosing strategies require study. The objective of this study was to evaluate fluconazole drug exposure in critically ill patients comparing a novel model-optimized dose selection method with established approaches over a standard 14-day (336-h) treatment course. Target attainment was evaluated in a representative population of 1,000 critically ill adult patients for (i) guideline dosing (800-mg loading and 400-mg maintenance dosing adjusted to renal function), (ii) guideline dosing followed by therapeutic drug monitoring (TDM)-guided dose adjustment, and (iii) model-optimized dose selection based on patient factors (without TDM). Assuming a MIC of 2 mg/liter, free fluconazole 24-h area under the curve (fAUC24) targets of ≥200 mg · h/liter and <800 mg · h/liter were used for assessment of target attainment. Guideline dosing resulted in underexposure in 21% of patients at 48 h and in 23% of patients at 336 h. The TDM-guided strategy did not influence 0- to 48-h target attainment due to inherent procedural delays but resulted in 37% of patients being underexposed at 336 h. Model-optimized dosing resulted in ≥98% of patients meeting efficacy targets throughout the treatment course, while resulting in less overexposure compared with guideline dosing (7% versus 14%) at 336 h. Model-optimized dose selection enables fluconazole dose individualization in critical illness from the outset of therapy and should enable reevaluation of the comparative effectiveness of this drug in patients with severe fungal infections.

Model-Informed Precision Dosing of Antibiotics in Pediatric Patients: A Narrative Review

Optimal pharmacotherapy in pediatric patients with suspected infections requires understanding and integration of relevant data on the antibiotic, bacterial pathogen, and patient characteristics. Because of age-related physiological maturation and non-maturational covariates (e.g., disease state, inflammation, organ failure, co-morbidity, co-medication and extracorporeal systems), antibiotic pharmacokinetics is highly variable in pediatric patients and difficult to predict without using population pharmacokinetics models. The intra- and inter-individual variability can result in under- or overexposure in a significant proportion of patients. Therapeutic drug monitoring typically covers assessment of pharmacokinetics and pharmacodynamics, and concurrent dose adaptation after initial standard dosing and drug concentration analysis. Model-informed precision dosing (MIPD) captures drug, disease, and patient characteristics in modeling approaches and can be used to perform Bayesian forecasting and dose optimization. Incorporating MIPD in the electronic patient record system brings pharmacometrics to the bedside of the patient, with the aim of a consisted and optimal drug exposure. In this narrative review, we evaluated studies assessing optimization of antibiotic pharmacotherapy using MIPD in pediatric populations. Four eligible studies involving amikacin and vancomycin were identified from 418 records. Key articles, independent of year of publication, were also selected to highlight important attributes of MIPD. Although very little research has been conducted until this moment, the available data on vancomycin indicate that MIPD is superior compared to conventional dosing strategies with respect to target attainment. The utility of MIPD in pediatrics needs to be further confirmed in frequently used antibiotic classes, particularly aminoglycosides and beta-lactams.

Stratified Management for Bacterial Infections in Late Preterm and Term Neonates: Current Strategies and Future Opportunities Toward Precision Medicine

Bacterial infections remain a major cause of morbidity and mortality in the neonatal period. Therefore, many neonates, including late preterm and term neonates, are exposed to antibiotics in the first weeks of life. Data on the importance of inter-individual differences and disease signatures are accumulating. Differences that may potentially influence treatment requirement and success rate. However, currently, many neonates are treated following a "one size fits all" approach, based on general protocols and standard antibiotic treatment regimens. Precision medicine has emerged in the last years and is perceived as a new, holistic, way of stratifying patients based on large-scale data including patient characteristics and disease specific features. Specific to sepsis, differences in disease susceptibility, disease severity, immune response and pharmacokinetics and -dynamics can be used for the development of treatment algorithms helping clinicians decide when and how to treat a specific patient or a specific subpopulation. In this review, we highlight the current and future developments that could allow transition to a more precise manner of antibiotic treatment in late preterm and term neonates, and propose a research agenda toward precision medicine for neonatal bacterial infections.

Development and external evaluation of a population pharmacokinetic model for continuous and intermittent administration of vancomycin in neonates and infants using prospectively collected data

BACKGROUND

Vancomycin is commonly used for nosocomial bacterial pathogens causing late-onset septicaemia in preterm infants. We prospectively collected pharmacokinetic data aiming to describe pharmacokinetics and determine covariates contributing to the variability in neonatal vancomycin pharmacokinetics. Further, we aimed to use the model to compare the ratio of AUC24 at steady-state to the MIC (AUC24,ss/MIC) of several intermittent and continuous dosing regimens.

METHODS

Newborns receiving vancomycin for suspected or confirmed late-onset sepsis were included. Peak and trough concentrations for intermittent vancomycin dosing and steady-state concentrations for continuous vancomycin dosing were measured. NONMEM 7.3 was used for population pharmacokinetic analysis. Monte Carlo simulations were performed to compare dosing schemes.

RESULTS

Data from 54 infants were used for model development and from 34 infants for the model evaluation {corrected gestational age [median (range)] = 29 (23.7-41.9) weeks and 28 (23.4-41.7) weeks, respectively}. The final model was a one-compartment model. Weight and postmenstrual age were included a priori, and then no additional covariate significantly improved the model fit. Final model parameter estimates [mean (SEM)]: CL = 5.7 (0.3) L/h/70 kg and V = 39.3 (3.7) L/70 kg. Visual predictive check of the evaluation dataset confirmed the model can predict external data. Simulations using MIC of 1 mg/L showed that for neonates with gestational age ≤25 weeks and postnatal age ≤2 weeks AUC24,ss/MIC was lower with the intermittent regimen (median 482 versus 663).

CONCLUSIONS

A population pharmacokinetic model for continuous and intermittent vancomycin administration in infants was developed. Continuous administration might be favourable for treating infections caused by resistant microorganisms in very young and immature infants.

Model-Informed Precision Dosing of Vancomycin in Hospitalized Children: Implementation and Adoption at an Academic Children's Hospital

Background

Model-informed precision dosing (MIPD) can serve as a powerful tool during therapeutic drug monitoring (TDM) to help individualize dosing in populations with large pharmacokinetic variation. Yet, adoption of MIPD in the clinical setting has been limited. Overcoming technologic hurdles that allow access to MIPD at the point-of-care and placing it in the hands of clinical specialists focused on medication dosing may encourage adoption.

Objective

To describe the hospital implementation and usage of a MIPD clinical decision support (CDS) tool for vancomycin in a pediatric population.

Methods

Within an academic children’s hospital, MIPD for vancomycin was implemented via a commercial cloud-based CDS tool that utilized Bayesian forecasting. Clinical pharmacists were recognized as local champions to facilitate adoption of the tool and operated as end-users. Integration within the electronic health record (EHR) and automatic transmission of patient data to the tool were identified as important requirements. A web-link icon was developed within the EHR which when clicked sends users and needed patient-level clinical data to the CDS platform. Individualized pharmacokinetic predictions and exposure metrics for vancomycin are then presented in the form of a web-based dashboard. Use of the CDS tool as part of TDM was tracked and users were surveyed on their experience.

Results

After a successful pilot phase in the neonatal intensive care unit, implementation of MIPD was expanded to the pediatric intensive care unit, followed by availability to the entire hospital. During the first 2+ years since implementation, a total of 853 patient-courses (n = 96 neonates, n = 757 children) and 2,148 TDM levels were evaluated using the CDS tool. For the most recent 6 months, the CDS tool was utilized to support 79% (181/230) of patient-courses in which TDM was performed. Of 26 users surveyed, > 96% agreed or strongly agreed that automatic transmission of patient data to the tool was a feature that helped them complete tasks more efficiently; 81% agreed or strongly agreed that they were satisfied with the CDS tool.

Conclusions

Integration of a vancomycin CDS tool within the EHR, along with leveraging the expertise of clinical pharmacists, allowed for successful adoption of MIPD in clinical care.

Challenges of Vancomycin Dosing and Therapeutic Monitoring in Neonates

Late-onset sepsis in neonates can lead to significant morbidity and mortality, especially in preterm infants. Vancomycin is commonly prescribed for the treatment of Gram-positive organisms, particularly methicillin-resistant Staphylococcus aureus (MRSA), coagulase-negative staphylococci, and ampicillin-resistant Enterococcus species in adult and pediatric patients. Currently, there is no consensus on optimal dosing and monitoring of vancomycin in neonates. Different vancomycin dosing regimens exist for neonates, but with many of these regimens, obtaining therapeutic trough concentrations can be difficult. In 2011, the Infectious Diseases Society of America recommended vancomycin trough concentrations of 15 to 20 mg/L or an AUC/MIC ratio of ≥400 for severe invasive diseases (e.g., MRSA) in adult and pediatric patients. Owing to recent reports of increased risk of nephrotoxicity associated with vancomycin trough concentrations of 15 to 20 mg/L and AUC/MIC of ≥400, a revised consensus guideline, recently published in 2020, no longer recommends monitoring vancomycin trough concentrations in adult patients. The guideline recommends an AUC/MIC of 400 to 600, which has been found to achieve clinical efficacy while reducing nephrotoxicity. However, these recommendations were derived solely from adult literature, as there are limited clinical outcomes data in pediatric and neonatal patients. Furthermore, owing to the variation of vancomycin pharmacokinetic parameters among the neonatal population, these recommendations for achieving vancomycin AUC/MIC of 400 to 600 in neonates require further investigation. This review will discuss the challenges of achieving optimal vancomycin dosing and monitoring in neonatal patients.

Antibiotic-related adverse events in paediatrics: unique characteristics

Introduction: Antibiotics have saved and are still saving countless human lives from the burden of infectious diseases. However, as with all other drugs, they can cause adverse events. Generally, these are uncommon, mild and spontaneously resolving. However, in some cases, they can cause relevant clinical problems. Compared with adults, children, particularly in the first years of life, have a higher risk of antibiotic-related adverse events for several reasons. Areas covered: In this paper, the conditions that can contribute to the elevated risk of antibiotic-related adverse events in children are discussed. Expert opinion: Antibiotic stewardship can be a solution to limit antibiotic abuse and misuse and consequently the incidence of antibiotic-related adverse events in children. Moreover, most of the antibiotic-associated adverse events can be avoided with more extensive pre-marketing medicine investigations, improved postmarket safety surveillance system, increased transparency throughout the clinical research enterprise, increased training of clinical pharmacologists and paediatric researchers, expanded pool of paediatric patients, and providing additional funding and incentives for paediatric drug development.

Revising Pediatric Vancomycin Dosing Accounting for Nephrotoxicity in a Pharmacokinetic-Pharmacodynamic Model

This study aimed to suggest an initial pediatric vancomycin dose regimen through population pharmacokinetic-pharmacodynamic modeling. A population pharmacokinetic approach was used to analyze vancomycin concentration-time data from a large pediatric cohort. Pharmacokinetic target attainment for patients with bloodstream isolates was compared with clinical outcome using logistic regression and classification and regression trees. Change in serum creatinine during treatment was used as an indicator of acute nephrotoxicity. Probability of acute kidney injury (50% increase from baseline) or kidney failure (75% increase from baseline) was evaluated using logistic regression. An initial dosing regimen was derived, personalized by age, weight, and serum creatinine, using stochastic simulations. Data from 785 hospitalized pediatric patients (1 day to 21 years of age) with suspected Gram-positive infections were collected. Estimated (relative standard error) typical clearance, volume of distribution 1, intercompartmental clearance, and volume of distribution 2 were (standardized to 70 kg) 4.84 (2.38) liters/h, 39.9 (8.15) liters, 3.85 (17.3) liters/h, and 37.8 (10.2) liters, respectively. While cumulative vancomycin exposure correlated positively with the development of nephrotoxicity (713 patients), no clear relationship between vancomycin area under the plasma concentration-time curve and efficacy was found (102 patients). Predicted probability of acute kidney injury and kidney failure with the optimized dosing regimen at day 5 was 10 to 15% and 5 to 10%, increasing by approximately 50% on day 7 and roughly 100% on day 10 across all age groups. This study presents the first data-driven pediatric dose selection to date accounting for nephrotoxicity, and it indicates that cumulative vancomycin exposure best describes risk of acute kidney injury and acute kidney failure.

What Does it Take to Make Model-Informed Precision Dosing Common Practice? Report from the 1st Asian Symposium on Precision Dosing

Model-informed precision dosing (MIPD) is modeling and simulation in healthcare to predict the drug dose for a given patient based on their individual characteristics that is most likely to improve efficacy and/or lower toxicity in comparison to traditional dosing. This paper describes the background and status of MIPD and the activities at the 1st Asian Symposium of Precision Dosing. The theme of the meeting was the question, "What does it take to make MIPD common practice?" Formal presentations highlighted the distinction between genetic and non-genetic sources of variability in drug exposure and response, the use of modeling and simulation as decision support tools, and the facilitators to MIPD implementation. A panel discussion addressed the types of models used for MIPD, how the pharmaceutical industry views MIPD, ways to upscale MIPD beyond academic hospital centers, and the essential role of healthcare professional education as a way to progress. The meeting concluded with an ongoing commitment to use MIPD to improve patient care.