Pharmacometric Approaches to Personalize Use of Primarily Renally Eliminated Antibiotics in Preterm and Term Neonates

Antibiotics, Analgesic Sedatives, and Antiseizure Medications Frequently Used in Critically Ill Neonates: A Narrative Review

Antibiotic, analgesic sedative, and antiseizure medications are among the most commonly used medications in preterm/sick neonates, who are at high risk of nosocomial infections, central nervous system complications, and are exposed to numerous painful/stressful procedures. These severe and potentially life-threatening complications may have serious short- and long-term consequences and should be prevented and/or promptly treated. The reported variability in the medications used in neonates indicates the lack of adequate neonatal studies regarding their effectiveness and safety. Important obstacles contributing to inadequate studies in preterm/sick infants include difficulties in obtaining parental consent, physicians' unwillingness to recruit preterm infants, the off-label use of many medications in neonates, and other scientific and ethical concerns. This review is an update on the use of antimicrobials (antifungals), analgesics (sedatives), and antiseizure medications in neonates, focusing on current evidence or knowledge gaps regarding their pharmacokinetics, indications, safety, dosage, and evidence-based guidelines for their optimal use in neonates. We also address the effects of early antibiotic use on the intestinal microbiome and its association with long-term immune-related diseases, obesity, and neurodevelopment (ND). Recommendations for empirical treatment and the emergence of pathogen resistance to antimicrobials and antifungals are also presented. Finally, future perspectives on the prevention, modification, or reversal of antibiotic resistance are discussed.

Enhanced sensitivity of extracellular antibiotic resistance genes (ARGs) to environmental concentrations of antibiotic

As emerging contaminants, antibiotics are frequently present in various environments, particularly rivers, albeit often at sublethal concentrations (ng/L∼μg/L). Assessing the risk associated with these low levels, which are far below the lethal threshold for most organisms, remains challenging. In this study, using microcosms containing planktonic bacteria and biofilm, we examined how antibiotic resistance genes (ARGs) in different physical states, including intracellular ARGs (iARGs) and extracellular ARGs (eARGs) responded to these low-level antibiotics. Our findings reveal a positive correlation between sub-lethal antibiotic exposure (ranging from 0.1 to 10 μg/L) and increased prevalence (measured as ARG copies/16s rDNA) of both iARGs and eARGs in planktonic bacteria. Notably, eARGs demonstrated greater sensitivity to antibiotic exposure compared to iARGs, with a lower threshold (0.1 μg/L for eARGs versus 1 μg/L for iARGs) for abundance increase. Moreover, ARGs in biofilms demonstrates higher sensitivity to antibiotic exposure compared to planktonic bacteria. To elucidate the underlying mechanisms, we established an integrated population dynamics-pharmacokinetics-pharmacodynamics (PD-PP) model. This model indicates that the enhanced sensitivity of eARGs is primarily driven by an increased potential for plasmid release from cells under low antibiotic concentrations. Furthermore, the accumulation of antibiotic in biofilms induces a greater sensitivity of ARG compared to the planktonic bacteria. This study provides a fresh perspective on the development of antibiotic resistance and offers an innovative approach for assessing the risk of sublethal antibiotic in the environment.

Pharmaceutical interventions for drug-related problems in the neonatal intensive care unit: incidence, types, and acceptability

Background: Drug-related problems (DRPs) are widespread in hospitalized neonates, but studies on the prevalence of DRPs in this population are limited. The presence of clinical pharmacists on multidisciplinary teams helps prevent and reduce DRPs. Aim: This investigation aimed to identify and classify the incidence of DRPs in the neonatal intensive care unit (NICU), to determine the determining factors associated with DRPs and to document clinical pharmacists' interventions, outcomes, acceptance rates and clinical significance. Method: A prospective descriptive hospital study was conducted from August to November 2023 at the NICU of Children's University Hospital, Assiut University, Egypt. DRPs were classified using the Pharmaceutical Care Network of Europe (PCNE) classification V9.1. Results: Three hundred sixteen neonates were included in the study, with a mean gestational age of 34 ± 4 weeks and a mean birth weight of 2.03 ± 0.85 kg. A total of 1723 DRPs occurred among 283 neonates (89.6%), an average of 5.5 ± 5.1 DRPs per patient. The main types were treatment effectiveness (P1) (799, 46.4%), followed by others (P3) (469, 27.2%), and treatment safety (P2) (455, 26.4%). The leading causes were dose selection (C3) (1264, 61.9%) and "other domain" (C9) (543, 26.6%). Of the 2149 interventions introduced by pharmacists, 98.8% were accepted and 93% were accepted, and fully implemented. As a result, 92% of the DRPs were resolved. Both length of hospital stay and number of medications were significantly associated with DRPs. Conclusion: DRPs are common in the NICU; this study demonstrated the crucial role of clinical pharmacists in identifying and resolving DRPs.

Pharmacometric in silico studies used to facilitate a national dose standardisation process in neonatology - application to amikacin

BACKGROUND AND AIMS

Pharmacometric in silico approaches are frequently applied to guide decisions concerning dosage regimes during the development of new medicines. We aimed to demonstrate how such pharmacometric modelling and simulation can provide a scientific rationale for optimising drug doses in the context of the Swiss national dose standardisation project in paediatrics using amikacin as a case study.

METHODS

Amikacin neonatal dosage is stratified by post-menstrual age (PMA) and post-natal age (PNA) in Switzerland and many other countries. Clinical concerns have been raised for the subpopulation of neonates with a post-menstrual age of 30-35 weeks and a post-natal age of 0-14 days ("subpopulation of clinical concern"), as potentially oto-/nephrotoxic trough concentrations (Ctrough >5 mg/l) were observed with a once-daily dose of 15 mg/kg. We applied a two-compartmental population pharmacokinetic model (amikacin clearance depending on birth weight and post-natal age) to real-world demographic data from 1563 neonates receiving anti-infectives (median birth weight 2.3 kg, median post-natal age six days) and performed pharmacometric dose-exposure simulations to identify extended dosing intervals that would ensure non-toxic Ctrough (Ctrough <5 mg/l) dosages in most neonates.

RESULTS

In the subpopulation of clinical concern, Ctrough <5 mg/l was predicted in 59% versus 79-99% of cases in all other subpopulations following the current recommendations. Elevated Ctrough values were associated with a post-natal age of less than seven days. Simulations showed that extending the dosing interval to ≥36 h in the subpopulation of clinical concern increased the frequency of a desirable Ctrough below 5 mg/l to >80%.

CONCLUSION

Pharmacometric in silico studies using high-quality real-world demographic data can provide a scientific rationale for national paediatric dose optimisation. This may increase clinical acceptance of fine-tuned standardised dosing recommendations and support their implementation, including in vulnerable subpopulations.

Foetal and neonatal exposure prediction and dosing evaluation for ampicillin using a physiologically-based pharmacokinetic modelling approach

AIMS

Ampicillin is frequently used in neonates for the treatment of sepsis and as an intrapartum prophylaxis option for Group B Streptococcus. Pharmacokinetic data to guide ampicillin dosing in neonates and during the intrapartum period are limited. The objective of this study was to build a physiologically-based pharmacokinetic (PBPK) model to characterize the disposition of ampicillin in neonates and foetuses and to inform corresponding optimal dosing regimens.

METHODS

An adult ampicillin PBPK model was first developed using the Simcyp® simulator. The adult model was then scaled to neonates by accounting for maturational changes in physiological parameters and age-dependent drug disposition or extended to a pregnancy model for mothers and foetuses. Models were verified using collected mean or individual-level concentration data from the literature.

RESULTS

The developed adult PBPK model included elimination via glomerular filtration, OAT3-mediated tubular secretion and biliary excretion as well as hepatic metabolism, and 89.8% of the observed mean concentrations in adults were within a 2-fold range of model mean predictions. Most of the observed individual-level observations in neonates (78.4%) and foetuses (about 65% in two studies) were within the 90% prediction intervals. The recommended 50 mg/kg every 8 h (q8h) ampicillin regimen achieved the 75% fraction time of total drug concentration above minimum inhibitory concentration (T > MIC) target for an MIC ≤8 mg/L in >90% virtual neonates, and 1 g ampicillin for pregnant women provided adequate foetal exposure (>0.25 mg/L) for 4 h prior to delivery.

CONCLUSIONS

A PBPK model was developed to characterize ampicillin's disposition in neonates, pregnant women, and foetuses, and the model supported optimal dosing evaluation in these vulnerable populations.

Strategies for Improving Vascularization in Kidney Organoids: A Review of Current Trends

Kidney organoids possess the potential to revolutionize the treatment of renal diseases. However, their growth and maturation are impeded by insufficient growth of blood vessels. Through a PubMed search, we have identified 34 studies that attempted to address this challenge. Researchers are exploring various approaches including animal transplantation, organ-on-chips, and extracellular matrices (ECMs). The most prevalent method to promote the maturation and vascularization of organoids involves transplanting them into animals for in vivo culture, creating an optimal environment for organoid growth and the development of a chimeric vessel network between the host and organoids. Organ-on-chip technology permits the in vitro culture of organoids, enabling researchers to manipulate the microenvironment and investigate the key factors that influence organoid development. Lastly, ECMs have been discovered to aid the formation of blood vessels during organoid differentiation. ECMs from animal tissue have been particularly successful, although the underlying mechanisms require further research. Future research building upon these recent studies may enable the generation of functional kidney tissues for replacement therapies.

Clinically practical pharmacometrics computer model to evaluate and personalize pharmacotherapy in pediatric rare diseases: application to Graves' disease

Objectives

Graves' disease (GD) with onset in childhood or adolescence is a rare disease (ORPHA:525731). Current pharmacotherapeutic approaches use antithyroid drugs, such as carbimazole, as monotherapy or in combination with thyroxine hormone substitutes, such as levothyroxine, as block-and-replace therapy to normalize thyroid function and improve patients' quality of life. However, in the context of fluctuating disease activity, especially during puberty, a considerable proportion of pediatric patients with GD is suffering from thyroid hormone concentrations outside the therapeutic reference ranges. Our main goal was to develop a clinically practical pharmacometrics computer model that characterizes and predicts individual disease activity in children with various severity of GD under pharmacotherapy.

Methods

Retrospectively collected clinical data from children and adolescents with GD under up to two years of treatment at four different pediatric hospitals in Switzerland were analyzed. Development of the pharmacometrics computer model is based on the non-linear mixed effects approach accounting for inter-individual variability and incorporating individual patient characteristics. Disease severity groups were defined based on free thyroxine (FT4) measurements at diagnosis.

Results

Data from 44 children with GD (75% female, median age 11 years, 62% receiving monotherapy) were analyzed. FT4 measurements were collected in 13, 15, and 16 pediatric patients with mild, moderate, or severe GD, with a median FT4 at diagnosis of 59.9 pmol/l (IQR 48.4, 76.8), and a total of 494 FT4 measurements during a median follow-up of 1.89 years (IQR 1.69, 1.97). We observed no notable difference between severity groups in terms of patient characteristics, daily carbimazole starting doses, and patient years. The final pharmacometrics computer model was developed based on FT4 measurements and on carbimazole or on carbimazole and levothyroxine doses involving two clinically relevant covariate effects: age at diagnosis and disease severity.

Discussion

We present a tailored pharmacometrics computer model that is able to describe individual FT4 dynamics under both, carbimazole monotherapy and carbimazole/levothyroxine block-and-replace therapy accounting for inter-individual disease progression and treatment response in children and adolescents with GD. Such clinically practical and predictive computer model has the potential to facilitate and enhance personalized pharmacotherapy in pediatric GD, reducing over- and underdosing and avoiding negative short- and long-term consequences. Prospective randomized validation trials are warranted to further validate and fine-tune computer-supported personalized dosing in pediatric GD and other rare pediatric diseases.

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.

Leveraging Predictive Pharmacometrics-Based Algorithms to Enhance Perinatal Care-Application to Neonatal Jaundice

The field of medicine is undergoing a fundamental change, transforming towards a modern data-driven patient-oriented approach. This paradigm shift also affects perinatal medicine as predictive algorithms and artificial intelligence are applied to enhance and individualize maternal, neonatal and perinatal care. Here, we introduce a pharmacometrics-based mathematical-statistical computer program (PMX-based algorithm) focusing on hyperbilirubinemia, a medical condition affecting half of all newborns. Independent datasets from two different centers consisting of total serum bilirubin measurements were utilized for model development (342 neonates, 1,478 bilirubin measurements) and validation (1,101 neonates, 3,081 bilirubin measurements), respectively. The mathematical-statistical structure of the PMX-based algorithm is a differential equation in the context of non-linear mixed effects modeling, together with Empirical Bayesian Estimation to predict bilirubin kinetics for a new patient. Several clinically relevant prediction scenarios were validated, i.e., prediction up to 24 h based on one bilirubin measurement, and prediction up to 48 h based on two bilirubin measurements. The PMX-based algorithm can be applied in two different clinical scenarios. First, bilirubin kinetics can be predicted up to 24 h based on one single bilirubin measurement with a median relative (absolute) prediction difference of 8.5% (median absolute prediction difference 17.4 μmol/l), and sensitivity and specificity of 95.7 and 96.3%, respectively. Second, bilirubin kinetics can be predicted up to 48 h based on two bilirubin measurements with a median relative (absolute) prediction difference of 9.2% (median absolute prediction difference 21.5 μmol/l), and sensitivity and specificity of 93.0 and 92.1%, respectively. In contrast to currently available nomogram-based static bilirubin stratification, the PMX-based algorithm presented here is a dynamic approach predicting individual bilirubin kinetics up to 48 h, an intelligent, predictive algorithm that can be incorporated in a clinical decision support tool. Such clinical decision support tools have the potential to benefit perinatal medicine facilitating personalized care of mothers and their born and unborn infants.

Population pharmacokinetics and dosing optimization of mezlocillin in neonates and young infants

OBJECTIVES

Mezlocillin is used in the treatment of neonatal infectious diseases. However, due to the absence of population pharmacokinetic studies in neonates and young infants, dosing regimens differ considerably in clinical practice. Hence, this study aimed to describe the pharmacokinetic characteristics of mezlocillin in neonates and young infants, and propose the optimal dosing regimen based on the population pharmacokinetic model of mezlocillin.

METHODS

A prospective, open-label pharmacokinetic study of mezlocillin was carried out in newborns. Blood samples were collected using an opportunistic sampling method. HPLC was used to measure the plasma drug concentrations. A population pharmacokinetic model was developed using NONMEM software.

RESULTS

Ninety-five blood samples from 48 neonates and young infants were included. The ranges of postmenstrual age and birth weight were 29-40 weeks and 1200-4000 g, respectively, including term and preterm infants. A two-compartment model with first-order elimination was developed to describe the population pharmacokinetics of mezlocillin. Postmenstrual age, current weight and serum creatinine concentration were the most important covariates. Monte Carlo simulation results indicated that the current dose of 50 mg/kg q12h resulted in 89.2% of patients achieving the therapeutic target, when the MIC of 4 mg/L was used as the breakpoint. When increasing the dosing frequency to q8h, a dose of 20 mg/kg resulted in 74.3% of patients achieving the therapeutic target.

CONCLUSIONS

A population pharmacokinetic model of mezlocillin in neonates and young infants was established. Optimal dosing regimens based on this model were provided for use in neonatal infections.

Optimal Teicoplanin Dosing Regimen in Neonates and Children Developed by Leveraging Real-World Clinical Information

BACKGROUND

Teicoplanin is a glycopeptide antibiotic used for the treatment of methicillin-resistant Staphylococcus aureus infections. To ensure successful target attainment, therapeutic drug monitoring-informed dosage adjustment is recommended. However, it relies on the experience of the clinician and the frequency of drug measurements. This study aimed to design a new optimal dosing regimen of teicoplanin with a maintenance dosing strategy for neonates and children based on their physiological characteristics.

METHODS

Data from teicoplanin-treated patients (n = 214) were collected from electronic medical records. Covariate analyses were performed using population pharmacokinetic (PK) modeling with 399 serum teicoplanin concentrations from 48 neonates and 166 children. Multiple PK simulations were conducted to explore optimal dosing regimens that would allow control of the trough concentration to the target of 15-30 mg/L quicker than the current standard regimen.

RESULTS

Allometrically scaled body weight, postmenstrual age (PMA), renal function, and serum albumin were implemented as substantial covariates for teicoplanin clearance in a two-compartment PK model. Covariate analyses and comprehensive simulation assessments recommended the following modifications to the current regimen: (1) decreased dose for premature babies (PMA ≤28 weeks), (2) decreased dose for children with renal dysfunction, and (3) increased dose for children (0.5-11 years) with an estimated glomerular filtration rate of ≥90 mL/min/1.73 m2.

CONCLUSIONS

This study leverages real-world clinical information and proposes new optimal dosing regimens for teicoplanin in neonates and children through PK modeling and simulation analyses, taking into account the age, including PMA, and renal function of patients.

Challenges and opportunities for improving access to approved neonatal drugs and devices

Neonatal drug and device development has lagged behind other patient populations. Oftentimes, providers are using drugs and devices without adequate study of safety and efficacy. Neonates deserve dedicated drug and device development programs, which will require novel approaches and unique collaborations between multiple key stakeholders. Legislative efforts, infrastructure, clinical trial methodology, and international collaborations have all contributed to improvements in neonatal drug and device development, but more work is still needed. Leadership from neonatologists, clinical care providers, and parents is essential to implement needed changes.

Pharmacokinetics of Antibiotics in Pediatric Intensive Care: Fostering Variability to Attain Precision Medicine

Children show important developmental and maturational changes, which may contribute greatly to pharmacokinetic (PK) variability observed in pediatric patients. These PK alterations are further enhanced by disease-related, non-maturational factors. Specific to the intensive care setting, such factors include critical illness, inflammatory status, augmented renal clearance (ARC), as well as therapeutic interventions (e.g., extracorporeal organ support systems or whole-body hypothermia [WBH]). This narrative review illustrates the relevance of both maturational and non-maturational changes in absorption, distribution, metabolism, and excretion (ADME) applied to antibiotics. It hereby provides a focused assessment of the available literature on the impact of critical illness—in general, and in specific subpopulations (ARC, extracorporeal organ support systems, WBH)—on PK and potential underexposure in children and neonates. Overall, literature discussing antibiotic PK alterations in pediatric intensive care is scarce. Most studies describe antibiotics commonly monitored in clinical practice such as vancomycin and aminoglycosides. Because of the large PK variability, therapeutic drug monitoring, further extended to other antibiotics, and integration of model-informed precision dosing in clinical practice are suggested to optimise antibiotic dose and exposure in each newborn, infant, or child during intensive care.

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.

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.

Population pharmacokinetics and dosing optimization of azlocillin in neonates with early-onset sepsis: a real-world study

OBJECTIVES

Nowadays, real-world data can be used to improve currently available dosing guidelines and to support regulatory approval of drugs for use in neonates by overcoming practical and ethical hurdles. This proof-of-concept study aimed to assess the population pharmacokinetics of azlocillin in neonates using real-world data, to make subsequent dose recommendations and to test these in neonates with early-onset sepsis (EOS).

METHODS

This prospective, open-label, investigator-initiated study of azlocillin in neonates with EOS was conducted using an adaptive two-step design. First, a maturational pharmacokinetic-pharmacodynamic model of azlocillin was developed, using an empirical dosing regimen combined with opportunistic samples resulting from waste material. Second, a Phase II clinical trial (ClinicalTrials.gov: NCT03932123) of this newly developed model-based dosing regimen of azlocillin was conducted to assure optimized target attainment [free drug concentration above MIC during 70% of the dosing interval ('70% fT>MIC')] and to investigate the tolerance and safety in neonates.

RESULTS

A one-compartment model with first-order elimination, using 167 azlocillin concentrations from 95 neonates (31.7-41.6 weeks postmenstrual age), incorporating current weight and renal maturation, fitted the data best. For the second step, 45 neonates (30.3-41.3 weeks postmenstrual age) were subsequently included to investigate target attainment, tolerance and safety of the pharmacokinetic-pharmacodynamic model-based dose regimen (100 mg/kg q8h). Forty-three (95.6%) neonates reached their pharmacokinetic target and only two neonates experienced adverse events (feeding intolerance and abnormal liver function), possibly related to azlocillin.

CONCLUSIONS

Target attainment, tolerance and safety of azlocillin was shown in neonates with EOS using a pharmacokinetic-pharmacodynamic model developed with real-world data.

Progress in Drug Development-Pediatric Dose Selection: Workshop Summary

The "Pediatric Dose Selection" workshop was held in October 2020 and sponsored by the U.S. Food and Drug Administration and the University of Maryland Center for Excellence in Regulatory Science and Innovation. A summary of the presentations in the context of pediatric drug development is summarized in this article.

Considerations for Drug Dosing in Premature Infants

In premature infants, effective and safe drug therapy depends on optimal dose selection and requires a thorough understanding of the underlying disease(s) of these fragile infants as well as the pharmacokinetics and pharmacodynamics of the drugs selected to treat their diseases. Differences in gestational and postnatal age or weight are the major determinants of the observed variability in drug disposition and effect in these infants. This article presents an outline on how to translate the results of a population pharmacokinetic/pharmacodynamic study into rational dosing regimens, and how physiologically based pharmacokinetic modeling, electronic health records, and the abundantly available data of vital functions of premature infants during their stay in the neonatal intensive care unit for evaluation of their pharmacotherapy can be used to tailor the most safe and effective dose in these infants.

Drug Clearance in Neonates: A Combination of Population Pharmacokinetic Modelling and Machine Learning Approaches to Improve Individual Prediction

BACKGROUND

Population pharmacokinetic evaluations have been widely used in neonatal pharmacokinetic studies, while machine learning has become a popular approach to solving complex problems in the current era of big data.

OBJECTIVE

The aim of this proof-of-concept study was to evaluate whether combining population pharmacokinetic and machine learning approaches could provide a more accurate prediction of the clearance of renally eliminated drugs in individual neonates.

METHODS

Six drugs that are primarily eliminated by the kidneys were selected (vancomycin, latamoxef, cefepime, azlocillin, ceftazidime, and amoxicillin) as 'proof of concept' compounds. Individual estimates of clearance obtained from population pharmacokinetic models were used as reference clearances, and diverse machine learning methods and nested cross-validation were adopted and evaluated against these reference clearances. The predictive performance of these combined methods was compared with the performance of two other predictive methods: a covariate-based maturation model and a postmenstrual age and body weight scaling model. Relative error was used to evaluate the different methods.

RESULTS

The extra tree regressor was selected as the best-fit machine learning method. Using the combined method, more than 95% of predictions for all six drugs had a relative error of < 50% and the mean relative error was reduced by an average of 44.3% and 71.3% compared with the other two predictive methods.

CONCLUSION

A combined population pharmacokinetic and machine learning approach provided improved predictions of individual clearances of renally cleared drugs in neonates. For a new patient treated in clinical practice, individual clearance can be predicted a priori using our model code combined with demographic data.

An Ensemble Model for Prediction of Vancomycin Trough Concentrations in Pediatric Patients

Purpose

This study aimed to establish an optimal model to predict vancomycin trough concentrations by using machine learning.

Patients and Methods

We enrolled 407 pediatric patients (age < 18 years) who received vancomycin intravenously and underwent therapeutic drug monitoring from June 2013 to April 2020 at Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine. The median (interquartile range) age and weight of the patients were 2 (0.63–5) years and 12 (7.8–19) kg. Vancomycin trough concentrations were considered as the target variable, and eight different algorithms were used for predictive performance comparison. The whole dataset (407 cases) was divided into training group and testing group at the ratio of 80%: 20%, which were 325 and 82 cases, respectively.

Results

Ultimately, five algorithms (XGBoost, GBRT, Bagging, ExtraTree and decision tree) with high R² (0.657, 0.514, 0.468, 0.425 and 0.450, respectively) were selected and further ensembled to establish the final model and achieve an optimal result. For missing data, through filling the missing values and model ensemble, we obtained R²=0.614, MAE=3.32, MSE=24.39, RMSE=4.94 and a prediction accuracy of 51.22% (predicted trough concentration within ±30% of the actual trough concentration). In comparison with the pharmacokinetic models (R²=0.3), the machine learning model works better in model fitting and has better prediction accuracy.

Conclusion

Therefore, the ensemble model is useful for the vancomycin concentration prediction, especially in the population of children with great individual variation. As machine learning methods evolve, the clinical value of the ensemble model will be demonstrated in the clinical practice.

Serum Creatinine and Serum Cystatin C are Both Relevant Renal Markers to Estimate Vancomycin Clearance in Critically Ill Neonates

Purpose: Serum creatinine (SCr) is used as a marker of kidney function to guide dosing of renally eliminated drugs. Serum Cystatin C (S-CysC) has been suggested as a more reliable kidney marker than SCr in adults and children. Purpose of this study was to investigate S-CysC as alternative renal marker to SCr for estimating vancomycin clearance in neonates undergoing intensive care.

Methods: Vancomycin pharmacokinetics (PK), SCr and S-CysC data were collected in patients undergoing vancomycin treatment in the neonatal intensive care unit of Robert Debré Hospital - Paris. A population PK analysis was performed utilizing routine therapeutic drug monitoring samples. S-CysC and SCr were compared as covariates on vancomycin clearance using stepwise covariate modeling (forward inclusion [p < 0.05] and backward elimination [p < 0.01]). Model performance was evaluated by graphical and statistical criteria.

Results: A total of 108 vancomycin concentrations from 66 patients (postmenstrual age [PMA] of 26–46 weeks) were modeled with an allometric one-compartment model. The median (range) values for SCr and S-CysC were 41 (12–153) µmol/l and 1.43 (0.95–2.83) mg/l, respectively. Following stepwise covariate model building, SCr was retained as single marker of kidney function (after accounting for weight and PMA) in the final model. Compared to the final model based on SCr, the alternative model based on S-CysC showed very similar performance (e.g. BIC of 578.3 vs. 576.4) but included one additional covariate: impact of mechanical ventilation on vancomycin clearance, in addition to the effects of size and maturation.

Conclusion: ill neonates. However, if using S-CysC for this purpose mechanical ventilation needs to be taken into account.

Combatting the Rising Tide of Antimicrobial Resistance: Pharmacokinetic/Pharmacodynamic Dosing Strategies for Maximal Precision

OBJECTIVE

Antimicrobial pharmacokinetics/pharmacodynamics (PK/PD) principles and PK/PD models have been essential in characterizing the mechanism of antibiotic bacterial killing and determining the most optimal dosing regimen that maximizes clinical outcomes. This review summarized the fundamentals of antimicrobial PK/PD and the various types of PK/PD experiments that shaped the utilization and dosing strategies of antibiotics today.

METHODS

Multiple databases - including PubMed, Scopus, and EMBASE - were searched for published articles that involved PK/PD modelling and precision dosing. Data from in vitro, in vivo and mechanistic PK/PD models were reviewed as a basis for compiling studies that guide dosing regimens used in clinical trials.

RESULTS

Literature regarding the utilization of exposure-response analyses, mathematical modelling and simulations that were summarized are able to provide a better understanding of antibiotic pharmacodynamics that influence translational drug development. Optimal pharmacokinetic sampling of antibiotics from patients can lead to personalized dosing regimens that attain target concentrations while minimizing toxicity. Thus the development of a fully integrated mechanistic model based on systems pharmacology can continually adapt to data generated from clinical responses, which can provide the framework for individualized dosing regimens.

CONCLUSIONS

The promise of what PK/PD can provide through precision dosing for antibiotics has not been fully realized in the clinical setting. Antimicrobial resistance, which has emerged as a significant public health threat, has forced clinicians to empirically utilize therapies. Future research focused on implementation and translation of PK/PD-based approaches integrating novel approaches that combine knowledge of combination therapies, systems pharmacology and resistance mechanisms are necessary. To fully realize maximally precise therapeutics, optimal PK/PD strategies are critical to maximize antimicrobial efficacy against extremely-drug-resistant organisms, while minimizing toxicity.

Population Pharmacokinetic Analysis and Dose Regimen Optimization in Japanese Infants with an Extremely Low Birth Weight

Vancomycin is a synthetic antibiotic effective against Gram-positive pathogens. Although the clinical applicability of vancomycin for infants has been increasing, the pharmacokinetic data for vancomycin in extremely low-birth-weight infants are limited. The aim of this study was to construct a population pharmacokinetics model for vancomycin in extremely-low-birth-weight infants and establish an optimal dosage regimen. We enrolled children aged less than 1 year with a birth weight of less than 1,000 g and body weight at vancomycin prescription of less than 1,500 g. Pharmacokinetic data from 19 patients were analyzed, and a population pharmacokinetics model was developed using nonlinear mixed-effects modeling software. Goodness-of-fit plots, a nonparametric bootstrap analysis, and a prediction-corrected visual predictive check were employed to evaluate the final model. The dosage regimen was optimized based on the final model. The pharmacokinetic data fit a one-compartment model with first-order elimination, and body weight and estimated serum creatinine level were used as significant covariates. In a simulation using the final model, the optimal dosage regimen, especially when the serum creatinine level (>0.6 mg/dl) was high, was 5.0 to 7.5 mg/kg of body weight twice a day every 12 h; this was required to reduce the dosage compared with that in previous studies. The recommended doses based on the current target time course concentration curves may not be appropriate for extremely-low-birth-weight infants.

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.

Population Pharmacokinetics and Dosing Optimization of Amoxicillin in Chinese Infants

Amoxicillin is used to treat various bacterial infections (eg, pneumonia, sepsis, meningitis) in infants. Despite its frequent use, there is a lack of population pharmacokinetic studies in infants, resulting in a substantial variability in dosing regimens used in clinical practice. Therefore, the objective of this study was to evaluate the population pharmacokinetics of intravenous amoxicillin in infants and suggest an optimal dosage regimen. Blood samples were collected for the determination of amoxicillin concentrations using an opportunistic sampling strategy. The amoxicillin plasma concentrations were determined using high-performance liquid chromatography. Population pharmacokinetic analysis was performed using NONMEM. A total of 62 pharmacokinetic samples from 47 infants (age range, 0.09 to 2.0 years) were available for analysis. A 2-compartment model with first-order elimination was most suitable to describe the population pharmacokinetics of amoxicillin, and covariate analysis showed that only current body weight was a significant covariate. Monte Carlo simulation demonstrated that the currently used dosage regimen (25 mg/kg twice daily) resulted in only 22.4% of infants reaching their pharmacodynamic target, using a minimum inhibitory concentration (MIC) break point of 2 mg/L, whereas a dosage regimen (60 mg/kg thrice daily), as supported by the British National Formulary for Children, resulted in 80.9% of infants achieving their pharmacodynamic target. It is recommended to change antibiotics for infections caused by Escherichia coli (MIC = 8.0 mg/L) because only 27.9% of infants reached target using 60 mg/kg thrice daily.

Pediatric Renal Ontogeny and Applications in Drug Development

The clinical applications of renal ontogeny mainly include renal function evaluation and optimal dosing of renally eliminated drugs in pediatric patients, which rely on pharmacometric models and/or bedside estimated glomerular filtration rate equations. However, these applications in drug development are based on an understanding of renal function development, especially when considering premature infants, and the renal biomarkers that can be used for renal function assessment. This review provides a general overview on (1) renal function development, (2) the biomarkers that are used to assess renal function, and (3) the practical application of this knowledge to drug dosing for renally eliminated drugs during pediatric development. While pharmacometric approaches for estimating renal function during development have improved considerably, the number of drug development programs that have studied premature infants is small and suggests that caution should be taken in estimating doses for renally eliminated drugs during periods of rapid change in renal function.

Age-Dependent Changes of Kidney Injury Biomarkers in Pediatrics

Currently used creatinine-based parameters for monitoring kidney function are not reliable for early detection of kidney injury (KI), particularly tubular damage. Several KI biomarkers allow for early detection of glomerular and tubular damage and may help to prevent drug-related chronic kidney diseases in pediatrics. This literature review describes the state of current research and investigates reference values for these KI biomarkers in neonates, infants, and children to better understand age-related changes. A total of 12 of 237 screened studies fulfilled predefined criteria, including 219 preterm neonates, 70 neonates, 596 infants, and 1726 children. KI biomarkers were analyzed in urine (6 studies), in serum/plasma (5 studies) and in serum and urine (1 study). Four studies (n = 555) measured urinary kidney injury molecule-1, whereas urinary neutrophil gelatinase-associated lipocalin was assessed in 5 studies (n = 888), and 2 studies (n = 203) investigated serum cystatin C. This review of KI biomarkers in different pediatric age groups indicates that (1) the majority of KI biomarkers are measured in urine; (2) the 3 most commonly analyzed KI biomarkers are urinary neutrophil gelatinase-associated lipocalin, urinary kidney injury molecule-1, and serum cystatin C; (3) values of KI biomarkers appear to decrease from prematurity to infancy; and (4) there is an unmet need to further enhance knowledge on age-dependent changes of KI biomarkers in pediatrics. Studies are needed to better characterize reference values for these key KI biomarkers in healthy pediatric populations and to evaluate the value of these markers in the early detection of drug-related KI in neonates, infants, and children.

Towards Personalized Antithrombotic Treatments: Focus on P2Y12 Inhibitors and Direct Oral Anticoagulants

Oral anticoagulants and antiplatelet drugs are commonly prescribed to lower the risk of cardiovascular diseases, such as venous and arterial thrombosis, which represent the leading causes of mortality worldwide. A significant percentage of patients taking antithrombotics will nevertheless experience bleeding or recurrent ischemic events, and this represents a major public health issue. Cardiovascular medicine is now questioning the one-size-fits-all policy, and more personalized approaches are increasingly being considered. However, the available tools are currently limited and they are only moderately able to predict clinical events or have a significant impact on clinical outcomes. Predicting concentrations of antithrombotics in blood could be an effective means of personalization as they have been associated with bleeding and recurrent ischemia. Target concentration interventions could take advantage of physiologically based pharmacokinetic (PBPK) and population-based pharmacokinetic (POPPK) models, which are increasingly used in clinical settings and have attracted the interest of governmental regulatory agencies, to propose dosages adapted to specific population characteristics. These models have the benefit of combining parameters from different sources, such as experimental in vitro data and patients' demographic, genetic, and physiological in vivo data, to characterize the dose-concentration relationships of compounds of interest. As such, they can be used to predict individual drug exposure. In the near future, these models could therefore be a valuable means of predicting personalized antithrombotic blood concentrations and, hopefully, of preventing clinical non-response or bleeding in a given patient. Existing approaches for personalization of antithrombotic prescriptions will be reviewed using practical examples for P2Y₁₂ inhibitors and direct oral anticoagulants. The review will additionally focus on the existing PBPK and POPPK models for these two categories of drugs. Lastly, we address potential scenarios for their implementation in clinics, along with the main limitations and challenges.

The Utility of Pharmacometric Models in Clinical Pharmacology Research in Infants

Purpose of commentary

Acquiring knowledge on drug disposition and action in infant is challenging because of the problem of sparse and unbalanced data obtained for each individual infant due to the limited blood volume as well as the issue of extensive inter-subject and intra-subject variability in drug exposure and response due to the fast growth and dynamic maturation changes in infants. This commentary highlights the importance of using population-based pharmacometric models to improve knowledge on drug disposition and action in infants.

Recent findings

Pharmacometric modeling remains to be critical in clinical pharmacology research in infants. Many pediatric covariate models developed for scaling of drug clearance use a combination of allometric weight scaling to account for size change and a sigmoid function of antenatal development and postnatal maturation to characterize the age-related maturation. To expedite the development of safe and effective dosing regimens in infants, a number of strategies have been proposed recently, including the use of pediatric covariate model obtained from one drug for extrapolation to other drugs undergoing similar elimination pathways, as well as the combination of opportunistic clinical studies and population-based pharmacometrics models.

Summary

Population-based pharmacometric modeling plays a pivotal role in clinical pharmacology research in infants. Most of the covariate models reported so far focus on antibiotics undergoing renal elimination. Novel modeling strategies have been proposed recently to facilitate clinical pharmacology research and expedite the dose optimization process in infants.

Approaches to Dose Finding in Neonates, Illustrating the Variability between Neonatal Drug Development Programs

Drug dosing in neonates should be based on integrated knowledge concerning the disease to be treated, the physiological characteristics of the neonate, and the pharmacokinetics (PK) and pharmacodynamics (PD) of a given drug. It is critically important that all sources of information be leveraged to optimize dose selection for neonates. Sources may include data from adult studies, pediatric studies, non-clinical (juvenile) animal models, in vitro studies, and in silico models. Depending on the drug development program, each of these modalities could be used to varying degrees and with varying levels of confidence to guide dosing. This paper aims to illustrate the variability between neonatal drug development programs for neonatal diseases that are similar to those seen in other populations (meropenem), neonatal diseases related but not similar to pediatric or adult populations (clopidogrel, thyroid hormone), and diseases unique to neonates (caffeine, surfactant). Extrapolation of efficacy from older children or adults to neonates is infrequently used. Even if a disease process is similar between neonates and children or adults, such as with anti-infectives, additional dosing and safety information will be necessary for labeling, recognizing that dosing in neonates is confounded by maturational PK in addition to body size.

DRUG-RELATED PROBLEMS IN CARDIAC NEONATES UNDER INTENSIVE CARE

Objective:

To determine the frequency and nature of the Drug Related Problems (DRP) in neonates with cardiac diseases admitted to an Intensive Care Unit.

Methods:

This prospective cross-sectional study was developed at the Neonatal Intensive Care Unit (NICU) of a teaching maternity hospital in Brazil from January 2014 to December 2016. All neonates diagnosed with any heart disease (congenital heart disease, cardiomyopathy, arrhythmias, etc.) and who were admitted to the NICU for more than 24 hours with at least one prescribed drug were included in the study. Demographic and clinical data were collected from the records of the institution’s clinical pharmacy service. DRP and their respective interventions were independently reviewed and classified by two pharmacists. DRP classification was performed through the Pharmaceutical Care Network Europe v6.2 system.

Results:

122 neonates were included in the study. The frequency of neonates exposed to DRP was 76.4% (confidence interval of 95% [95%CI] 65.9–82.0), with a mean of 3.2±3.8 cases/patient. In total, 390 DRP were identified, of which 49.0% were related to “treatment effectiveness”, 46.7% to “adverse reactions” and 1.0% to “treatment costs”. The medicines most involved in DRP were Vancomycin (10.2%; n=46), Meropenem (8.0%; n=36) and Furosemide (7.1%; n=32). Pharmacists performed 331 interventions, of which 92.1% were accepted by physicians and nurses.

Conclusions:

The study showed that DRP are very frequent in patients with cardiac diseases hospitalized in the NICU, predominating problems related to the effectiveness and safety of the drug treatment.

Oral antibiotics for neonatal infections: a systematic review and meta-analysis

BACKGROUND

Worldwide many neonates suffer from bacterial infections. Adequate treatment is important but is associated with prolonged hospitalization for intravenous administration. In older children, oral switch therapy has been proven effective and safe for several indications and is now standard care.

OBJECTIVES

To evaluate the currently available evidence on pharmacokinetics, safety and efficacy of oral antibiotics and oral switch therapy in neonates (0-28 days old).

METHODS

We performed systematic searches in Medline, Embase.com, Cochrane, Google Scholar and Web of Science. Studies were eligible if they described the use of oral antibiotics in neonates (0-28 days old), including antibiotic switch studies and pharmacological studies.

RESULTS

Thirty-one studies met the inclusion criteria. Compared with parenteral administration, oral antibiotics generally reach their maximum concentration later and have a lower bioavailability, but in the majority of cases adequate serum levels for bacterial killing are reached. Furthermore, studies on efficacy of oral antibiotics showed equal relapse rates (OR 0.95; 95% CI 0.79-1.16; I2 0%) or mortality (OR 1.11; 95% CI 0.72-1.72; I2 0%). Moreover, a reduction in hospital stay was observed.

CONCLUSIONS

Oral antibiotics administered to neonates are absorbed and result in adequate serum levels, judged by MICs of relevant pathogens, over time. Efficacy studies are promising but robust evidence is lacking, most importantly because in many cases clinical efficacy and safety are not properly addressed. Early oral antibiotic switch therapy in neonates could be beneficial for both families and healthcare systems. There is a need for additional well-designed trials in different settings.

Pediatric Age Groups and Approach to Studies

Pediatric clinical trials are often requested according to specific age ranges. In the past and still today, these ages may correspond to developmental stages, such as newborn, infancy, childhood, and adolescence. Selection of ages for pediatric participation in medication studies should correspond to ages of rapid changes in pharmacokinetics and pharmacodynamics. Age-related changes in several enzymes involved in drug metabolism and glomerular filtration are described as examples of optimal ages for study of specific drugs according to their pathways of disposition.

Risk assessment of patient factors and medications for drug-related problems from a prospective longitudinal study of newborns admitted to a neonatal intensive care unit in Brazil

OBJECTIVE

To identify patient factors and medications associated with the occurrence of drug-related problems (DRPs) in neonates admitted to neonatal intensive care units (NICUs).

DESIGN

Prospective, longitudinal study.

SETTING

NICU of a teaching hospital in Brazil.

PARTICIPANTS

Data were collected from the records of the clinical pharmacy service of all neonates admitted between April 2014 and January 2017, excluding neonates with length of stay in the NICU <24 hours or without prescribed drugs.

PRIMARY OUTCOME MEASURES

Occurrence of one or more DRP (conditions interfering in the patient's pharmacotherapy with potential undesired clinical outcomes).

RESULTS

The study observed 600 neonates who had a median length of stay in the NICU of 13 days (range 2-278 days). DRPs were identified in most neonates (60.5%). In a multivariate logistic regression model, the factors independently associated with DRP were gestational age (adjusted OR (AOR) 0.85, 95% CI 0.81 to 0.89), 5 min Apgar <7 (AOR 1.74, 95% CI 1.00 to 3.13), neurological disease (AOR 2.49, 95% CI 1.09 to 5.69), renal disease (AOR 5.75, 95% CI 1.85 to 17.8) and cardiac disease (AOR 2.36, 95% CI 1.31 to 4.24). The medications with greater risk for DRP were amphotericin B (AOR 4.80), meropenem (AOR 4.09), alprostadil (AOR 3.38), vancomycin (AOR 3.34), ciprofloxacin (AOR 3.03), gentamicin (AOR 2.43), cefepime (AOR 1.88), amikacin (AOR 1.82) and omeprazole (AOR 1.66). These medicines represented one-third of all prescribed drugs.

CONCLUSIONS

Gestational age, 5 min Apgar <7, and neurological, cardiac and renal diseases are risk factors for DRP in NICUs. Alprostadil, omeprazole and several anti-infectives were associated with greater risk of DRP.

Population Pharmacokinetic Modeling of Gentamicin in Pediatrics

The primary objective of this work was to characterize the pharmacokinetics (PK) of gentamicin across the whole pediatric age spectrum from premature neonates to young adults with a single model by identifying significant clinical predictors. A nonlinear mixed-effect population PK model was developed with retrospective therapeutic drug-monitoring data. A total of 6459 drug concentration measurements from 3370 hospitalized patients were collected for model building (n = 2357) and evaluation (n = 1013). In agreement with previously reported models, a 2-compartment model with first-order elimination best described the drug PK. Patient-specific factors significantly impacting gentamicin clearance included fat-free mass, postmenstrual age, and serum creatinine (SCr). Based on our model, the deviation of the individual SCr from the age-dependent expected mean SCr value (SCrM) can result in a 40% lower clearance in a patient with renal impairment than that in a patient with normal kidney function, with SCrM:SCr ratios between 0.16 and 3.2 in this study. Consistent with the known age-dependent changes of the proportion of extracellular water in body weight, the inclusion of the impact of extracellular water maturation on the central volume of distribution was found to improve the model fitting significantly. In comparison with other published models, model evaluation suggested the developed model was the least biased and physiologically most representative. These results will be used to inform individualized initial dosing strategies and serve as a prior PK model for Bayesian updating and forecasting as individual clinical observations become available.

Drug related problems in the neonatal intensive care unit: incidence, characterization and clinical relevance

BACKGROUND

Any event involving drug therapy that may interfere in a patient's desired clinical outcome is called a drug related problem (DRP). DRP are very common in intensive therapy, however, little is known about DRP in the Neonatal Intensive Care Unit (NICU). The purpose of this study was to determine the incidence of DRPs in NICU patients and to characterize DRPs according to type, cause and corresponding pharmaceutical conducts.

METHODS

Prospective observational study conducted in the NICU at a teaching hospital in Brazil from January 2014 to November 2016. The data were collected from the records of the clinical pharmacy service, excluding neonates admitted for less than 24 h and those who had no drugs prescribed. DRPs were classified according to the Pharmaceutical Care Network Europe system and evaluated for relevance-safety.

RESULTS

Six hundred neonates were included in the study, with mean gestational age of 31.9 ± 4.1 weeks and mean birth weight of 1779 ± 885 g. The incidence of DRPs in the NICU was 6.8% patient-days (95%CI 6.2-7.3%) and affected 59.8% of neonates (95% CI 55.8-63.8%). Sub-optimal effect (52.8%) and inappropriate dose selection (39.75%) were the most common problem and cause, respectively. Anti-infectives was the medication class most involved in DRPs. More than one-third of neonates were exposed to DRP of significant or high safety-relevance. Most of the pharmaceutical interventions were related with drug prescription, with over 90% acceptance by attending physicians.

CONCLUSION

DRP are common in NICU, predominating problems of sub-optimal treatment, mainly due to inappropriate dose selection.

Dynamics of Organic Anion Transporter-Mediated Tubular Secretion during Postnatal Human Kidney Development and Maturation

BACKGROUND AND OBJECTIVES

The neonatal and juvenile human kidney can be exposed to a variety of potentially toxic drugs (e.g., nonsteroidal anti-inflammatory drugs, antibiotics, antivirals, diuretics), many of which are substrates of the kidney organic anion transporters, OAT1 (SLC22A6, originally NKT) and OAT3 (SLC22A8). Despite the immense concern about the consequences of drug toxicity in this vulnerable population, the developmental regulation of OATs in the immature postnatal kidney is poorly understood.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

Recognizing that today it is difficult to obtain rich data on neonatal kidney handling of OAT probes due to technical, logistic, and ethical considerations, multiple older physiologic studies that used the prototypical organic anion substrate para-aminohippurate (PAH) were reanalyzed in order to provide a quantitative description of OAT-mediated tubular secretion across the pediatric age continuum. Parametric and semiparametric models were evaluated for kidney function outcome variables of interest (maximum tubular secretory capacity of PAH [Tm_PAH], effective renal plasma flow [ERPF], and GFR).

RESULTS

Data from 119 neonates, infants, and children ranging in age from 1 day to 11.8 years were used to fit Tm_PAH, ERPF, and GFR as functions of postnatal age. Tm_PAH is low in the immediate postnatal period and increases markedly after birth, reaching 50% of the adult value (80 mg/min) at 8.3 years of age. During the first 2 years of life, Tm_PAH is lower than that of GFR when viewed as the fraction of the adult value.

CONCLUSIONS

During postnatal human kidney development, proximal tubule secretory function-as measured using PAH, a surrogate for OAT-mediated secretion of organic anion drugs, metabolites, and toxins-is low initially but increases rapidly. Despite developmental differences between species, this overall pattern is roughly consistent with animal studies. The human data raise the possibility that the acquisition of tubular secretory function may not closely parallel glomerular filtration.

Research on medication use in the neonatal intensive care unit

INTRODUCTION

Research on medication use aims at assessing how much of current pharmacotherapy is rational. In neonates, this is hampered by extensive off-label drug use and limited knowledge. Areas covered: We report on medication use research and have conducted a systematic review of observational studies on medication use to provide an updated overview on characteristics, objectives, methods, and patterns in hospitalized neonates. Moreover, a review on aspects of medication use for opioids, anti-epileptics, gastric acid-related disorders and respiratory stimulants with emphasis on trends and impact of interventions is presented, illustrating how research on medication use can contribute to improved neonatal pharmacotherapy and more focused research. Medication use reports describe patterns and provide signals on irrational use, benchmarking, or can guide research priorities. Moreover, this may generate information on how neonatal health topics and their pharmacotherapy are handled over time or across regions. Expert opinion: Research on medicine utilization is relevant, since it will inform us on aspects like trends, variability, or about the impact and pattern of implementation of guidelines in neonates. Further progress necessitates to merge datasets on medication use with clinical characteristics, and perinatal drug use remains an area in need of additional research.

Rational Use of Antibiotics in Neonates: Still in Search of Tailored Tools

Rational medicine use in neonates implies the prescription and administration of age-appropriate drug formulations, selecting the most efficacious and safe dose, all based on accurate information on the drug and its indications in neonates. This review illustrates that important uncertainties still exist concerning the different aspects (when, what, how) of rational antibiotic use in neonates. Decisions when to prescribe antibiotics are still not based on robust decision tools. Choices (what) on empiric antibiotic regimens should depend on the anticipated pathogens, and the available information on the efficacy and safety of these drugs. Major progress has been made on how (beta-lactam antibiotics, aminoglycosides, vancomycin, route and duration) to dose. Progress to improve rational antibiotic use necessitates further understanding of neonatal pharmacology (short- and long-term safety, pharmacokinetics, duration and route) and the use of tailored tools and smarter practices (biomarkers, screening for colonization, and advanced therapeutic drug monitoring techniques). Implementation strategies should not only facilitate access to knowledge and guidelines, but should also consider the most effective strategies (‘skills’) and psychosocial aspects involved in the prescription process: we should be aware that both the decision not to prescribe as well as the decision to prescribe antibiotics is associated with risks and benefits.

Renal Clearance in Newborns and Infants: Predictive Performance of Population-Based Modeling for Drug Development

The objective of this study was to evaluate the predictive performance of population models to predict renal clearance in newborns and infants. Pharmacokinetic (PK) data from eight drugs in 788 newborns and infants were used to evaluate the predictive performance of the population models based on postmenstrual age (PMA), postnatal age, gestational age, and body weight. For the PMA model, the average fold error for clearance (CL)_predicted /CL_observed was within a twofold range for each drug in all subgroups. For drugs with > 90% renal elimination, the prediction bias ranged from 0.7-1.3. For drugs with 60-80% renal elimination, the prediction bias ranged 0.6-2.0. Our results suggest that PMA-based sigmoidal maximum effect (E_max ) model, in combination with bodyweight-based scaling and kidney function assessment, can be used in population PK (PopPK) modeling for drugs that are primarily eliminated via renal pathway to inform initial dose selection for newborns and infants with normal renal function in clinical trials.

Glomerular Filtration Rate Estimation Formulas for Pediatric and Neonatal Use

Renal function assessment is of the utmost importance in predicting drug clearance and in ensuring safe and effective drug therapy in neonates. The challenges to making this prediction relate not only to the extreme vulnerability and rapid maturation of this pediatric subgroup but also to the choice of renal biomarker, covariates, and glomerular filtration rate (GFR) estimating formula. In order to avoid burdensome administration of exogenous markers and/or urine collection in vulnerable pediatric patients, estimation of GFR utilizing endogenous markers has become a useful tool in clinical practice. Several estimation methods have been developed over recent decades, exploiting various endogenous biomarkers (serum creatinine, cystatin C, blood urea nitrogen) and anthropometric measures (body length/height, weight, muscle mass). This article reviews pediatric GFR estimation methods with a focus on their suitability for use in the neonatal population.

Rational Use of Medicines in Neonates: Current Observations, Areas for Research and Perspectives

A focused reflection on rational medicines use in neonates is valuable and relevant, because indicators to assess rational medicines use are difficult to apply to neonates. Polypharmacy and exposure to antibiotics are common, while dosing regimens or clinical guidelines are only rarely supported by robust evidence in neonates. This is at least in part due to the extensive variability in pharmacokinetics and subsequent effects of medicines in neonates. Medicines utilization research informs us on trends, on between unit variability and on the impact of guideline implementation. We illustrate these aspects using data on drugs for gastroesophageal reflux, analgesics or anti-epileptic drugs. Areas for additional research are drug-related exposure during breastfeeding (exposure prediction) and how to assess safety (tools to assess seriousness, causality, and severity tailored to neonates) since both efficacy and safety determine rational drug use. To further improve rational medicines use, we need more data and tools to assess efficacy and safety in neonates. Moreover, we should facilitate access to such data, and explore strategies for effective implementation. This is because prescription practices are not only rational decisions, but also have psychosocial aspects that may guide clinicians to irrational practices, in part influenced by the psychosocial characteristics of this population.

Reviewing the WHO guidelines for antibiotic use for sepsis in neonates and children

Background Guidelines from 2005 for treating suspected sepsis in low- and middle-income countries (LMIC) recommended hospitalisation and prophylactic intramuscular (IM) or intravenous (IV) ampicillin and gentamicin. In 2015, recommendations when referral to hospital is not possible suggest the administration of IM gentamicin and oral amoxicillin. In an era of increasing antimicrobial resistance, an updated review of the appropriate empirical therapy for treating sepsis (taking into account susceptibility patterns, cost and risk of adverse events) in neonates and children is necessary. Methods Systematic literature review and international guidelines were used to identify published evidence regarding the treatment of (suspected) sepsis. Results Five adequately designed and powered studies comparing antibiotic treatments in a low-risk community in neonates and young infants in LMIC were identified. These addressed potential simplifications of the current WHO treatment of reference, for infants for whom admission to inpatient care was not possible. Research is lacking regarding the treatment of suspected sepsis in neonates and children with hospital-acquired sepsis, despite rising antimicrobial resistance rates worldwide. Conclusions Current WHO guidelines supporting the use of gentamicin and penicillin for hospital-based patients or gentamicin (IM) and amoxicillin (oral) when referral to a hospital is not possible are in accordance with currently available evidence and other international guidelines, and there is no strong evidence to change this. The benefit of a cephalosporin alone or in combination as a second-line therapy in regions with known high rates of non-susceptibility is not well established. Further research into hospital-acquired sepsis in neonates and children is required.

Pharmacokinetics of Penicillin G in Preterm and Term Neonates

Group B streptococci are common causative agents of early-onset neonatal sepsis (EOS). Pharmacokinetic (PK) data for penicillin G have been described for extremely preterm neonates but have been poorly described for late-preterm and term neonates. Thus, evidence-based dosing recommendations are lacking. We describe the PK of penicillin G in neonates with a gestational age (GA) of ≥32 weeks and a postnatal age of <72 h. Penicillin G was administered intravenously at a dose of 25,000 or 50,000 IU/kg of body weight every 12 h (q12h). At steady state, PK blood samples were collected prior to and at 5 min, 1 h, 3 h, 8 h, and 12 h after injection. Noncompartmental PK analysis was performed with WinNonlin software. With those data in combination with data from neonates with a GA of ≤28 weeks, we developed a population PK model using NONMEM software and performed probability of target attainment (PTA) simulations. In total, 16 neonates with a GA of ≥32 weeks were included in noncompartmental analysis. The median volume of distribution (V) was 0.50 liters/kg (interquartile range, 0.42 to 0.57 liters/kg), the median clearance (CL) was 0.21 liters/h (interquartile range, 0.16 to 0.29 liters/kg), and the median half-life was 3.6 h (interquartile range, 3.2 to 4.3 h). In the population PK analysis that included 35 neonates, a two-compartment model best described the data. The final parameter estimates were 10.3 liters/70 kg and 29.8 liters/70 kg for V of the central and peripheral compartments, respectively, and 13.2 liters/h/70 kg for CL. Considering the fraction of unbound penicillin G to be 40%, the PTA of an unbound drug concentration that exceeds the MIC for 40% of the dosing interval was >90% for MICs of ≤2 mg/liter with doses of 25,000 IU/kg q12h. In neonates, regardless of GA, the PK parameters of penicillin G were similar. The dose of 25,000 IU/kg q12h is suggested for treatment of group B streptococcal EOS diagnosed within the first 72 h of life. (This study was registered with the EU Clinical Trials Register under EudraCT number 2012-002836-97.).

Quantitative Analysis of Gentamicin Exposure in Neonates and Infants Calls into Question Its Current Dosing Recommendations

Optimal dosing of gentamicin in neonates is still a matter of debate despite its common use. We identified gentamicin dosing regimens from eight international guidelines and seven Swiss neonatal intensive care units. The dose per administration, the dosing interval, the total daily dose, and the demographic characteristics between guidelines were compared. There was considerable variability with respect to dose (4 to 6 mg/kg), dosing interval (24 h to 48 h), total daily dose (2.5 to 6 mg/kg/day), and patient demographic characteristics that were used to calculate individualized dosing regimens. A model-based simulation study in 1071 neonates was performed to determine the achievement of efficacious peak gentamicin concentrations according to predefined MICs (Cmax/MIC ≥ 10) and safe trough concentrations (Cmin ≤ 2 mg/liter) with recommended dosing regimens. MIC targets of 0.5 and 1 mg/liter were used. Dosing optimization was performed giving priority to the first day of treatment and with the goal of simplifying dosing. Current gentamicin neonatal guidelines allow to achieve effective peak concentrations for MICs ≤ 0.5 mg/liter but not higher. Model-based simulations indicate that to attain peak gentamicin concentrations of ≥10 mg/liter, a dose of 7.5 mg/kg should be administered using an extended dosing interval regimen. Trough concentrations of ≤2 mg/liter can be maintained with a dosing interval of 36 to 48 h in neonates according to gestational and postnatal age. For treatment beyond 3 days, therapeutic drug monitoring is advised to maintain adequate serum concentrations.

Evaluating the Relationship between Vancomycin Trough Concentration and 24-Hour Area under the Concentration-Time Curve in Neonates

Bacterial sepsis is a major cause of morbidity and mortality in neonates, especially those involving methicillin-resistant Staphylococcus aureus (MRSA). Guidelines by the Infectious Diseases Society of America recommend the vancomycin 24-h area under the concentration-time curve to MIC ratio (AUC₂₄/MIC) of >400 as the best predictor of successful treatment against MRSA infections when the MIC is ≤1 mg/liter. The relationship between steady-state vancomycin trough concentrations and AUC₂₄ values (mg·h/liter) has not been studied in an Asian neonatal population. We conducted a retrospective chart review in Singapore hospitals and collected patient characteristics and therapeutic drug monitoring data from neonates on vancomycin therapy over a 5-year period. A one-compartment population pharmacokinetic model was built from the collected data, internally validated, and then used to assess the relationship between steady-state trough concentrations and AUC₂₄ A Monte Carlo simulation sensitivity analysis was also conducted. A total of 76 neonates with 429 vancomycin concentrations were included for analysis. Median (interquartile range) was 30 weeks (28 to 36 weeks) for postmenstrual age (PMA) and 1,043 g (811 to 1,919 g) for weight at the initiation of treatment. Vancomycin clearance was predicted by weight, PMA, and serum creatinine. For MRSA isolates with a vancomycin MIC of ≤1, our major finding was that the minimum steady-state trough concentration range predictive of achieving an AUC₂₄/MIC of >400 was 8 to 8.9 mg/liter. Steady-state troughs within 15 to 20 mg/liter are unlikely to be necessary to achieve an AUC₂₄/MIC of >400, whereas troughs within 10 to 14.9 mg/liter may be more appropriate.