Predictive performance of a gentamicin population pharmacokinetic model in neonates receiving full-body hypothermia

Predictive Performance of a Gentamicin Pharmacokinetic Model in Term Neonates with Perinatal Asphyxia Undergoing Controlled Therapeutic Hypothermia

BACKGROUND

Model validation procedures are crucial when population pharmacokinetic (PK) models are used to develop dosing algorithms and to perform model-informed precision dosing. We have previously published a population PK model describing the PK of gentamicin in term neonates with perinatal asphyxia during controlled therapeutic hypothermia (TH), which showed altered gentamicin clearance during the hypothermic phase dependent on gestational age and weight. In this study, the predictive performance and generalizability of this model were assessed using an independent data set of neonates with perinatal asphyxia undergoing controlled TH.

METHODS

The external data set contained a subset of neonates included in the prospective observational multicenter PharmaCool Study. Predictive performance was assessed by visually inspecting observed-versus-predicted concentration plots and calculating bias and precision. In addition, simulation-based diagnostics, model refitting, and bootstrap analyses were performed.

RESULTS

The external data set included 323 gentamicin concentrations of 39 neonates. Both the model-building and external data set included neonates from multiple centers. The original gentamicin PK model predicted the observed gentamicin concentrations with adequate accuracy and precision during all phases of controlled TH. Model appropriateness was confirmed with prediction-corrected visual predictive checks and normalized prediction distribution error analyses. Model refitting to the merged data set (n = 86 neonates with 935 samples) showed accurate estimation of PK parameters.

CONCLUSIONS

The results of this external validation study justify the generalizability of the gentamicin dosing recommendations made in the original study for neonates with perinatal asphyxia undergoing controlled TH (5 mg/kg every 36 or 24 h with gestational age 36-41 and 42 wk, respectively) and its applicability in model-informed precision dosing.

The Effect of Inflammatory Bowel Disease and Irritable Bowel Syndrome on Pravastatin Oral Bioavailability: In vivo and in silico evaluation using bottom-up wbPBPK modeling

The common disorders irritable bowel syndrome (IBS) and inflammatory bowel disease (IBD) can modify the drugs' pharmacokinetics via their induced pathophysiological changes. This work aimed to investigate the impact of these two diseases on pravastatin oral bioavailability. Rat models for IBS and IBD were used to experimentally test the effects of IBS and IBD on pravastatin pharmacokinetics. Then, the observations made in rats were extrapolated to humans using a mechanistic whole-body physiologically-based pharmacokinetic (wbPBPK) model. The rat in vivo studies done herein showed that IBS and IBD decreased serum albumin (> 11% for both), decreased PRV binding in plasma, and increased pravastatin absolute oral bioavailability (0.17 and 0.53 compared to 0.01) which increased plasma, muscle, and liver exposure. However, the wbPBPK model predicted muscle concentration was much lower than the pravastatin toxicity thresholds for myotoxicity and rhabdomyolysis. Overall, IBS and IBD can significantly increase pravastatin oral bioavailability which can be due to a combination of increased pravastatin intestinal permeability and decreased pravastatin gastric degradation resulting in higher exposure. This is the first study in the literature investigating the effects of IBS and IBD on pravastatin pharmacokinetics. The high interpatient variability in pravastatin concentrations as induced by IBD and IBS can be reduced by oral administration of pravastatin using enteric-coated tablets. Such disease (IBS and IBD)-drug interaction can have more drastic consequences for narrow therapeutic index drugs prone to gastric degradation, especially for drugs with low intestinal permeability.

Evaluating the Pharmacokinetics of Fentanyl in the Brain Extracellular Fluid, Saliva, Urine, and Plasma of Newborns from Transplacental Exposure from Parturient Mothers Dosed with Epidural Fentanyl Utilizing PBPK Modeling

BACKGROUND AND OBJECTIVE

Fentanyl can mitigate the mother and newborn complications resulting from labor pain. However, fentanyl shows a narrow therapeutic index between its respiratory depressive and analgesic effects. Thus, prenatally acquired high fentanyl levels in the newborn brain extracellular fluid (bECF) may induce respiratory depression which requires therapeutic drug monitoring (TDM). TDM using saliva and urine in newborns can reduce the possibility of infections and distress associated with TDM using blood. The objective of this study was to develop  a physiologically based pharmacokinetic (PBPK) model to predict fentanyl concentrations in different newborn tissues due to intrauterine exposure.

METHODS

A fentanyl PBPK model in adults after intravenous and epidural administration was built, validated, and scaled to pregnancy and newborn populations. The dose that the newborn received transplacentally at birth was calculated using the pregnancy model. Then, the newborn bECF, saliva, plasma, and urine concentrations after such a dose were predicted using the newborn PBPK model.

RESULTS

After a maternal epidural dose of fentanyl 245 µg, the predicted newborn plasma and bECF levels were below the toxicity thresholds. Furthermore, the salivary threshold levels in newborns for fentanyl analgesic and respiratory depression effects were estimated to be 0.39 and 14.7-18.2 ng/ml, respectively.

CONCLUSION

The salivary TDM of fentanyl in newborns can be useful in newborns exposed to intrauterine exposure from parturient females dosed with epidural fentanyl. However, newborn-specific values of µ-opioid receptors IC50 for respiratory depression are needed.

The Analysis of Pethidine Pharmacokinetics in Newborn Saliva, Plasma, and Brain Extracellular Fluid After Prenatal Intrauterine Exposure from Pregnant Mothers Receiving Intramuscular Dose Using PBPK Modeling

BACKGROUND AND OBJECTIVE

Pethidine (meperidine) can decrease labor pain-associated mother's hyperventilation and high cortisol-induced newborn complications. However, prenatal transplacentally acquired pethidine can cause side effects in newborns. High pethidine concentrations in the newborn brain extracellular fluid (bECF) can cause a serotonin crisis. Therapeutic drug monitoring (TDM) in newborns' blood distresses them and increases infection incidence, which can be overcome by using salivary TDM. Physiologically based pharmacokinetic (PBPK) modeling can predict drug concentrations in newborn plasma, saliva, and bECF after intrauterine pethidine exposure.

METHODS

A healthy adult PBPK model was constructed, verified, and scaled to newborn and pregnant populations after intravenous and intramuscular pethidine administration. The pregnancy PBPK model was used to predict the newborn dose received transplacentally at birth, which was used as input to the newborn PBPK model to predict newborn plasma, saliva, and bECF pethidine concentrations and set correlation equations between them.

RESULTS

Pethidine can be classified as a Salivary Excretion Classification System class II drug. The developed PBPK model predicted that, after maternal pethidine intramuscular doses of 100 mg and 150 mg, the newborn plasma and bECF concentrations were below the toxicity thresholds. Moreover, it was estimated that newborn saliva concentrations of 4.7 µM, 11.4 µM, and 57.7 µM can be used as salivary threshold concentrations for pethidine analgesic effects, side effects, and the risk for serotonin crisis, respectively, in newborns.

CONCLUSION

It was shown that saliva can be used for pethidine TDM in newborns during the first few days after delivery to mothers receiving pethidine.

The investigation of the complex population-drug-drug interaction between ritonavir-boosted lopinavir and chloroquine or ivermectin using physiologically-based pharmacokinetic modeling

OBJECTIVES

Therapy failure caused by complex population-drug-drug (PDDI) interactions including CYP3A4 can be predicted using mechanistic physiologically-based pharmacokinetic (PBPK) modeling. A synergy between ritonavir-boosted lopinavir (LPVr), ivermectin, and chloroquine was suggested to improve COVID-19 treatment. This work aimed to study the PDDI of the two CYP3A4 substrates (ivermectin and chloroquine) with LPVr in mild-to-moderate COVID-19 adults, geriatrics, and pregnancy populations.

METHODS

The PDDI of LPVr with ivermectin or chloroquine was investigated. Pearson's correlations between plasma, saliva, and lung interstitial fluid (ISF) levels were evaluated. Target site (lung epithelial lining fluid [ELF]) levels of ivermectin and chloroquine were estimated.

RESULTS

Upon LPVr coadministration, while the chloroquine plasma levels were reduced by 30, 40, and 20%, the ivermectin plasma levels were increased by a minimum of 425, 234, and 453% in adults, geriatrics, and pregnancy populations, respectively. The established correlation equations can be useful in therapeutic drug monitoring (TDM) and dosing regimen optimization.

CONCLUSIONS

Neither chloroquine nor ivermectin reached therapeutic ELF levels in the presence of LPVr despite reaching toxic ivermectin plasma levels. PBPK modeling, guided with TDM in saliva, can be advantageous to evaluate the probability of reaching therapeutic ELF levels in the presence of PDDI, especially in home-treated patients.

Enhancing Atorvastatin In Vivo Oral Bioavailability in the Presence of Inflammatory Bowel Disease and Irritable Bowel Syndrome Using Supercritical Fluid Technology Guided by wbPBPK Modeling in Rat and Human

Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are common disorders that can change the body's physiology and drugs pharmacokinetics. Solid dispersion (SD) preparation using supercritical fluid technology (SFT) has many advantages. Our study aimed to explore the effect of IBS and IBD on atorvastatin (ATV) pharmacokinetics, enhance ATV oral bioavailability (BCS II drug) using SFT, and analyze drug-disease-formulation interaction using a whole-body physiologically based pharmacokinetic (wbPBPK) model in rat and human. A novel ATV formulation was prepared using SFT and characterized in vitro and in vivo in healthy, IBS, and IBD rats. The resulting ATV plasma levels were analyzed using a combination of conventional and wbPBPK approaches. The novel formulation increased ATV solubility by 20-fold and resulted in a zero-order release of up to 95%. Both IBS and IBD increased ATV exposure after oral and intravenous administration by more than 30%. The novel SFT formulation increased ATV bioavailability by 28, 14, and 18% in control, IBD, and IBD rat groups and resulted in more consistent exposure as compared to raw ATV solution. Higher improvements in ATV bioavailability of more than 2-fold upon receiving the novel SFT formulation were predicted by the human wbPBPK model as compared to receiving the conventional tablets. Finally, the established wbPBPK model could describe ATV ADME in the presence of IBS and IBD after oral administration of raw ATV and using the novel SFT formula and can help scale the optimized ATV dosing regimens in the presence of IBS and IBD from rats to humans.

Pharmacometric approach to assist dosage regimen design in neonates undergoing therapeutic hypothermia

BACKGROUND

Therapeutic hypothermia (TH) is the treatment of choice for neonates diagnosed with perinatal asphyxia (PA). Dosing recommendations of various therapeutic agents including antimicrobials were not specifically available for the neonates undergoing TH.

METHODS

A systematic search methodology was used to identify pharmacokinetic (PK) studies of antimicrobials during TH. Antimicrobials with multiple PK studies were identified to create a generalizable PK model. Pharmacometric simulations were performed using the PUMAS software platform to reproduce the results of published studies. A suitable model that could reproduce the results of all other published studies was identified. With the help of a generalizable model, an optimal dosage regimen was designed considering the important covariates of the identified model.

RESULTS

With the systematic search, only gentamicin had multiple PK reports during TH. A generalizable model was identified and the model predictions could match the reported/observed concentrations of publications. Birth weight and serum creatinine were the significant covariates influencing the PK of gentamicin in neonates. A dosage nomogram was designed using pharmacometric simulations to maintain gentamicin concentrations below 10 μg/mL at peak and below 2 μg/mL at trough.

CONCLUSIONS

A generalizable PK model for gentamicin during TH in neonates was identified. Using the model, a dosing nomogram for gentamicin was designed.

IMPACT

Dosing guidelines for antimicrobials during TH in neonates is lacking. This is the first study to identify the generalizable model for gentamicin during TH in neonates. Nomogram, proposed in the study, will aid the clinicians to individualize gentamicin dosing regimen for neonates considering the birth weight and serum creatinine.

Physiologically-based pharmacokinetic model for alectinib, ruxolitinib, and panobinostat in the presence of cancer, renal impairment, and hepatic impairment

Renal (RIP) and hepatic (HIP) impairments are prevalent conditions in cancer patients. They can cause changes in gastric emptying time, albumin levels, hematocrit, glomerular filtration rate, hepatic functional volume, blood flow rates, and metabolic activity that can modify drug pharmacokinetics. Performing clinical studies in such populations has ethical and practical issues. Using predictive physiologically-based pharmacokinetic (PBPK) models in the evaluation of the PK of alectinib, ruxolitinib, and panobinostat exposures in the presence of cancer, RIP, and HIP can help in using optimal doses with lower toxicity in these populations. Verified PBPK models were customized under scrutiny to account for the pathophysiological changes induced in these diseases. The PBPK model-predicted plasma exposures in patients with different health conditions within average 2-fold error. The PBPK model predicted an area under the curve ratio (AUCR) of 1, and 1.8, for ruxolitinib and panobinostat, respectively, in the presence of severe RIP. On the other hand, the severe HIP was associated with AUCR of 1.4, 2.9, and 1.8 for alectinib, ruxolitinib, and panobinostat, respectively, in agreement with the observed AUCR. Moreover, the PBPK model predicted that alectinib therapeutic cerebrospinal fluid levels are achieved in patients with non-small cell lung cancer, moderate HIP, and severe HIP at 1-, 1.5-, and 1.8-fold that of healthy subjects. The customized PBPK models showed promising ethical alternatives for simulating clinical studies in patients with cancer, RIP, and HIP. More work is needed to quantify other pathophysiological changes induced by simultaneous affliction by cancer and RIP or HIP.

Simplified Dosing Regimens for Gentamicin in Neonatal Sepsis

Background: The effectiveness of antibiotics for the treatment of severe bacterial infections in newborns in resource-limited settings has been determined by empirical evidence. However, such an approach does not warrant optimal exposure to antibiotic agents, which are known to show different disposition characteristics in this population. Here we evaluate the rationale for a simplified regimen of gentamicin taking into account the effect of body size and organ maturation on pharmacokinetics. The analysis is supported by efficacy data from a series of clinical trials in this population.

Methods: A previously published pharmacokinetic model was used to simulate gentamicin concentration vs. time profiles in a virtual cohort of neonates. Model predictive performance was assessed by supplementary external validation procedures using therapeutic drug monitoring data collected in neonates and young infants with or without sepsis. Subsequently, clinical trial simulations were performed to characterize the exposure to intra-muscular gentamicin after a q.d. regimen. The selection of a simplified regimen was based on peak and trough drug levels during the course of treatment.

Results: In contrast to current World Health Organization guidelines, which recommend gentamicin doses between 5 and 7.5 mg/kg, our analysis shows that gentamicin can be used as a fixed dose regimen according to three weight-bands: 10 mg for patients with body weight <2.5 kg, 16 mg for patients with body weight between 2.5 and 4 kg, and 30 mg for those with body weight >4 kg.

Conclusion: The choice of the dose of an antibiotic must be supported by a strong scientific rationale, taking into account the differences in drug disposition in the target patient population. Our analysis reveals that a simplified regimen is feasible and could be used in resource-limited settings for the treatment of sepsis in neonates and young infants with sepsis aged 0–59 days.

Dosing Recommendations for Lamotrigine in Children: Evaluation Based on Previous and New Population Pharmacokinetic Models

Lamotrigine is a broad-spectrum antiepileptic drug with high interindividual variability in serum concentrations in children. The aims of this study were to evaluate the predictive performance of pediatric population pharmacokinetic (PPK) models published on lamotrigine, to build a new model with our monitoring data and to evaluate the current recommended doses. A validation cohort included patients treated with lamotrigine who had a serum level assayed during therapeutic drug monitoring (TDM). PPK models published in the literature were first applied to the validation cohort. We assessed their predictive performance using mean prediction errors, root mean squared errors, and visual predictive checks. A new model was then built using the data. Dose simulations were performed to evaluate the doses recommended. We included 270 lamotrigine concentrations ranging from 0.5 to 17.9 mg/L from 175 patients. The median (range) age and weight were 11.8 years (0.8-18 years) and 32.7 kg (8-110 kg). We tested 6 PPK models; most had acceptable bias and precision but underestimated the variability of the cohort. We built a 1-compartment model with first-order absorption and elimination, allometric scaling, and effects of inhibitor and inducer comedications. In our cohort, 22.6% of trough concentrations were below 2.5 mg/L. In conclusion, we proposed a PPK model that can be used for TDM of lamotrigine in children. In our population, a high percentage of children had low trough concentrations of lamotrigine. As the intervals of recommended doses are large, we suggest aiming at the higher range of doses to reach the target concentration.

Infection control and other stewardship strategies in late onset sepsis, necrotizing enterocolitis, and localized infection in the neonatal intensive care unit

Suspected or proven late onset sepsis, necrotizing enterocolitis, urinary tract infections, and ventilator associated pneumonia occurring after the first postnatal days contribute significantly to the total antibiotic exposures in neonatal intensive care units. The variability in definitions and diagnostic criteria in these conditions lead to unnecessary antibiotic use. The length of treatment and choice of antimicrobial agents for presumed and proven episodes also vary among centers due to a lack of supportive evidence and guidelines. Implementation of robust antibiotic stewardship programs can encourage compliance with appropriate dosages and narrow-spectrum regimens.

Can Population Pharmacokinetics of Antibiotics be Extrapolated? Implications of External Evaluations

BACKGROUND AND OBJECTIVE

External evaluation is an important issue in the population pharmacokinetic analysis of antibiotics. The purpose of this review was to summarize the current approaches and status of external evaluations and discuss the implications of external evaluation results for the future individualization of dosing regimens.

METHODS

We systematically searched the PubMed and EMBASE databases for external evaluation studies of population analysis and extracted the relevant information from these articles. A total of 32 studies were included in this review.

RESULTS

Vancomycin was investigated in 17 (53.1%) articles and was the most studied drug. Other studied drugs included gentamicin, tobramycin, amikacin, amoxicillin, ceftaroline, meropenem, fluconazole, voriconazole, and rifampicin. Nine (28.1%) studies were prospective, and the sample size varied widely between studies. Thirteen (40.6%) studies evaluated the population pharmacokinetic models by systematically searching for previous studies. Seven (21.9%) studies were multicenter studies, and 27 (84.4%) adopted the sparse sampling strategy. Almost all external evaluation studies of antibiotics (93.8%) used metrics for prediction-based diagnostics, while relatively fewer studies were based on simulations (46.9%) and Bayesian forecasting (25.0%).

CONCLUSION

The results of external evaluations in previous studies revealed the poor extrapolation performance of existing models of prediction- and simulation-based diagnostics, whereas the posterior Bayesian method could improve predictive performance. There is an urgent need for the development of standards and guidelines for external evaluation studies.

A review of population pharmacokinetic models of gentamicin in paediatric patients

WHAT IS KNOWN AND OBJECTIVES

Gentamicin is often used for the treatment of Gram-negative infections. Due to pharmacokinetic variability in paediatric patients, appropriate dosing of gentamicin in the paediatric population is challenging. This article reviews published population pharmacokinetic models of gentamicin in paediatric patients, identifies covariates that significantly influence gentamicin pharmacokinetics, and determines whether there is a consensus on proposed dosing for intravenous gentamicin in this population.

METHODS

The PubMed database was searched for articles published until the end of 2017. If the articles described population pharmacokinetic models of gentamicin in the paediatric population (after intravenous administration of gentamicin), the following data were extracted: type of study, year of publication, population characteristics and number of patients, gentamicin dosing, total number of gentamicin (serum and/or plasma) concentrations, type of population modelling approach, developed model with pharmacokinetic parameters and covariates included.

RESULTS AND DISCUSSION

In most of the studies, one- or two-compartment modelling was applied. The mean estimated gentamicin clearance for newborns, infants and the complete paediatric population was 0.048, 0.13 and 0.067 L/h/kg, respectively, and the mean predicted volume of distribution was 0.475, 0.35 and 0.33 L/kg, respectively. The values reflect differences in body composition and kidney maturation within the different paediatric populations. Gentamicin pharmacokinetics were most influenced by age, body size and renal function.

WHAT IS NEW AND CONCLUSION

Based on our review, the authors agree on a prolonged dosing interval for preterm and term newborns (up to 48 hours). However, there was no agreement on proposed dosing with respect to gestational age. In general, the proposed daily doses were lower compared to those initially applied for preterm newborns and comparable to those for term newborns. For infants and children, the dosing interval remained unchanged (24 hours), but the proposed daily doses were higher than actually applied. When differences in the paediatric population are considered and an appropriate population PK model with applicable covariates is applied, dosing can be individualized. In the future, studies of gentamicin pharmacokinetics in paediatric patients should focus on currently underestimated covariates, such as fat-free mass, concomitantly administered drugs, body temperature and critical illness because these can change gentamicin PK considerably. Consequently, different dosing is required and TDM becomes even more important.

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.

Population Pharmacokinetics of Gentamicin in Neonates with Hypoxemic-Ischemic Encephalopathy Receiving Controlled Hypothermia

OBJECTIVE

Identify population pharmacokinetics and pharmacodynamic target attainment of gentamicin in neonates with hypoxic-ischemic encephalopathy (HIE) undergoing controlled hypothermia (CH).

DESIGN

Prospective open-label pharmacokinetic study. Gentamicin concentrations were modeled and dosing regimens simulated for a 5000-patient neonatal population with HIE receiving CH using PMetrics, a nonparametric, pharmacometric modeling, and simulation package for R.

SETTING

A 189-bed children's tertiary care teaching hospital.

RESULTS

Twelve patients, 5 (42%) females and 7 (58%) males, met inclusion criteria with a median gestation age of 39.9 weeks (interquartile range [IQR] 38.5-40.2 wks) and a median birthweight (BW) of 3.3 kg (IQR 3.1-3.7 kg). Gentamicin concentrations were best described by a two-compartment model with first-order elimination with BW as a covariate on volume of distribution (Vd). The mean total body population clearance (CL) was 2.2 ± 0.7 ml/minute/kg, and the volume of the central compartment was 0.44 ± 0.06 L/kg. The R² , bias, and precision for the observed versus population predicted model were 0.917, 1.15, and 10.9 μg/ml; the R² , bias, and precision for the observed versus individual predicted model were 0.982, -0.132, and 0.932 μg/ml, respectively. The calculated mean population estimate for the total Vd was 0.96 ± 0.4 L/kg. The dosing regimen that most consistently produced a maximum concentration (C_max ) in the range of 10-12 mg/L with a minimum concentration (C_min ) level less than 2 mg/L was 5 mg/kg/dose given every 36 hours.

CONCLUSION

These data suggest the population pharmacokinetics of gentamicin in neonates with HIE receiving CH have an increase in gentamicin CL and are different from previous reports in neonates with HIE not receiving CH and/or neonates without HIE. This analysis suggests a dosing regimen of 5 mg/kg/dose every 36 hours results in a gentamicin C_max within the range of 10-12 mg/L with a C_min lower than 2 mg/L, which is appropriate for treating susceptible gram-negative organisms with minimum inhibitory concentrations of 1 mg/L or lower.

Vancomycin in Pediatric Patients with Solid or Hematological Malignant Disease: Predictive Performance of a Population Pharmacokinetic Model and New Optimized Dosing Regimens

BACKGROUND

The application of population pharmacokinetic models and Bayesian methods offers the potential to develop individualized therapeutic approaches.

OBJECTIVES

The current study presents an external evaluation of a vancomycin pharmacokinetic model in a pediatric cancer population and proposes an easy-to-use chart for clinicians for a priori vancomycin schedule adaptation to achieve target concentration.

METHODS

External evaluation of a population pharmacokinetic model of vancomycin administered via continuous infusion was realized in a new retrospective dataset of pediatric patients with cancer. The published population pharmacokinetic model was implemented in NONMEM 7.3 with the structural and variance parameter values set equal to estimates previously reported. Predictive performance was assessed by quantifying bias and accuracy of model prediction. Normalized prediction distribution errors were also evaluated. Dosage simulations were performed according to the target concentration.

RESULTS

A total of 77 patients were included in this study, representing 146 vancomycin courses and 289 concentrations. The model adequately predicted vancomycin concentrations (median prediction error % of - 9.4%, median |PE|% of 24.1%). Based on simulation results, vancomycin dosage (mg/kg) should be adapted for each child on the basis of body weight and cyclosporine coadministration.

CONCLUSION

The model previously proposed by Guilhaumou et al. in pediatric patients with solid or hematological malignant disease was externally validated. Simulations have enabled the description of new dosage schedules and creation of a chart to help clinicians adapt vancomycin dosage.

Dosing antibiotics in neonates: review of the pharmacokinetic data

Antibiotics are often used in neonates despite the absence of relevant dosing information in drug labels. For neonatal dosing, clinicians must extrapolate data from studies for adults and older children, who have strikingly different physiologies. As a result, dosing extrapolation can lead to increased toxicity or efficacy failures in neonates. Driven by these differences and recent legislation mandating the study of drugs in children and neonates, an increasing number of pharmacokinetic studies of antibiotics are being performed in neonates. These studies have led to new dosing recommendations with particular consideration for neonate body size and maturation. Herein, we highlight the available pharmacokinetic data for commonly used systemic antibiotics in neonates.

Phenobarbital in intensive care unit pediatric population: predictive performances of population pharmacokinetic model

An external evaluation of phenobarbital population pharmacokinetic model described by Marsot et al. was performed in pediatric intensive care unit. Model evaluation is an important issue for dose adjustment. This external evaluation should allow confirming the proposed dosage adaptation and extending these recommendations to the entire intensive care pediatric population. External evaluation of phenobarbital published population pharmacokinetic model of Marsot et al. was realized in a new retrospective dataset of 35 patients hospitalized in a pediatric intensive care unit. The published population pharmacokinetic model was implemented in nonmem 7.3. Predictive performance was assessed by quantifying bias and inaccuracy of model prediction. Normalized prediction distribution errors (NPDE) and visual predictive check (VPC) were also evaluated. A total of 35 infants were studied with a mean age of 33.5 weeks (range: 12 days-16 years) and a mean weight of 12.6 kg (range: 2.7-70.0 kg). The model predicted the observed phenobarbital concentrations with a reasonable bias and inaccuracy. The median prediction error was 3.03% (95% CI: -8.52 to 58.12%), and the median absolute prediction error was 26.20% (95% CI: 13.07-75.59%). No trends in NPDE and VPC were observed. The model previously proposed by Marsot et al. in neonates hospitalized in intensive care unit was externally validated for IV infusion administration. The model-based dosing regimen was extended in all pediatric intensive care unit to optimize treatment. Due to inter- and intravariability in pharmacokinetic model, this dosing regimen should be combined with therapeutic drug monitoring.

The amikacin research program: a stepwise approach to validate dosing regimens in neonates

INTRODUCTION

For safe and effective use of antibacterial agents in neonates, specific knowledge on the pharmacokinetics (PK) and its covariates is needed. This necessitates a stepwise approach, including prospective validation. Areas covered: We describe our approach throughout almost two decades to improve amikacin exposure in neonates. A dosing regimen has been developed and validated using pharmacometrics, considering current weight, postnatal age, perinatal asphyxia, and ibuprofen use. This regimen has been developed based on clinical and therapeutic drug monitoring (TDM) data collected during routine care, and subsequently underwent prospective validation. A similar approach has been scheduled to quantify the impact of hypothermia. Besides plasma observations, datasets on deep compartment PK were also collected. Finally, the available literature on developmental toxicology (hearing, renal) of amikacin is summarized. Expert opinion: The amikacin model reflects a semi-physiological function for glomerular filtration. Consequently, this model can be used to develop dosing regimens for other aminoglycosides or to validate physiology-based pharmacokinetic models. Future studies should explore safety with incorporation of covariates like pharmacogenetics, biomarkers, and long-term outcomes. This includes a search for mechanisms of developmental toxicity. Following knowledge generation and grading the level of evidence in support of data, dissemination and implementation initiatives are needed.

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

Sepsis remains a major cause of mortality and morbidity in neonates, and, as a consequence, antibiotics are the most frequently prescribed drugs in this vulnerable patient population. Growth and dynamic maturation processes during the first weeks of life result in large inter- and intrasubject variability in the pharmacokinetics (PK) and pharmacodynamics (PD) of antibiotics. In this review we (1) summarize the available population PK data and models for primarily renally eliminated antibiotics, (2) discuss quantitative approaches to account for effects of growth and maturation processes on drug exposure and response, (3) evaluate current dose recommendations, and (4) identify opportunities to further optimize and personalize dosing strategies of these antibiotics in preterm and term neonates. Although population PK models have been developed for several of these drugs, exposure-response relationships of primarily renally eliminated antibiotics in these fragile infants are not well understood, monitoring strategies remain inconsistent, and consensus on optimal, personalized dosing of these drugs in these patients is absent. Tailored PK/PD studies and models are useful to better understand relationships between drug exposures and microbiological or clinical outcomes. Pharmacometric modeling and simulation approaches facilitate quantitative evaluation and optimization of treatment strategies. National and international collaborations and platforms are essential to standardize and harmonize not only studies and models but also monitoring and dosing strategies. Simple bedside decision tools assist clinical pharmacologists and neonatologists in their efforts to fine-tune and personalize the use of primarily renally eliminated antibiotics in term and preterm neonates.

Predicting neonatal pharmacokinetics from prior data using population pharmacokinetic modeling

Selection of the first dose for neonates in clinical trials is very challenging. The objective of this analysis was to assess if a population pharmacokinetic (PK) model developed with data from infants to adults is predictive of neonatal clearance and to evaluate what age range of prior PK data is needed for informative modeling to predict neonate exposure. Two sources of pharmacokinetic data from 8 drugs were used to develop population models: (1) data from all patients > 2 years of age, and (2) data from all nonneonatal patients aged > 28 days. The prediction error based on the models using data from subjects > 2 years of age showed bias toward overprediction, with median average fold error (AFE) for CL predicted/CLobserved greater than 1.5. The bias for predicting neonatal PK was improved when using all prior PK data including infants as opposed to an assessment without infant PK data, with the median AFE 0.91. As an increased number of pediatric trials are conducted in neonates under the Food and Drug Administration Safety and Innovation Act, dose selection should be based on the best estimates of neonatal pharmacokinetics and pharmacodynamics prior to conducting efficacy and safety studies in neonates.