Changes in individual drug-independent system parameters during virtual paediatric pharmacokinetic trials: introducing time-varying physiology into a paediatric PBPK model

Supplementing clinical lactation studies with PBPK modeling to inform drug therapy in lactating mothers: Prediction of primaquine exposure as a case example

Evaluating the safety of primaquine (PQ) during breastfeeding requires an understanding of its pharmacokinetics (PKs) in breast milk and its exposure in the breastfed infant. Physiologically-based PK (PBPK) modeling is primed to assess the complex interplay of factors affecting the exposure of PQ in both the mother and the nursing infant. A published PBPK model for PQ describing the metabolism by monoamine oxidase A (MAO-A; 90% contribution) and cytochrome P450 2D6 (CYP2D6; 10%) in adults was applied to predict the exposure of PQ in mothers and their breastfeeding infants. Plasma exposures following oral daily dosing of 0.5 mg/kg in the nursing mothers in a clinical lactation study were accurately captured, including the observed ranges. Reported infant daily doses based on milk data from the clinical study were used to predict the exposure of PQ in breastfeeding infants greater than or equal to 28 days. On average, the predicted exposures were less than or equal to 0.13% of the mothers. Furthermore, in simulations involving neonates less than 28 days, PQ exposures remain less than 0.16% of the mothers. Assuming that MAO-A increases slowly with age, the predicted relative exposure of PQ remains low in neonates (<0.46%). Thus, the findings of our study support the recommendation made by the authors who reported the results of the clinical lactation study, that is, that when put into context of safety data currently available in children, PQ should not be withheld in lactating women as it is unlikely to cause adverse events in breastfeeding infants greater than or equal to 28 days old.

Physiologically Based Pharmacokinetic Modeling in Neonates: Current Status and Future Perspectives

Rational drug use in special populations is a clinical problem that doctors and pharma-cists must consider seriously. Neonates are the most physiologically immature and vulnerable to drug dosing. There is a pronounced difference in the anatomical and physiological profiles be-tween neonates and older people, affecting the absorption, distribution, metabolism, and excretion of drugs in vivo, ultimately leading to changes in drug concentration. Thus, dose adjustments in neonates are necessary to achieve adequate therapeutic concentrations and avoid drug toxicity. Over the past few decades, modeling and simulation techniques, especially physiologically based pharmacokinetic (PBPK) modeling, have been increasingly used in pediatric drug development and clinical therapy. This rigorously designed and verified model can effectively compensate for the deficiencies of clinical trials in neonates, provide a valuable reference for clinical research design, and even replace some clinical trials to predict drug plasma concentrations in newborns. This review introduces previous findings regarding age-dependent physiological changes and pathological factors affecting neonatal pharmacokinetics, along with their research means. The application of PBPK modeling in neonatal pharmacokinetic studies of various medications is also reviewed. Based on this, we propose future perspectives on neonatal PBPK modeling and hope for its broader application.

Using population pharmacokinetics to optimize initial vancomycin dosing guidelines for neonates to treat sepsis caused by coagulase-negative staphylococcus

INTRODUCTION

Vancomycin dosing tailored for newborns is challenging due to the significant influence of maturation and organ function on pharmacokinetics. Population pharmacokinetic (popPK) models can be used to improve target attainment in neonates.

OBJECTIVES

The primary objective was to derive and evaluate a popPK model of intravenous vancomycin for neonates. Second, the predictive performance of this popPK model was compared with published popPK models.

METHODS

This is a retrospective cohort study of neonates admitted to the neonatal intensive care unit receiving intravenous vancomycin. A popPK model was derived with 70% of the dataset using a nonlinear mixed effects modeling method. The predictive performance of the current popPK model was validated and compared with 22 published popPK models using the remaining 30% of the dataset. Monte Carlo simulations (MCS) were performed to derive optimal dosing regimens to treat neonatal sepsis caused by coagulase-negative staphylococci (CoNS).

RESULTS

Among 655 vancomycin courses from 448 neonates, 78% of vancomycin trough concentrations were outside target range (10-15 mg/L) for central nervous system infections and 43% were outside target range (5-12 mg/L) for other infections using the institution's vancomycin dosing. A one-compartment model best described the observed data with a mean clearance of 0.11 ± 0.03 L/kg/h and volume of distribution (V) of 1.02 ± 0.08 L/kg. Body weight (WT), postmenstrual age (PMA), and serum creatinine (SCr) were significant covariates associated with clearance (p < 0.001) and body WT was a significant covariate associated with V (p = 0.009). Our study's popPK model has similar or better accuracy and precision than other published models. MCS-derived vancomycin doses from the validated model achieved >90% target attainment for a steady state through target range of 10-15 mg/L in the majority of PMA and SCr categories (78%) to treat CoNS sepsis.

CONCLUSION

A vancomycin dosing guideline derived from a validated popPK model in neonates with CoNS sepsis is recommended to improve target attainment.

Physiologically Based Pharmacokinetics Modeling in the Neonatal Population-Current Advances, Challenges, and Opportunities

Physiologically based pharmacokinetic (PBPK) modeling is an approach to predicting drug pharmacokinetics, using knowledge of the human physiology involved and drug physiochemical properties. This approach is useful when predicting drug pharmacokinetics in under-studied populations, such as pediatrics. PBPK modeling is a particularly important tool for dose optimization for the neonatal population, given that clinical trials rarely include this patient population. However, important knowledge gaps exist for neonates, resulting in uncertainty with the model predictions. This review aims to outline the sources of variability that should be considered with developing a neonatal PBPK model, the data that are currently available for the neonatal ontogeny, and lastly to highlight the data gaps where further research would be needed.

Case report: Use of therapeutic drug monitoring and pharmacogenetic testing as opportunities to individualize care in a case of flecainide toxicity after fetal supraventricular tachycardia

Flecainide is a class IC antiarrhythmic utilized in prophylaxis of refractory paroxysmal supraventricular tachycardias in pediatric populations. Despite being a highly effective agent, its narrow therapeutic index increases the risk of toxicity and proarrhythmic events, including wide-complex tachycardia. In the absence of direct plasma sampling in the fetus to quantitate flecainide systemic concentrations, clinicians typically make drug dosing decisions from maternal plasma concentrations and QRS duration on maternal ECGs. There remains a paucity of standard guidelines and data to inform the timing and frequency of the aforementioned test in pregnancy and timing of flecainide discontinuation prior to childbirth. Flecainide primarily undergoes metabolism via cytochrome P450 (CYP). Given the variance of CYP-mediated metabolism at the level of the individual patient, pharmacogenomics can be considered in patients who present with flecainide toxicity to determine the maternal vs. fetal factors as an etiology for the event. Finally, pharmacogenetic testing can be utilized as an adjunct to guide flecainide dosing decisions, but must be done with caution in neonates <2 weeks of age. This case report highlights utilization of pharmacogenomic testing and therapeutic drug monitoring as adjuncts to guide therapy for a newborn with refractory supraventricular tachycardia, who experienced flecainide toxicity immediately post-partum and was trialed unsuccessfully on multiple alternative antiarrhythmics without rhythm control.

The MPRINT Hub Data, Model, Knowledge and Research Coordination Center: Bridging the gap in maternal-pediatric therapeutics research through data integration and pharmacometrics

Maternal and pediatric populations have historically been considered "therapeutic orphans" due to their limited inclusion in clinical trials. Physiologic changes during pregnancy and lactation and growth and maturation of children alter pharmacokinetics (PK) and pharmacodynamics (PD) of drugs. Precision therapy in these populations requires knowledge of these effects. Efforts to enhance maternal and pediatric participation in clinical studies have increased over the past few decades. However, studies supporting precision therapeutics in these populations are often small and, in isolation, may have limited impact. Integration of data from various studies, for example through physiologically based pharmacokinetic/pharmacodynamic (PBPK/PD) modeling or bioinformatics approaches, can augment the value of data from these studies, and help identify gaps in understanding. To catalyze research in maternal and pediatric precision therapeutics, the Obstetric and Pediatric Pharmacology and Therapeutics Branch of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) established the Maternal and Pediatric Precision in Therapeutics (MPRINT) Hub. Herein, we provide an overview of the status of maternal-pediatric therapeutics research and introduce the Indiana University-Ohio State University MPRINT Hub Data, Model, Knowledge and Research Coordination Center (DMKRCC), which aims to facilitate research in maternal and pediatric precision therapeutics through the integration and assessment of existing knowledge, supporting pharmacometrics and clinical trials design, development of new real-world evidence resources, educational initiatives, and building collaborations among public and private partners, including other NICHD-funded networks. By fostering use of existing data and resources, the DMKRCC will identify critical gaps in knowledge and support efforts to overcome these gaps to enhance maternal-pediatric precision therapeutics.

Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies

Robust prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically-based pharmacokinetic (P-PBPK) models is an essential step toward enabling precision dosing of these vulnerable groups. Twenty-two manuscripts involving P-PBPK predictions and corresponding observed PK data (e.g., area under the curve and clearance) for 22 small-molecule compounds metabolized by CYP (3A4, 1A2, and 2C9), UGT (1A9 and 2B7), FMO3, renal, non-renal, and complex routes were identified; ratios of mean predicted/observed (P/O) PK parameters were calculated. Seventy-eight of 115 mean predicted PK parameters were within 0.8 to 1.25-fold of observed data, 98 within 0.67 to 1.5-fold, 109 within 2-fold, and only 6 P/O ratios were outside of these bounds. A set of 12 CYP3A4-metabolized compounds and a set of 6 metabolized by other enzymes, CYP1A2 (1 compound), CYP2C9 (2 compounds), UGT1A9 (1 compound) and UGT2B7 (2 compounds) had 56 of 59 and 22 of 25 mean P/O ratios, respectively, that fell within the > 0.5 and < 2.0-fold boundaries. For compounds covering renal, non-renal, complex, and FM03 routes of elimination, 29 of 31 mean P/O ratios fell within the 0.67 to 1.5-fold bounds, including 4 of 5 P/O ratios from newborns. P-PBPK modeling and simulation is a strategic component of the complement of precision dosing methods and has a vital role to play in dose adjustment in vulnerable pediatric populations, such as those with disease or in different ethnic groups. Qualification of such models is an essential step toward acceptance of this methodology by regulators.

Population pharmacokinetics of FCN-159, a MEK1/2 inhibitor, in adult patients with advanced melanoma and neurofibromatosis type 1 (NF1) and model informed dosing recommendations for NF1 pediatrics

Objective: FCN-159 is a highly active mitogen-activated extracellular signal-regulated kinase 1/2 (MEK1/2) inhibitor in patients with advanced melanoma and neurofibromatosis type 1 (NF1). We report a population pharmacokinetic (PopPK) model-based analysis of FCN-159 and its application to inform dose selection for NF1 pediatric trials. Methods: PK data collected from patients with advanced melanoma and NF1 in two clinical studies (NCT03932253 and NCT04954001) were analyzed using a non-linear mixed effects model. The adult model was adapted by incorporating allometric scaling for PK projection in 2-17 years old children. Pediatric exposure in different body surface area (BSA) bins was simulated to identify nominal doses (i.e., dose amounts given as integers) and BSA bin cutoffs to achieve exposure comparable to adults' optimal exposure across the entire pediatric BSA range. Results: The final dataset consisted of 45 subjects with a total of 1030 PK samples. The PK of FCN-159 was well-described by a 2-compartment model with first-order linear elimination and delayed first-order absorption. Covariates, including BSA, age, sex, albumin, total protein, and cancer type, were identified as statistically significant predictors of FCN-159 disposition. Simulations based on the final model projected daily doses of 4 mg/m2 QD with optimized BSA bin cutoffs would allow fixed nominal doses within each bin and result in steady state exposure approximating the adult exposure observed at the recommended phase 2 dose (RP2D) in NF1, which is 8 mg QD. Conclusion: The developed population PK model adequately described the PK profile of FCN-159, which was adapted using allometric scaling to inform dose selection for NF1 pediatric trials.

A simple LC-MS/MS method for the simultaneous quantification of drug metabolic enzymes

OBJECTIVE

The aim of this study is to develop a LC-MS/MS method for the quantitation of seven cytochrome P450 (CYP450) enzymes.

METHODS

A high-performance liquid chromatography-tandem mass spectrometry method was developed using multiple reaction monitoring mode with positive electrospray ionization. The method was validated with selectivity, linearity, stability, accuracy and precious. In addition, the abundance of seven CYP450 enzymes in human liver microsomes and CYP3A4 in placenta were determined using the current method.

RESULTS

The linear range for CYP1A2, CYP2B6 and CYP2C8 was 0.036-3.6 nM and for CYP2C9, CYP2C19, CYP2D6 and CYP3A4 was 0.090-9.0 nM. No interference was found between the blank matrix and each specific peptides. The accuracy and precious results were in accord with the requirement of analytical methods for biological samples in Chinese Pharmacopoeia. In addition, the peptides were stable under current stability conditions. The content of CYP3A4 in placenta and the seven CYP450 enzymes in human liver microsomes were accurately quantified.

CONCLUSION

The developed method is sensitive and specific and can be applied to the quantification of enzymes abundance in different human derived samples like placenta and liver microsomes.

A longitudinal study of cytochrome P450 2D6 (CYP2D6) activity during adolescence

CYP2D6 substrates are among the most highly prescribed medications in teenagers and also commonly associated with serious adverse events. To investigate the relative contributions of genetic variation, growth, and development on CYP2D6 activity during puberty, healthy children and adolescents 7-15 years of age at enrollment participated in a longitudinal phenotyping study involving administration of 0.3 mg/kg dextromethorphan (DM) and 4-h urine collection every 6 months for 3 years (7 total visits). At each visit, height, weight, and sexual maturity were recorded, and CYP2D6 activity was determined as the urinary molar ratio of DM to its metabolite dextrorphan (DX). A total of 188 participants completed at least one visit, and 102 completed all seven study visits. Following univariate analysis, only CYP2D6 activity score (p < 0.001), urinary pH (p < 0.001), weight (p = 0.018), and attention-deficit/hyperactivity disorder (ADHD) diagnosis (p < 0.001) were significantly correlated with log(DM/DX). Results of linear mixed model analysis with random intercept, random slope covariance structure revealed that CYP2D6 activity score had the strongest effect on log(DM/DX), with model-estimated average log(DM/DX) being 3.8 SDs higher for poor metabolizers than for patients with activity score 3. A moderate effect on log(DM/DX) was observed for sex, and smaller effects were observed for ADHD diagnosis and urinary pH. The log(DM/DX) did not change meaningfully with age or pubertal development. CYP2D6 genotype remains the single, largest determinant of variability in CYP2D6 activity during puberty. Incorporation of genotype-based dosing guidelines should be considered for CYP2D6 substrates given the prevalent use of these agents in this pediatric age group.

Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors

Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients.

Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations.

Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old.

Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including C_min, C_max, and AUC_tau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults.

Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.

Current and future physiologically based pharmacokinetic (PBPK) modeling approaches to optimize pharmacotherapy in preterm neonates

INTRODUCTION

There is a need for structured approaches to inform on pharmacotherapy in preterm neonates. With their proven track record up to regulatory acceptance, physiologically based pharmacokinetic (PBPK) modeling and simulation provide such a structured approach, and hold the promise to support drug development in preterm neonates.

AREAS COVERED

Compared to the general and pediatric use of PBPK modeling, its use to inform pharmacotherapy in preterms is limited. Using a systematic search (PBPK + preterm), we retained 25 records (20 research papers, 2 letters, 3 abstracts). We subsequently collated the published information on PBPK software packages (PK-Sim®, Simcyp®), and their applications and optimization efforts in preterm neonates. It is encouraging that these applications cover a broad range of scenarios (pharmacokinetic-dynamic analyses, drug-drug interactions, developmental pharmacogenetics, lactation related exposure) and compounds (small molecules, proteins). Furthermore, specific compartments (cerebrospinal fluid, tissue) or (patho)physiologic processes (cardiac output, biliary excretion, first pass metabolism) are considered.

EXPERT OPINION

Knowledge gaps exist, giving rise to various levels of model uncertainty in PBPK applications in preterm neonates. To improve this setting, we need cross talk between clinicians and modelers to generate and integrate knowledge (PK datasets, system knowledge, maturational physiology and pathophysiology) to further refine PBPK models.

A population physiologically-based pharmacokinetic model to characterize antibody disposition in pediatrics and evaluation of the model using infliximab

AIMS

In order to better predict the pharmacokinetics (PK) of antibodies in children, and to facilitate dose optimization of antibodies in paediatric patients, there is a need to develop systems PK models that integrate ontogeny-related changes in human physiological parameters.

METHODS

A population-based physiological-based PK (PBPK) model to characterize antibody PK in paediatrics has been developed, by incorporating age-related changes in body weight, organ weight, organ blood flow rate and interstitial volumes in a previously published platform model. The model was further used to perform Monte Carlo simulations to investigate clearance vs. age and dose-exposure relationships for infliximab.

RESULTS

By estimating only one parameter and associated interindividual variability, the model was able to characterize clinical PK of infliximab from two paediatric cohorts (n = 141, 4-19 years) reasonably well. Model simulations demonstrated that only 50% of children reached desired trough concentrations when receiving FDA-labelled dosing regimen for infliximab, suggesting that higher doses and/or more frequent dosing are needed to achieve target trough concentrations of this antibody.

CONCLUSION

The paediatric PBPK model presented here can serve as a framework to characterize the PK of antibodies in paediatric patients. The model can also be applied to other protein therapeutics to advance precision medicine paradigm and optimize antibody dosing regimens in children.

Application of a Physiologically Based Pharmacokinetic Approach to Predict Theophylline Pharmacokinetics Using Virtual Non-Pregnant, Pregnant, Fetal, Breast-Feeding, and Neonatal Populations

Perinatal pharmacology is influenced by a myriad of physiological variables that are changing dynamically. The influence of these covariates has not been assessed systemically. The objective of this work was to use theophylline as a model drug and to predict its pharmacokinetics before, during (including prediction of the umbilical cord level), and after pregnancy as well as in milk (after single and multiple doses) and in neonates using a physiological-based pharmacokinetic (PBPK) model. Neonatal theophylline exposure from milk consumption was projected in both normal term and preterm subjects. Predicted infant daily doses were calculated using theophylline average and maximum concentration in the milk as well as an estimate of milk consumption. Predicted concentrations and parameters from the PBPK model were compared to the observed data. PBPK predicted theophylline concentrations in non-pregnant and pregnant populations at different gestational weeks were within 2-fold of the observations and the observed concentrations fell within the 5th-95th prediction interval from the PBPK simulations. The PBPK model predicted an average cord-to-maternal plasma ratio of 1.0, which also agrees well with experimental observations. Predicted postpartum theophylline concentration profiles in milk were also in good agreement with observations with a predicted milk-to-plasma ratio of 0.68. For an infant of 2 kg consuming 150 ml of milk per day, the lactation model predicted a relative infant dose (RID) of 12 and 17% using predicted average (C_avg,ss) and maximum (C_max,ss) concentration in milk at steady state. The maximum RID of 17% corresponds to an absolute infant daily dose of 1.4 ± 0.5 mg/kg/day. This dose, when administered as 0.233 mg/kg every 4 h, to resemble breastfeeding frequency, resulted in plasma concentrations as high as 3.9 (1.9-6.8) mg/L and 2.8 (1.3-5.3) (5th-95th percentiles) on day 7 in preterm (32 GW) and full-term neonatal populations.

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.

Physiologically Based Pharmacokinetic Modeling and Allometric Scaling in Pediatric Drug Development: Where Do We Draw the Line?

Developing medicines for children is now established in legislation in both the United States and Europe; new drugs require pediatric study or investigation plans as part of their development. Particularly in early age groups, many developmental processes are not reflected by simple scalars such as body weight or body surface area, and even projecting doses based on simple allometric scaling can lead to significant overdoses in certain age groups. Modeling and simulation methodology, including physiologically based modeling, has evolved as part of the drug development toolkit and is being increasingly applied to various aspects of pediatric drug development. Pediatric physiologically based pharmacokinetic (PBPK) models account for the development of organs and the ontogeny of specific enzymes and transporters that determine the age-related pharmacokinetic profiles. However, when should this approach be used, and when will simpler methods such as allometric scaling suffice in answering specific problems? The aim of this review article is to illustrate the application of allometric scaling and PBPK in pediatric drug development and explore the optimal application of the latter approach with reference to case examples. In reality, allometric scaling included as part of population pharmacokinetic and PBPK approaches are all part of a model-informed drug development toolkit helping with decision making during the process of drug discovery and development; to that end, they should be viewed as complementary.

Application of Physiologically Based Pharmacokinetic-Pharmacodynamic Modeling in Preterm Neonates to Guide Gentamicin Dosing Decisions and Predict Antibacterial Effect

Clinical studies in preterm neonates are rarely performed due to ethical concerns and difficulties associated with trials and recruitment. Consequently, dose selection in this population is primarily empirical. Scaling neonatal doses from adult doses does not account for developmental changes and may not accurately predict drug kinetics. This is especially important for gentamicin, a narrow therapeutic index aminoglycoside antibiotic. While gentamicin's bactericidal effect is associated with its peak plasma concentration, keeping trough concentrations below 1 µg/mL prevents toxicity and also helps to counteract adaptive resistance in bacteria such as Escherichia coli. In this study, physiologically based pharmacokinetic-pharmacodynamic (PBPK-PD) modeling was used to support and/or guide dosing decisions and to predict the antibacterial effect in preterm neonates. A gentamicin PBPK model was successfully verified in healthy adults and preterm neonates across all gestational ages. Clinical data from a neonatal intensive care unit at NYU Langone Hospital-Long Island was used to identify dosing regimens associated with increased incidence of elevated gentamicin trough concentrations in different preterm patient cohorts. Model predictions demonstrated that a higher dose with an extended-dosing interval (every 36 hours) in neonates with a postmenstrual age of 30 to 34 weeks and ≥35 weeks, with postnatal age 8 to 28 days and 0 to 7 days, respectively, were more likely to have a trough <1 µg/mL when compared with once-daily (every 24 hours) dosing. PBPK-PD modeling suggested that a higher dose administered every 36 hours may provide effective antibacterial therapy.

A Preterm Physiologically Based Pharmacokinetic Model. Part I: Physiological Parameters and Model Building

BACKGROUND

Developmental physiology can alter pharmacotherapy in preterm populations. Because of ethical and clinical constraints in studying this vulnerable age group, physiologically based pharmacokinetic models offer a viable alternative approach to predicting drug pharmacokinetics and pharmacodynamics in this population. However, such models require comprehensive information on the changes of anatomical, physiological and biochemical variables, where such data are not available in a single source.

OBJECTIVE

The objective of this study was to integrate the relevant physiological parameters required to build a physiologically based pharmacokinetic model for the preterm population.

METHODS

Published information on developmental preterm physiology and some drug-metabolising enzymes were collated and analysed. Equations were generated to describe the changes in parameter values during growth.

RESULTS

Data on organ size show different growth patterns that were quantified as functions of bodyweight to retain physiological variability and correlation. Protein binding data were quantified as functions of age as the body weight was not reported in the original articles. Ontogeny functions were derived for cytochrome P450 1A2, 3A4 and 2C9. Tissue composition values and how they change with age are limited.

CONCLUSIONS

Despite the limitations identified in the availability of some tissue composition values, the data presented in this article provide an integrated resource of system parameters needed for building a preterm physiologically based pharmacokinetic model.

Ontogeny of Phase I Metabolism of Drugs

Capturing ontogeny of enzymes involved in phase I metabolism is crucial to improve prediction of dose-concentration and concentration-effect relationships throughout infancy and childhood. Once captured, these patterns can be integrated in semiphysiologically or physiology-based pharmacokinetic models to support predictions in specific pediatric settings or to support pediatric drug development. Although these translational efforts are crucial, isoenzyme-specific ontogeny-based models should also incorporate data on variability of maturational and nonmaturational covariates (eg, disease, treatment modalities, pharmacogenetics). Therefore, this review provides a summary of the ontogeny of phase I drug-metabolizing enzymes, indicating current knowledge gaps and recent progresses. Furthermore, we tried to illustrate that straightforward translation of isoenzyme-specific ontogeny to predictions does not allow full exploration of scenarios of potential variability related to maturational (non-age-related variability, other isoenzymes or transporters) or nonmaturational (disease, pharmacogenetics) covariates, and necessitates integration in a "systems" concept.

Chloroquine Dosing Recommendations for Pediatric COVID-19 Supported by Modeling and Simulation

As chloroquine (CHQ) is part of the Dutch Centre for Infectious Disease Control coronavirus disease 2019 (COVID-19) experimental treatment guideline, pediatric dosing guidelines are needed. Recent pediatric data suggest that existing World Health Organization (WHO) dosing guidelines for children with malaria are suboptimal. The aim of our study was to establish best-evidence to inform pediatric CHQ doses for children infected with COVID-19. A previously developed physiologically-based pharmacokinetic (PBPK) model for CHQ was used to simulate exposure in adults and children and verified against published pharmacokinetic data. The COVID-19 recommended adult dosage regimen of 44 mg/kg total was tested in adults and children to evaluate the extent of variation in exposure. Based on differences in area under the concentration-time curve from zero to 70 hours (AUC0-70h ) the optimal CHQ dose was determined in children of different ages compared with adults. Revised doses were re-introduced into the model to verify that overall CHQ exposure in each age band was within 5% of the predicted adult value. Simulations showed differences in drug exposure in children of different ages and adults when the same body-weight based dose is given. As such, we propose the following total cumulative doses: 35 mg/kg (CHQ base) for children 0-1 month, 47 mg/kg for 1-6 months, 55 mg/kg for 6 months-12 years, and 44 mg/kg for adolescents and adults, not to exceed 3,300 mg in any patient. Our study supports age-adjusted CHQ dosing in children with COVID-19 in order to avoid suboptimal or toxic doses. The knowledge-driven, model-informed dose selection paradigm can serve as a science-based alternative to recommend pediatric dosing when pediatric clinical trial data is absent.

Repository Describing an Aging Population to Inform Physiologically Based Pharmacokinetic Models Considering Anatomical, Physiological, and Biological Age-Dependent Changes

BACKGROUND

Aging is characterized by anatomical, physiological, and biological changes that can impact drug kinetics. The elderly are often excluded from clinical trials and knowledge about drug kinetics and drug-drug interaction magnitudes is sparse. Physiologically based pharmacokinetic modeling can overcome this clinical limitation but detailed descriptions of the population characteristics are essential to adequately inform models.

OBJECTIVE

The objective of this study was to develop and verify a population database for aging Caucasians considering anatomical, physiological, and biological system parameters required to inform a physiologically based pharmacokinetic model that included population variability.

METHODS

A structured literature search was performed to analyze age-dependent changes of system parameters. All collated data were carefully analyzed, and descriptive mathematical equations were derived.

RESULTS

A total of 362 studies were found of which 318 studies were included in the analysis as they reported rich data for anthropometric parameters and specific organs (e.g., liver). Continuous functions could be derived for most system parameters describing a Caucasian population from 20 to 99 years of age with variability. Areas with sparse data were identified such as tissue composition, but knowledge gaps were filled with plausible qualified assumptions. The developed population was implemented in Matlab^® and estimated system parameters from 1000 virtual individuals were in accordance with independent observed data showing the robustness of the developed population.

CONCLUSIONS

The developed repository for aging subjects provides a singular specific source for key system parameters needed for physiologically based pharmacokinetic modeling and can in turn be used to investigate drug kinetics and drug-drug interaction magnitudes in the elderly.

Investigating the Role of Altered Systemic Albumin Concentration on the Disposition of Theophylline in Adult and Pediatric Patients with Asthma by Using the Physiologically Based Pharmacokinetic Approach

Theophylline is commonly used for the treatment of asthma and has a low hepatic clearance. The changes in plasma albumin concentration occurring in asthma may affect the exposure of theophylline. The aim of the presented work was to predict theophylline pharmacokinetics (PK) after incorporating the changes in plasma albumin concentration occurring in patients with asthma into a physiologically based pharmacokinetic (PBPK) model to see whether these changes can affect the systemic theophylline concentrations in asthma. The PBPK model was developed following a systematic model building approach using Simcyp. The predictions were performed initially in healthy adults after intravenous and oral drug administration. Only when the developed adult PBPK model had adequately predicted theophylline PK in healthy adults, the changes in plasma albumin concentrations were incorporated into the model for predicting drug exposure in patients with asthma. After evaluation of the developed model in the adult population, it was scaled to children on physiologic basis. The model evaluation was performed by using visual predictive checks and comparison of ratio of observed and predicted (R_obs/Pre) PK parameters along with their 2-fold error range. The developed PBPK model has effectively described theophylline PK in both healthy and diseased populations, as R_obs/Pre for all the PK parameters were within the 2-fold error limit. The predictions in patients with asthma showed that there were no significant changes in PK parameters after incorporating the changes in serum albumin concentration. The mechanistic nature of the developed asthma-PBPK model can facilitate its extension to other drugs. SIGNIFICANCE STATEMENT: Exposure of a low hepatic clearance drug like theophylline may be susceptible to plasma albumin concentration changes that occur in asthma. These changes in systemic albumin concentrations can be incorporated into a physiologically based pharmacokinetic model to predict theophylline pharmacokinetics in adult and pediatric asthma populations. The presented work is focused on predicting theophylline absorption, distribution, metabolism, and elimination in adult and pediatric asthma populations after incorporating reported changes in serum albumin concentrations to see their impact on the systemic theophylline concentrations.

Pharmacokinetic modeling of intravenous sildenafil in newborns with congenital diaphragmatic hernia

PURPOSE

We developed a pharmacokinetic model of intravenous sildenafil in newborns with congenital diaphragmatic hernia (CDH) to achieve a target plasma concentration of over 50 μg/l.

METHODS

Twenty-three CDH newborns with pulmonary hypertension (64 blood samples) received intravenous sildenafil. Patients received a loading dose of 0.35 mg/kg (IQR 0.16 mg/kg) for 3 h, followed by a continuous infusion of 1.5 mg/kg/day (IQR 0.1 mg/kg/day). For model development, non-linear mixed modeling was used. Inter-individual variability (IIV) and inter-occasion variability were tested. Demographic and laboratory parameters were evaluated as covariates. Normalized prediction distribution errors (NPDE) and visual predictive check (VPC) were used for model validation.

RESULTS

A two-compartment disposition model of sildenafil and a one-compartment disposition model of desmethyl sildenafil (DMS) was observed with IIV in sildenafil and DMS clearance and volume of distribution of sildenafil. NPDE and VPC revealed adequate predictability. Only postnatal age increased sildenafil clearance. This was partly compensated by a higher DMS concentration, which also has a therapeutic effect. In this small group of patients, sildenafil was tolerated well.

CONCLUSIONS

This model for sildenafil in CDH patients shows that concentration-targeted sildenafil dosing of 0.4 mg/kg in 3 h, followed by 1.6 mg/kg/day continuous infusion achieves appropriate sildenafil plasma levels.

Rapidly maturing fentanyl clearance in preterm neonates

BACKGROUND

Fentanyl is frequently used off-label in preterm newborns. Due to very limited pharmacokinetic and pharmacodynamic data, fentanyl dosing is mostly based on bodyweight. This study describes the maturation of the pharmacokinetics in preterm neonates born before 32 weeks of gestation.

METHODS

442 plasma samples from 98 preterm neonates (median gestational age: 26.9 (range 23.9-31.9) weeks, postnatal age: 3 (range 0-68) days, bodyweight 1.00 (range 0.39-2.37) kg) were collected in an opportunistic trial and fentanyl plasma levels were determined. NONMEM V.7.3 was used to develop a population pharmacokinetic model and to perform simulations.

RESULTS

Fentanyl pharmacokinetics was best described by a two-compartment model. A pronounced non-linear influence of postnatal and gestational age on clearance was identified. Clearance (L/hour/kg) increased threefold, 1.3-fold and 1.01-fold in the first, second and third weeks of life, respectively. In addition, clearance (L/hour/kg) was 1.4-fold and 1.7-fold higher in case of a gestational age of 28 and 31 weeks, respectively, compared with 25 weeks. Volume of distribution changed linearly with bodyweight and was 8.7 L/kg. To achieve similar exposure across the entire population, a continuous infusion (µg/kg/hour) dose should be reduced by 50% and 25% in preterm neonates with a postnatal age of 0-4 days and 5-9 days in comparison to 10 days and older.

CONCLUSION

Because of low clearance, bodyweight-based dosages may result in fentanyl accumulation in neonates with the lowest postnatal and gestational ages which may require dose reduction. Together with additional information on the pharmacodynamics, the results of this study can be used to guide dosing.

Pharmacokinetic assessment of alprazolam-induced neonatal abstinence syndrome using physiologically based pharmacokinetic model

Sustained benzodiazepine use during pregnancy can induce neonatal abstinence syndrome (NAS). In this study, the association between NAS and plasma alprazolam concentration was examined using the measured neonatal concentrations in the time series as well as simulated plasma concentrations of pregnant woman and neonate by physiologically based pharmacokinetic (PBPK) modeling. A neonate born to a mother taking alprazolam daily throughout pregnancy exhibited symptoms such as apnea and vomiting from 9 h to 4 days after birth. Finnegan score was 7 at birth and decreased to 0 by day 4. Apnea improved by 24 h post-delivery and gastrointestinal symptoms disappeared by day 4. The plasma alprazolam concentration in the neonate was 15.2 ng/mL immediately after birth and gradually decreased over 3 days. Measured neonate and estimated maternal plasma alprazolam concentrations were within the 90% prediction intervals of each concentration by PBPK simulation using "pregnancy" and "pediatrics" population parameters including in Simcyp population-based ADME simulator. In conclusion, NAS symptoms such as apnea and digestive events disappeared in parallel with the decrease of the neonate's plasma alprazolam concentrations. Moreover, PBPK modeling and simulation is a useful methodology for toxicological assessment in special characteristics populations lacking specific experimental data.

Pharmacokinetic modelling and Bayesian estimation-assisted decision tools to optimize vancomycin dosage in neonates: only one piece of the puzzle

Introduction: Vancomycin is commonly administered to neonates, while observational data on therapeutic drug monitoring (TDM, trough levels) suggest that vancomycin exposure and dosage remain substandard. Area covered: Data on vancomycin pharmacokinetics (PK) and its covariates are abundant. Consequently, modeling is an obvious tool to improve targeted exposure, with a shift from TDM trough levels to area under the curve (AUC_24h) targets, as in adults. Continuous administration appeared as a practice to facilitate AUC_24h target attainment, while Bayesian model-supported targeting emerged as a novel tool. However, the AUC_24h/MIC (minimal inhibitory concentration) target itself should consider neonate-specific aspects (bloodstream infections, coagulase-negative staphylococci, protein binding, underexplored causes of variability, like assays, preparation and administration inaccuracies, or missing covariates). Expert opinion: To improve targeted exposure in neonates, initial vancomycin prescription should be based on 'a priori model-based individual dosing' using validated dosing regimens, followed by further tailoring by dosing optimization applying Bayesian estimation-assisted TDM. Future research should focus on the feasibility to integrate these tools (individualized dosing, Bayesian models) in clinical practice, and to perform PK/PD studies in the relevant animal models and human neonatal setting (coagulase-negative staphylococci, bloodstream infections).

Population Pharmacokinetic Modeling in the Presence of Missing Time-Dependent Covariates: Impact of Body Weight on Pharmacokinetics of Paracetamol in Neonates

Body weight is the primary covariate in pharmacokinetics of many drugs and dramatically changes during the first weeks of life of neonates. The objective of this study is to determine if missing body weights in preterm and term neonates affect estimates of model parameters and which methods can be used to improve performance of a population pharmacokinetic model of paracetamol. Data for our analysis were obtained from previously published studies on the pharmacokinetics of intravenous paracetamol in neonates. We adopted a population model of body weight change in neonates to implement three previously introduced methods of handling missing covariates based on data imputation, likelihood function modification, and full random effects modeling. All models were implemented in NONMEM 7.4, and population parameters were estimated using the FOCE method. Our major finding was that missing body weights minimally affect population estimates of pharmacokinetic parameters but do affect the covariate relationship parameters, particularly the one describing dependence of clearance on body weight. None of the tested methods changed estimates of between-subject variability nor impacted the predictive performance of the model. Our analysis shows that a modeling approach towards handling missing covariates allows borrowing information gathered in various studies as long as they target the same population. This approach is particularly useful for handling time-dependent missing covariates.

Physiologically-based pharmacokinetics of ziprasidone in pregnant women

AIMS

Pregnancy is associated with physiological changes that alter the pharmacokinetics (PK) of drugs. The aim of this study was to predict the PK of ziprasidone in pregnant women.

METHODS

A full physiologically-based pharmacokinetic (PBPK) model of ziprasidone was developed and validated for the non-pregnant population (healthy adults, paediatrics, geriatrics), and this was extended to the pregnant state to assess the change in PK profile of ziprasidone throughout pregnancy.

RESULTS

The PBPK model successfully predicted the ziprasidone disposition in healthy adult volunteers, wherein the predicted and observed AUC, C_max and t_max were within the fold-difference of 0.94-1.09, 0.89-1.40 and 0.80-1.08, respectively. The paediatric and geriatric population, also showed predicted AUC, C_max and t_max within a two-fold range of the observed values. The simulated exposure in pregnant women using a p-PBPK model showed no significant difference when compared to non-pregnant women.

CONCLUSIONS

The PBPK model predicted the impact of physiological changes during pregnancy on PK and exposure of ziprasidone, suggesting that dose adjustment is not necessary in this special population.

A Theoretical Physiologically-Based Pharmacokinetic Approach to Ascertain Covariates Explaining the Large Interpatient Variability in Tacrolimus Disposition

Physiologically‐based pharmacokinetic (PBPK) modeling allows assessment of the covariates contributing to the large pharmacokinetic (PK) variability of tacrolimus; these include multiple physiological and biochemical differences among patients. A PBPK model of tacrolimus was developed, including a virtual population with physiological parameter distributions reflecting renal transplant patients. The ratios of predicted to observed dose‐normalized maximum plasma concentration (C_max), 0–12‐hour area under the concentration–time curve (AUC_0–12 hour), and trough plasma concentration (C_trough) ranged from 0.92‐fold to 1.15‐fold, indicating good predictive performance. The model quantitatively indicated the impact of cytochrome P450 (CYP)3A4 abundance, hematocrit, and serum albumin levels, in addition to CYP3A5 genotype status, on tacrolimus PK and associated variability. Age‐dependent change in tacrolimus trough concentration in pediatric patients was mainly attributed to the CYP3A ontogeny profile. This study demonstrates the utility of PBPK modeling as a tool for mechanistic and quantitative assessment of the impact of patient physiological differences on observed large PK variability.

Physiologically based pharmacokinetic (PBPK) modeling and simulation in neonatal drug development: how clinicians can contribute

Introduction: Legal initiatives to stimulate neonatal drug development should be accompanied by development of valid research tools. Physiologically based (PB)-pharmacokinetic (PK) modeling and simulation are established tools, accepted by regulatory authorities. Consequently, PBPK holds promise to be a strong research tool to support neonatal drug development. Area covered: The currently available PBPK models still have poor predictive performance in neonates. Using an illustrative approach on distinct PK processes of absorption, distribution, metabolism, excretion, and real-world data in neonates, we provide evidence on the need to further refine available PBPK system parameters through generation and integration of new knowledge. This necessitates cross talk between clinicians and modelers to integrate knowledge (PK datasets, system knowledge, maturational physiology) or test and refine PBPK models. Expert opinion: Besides refining these models for 'small molecules', PBPK model development should also be more widely applied for therapeutic proteins and to determine exposure through breastfeeding. Researchers should also be aware that PBPK modeling in combination with clinical observations can also be used to elucidate age-related changes that are almost impossible to study based on in vivo or in vitro data. This approach has been explored for hepatic biliary excretion, renal tubular activity, and central nervous system exposure.

Development of growth equations from longitudinal studies of body weight and height in the full term and preterm neonate: From birth to four years postnatal age

Physiologically based pharmacokinetic (PBPK) models are developed from compound-independent information to describe important anatomical and physiological characteristics of an individual or population of interest. Modeling pediatric populations is challenging because of the rapid changes that occur during growth, particularly in the first few weeks and months after birth. Neonates who are born premature pose several unique challenges in PBPK model development. To provide appropriate descriptions for body weight (BW) and height (Ht) for age and appropriate incremental gains in PBPK models of the developing preterm and full term neonate, anthropometric measurements collected longitudinally from 1,063 preterm and 158 full term neonates were combined with 2,872 cross-sectional measurements obtained from the NHANES 2007-2010 survey. Age-specific polynomial growth equations for BW and Ht were created for male and female neonates with corresponding gestational birth ages of 25, 28, 31, 34, and 40 weeks. Model-predicted weights at birth were within 20% of published fetal/neonatal reference standards. In comparison to full term neonates, postnatal gains in BW and Ht were slower in preterm subgroups, particularly in those born at earlier gestational ages. Catch up growth for BW in neonates born at 25, 28, 31, and 34 weeks gestational age was complete by 13, 8, 6, and 2 months of life (males) and by 10, 6, 5, and 2 months of life (females), respectively. The polynomial growth equations reported in this paper represent extrauterine growth in full term and preterm neonates and differ from the intrauterine growth standards that were developed for the healthy unborn fetus.

PBPK Model of Morphine Incorporating Developmental Changes in Hepatic OCT1 and UGT2B7 Proteins to Explain the Variability in Clearances in Neonates and Small Infants

Morphine has large pharmacokinetic variability, which is further complicated by developmental changes in neonates and small infants. The impacts of organic cation transporter 1 (OCT1) genotype and changes in blood-flow on morphine clearance (CL) were previously demonstrated in children, whereas changes in UDP-glucuronosyltransferase 2B7 (UGT2B7) activity showed a small effect. This study, targeting neonates and small infants, was designed to assess the influence of developmental changes in OCT1 and UGT2B7 protein expression and modified blood-flow on morphine CL using physiologically based pharmacokinetic (PBPK) modeling. The implementation of these three age-dependent factors into the pediatric system platform resulted in reasonable prediction for an age-dependent increase in morphine CL in these populations. Sensitivity of morphine CL to changes in cardiac output increased with age up to 3 years, whereas sensitivity to changes in UGT2B7 activity decreased. This study suggests that morphine exhibits age-dependent extraction, likely due to the developmental increase in OCT1 and UGT2B7 protein expression/activity and hepatic blood-flow.

Consequences of Phenytoin Exposure on Hepatic Cytochrome P450 Expression during Postnatal Liver Maturation in Mice

The induction of cytochrome P450 (P450) enzymes in response to drug treatment is a significant contributing factor to drug-drug interactions, which may reduce therapeutic efficacy and/or cause toxicity. Since most studies on P450 induction are performed in adults, enzyme induction at neonatal, infant, and adolescent ages is not well understood. Previous work defined the postnatal ontogeny of drug-metabolizing P450s in human and mouse livers; however, there are limited data on the ontogeny of the induction potential of each enzyme in response to drug treatment. Induction of P450s at the neonatal age may also cause permanent alterations in P450 expression in adults. The goal of this study was to investigate the short- and long-term effects of phenytoin treatment on mRNA and protein expressions and enzyme activities of CYP2B10, 2C29, 3A11, and 3A16 at different ages during postnatal liver maturation in mice. Induction of mRNA immediately following phenytoin treatment appeared to depend on basal expression of the enzyme at a specific age. While neonatal mice showed the greatest fold changes in CYP2B10, 2C29, and 3A11 mRNA expression following treatment, the levels of induced protein expression and enzymatic activity were much lower than that of induced levels in adults. The expression of fetal CYP3A16 was repressed by phenytoin treatment. Neonatal treatment with phenytoin did not permanently induce enzyme expression in adulthood. Taken together, our data suggest that inducibility of drug-metabolizing P450s is much lower in neonatal mice than it is in adults and neonatal induction by phenytoin is not permanent.

Drug evaluation studies in neonates: how to overcome the current limitations

INTRODUCTION

Regulatory initiatives have stimulated drug research in infants, but the potential impact of drugs to improve health outcome in neonates remains underexplored. Areas covered: In this review, we focus on current limitations in drug evaluation studies and how to overcome these. The low volume of studies has additional weaknesses such as single center studies, non-commercial sponsorship, overrepresentation of high postulated risk reductions, and underrepresentation of therapeutic exploratory studies. Master protocols and selection criteria for neonatal centers to participate in studies are useful to improve logistics related to performance. Limitations also relate to inaccurate assessment of drug effects (efficacy/safety). This is because of poor symptom recognition, case definitions, and suboptimal data on adverse drug reactions (ADRs) epidemiology. To overcome these limitations, it is necessary to develop core outcome sets, reference values, and specific ADR tools. The limitations identified and approaches suggested to improve drug evaluation are illustrated using neonatal abstinence syndrome as an example. Expert commentary: We anticipate to see an evolving neonatal clinical pharmacology discipline driven by neonatal pathophysiology and knowledge. Multidisciplinary collaborative efforts between health care providers, academia, pharmaceutical industry, advocacy groups and regulatory agencies are crucial to improve the impact of drug evaluation studies in neonates.

Drug metabolism in early infancy: opioids as an illustration

INTRODUCTION

Drug dosing in infants frequently depends on body weight as a crude indicator for maturation. Fentanyl (metabolized by Cytochrome P450 3A4) and morphine (glucuronidated by UDP-glucuronosyltransferase-2B7) served as model drugs to provide insight in maturation patterns of these enzymes and provide understanding of the impact of non-maturational factors to optimize dosing in infants. Areas covered: Systematic searches on metabolism and population pharmacokinetic (Pop-PK) models for fentanyl and morphine were performed. Pre- and post-model selection criteria were applied to assess and evaluate the validity of these models. It was observed that maturational changes have been rather well investigated, be it with variability in the maturational function estimates. The same holds true for Pop-PK models, where non-maturational covariates have also been reported (pharmacogenetics, disease state or external influences), although less incorporated in the PK models and with limited knowledge on mechanisms involved. Expert opinion: PK models for fentanyl and morphine are currently available. Consequently, we suggest that researchers should not continue to develop new models, but should investigate whether collected data fit in already existing models and provide additional value concerning the impact of (non)-maturational factors like drug-drug interactions or pharmacogenetics.

Challenges and Opportunities for Increasing the Knowledge Base Related to Drug Biotransformation and Pharmacokinetics during Growth and Development

It is generally acknowledged that there is a need and role for informative pharmacokinetic models to improve predictions and simulation as well as individualization of drug therapy in pediatric populations of different ages and developmental stages. This special issue contains more than 20 papers responding to the challenge of providing new information on scaling factors, ontogeny functions for drug metabolizing enzymes and transporters, the mechanisms underlying the observed developmental trajectories for these gene products, age-dependent changes in physiologic processes affecting drug disposition in children, as well as in vitro and in vivo studies describing the relative contribution of ontogeny and genetic factors as sources of variability in drug disposition in children. Considered together, these contributions serve to illustrate some of the current limitations regarding sample availability, number, and quality, but also provide a framework that allows for the potential value of the results of a given study to be interpreted within the context of these limitations. Among the challenges for the future are improving our understanding of the mechanisms regulating age-dependent changes in factors influencing drug disposition and response, thereby facilitating generalization to systems lacking detailed data, better integrating age-dependent changes in pharmacokinetics with age-dependent changes in pharmacodynamics, and allowing better predictability and individualization of drug disposition and response across the pediatric age spectrum.

Physiologically Based Pharmacokinetic Prediction of Linezolid and Emtricitabine in Neonates and Infants

INTRODUCTION

Modeling and simulation approaches are increasingly being utilized in pediatric drug development. Physiologically based pharmacokinetic (PBPK) modeling offers an enhanced ability to predict age-related changes in pharmacokinetics in the pediatric population.

METHODS

In the current study, adult PBPK models were developed for the renally excreted drugs linezolid and emtricitabine. PBPK models were then utilized to predict pharmacokinetics in pediatric patients for various age groups from the oldest to the youngest patients in a stepwise approach.

RESULTS

Pharmacokinetic predictions for these two drugs in the pediatric population, including infants and neonates, were within a twofold range of clinical observations. Based on this study, linezolid and emtricitabine pediatric PBPK models incorporating the ontogeny in renal maturation describe the pharmacokinetic differences between adult and pediatric populations, even though the contribution of renal clearance to the total clearance of two drugs was very different (30 % for linezolid vs. 86 % for emtricitabine).

CONCLUSION

These results suggest that PBPK modeling may provide one option to help predict the pharmacokinetics of renally excreted drugs in neonates and infants.

Humans Vary, So Cardiac Models Should Account for That Too!

The utilization of mathematical modeling and simulation in drug development encompasses multiple mathematical techniques and the location of a drug candidate in the development pipeline. Historically speaking they have been used to analyze experimental data (i.e., Hill equation) and clarify the involved physical and chemical processes (i.e., Fick laws and drug molecule diffusion). In recent years the advanced utilization of mathematical modeling has been an important part of the regulatory review process. Physiologically based pharmacokinetic (PBPK) models identify the need to conduct specific clinical studies, suggest specific study designs and propose appropriate labeling language. Their application allows the evaluation of the influence of intrinsic (e.g., age, gender, genetics, disease) and extrinsic [e.g., dosing schedule, drug-drug interactions (DDIs)] factors, alone or in combinations, on drug exposure and therefore provides accurate population assessment. A similar pathway has been taken for the assessment of drug safety with cardiac safety being one the most advanced examples. Mechanistic mathematical model-informed safety evaluation, with a focus on drug potential for causing arrhythmias, is now discussed as an element of the Comprehensive in vitro Proarrhythmia Assay. One of the pillars of this paradigm is the use of an in silico model of the adult human ventricular cardiomyocyte to integrate in vitro measured data. Existing examples (in vitro—in vivo extrapolation with the use of PBPK models) suggest that deterministic, epidemiological and clinical data based variability models can be merged with the mechanistic models describing human physiology. There are other methods available, based on the stochastic approach and on population of models generated by randomly assigning specific parameter values (ionic current conductance and kinetic) and further pruning. Both approaches are briefly characterized in this manuscript, in parallel with the drug-specific variability.

European regulatory perspective on pediatric physiologically based pharmacokinetic models

Physiologically based pharmacokinetic (PBPK) models offer a mechanistic understanding of the disposition of the drug in the body. When well informed and conducted, this may lead to more efficient clinical studies in the vulnerable pediatric population. A review of pediatric submissions to European regulatory authorities has shown a limited number of recent examples. The use of PBPK models to inform pediatric drug development is encouraged. It is, however, important to consider the confidence in the predictions. A qualification of the PBPK platform for the intended purpose should be performed, and a learn-and-confirm approach is recommended. Further research in this area is encouraged to inform important parameters, and to increase availability of pediatric data for model qualification.

Characterization of Contributing Factors to Variability in Morphine Clearance Through PBPK Modeling Implemented With OCT1 Transporter

Morphine shows large interindividual variability in its pharmacokinetics; however, the cause of this has not been fully addressed. The variability in morphine disposition is considered to be due to a combination of pharmacogenetic and physiological determinants related to morphine disposition. We previously reported the effect of organic cation transporter (OCT1) genotype on morphine disposition in pediatric patients. To further explore the underlying mechanisms for variability arising from relevant determinants, including OCT1, a physiologically based pharmacokinetic (PBPK) model of morphine was developed. The PBPK model predicted morphine concentration‐time profiles well, in both adults and children. Almost all of the observed morphine clearances in pediatric patients fell within a twofold range of median predicted values for each OCT1 genotype in each age group. This PBPK modeling approach quantitatively demonstrates that OCT1 genotype, age‐related growth, and changes in blood flow as important contributors to morphine pharmacokinetic (PK) variability.

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.

Recent Advances in Development and Application of Physiologically-Based Pharmacokinetic (PBPK) Models: a Transition from Academic Curiosity to Regulatory Acceptance

There is a renewed surge of interest in applications of physiologically-based pharmacokinetic (PBPK) models by the pharmaceutical industry and regulatory agencies. Developing PBPK models within a systems pharmacology context allows separation of the parameters pertaining to the animal or human body (the system) from that of the drug and the study design which is essential to develop generic drug-independent models used to extrapolate PK/PD properties in various healthy and patient populations. This has expanded the classical paradigm to a ‘predict-learn-confirm-apply’ concept. Recently, a number of drug labels are informed by simulation results generated using PBPK models. These cases show that either the simulations are used in lieu of conducting clinical studies or have informed the drug label that otherwise would have been silent in some specific situations. It will not be surprising to see applications of these models in implementing precision dosing at the point of care in the near future.

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.