A Mechanistic Approach for the Scaling of Clearance in Children

Extrapolation of Midazolam Disposition in Neonates Using Physiological-Based Pharmacokinetic/Pharmacodynamic Modeling

There is a shortage of data in clinical studies of neonatal populations, which often utilize extrapolation strategies and model simulation techniques to support drug development and clinical applications. This study established an adult physiological-based pharmacokinetic/pharmacodynamic (PBPK/PD) model in the modeling software and extended it to neonates using pediatric extrapolation strategies based on maturation formulas for plasma albumin and CYP3A4/5. The neonatal model was then utilized to simulate midazolam dosage regimens for sedation in newborns. Individualized validation for adults indicated that 95.1% of predicted concentration values and all area under curve (AUC) values fell within a 2-fold range. The extrapolated neonatal model showed 84.4% of predicted concentrations within 2-fold, an absolute average fold error (AAFE) valuen <2, and an average fold error (AFE) value between 0.5 and 1.5, confirming the model's adequacy. The validated neonatal PBPK/PD model indicated that virtual term neonates maintained the target plasma concentration for 25 hours with the recommended dosage (0.06 mg/kg/h, intravenous infusion 12 hours). Premature infants may require a slightly higher dose than the label's recommendation (0.03 mg/kg/h, intravenous infusion 12 hours). Our findings recommend this research strategy based on extrapolation and model simulation for drug dose prediction and optimization in the neonatal population.

Physiologically based pharmacokinetic (PBPK) modeling of gliclazide for different genotypes of CYP2C9 and CYP2C19

Gliclazide is a sulfonylurea hypoglycemic agent used to treat type 2 diabetes. Cytochrome P450 (CYP) 2C9 and CYP2C19 are primarily involved in the hepatic metabolism of gliclazide. The two CYP isozymes are highly polymorphic, and their genetic polymorphisms are known to significantly impact the pharmacokinetics of gliclazide. In the present study, the physiologically based pharmacokinetic (PBPK) model was developed using data from subjects whose pharmacokinetic parameters were influenced by the genetic polymorphisms of the CYP metabolic enzymes. All predicted plasma concentration-time profiles generated by the model showed visual agreement with the observed data, and the pharmacokinetic results were within the twofold error range. Individual simulation results showed additional metrics: average fold error (- 0.19 to 0.07), geometric mean fold error (1.13-1.56), and mean relative deviation (1.18-1.58) for AUC, Cmax, T1/2, Tmax, CL/F, and Vd values. These results met the standard evaluation criteria. The validation across a total of 8 studies and 7 races also satisfied the twofold error range for AUC, Cmax, and T1/2. Therefore, variations in gliclazide exposure according to individuals' CYP2C9 and CYP2C19 genotypes were properly captured through PBPK modeling in this study. This PBPK model may allow us to predict the gliclazide pharmacokinetics of patients with genetic polymorphisms in CYP2C9 and CYPC19 under various conditions, ultimately contributing to the realization of individualized drug therapy.

Dosage Optimization Using Physiologically Based Pharmacokinetic Modeling for Pediatric Patients with Renal Impairment: A Case Study of Meropenem

The pharmacokinetics of renally eliminated antibiotics can be influenced by changes associated with renal function and development in a growing subject. Little is known about the effects of renal insufficiency on the pharmacokinetics of meropenem in pediatric subjects. The aim of this study was to develop a physiologically based pharmacokinetic (PBPK) model of meropenem for pediatric patients that can be used to optimize meropenem dosing in pediatric patients with renal impairment (RI). The PBPK model was developed using GastroPlus™ 9.9 based on clinical data obtained from the literature and then scaled to pediatric patients with RI for dose optimization of meropenem. The goodness of fit of the model was assessed by comparing the predicted values of AUC0-t, AUC0-α, and Cmax with the observed data and the average fold errors (AFE). The AFE values for AUC0-t, AUC0-α, and Cmax in the pediatric population were measured to be 1.60, 1.08, and 1.48, respectively. In addition, dose optimization was performed in virtual pediatric populations with varying degrees of RI and a dose reduction to 10 mg/kg and 7.5 mg/kg was recommended for moderate and severe RI, respectively. In all virtual pediatric populations with RI, the plasma concentration reached the recommended time above the minimum inhibitory concentration (MIC) at all optimized doses. The developed PBPK model for meropenem provides a quantitative tool to assess the impact of RI on the pharmacokinetics of meropenem in pediatric patients, which may be useful for optimizing the dosing regimen.

Physiologically Based Pharmacokinetic Modeling of Vancomycin in Critically Ill Neonates: Assessing the Impact of Pathophysiological Changes

Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.

Dosing of Venetoclax in Pediatric Patients with Relapsed Acute Myeloid Leukemia: Analysis of Developmental Pharmacokinetics and Exposure-Response Relationships

PURPOSE

This work aimed to characterize the pharmacokinetics and exposure-response relationships of venetoclax in pediatric patients with relapsed or refractory (R/R) acute myeloid leukemia (AML) to identify venetoclax doses to be administered to pediatric patients in the phase 3 study.

METHODS

Data from 121 patients across three phase 1 studies enrolling pediatric patients with R/R malignancies were utilized to develop a population pharmacokinetic model to describe venetoclax pharmacokinetics in pediatric patients. Individual patient average venetoclax plasma concentration up to the event of interest, derived based on the population pharmacokinetics analysis, was used to evaluate the exposure-response relationships to efficacy (complete response) and safety (neutropenia and thrombocytopenia) endpoints for patients with AML who received venetoclax in combination with azacitidine, decitabine, or cytarabine (n = 36). The population pharmacokinetic model was then used to simulate exposures in pediatric age- and weight-based subgroups to identify the venetoclax doses for pediatric patients.

FINDINGS

The pharmacokinetic data were adequately described by the two-compartment population pharmacokinetic model with first-order absorption and elimination. The model accounted for cytochrome P450 3A developmental changes using a maturation function and incorporated allometric scaling to account for growth and body size effect. Weight was identified as a statistically significant covariate on clearance and volume of distribution and retained in the final model. Population pharmacokinetic estimates were comparable to previously reported estimates in adults. Exposure-response analyses suggested that the clinical efficacy of venetoclax in combination with high-dose cytarabine (HDAC) is maximized at 600 mg adult-equivalent, and higher doses are unlikely to enhance clinical efficacy. Venetoclax 600 mg adult-equivalent was selected for further development in combination with HDAC. Additionally, venetoclax 400 mg adult-equivalent was selected for bridging/maintenance therapy in combination with azacitidine. Flat exposure-response relationships were observed with Grade ≥3 neutropenia and thrombocytopenia. Doses were selected based on weight (allometric scaling) for children aged ≥2 years old and based on weight and CYP3A ontogeny for children aged <2 years. The selected age- and weight-based dosing scheme of venetoclax is projected to achieve venetoclax exposures in pediatric subgroups comparable to those observed in adults receiving venetoclax 400 mg or 600 mg.

IMPLICATIONS

This work characterized the pharmacokinetics and exposure-response relationships of venetoclax in pediatric patients and guided the selection of pediatric dosing regimens in support of the venetoclax phase 3 trial in pediatric AML (NCT05183035).

CLINICAL STUDIES

NCT03236857, NCT03181126, and NCT03194932.

Application of physiologically based pharmacokinetic modeling of novel drugs approved by the U.S. food and drug administration

Physiologically based pharmacokinetic (PBPK) models which can leverage preclinical data to predict the pharmacokinetic properties of drugs rapidly became an essential tool to improve the efficiency and quality of novel drug development. In this review, by searching the Application Review Files in Drugs@FDA, we analyzed the current application of PBPK models in novel drugs approved by the U.S. Food and Drug Administration (FDA) in the past five years. According to the results, 243 novel drugs were approved by the FDA from 2019 to 2023. During this period, 74 Application Review Files of novel drugs approved by the FDA that used PBPK models. PBPK models were used in various areas, including drug-drug interactions (DDI), organ impairment (OI) patients, pediatrics, drug-gene interaction (DGI), disease impact, and food effects. DDI was the most widely used area of PBPK models for novel drugs, accounting for 74.2 % of the total. Software platforms with graphical user interfaces (GUI) have reduced the difficulty of PBPK modeling, and Simcyp was the most popular software platform among applicants, with a usage rate of 80.5 %. Despite its challenges, PBPK has demonstrated its potential in novel drug development, and a growing number of successful cases provide experience learned for researchers in the industry.

Application of Physiologically Based Pharmacokinetic Modeling to Characterize the Effects of Age and Obesity on the Disposition of Levetiracetam in the Pediatric Population

BACKGROUND

Levetiracetam is an antiseizure medication used for several seizure types in adults and children aged 1 month and older; however, due to a lack of data, pharmacokinetic (PK) variability of levetiracetam is not adequately characterized in certain populations, particularly neonates, children younger than 2 years of age, and children older than 2 years of age with obesity.

OBJECTIVE

This study aimed to address the gap by leveraging PK data from two prospective standard-of-care pediatric trials (n = 88) covering an age range from 1 month to 19 years, including those with obesity (64%), and applying a physiologically based PK (PBPK) modeling framework.

METHODS

A published PBPK model of levetiracetam for children aged 2 years and older was extended to pediatric patients younger than 2 years of age and patients older than 2 years of age with obesity by accounting for the obesity and age-related changes in PK using PK-Sim® software. The prospective pediatric data, along with the literature data for neonates and children younger than 2 years of age, were used to evaluate the extended PBPK models.

RESULTS

Overall, 82.4% of data fell within the 90% interval of model-predicted concentrations, with an average fold error within twofold of the accepted criteria. PBPK modeling revealed that children with obesity had lower weight-normalized clearances (0.053 L/h/kg) on average than children without obesity (0.063 L/h/kg). The effect of maturation was well-characterized, resulting in comparable PBPK-simulated, weight-normalized clearances for neonates and children younger than 2 years of age reported from the literature.

CONCLUSIONS

PBPK modeling simulations revealed that the current US FDA-labeled pediatric dosing regimen listed in the prescribing information can produce the required exposure of levetiracetam in these target populations with dose adjustments for children with obesity aged 4 years to younger than 16 years.

Activity-Based Protein Profiling to Probe Relationships between Cytochrome P450 Enzymes and Early-Age Metabolism of Two Polycyclic Aromatic Hydrocarbons (PAHs): Phenanthrene and Retene

A growing body of literature has linked early-life exposures to polycyclic aromatic hydrocarbons (PAH) with adverse neurodevelopmental effects. Once in the body, metabolism serves as a powerful mediator of PAH toxicity by bioactivating and detoxifying PAH metabolites. Since enzyme expression and activity vary considerably throughout human development, we evaluated infant metabolism of PAHs as a potential contributing factor to PAH susceptibility. We measured and compared rates of phenanthrene and retene (two primary PAH constituents of woodsmoke) metabolism in human hepatic microsomes from individuals ≤21 months of age to a pooled sample (n = 200) consisting primarily of adults. We used activity-based protein profiling (ABPP) to characterize cytochrome P450 enzymes (CYPs) in the same hepatic microsome samples. Once incubated in microsomes, phenanthrene demonstrated rapid depletion. Best-fit models for phenanthrene metabolism demonstrated either 1 or 2 phases, depending on the sample, indicating that multiple enzymes could metabolize phenanthrene. We observed no statistically significant differences in phenanthrene metabolism as a function of age, although samples from the youngest individuals had the slowest phenanthrene metabolism rates. We observed slower rates of retene metabolism compared with phenanthrene also in multiple phases. Rates of retene metabolism increased in an age-dependent manner until adult (pooled) metabolism rates were achieved at ∼12 months. ABPP identified 28 unique CYPs among all samples, and we observed lower amounts of active CYPs in individuals ≤21 months of age compared to the pooled sample. Phenanthrene metabolism correlated to CYPs 1A1, 1A2, 2C8, 4A22, 3A4, and 3A43 and retene metabolism correlated to CYPs 1A1, 1A2, and 2C8 measured by ABPP and vendor-supplied substrate marker activities. These results will aid efforts to determine human health risk and susceptibility to PAHs exposure during early life.

Maximum likelihood estimation of renal transporter ontogeny profiles for pediatric PBPK modeling

Optimal treatment of infants with many renally cleared drugs must account for maturational differences in renal transporter (RT) activity. Pediatric physiologically-based pharmacokinetic (PBPK) models may incorporate RT activity, but this requires ontogeny profiles for RT activity in children, especially neonates, to predict drug disposition. Therefore, RT expression measurements from human kidney postmortem cortical tissue samples were normalized to represent a fraction of mature RT activity. Using these data, maximum likelihood estimated the distributions of RT activity across the pediatric age spectrum, including preterm and term neonates. PBPK models of four RT substrates (acyclovir, ciprofloxacin, furosemide, and meropenem) were evaluated with and without ontogeny profiles using average fold error (AFE), absolute average fold error (AAFE), and proportion of observations within the 5-95% prediction interval. Novel maximum likelihood profiles estimated ontogeny distributions for the following RT: OAT1, OAT3, OCT2, P-gp, URAT1, BCRP, MATE1, MRP2, MRP4, and MATE-2 K. Profiles for OAT3, P-gp, and MATE1 improved infant furosemide and neonate meropenem PBPK model AFE from 0.08 to 0.70 and 0.53 to 1.34 and model AAFE from 12.08 to 1.44 and 2.09 to 1.36, respectively, and improved the percent of data within the 5-95% prediction interval from 48% to 98% for neonatal ciprofloxacin simulations, respectively. Even after accounting for other critical population-specific maturational differences, novel RT ontogeny profiles substantially improved neonatal PBPK model performance, providing validated estimates of maturational differences in RT activity for optimal dosing in children.

Maternal Ezetimibe Concentrations Measured in Breast Milk and Its Use in Breastfeeding Infant Exposure Predictions

BACKGROUND

Lactating mothers taking ezetimibe, an antihyperlipidemic agent, may be hesitant to breastfeed despite the known benefit of breastfeeding to both mother and infant. Currently, no data exist on the presence or concentration of ezetimibe and its main active metabolite, ezetimibe-glucuronide (EZE-glucuronide), in human breast milk.

METHODS

Voluntary breast milk samples containing ezetimibe and EZE-glucuronide were attained from lactating mothers taking ezetimibe as part of their treatment. An assay was developed and validated to measure ezetimibe and EZE-glucuronide concentrations in breast milk. A workflow that utilized a developed and evaluated pediatric physiologically based pharmacokinetic (PBPK) model, the measured concentrations in milk, and weight-normalized breast milk intake volumes was applied to predict infant exposures and determine the upper area under the curve ratio (UAR).

RESULTS

Fifteen breast milk samples from two maternal-infant pairs were collected. The developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay showed an analytical range of 0.039-5.0 ng/mL and 0.39-50.0 ng/mL for ezetimibe and EZE-glucuronide, respectively. The measured concentrations in the breast milk samples were 0.17-1.02 ng/mL and 0.42-2.65 ng/mL of ezetimibe and EZE-glucuronide, respectively. The evaluated pediatric PBPK model demonstrated minimal exposure overlap in adult therapeutic dose and breastfed infant simulated area under the concentration-time curve from time zero to 24 h (AUC24). Calculated UAR across infant age groups ranged from 0.0015 to 0.0026.

CONCLUSIONS

PBPK model-predicted ezetimibe and EZE-glucuronide exposures and UAR suggest that breastfeeding infants would receive non-therapeutic exposures. Future work should involve a 'mother-infant pair study' to ascertain breastfed infant plasma ezetimibe and EZE-glucuronide concentrations to confirm the findings of this work.

Physiologically Based Pharmacokinetic Modeling of Lacosamide in Patients With Hepatic and Renal Impairment and Pediatric Populations to Support Pediatric Dosing Optimization

PURPOSE

Lacosamide (LCM) is a new-generation anti-seizure medication that is efficacious in patients with focal seizures with or without secondary generalization. Until now, the efficacy, safety, and tolerability of LCM are still lacking in Chinese epilepsy patients, particularly for pediatric populations and patients with renal or hepatic impairment.

METHODS

This study was conducted to develop a physiologically based pharmacokinetic (PBPK) model to characterize the pharmacokinetics of LCM in Chinese populations and predict the pharmacokinetics of LCM in Chinese pediatric populations and patients with renal or hepatic impairment. Using data from clinical investigations, the developed PBPK model was validated by comparing predicted and observed blood concentration data.

FINDINGS

Doses should be reduced to approximately 82%, 75%, 63%, and 76% of the Chinese healthy adult dose in patients with mild, moderate, and severe renal impairment and end-stage renal disease; and approximately 89%, 72%, and 36% of the Chinese healthy adult dose in patients with Child Pugh-A, B, and C hepatic impairment. For pediatric populations, intravenous doses should be adjusted to 1.75 mg/kg for newborns, 2.5 mg/kg for toddlers, 2.2 mg/kg mg for preschool and school age, and 2 mg/kg mg for adolescents to achieve an equivalent plasma exposure of 2 mg/kg LCM in adults. The oral doses should be adjusted to 20 mg for toddlers, 32 mg for preschool, 45 mg for school age, and 95 mg for adolescents to achieve an approximately equivalent plasma exposure of 100 mg LCM in adults.

IMPLICATIONS

The PBPK model of LCM can be utilized to optimize dosage regimens for special populations.

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.

Development and Verification of a Japanese Pediatric Physiologically Based Pharmacokinetic Model with Emphasis on Drugs Eliminated by Cytochrome P450 or Renal Excretion

Physiologically based pharmacokinetic (PBPK) models are useful in bridging drug exposure in different ethnic groups, and there is increasing regulatory application of this approach in adults. Reported pediatric PBPK models tend to focus on the North European population, with few examples in other ethnic groups. This study describes the development and verification of a Japanese pediatric PBPK population. The development of the model was based on the existing North European pediatric population. Japanese systems and clinical data were collated from public databases and the literature, and the underlying demographics and equations were optimized so that physiological outputs represented the Japanese pediatric population. The model was tested using 14 different small molecule drugs, eliminated by a variety of pathways, including cytochrome P450 3A4 (CYP3A4) metabolism and renal excretion. Given the limitations of the clinical data, the overall performance of the model was good, with 44/62 predictions for PK parameters (area under the plasma drug concentration-time curve, AUC; maximum serum concentration, Cmax ; clearance, CL) being within 0.8- to 1.25-fold, 56/62 within 0.67- to 1.5-fold, and 61/62 within 0.5- to 2.0-fold of the observed values. Specific results for the 5 CYP3A4 substrates showed 20/31 cases were predicted within 0.8- to 1.25-fold, 27/31 within 0.67- to 1.5-fold, and all were within 0.5- to 2.0-fold of the observed values. Given the increased regulatory use of pediatric PBPK in drug development, expanding these models to other ethnic groups are important. Considering qualifying these models based on the context of use, there is a need to expand on the current research to include a larger range of drugs with different elimination pathways. Collaboration among academic, industry, model providers, and regulators will facilitate further development.

Use of Developmental Midazolam and 1-Hydroxymidazolam Data with Pediatric Physiologically Based Modeling to Assess Cytochrome P450 3A4 and Uridine Diphosphate Glucuronosyl Transferase 2B4 Ontogeny In Vivo

Pediatric physiologically based pharmacokinetics modeling in drug development has grown in the past decade but uncertainty remains regarding ontogeny of some drug metabolizing enzymes. In this study, a midazolam and 1-hydroxymidazolam physiologically based pharmacokinetic model (PBPK) model was developed and used to define the ontogeny for hepatic cytochrome P450 (CYP) 3A4 and uridine diphosphate glucuronosyl transferase (UGT) 2B4. Data for model development and pharmacokinetic studies on intravenous midazolam in adults and pediatrics were collated from the literature. The PBPK model was verified in the adult population and then used to compare the performance of two ontogeny profiles for CYP3A4 in terms of parent drug elimination in pediatrics. Four studies also published data on the 1-hydroxymidazolam, and this was used to evaluate the known ontogeny for UGT2B4.For midazolam elimination, the Upreti CYP3A4 ontogeny performed better than Salem; mean error (bias) and mean squared error (precision) were 0.14 and 0.064 compared with 0.69 and 1.21, respectively. For 1-hydroxymidazolam elimination, the Simcyp default ontogeny of UGT2B4 appeared to perform best for studies covering the age range 0.5 to 15.7 years, while for a study in younger ages 0 to 1 years it was the Badee UGT2B4 ontogeny. In preterm neonates, overall expression of UGT appeared to be around 10% of that in adults.Identifying the optimal model of CYP3A4 ontogeny is important for the regulatory use of PBPK. The results for midazolam are conclusive but research about other CYP3A4 metabolized compounds will underpin generalizability of the CYP3A4 ontogeny. UGT2B4 ontogeny is less certain, but this study indicates the most likely scenarios. SIGNIFICANCE STATEMENT: A PBPK model for midazolam and 1-hydroxymidazolam was developed to test various ontogeny scenarios for CYP3A4 and UGT2B4. The CYP3A4 ontogeny of Upreti resulted in more accurate prediction of midazolam CL across nine clinical studies, age range birth to 18 years. 1-Hydroxy midazolam was used as a marker of UGT. The Simcyp default 'no ontogeny' profiles for UGT2B4 performed the best; however, for <1 year of age, there was some evidence of overactivity of this enzyme compared to adults.

Model-informed approach to support pediatric dosing for the pan-PI3K inhibitor copanlisib in children and adolescents with relapsed/refractory solid tumors

Copanlisib is an intravenously administered phosphatidylinositol 3-kinase (PI3K) inhibitor which was investigated in pediatric patients with relapsed/refractory solid tumors. A model-informed approach was undertaken to support and confirm an empirically selected starting dose of 28 mg/m2 for pediatric patients ≥1 year old, corresponding to 80% of the adult recommended dose adjusted for body surface area. An adult physiologically based pharmacokinetic (PBPK) model was initially established using copanlisib physicochemical and disposition properties and clinical pharmacokinetics (PK) data and was shown to adequately capture clinical PK across a range of copanlisib doses in adult cancer patients. The adult PBPK model was then extended to the pediatric population through incorporation of age-dependent anatomical and physiological changes and used to simulate copanlisib exposures in pediatric cancer patient age groups. The pediatric PBPK model predicted that the copanlisib 28 mg/m2 dose would achieve similar copanlisib exposures across pediatric ages when compared with historical adult exposures following the approved copanlisib 60 mg dose administered on Days 1, 8, and 15 of a 28-day cycle. Clinical PK were collected from a phase I study in pediatric patients with relapsed/refractory solid tumors (aged ≥4 years). An established adult population PK model was extended to incorporate an allometrically-scaled effect of body surface area and confirmed that the copanlisib maximum tolerated dose of 28 mg/m2 was appropriate to achieve uniform copanlisib exposures across the investigated pediatric age range and consistent exposures to historical data in adult cancer patients. The model-informed approach successfully supported and confirmed the copanlisib pediatric dose recommendation.

Estimation of FMO3 Ontogeny by Mechanistic Population Pharmacokinetic Modelling of Risdiplam and Its Impact on Drug-Drug Interactions in Children

BACKGROUND AND OBJECTIVE

Spinal muscular atrophy (SMA) is a progressive neuromuscular disease caused by insufficient levels of survival motor neuron (SMN) protein. Risdiplam (EvrysdiTM) increases SMN protein and is approved for the treatment of SMA. Risdiplam has high oral bioavailability and is primarily eliminated through hepatic metabolism by flavin-containing monooxygenase3 (FMO3) and cytochrome P450 (CYP) 3A, by 75% and 20%, respectively. While the FMO3 ontogeny is critical input data for the prediction of risdiplam pharmacokinetics (PK) in children, it was mostly studied in vitro, and robust in vivo FMO3 ontogeny is currently lacking. We derived in vivo FMO3 ontogeny by mechanistic population PK modelling of risdiplam and investigated its impact on drug-drug interactions in children.

METHODS

Population and physiologically based PK (PPK and PBPK) modelling conducted during the development of risdiplam were integrated into a mechanistic PPK (Mech-PPK) model to estimate in vivo FMO3 ontogeny. A total of 10,205 risdiplam plasma concentration-time data from 525 subjects aged 2 months-61 years were included. Six different structural models were examined to describe the in vivo FMO3 ontogeny. Impact of the newly estimated FMO3 ontogeny on predictions of drug-drug interaction (DDI) in children was investigated by simulations for dual CYP3A-FMO3 substrates including risdiplam and theoretical substrates covering a range of metabolic fractions (fm) of CYP3A and FMO3 (fmCYP3A:fmFMO3 = 10%:90%, 50%:50%, 90%:10%).

RESULTS

All six models consistently predicted higher FMO3 expression/activity in children, reaching a maximum at the age of 2 years with an approximately threefold difference compared with adults. Different trajectories of FMO3 ontogeny in infants < 4 months of age were predicted by the six models, likely due to limited observations for this age range. Use of this  in vivo FMO3 ontogeny function improved prediction of risdiplam PK in children compared to in vitro FMO3 ontogeny functions. The simulations of theoretical dual CYP3A-FMO3 substrates predicted comparable or decreased CYP3A-victim DDI propensity in children compared to adults across the range of fm values. Refinement of FMO3 ontogeny in the risdiplam model had no impact on the previously predicted low CYP3A-victim or -perpetrator DDI risk of risdiplam in children.

CONCLUSION

Mech-PPK modelling successfully estimated in vivo FMO3 ontogeny from risdiplam data collected from 525 subjects aged 2 months-61 years. To our knowledge, this is the first investigation of in vivo FMO3 ontogeny by population approach using comprehensive data covering a wide age range. Derivation of a robust in vivo FMO3 ontogeny function has significant implications on the prospective prediction of PK and DDI in children for other FMO3 substrates in the future, as illustrated in the current study for FMO3 and/or dual CYP3A-FMO3 substrates.

CLINICAL TRIAL REGISTRY NUMBERS

NCT02633709, NCT03032172, NCT02908685, NCT02913482, NCT03988907.

Anakinra Pilot - a clinical trial to demonstrate safety, feasibility and pharmacokinetics of interleukin 1 receptor antagonist in preterm infants

BACKGROUND

Bronchopulmonary dysplasia (BPD), its complication pulmonary hypertension (BPD-PH) and preterm brain and gut injury lead to significant morbidity and mortality in infants born extremely prematurely. There is extensive evidence that the pro-inflammatory cytokine interleukin 1 (IL-1) plays a key role in the pathophysiology of these illnesses. Two decades of clinical use in paediatric and adult medicine have established an excellent safety and efficacy record for IL-1 blockade with IL-1 receptor antagonist (IL-1Ra, medication name anakinra). Building on robust pre-clinical evidence, the Anakinra Pilot trial aims to demonstrate safety and feasibility of administering anakinra to preterm infants, and to establish pharmacokinetics in this population. Its ultimate goal is to facilitate large studies that will test whether anakinra can ameliorate early-life inflammation, thus alleviating multiple complications of prematurity.

METHODS AND ANALYSIS

Anakinra Pilot is an investigator-initiated, single arm, safety and feasibility dose-escalation trial in extremely preterm infants born between 24 weeks 0 days (240) and 276 weeks of gestational age (GA). Enrolled infants will receive anakinra intravenously over the first 21 days after birth, starting in the first 24 h after birth. In the first phase, dosing is 1 mg/kg every 48 h, and dosage will increase to 1.5 mg/kg every 24 h in the second phase. Initial anakinra dosing was determined through population pharmacokinetic model simulations. During the study, there will be a interim analysis to confirm predictions before undertaking dose assessment. Anakinra therapy will be considered safe if the frequency of adverse outcomes/events does not exceed that expected in infants born at 240-276 weeks GA.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/, identifier NCT05280340.

Daptomycin Physiology-Based Pharmacokinetic Modeling to Predict Drug Exposure and Pharmacodynamics in Skin and Bone Tissues

BACKGROUND AND OBJECTIVE

Daptomycin has been recommended in the treatment of bone and joint infection. Previous work showed that the approved dosage of daptomycin may be insufficient to achieve optimal exposure in patients with bone and joint infection. However, those studies assumed that bone exposure was similar to steady-state daptomycin-free plasma concentrations. We sought to establish a physiologically based pharmacokinetic (PBPK) model of daptomycin to describe the dynamics of daptomycin disposition in bone and skin tissue.

METHODS

A PBPK model of daptomycin was built using PK-Sim^®. Daptomycin concentrations in plasma and bone were obtained from three previously published studies. Physicochemical drug characteristics, mass balance, anthropometrics, and experimental data were used to build and refine the PBPK model. Internal validation of the PBPK model was performed using the usual diagnostic plots. The final PBPK model was then used to run simulations with doses of 6, 8, 10, and 12 mg/kg/24 h. Pharmacokinetic profiles were simulated in 1000 subjects and the probabilities of target attainment for the area under the concentration-time curve over the bacterial minimum inhibitory concentration were computed in blood, skin, and bone compartments.

RESULTS

The final model showed a good fit of all datasets with an absolute average fold error between 0.5 and 2 for all pharmacokinetic quantities in blood, skin and bone tissues. Results of dosing simulations showed that doses ≥10 mg/kg should be used in the case of bacteremia caused by Staphylococcus aureus with a minimum inhibitory concentration >0.5 mg/L or Enterococcus faecalis with a minimum inhibitory concentration >1 mg/L, while doses ≥12 mg/kg should be used in the case of bone and joint infection or complicated skin infection. When considering a lower minimum inhibitory concentration, doses of 6-8 mg/kg would likely achieve a sufficient success rate. However, in the case of infections caused by E. faecalis with a minimum inhibitory concentration >2 mg/L, a higher dosage and combination therapy would be necessary to maximize efficacy.

CONCLUSIONS

We developed the first daptomycin PBPK/pharmacodynamic model for bone and joint infection, which confirmed that a higher daptomycin dosage is needed to optimize exposure in bone tissue. However, such higher dosages raise safety concerns. In this setting, therapeutic drug monitoring and model-informed precision dosing appear necessary to ensure the right exposure on an individual basis.

Development and application of a pediatric mechanistic kidney model

Pediatric physiologically‐based pharmacokinetic (P‐PBPK) models have been used to predict age related changes in the pharmacokinetics (PKs) of renally cleared drugs mainly in relation to changes in glomerular filtration rate. With emerging data on ontogeny of renal transporters, mechanistic models of renal clearance accounting for the role of active and passive secretion should be developed and evaluated. Data on age‐related physiological changes and ontogeny of renal transporters were applied into a mechanistic kidney within a P‐PBPK model. Plasma concentration–time profile and PK parameters of cimetidine, ciprofloxacin, metformin, tenofovir, and zidovudine were predicted in subjects aged 1 day to 18 years. The predicted and observed plasma concentration–time profiles and PK parameters were compared. The predicted concentration–time profile means and 5th and 95th percent intervals generally captured the observed data and variability in various studies. Overall, based on drugs and age bands, predicted to observed clearance were all within two‐fold and in 11 of 16 cases within 1.5‐fold. Predicted to observed area under the curve (AUC) and maximum plasma concentration (C_max) were within two‐fold in 12 of 14 and 12 of 15 cases, respectively. Predictions in neonates and early infants (up to 14 weeks postnatal age) were reasonable with 15–20 predicted PK parameters within two‐fold of the observed. ciprofloxacin but not zidovudine PK predictions were sensitive to basal kidney uptake transporter ontogeny. The results indicate that a mechanistic kidney model accounting for physiology and ontogeny of renal processes and transporters can predict the PK of renally excreted drugs in children. Further data especially in neonates are required to verify the model and ontogeny profiles.

A Pilot Study Testing Intranasal Ketamine for the Treatment of Procedural Anxiety in Children Undergoing Laceration Repair

Identifying non-invasive methods for anxiolysis is becoming increasingly important in the pediatric emergency department (ED). Few studies have examined the use of intranasal (IN) ketamine for procedural anxiolysis. We aim to evaluate if IN ketamine provides satisfactory anxiolysis for patients undergoing laceration repair based on anxiety and sedation scoring. We also evaluated the feasibility of using IN ketamine in future trials based on its tolerability and side-effects. A pilot study evaluating IN ketamine in the treatment of procedural anxiety for patients, 2 years and older, weighing 40 kg or less, presenting to the pediatric ED with lacerations. The need for anxiolysis was defined by an elevated modified-Yale Preoperative Anxiety Scale-Short Form (mYPAS-SF) score. Patients received 5 mg/kg of IN ketamine in addition to topical anesthesia, mYPAS-SF scoring before and during the procedure, sedation scoring, adverse events, vital signs, age, weight, laceration size and location, and satisfaction surveys were recorded. Twenty-five patients were enrolled, with mean age of 61 ± 29.2 months and mean weight of 21 ± 6.4 kg. Lacerations were located on the face, extremities, and groin with mean size of 2.1 cm. A decrease in anxiety levels was observed, from median m-YPAS-SF score of 66.7 (62.50-80.2) to 33.3 (27.09-52.00), p < 0.001. Among the patients, 92% (n = 23) were less anxious during the procedure. IN ketamine appears to be safe and well-tolerated with a positive impact on procedural anxiety. A dosage of 5 mg/kg is a reasonable starting point, as 80% of patients had appropriate anxiolysis.

A General Biphasic Bodyweight Model for Scaling Basal Metabolic Rate, Glomerular Filtration Rate, and Drug Clearance from Birth to Adulthood

The objective of this study is to propose a unified, continuous, and bodyweight-only equation to quantify the changes of human basal metabolic rate (BMR), glomerular filtration rate (GFR), and drug clearance (CL) from infancy to adulthood. The BMR datasets were retrieved from a comprehensive historical database of male and female subjects (0.02 to 64 years). The CL datasets for 17 drugs and the GFR dataset were generated from published maturation and growth models with reported parameter values. A statistical approach was used to simulate the model-generated CL and GFR data for a hypothetical population with 26 age groups (from 0 to 20 years). A biphasic equation with two power-law functions of bodyweight was proposed and evaluated as a general model using nonlinear regression and dimensionless analysis. All datasets universally reveal biphasic curves with two distinct linear segments on log-log plots. The biphasic equation consists of two reciprocal allometric terms that asymptotically determine the overall curvature. The fitting results show a superlinear scaling phase (asymptotic exponent >1; ca. 1.5-3.5) and a sublinear scaling phase (asymptotic exponent <1; ca. 0.5-0.7), which are separated at the phase transition bodyweight ranging from 5 to 20 kg with a mean value of 10 kg (corresponding to 1 year of age). The dimensionless analysis generalizes and offers quantitative realization of the maturation and growth process. In conclusion, the proposed mixed-allometry equation is a generic model that quantitatively describes the phase transition in the human maturation process of diverse human functions.

An update on the use of allometric and other scaling methods to scale drug clearance in children: towards decision tables

INTRODUCTION

When pediatric data are not available for a drug, allometric and other methods are applied to scale drug clearance across the pediatric age-range from adult values. This is applied when designing first-in-child studies, but also for off-label drug prescription.

AREAS COVERED

This review provides an overview of the systematic accuracy of allometric and other pediatric clearance scaling methods compared to gold-standard PBPK predictions. The findings are summarized in decision tables to provide a priori guidance on the selection of appropriate pediatric clearance scaling methods for both novel drugs for which no pediatric data are available and existing drugs in clinical practice.

EXPERT OPINION

While allometric scaling principles are commonly used to scale pediatric clearance, there is no universal allometric exponent (i.e., 1, 0.75 or 0.67) that can accurately scale clearance for all drugs from adults to children of all ages. Therefore, pediatric scaling decision tables based on age, drug elimination route, binding plasma protein, fraction unbound, extraction ratio, and/or isoenzyme maturation are proposed to a priori select the appropriate (allometric) clearance scaling method, thereby reducing the need for full PBPK-based clearance predictions. Guidance on allometric scaling when estimating pediatric clearance values is provided as well.

Physiologically Based Pharmacokinetic Modeling of Meropenem in Preterm and Term Infants

BACKGROUND

Meropenem is a broad-spectrum carbapenem antibiotic approved by the US Food and Drug Administration for use in pediatric patients, including treating complicated intra-abdominal infections in infants < 3 months of age. The impact of maturation in glomerular filtration rate and tubular secretion by renal transporters on meropenem pharmacokinetics, and the effect on meropenem dosing, remains unknown. We applied physiologically based pharmacokinetic (PBPK) modeling to characterize the disposition of meropenem in preterm and term infants.

METHODS

An adult meropenem PBPK model was developed in PK-Sim® (Version 8) and scaled to infants accounting for renal transporter ontogeny and glomerular filtration rate maturation. The PBPK model was evaluated using 645 plasma concentrations from 181 infants (gestational age 23-40 weeks; postnatal age 1-95 days). The PBPK model-based simulations were performed to evaluate meropenem dosing in the product label for infants < 3 months of age treated for complicated intra-abdominal infections.

RESULTS

Our model predicted plasma concentrations in infants in agreement with the observed data (average fold error of 0.90). The PBPK model-predicted clearance in a virtual infant population was successfully able to capture the post hoc estimated clearance of meropenem in this population, estimated by a previously published model. For 90% of virtual infants, a 4-mg/L target plasma concentration was achieved for > 50% of the dosing interval following product label-recommended dosing.

CONCLUSIONS

Our PBPK model supports the meropenem dosing regimens recommended in the product label for infants <3 months of age.

Individualized precision dosing approaches to optimize antimicrobial therapy in pediatric populations

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

Risk Assessment of Perfluorooctane Sulfonate (PFOS) using Dynamic Age Dependent Physiologically based Pharmacokinetic Model (PBPK) across Human Lifetime

The widespread use of Perfluorooctane sulfonate (PFOS) in everyday life, its long half-life, and the lipophilicity that makes it easily accumulate in the body, raises the question of its safe exposure among different population groups. There are currently enough epidemiological studies showing evidence of PFOS exposure and its associated adverse effects on humans. Moreover, it is already known that physiological changes along with age e.g. organ volume, renal blood flow, cardiac output and albumin concentrations affect chemicals body burden. Human biomonitoring cohort studies have reported PFOS concentrations in blood and autopsy tissue data with PFOS present in sensitive organs across all human lifespan. However, to interpret such biomonitoring data in the context of chemical risk assessment, it is necessary to have a mechanistic framework that explains show the physiological changes across age affects the concentration of chemical inside different tissues of the human body. PBPK model is widely and successfully used in the field of risk assessment. The objective of this manuscript is to develop a dynamic age-dependent PBPK model as an extension of the previously published adult PFOS model and utilize this model to predict and compare the PFOS tissue distribution and plasma concentration across different age groups. Different cohort study data were used for exposure dose reconstruction and evaluation of time-dependent concentration in sensitive organs. Predicted plasma concentration followed trends observed in biomonitoring data and model predictions showed the increased disposition of PFOS in the geriatric population. PFOS model is sensitive to parameters governing renal resorption and elimination across all ages, which is related to PFOS half-life in humans. This model provides an effective framework for improving the quantitative risk assessment of PFOS throughout the human lifetime, particularly in susceptible age groups. The dynamic age-dependent PBPK model provides a step forward for developing such kind of dynamic model for other perfluoroalkyl substances.

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

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

Population pharmacokinetic analysis of rivaroxaban in children and comparison to prospective physiologically-based pharmacokinetic predictions

Rivaroxaban has been investigated in the EINSTEIN‐Jr program for the treatment of acute venous thromboembolism (VTE) in children aged 0 to 18 years and in the UNIVERSE program for thromboprophylaxis in children aged 2 to 8 years with congenital heart disease after Fontan‐procedure. Physiologically‐based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) modeling were used throughout the pediatric development of rivaroxaban according to the learn‐and‐confirm paradigm. The development strategy was to match pediatric drug exposures to adult exposure proven to be safe and efficacious. In this analysis, a refined pediatric PopPK model for rivaroxaban based on integrated EINSTEIN‐Jr data and interim PK data from part A of the UNIVERSE phase III study was developed and the influence of potential covariates and intrinsic factors on rivaroxaban exposure was assessed. The model adequately described the observed pediatric PK data. PK parameters and exposure metrics estimated by the PopPK model were compared to the predictions from a previously published pediatric PBPK model for rivaroxaban. Ninety‐one percent of the individual post hoc clearance estimates were found within the 5th to 95th percentile of the PBPK model predictions. In patients below 2 years of age, however, clearance was underpredicted by the PBPK model. The iterative and integrative use of PBPK and PopPK modeling and simulation played a major role in the establishment of the bodyweight‐adjusted rivaroxaban dosing regimen that was ultimately confirmed to be a safe and efficacious dosing regimen for children aged 0 to 18 years with acute VTE in the EINSTEIN‐Jr phase III study.

Application of a dual mechanistic approach to support bilastine dose selection for older adults

The objective of this study was to evaluate bilastine dosing recommendations in older adults and overcome the limitation of insufficient data from phase I studies in this underrepresented population. This was achieved by integrating bilastine physicochemical, in vitro and in vivo data in young adults and the effect of aging in the pharmacology by means of two alternative approaches: a physiologically‐based pharmacokinetic (PBPK) model and a semi‐mechanistic population pharmacokinetic (Senescence) model. Intestinal apical efflux and basolateral influx transporters were needed in the PBPK model to capture the observations from young adults after single i.v. (10 mg) and p.o. (20 mg) doses, supporting the hypothesis of involvement of gut transporters on secretion. The model was then used to extrapolate the pharmacokinetics (PKs) to elderly subjects considering their specific physiology. Additionally, the Senescence model was develop starting from a published population PK) model, previously applied for pediatrics, and incorporating declining functions on different physiological systems and changes in body composition with aging. Both models were qualified using observed data in a small group of young elderlies (N = 16, mean age = 68.69 years). The PBPK model was further used to evaluate the dose in older subjects (mean age = 80 years) via simulation. The PBPK model supported the hypothesis that basolateral influx and apical efflux transporters are involved in bilastine PK. Both, PBPK and Senescence models indicated that a 20 mg q.d. dose is safe and effective for geriatrics of any age. This approach provides an alternative to generate supplementary data to inform dosing recommendations in under‐represented groups in clinical trials.

Predictive Performance of Physiology-Based Pharmacokinetic Dose Estimates for Pediatric Trials: Evaluation With 10 Bayer Small-Molecule Compounds in Children

Development and guidance of dosing schemes in children have been supported by physiology-based pharmacokinetic (PBPK) modeling for many years. PBPK models are built on a generic basis, where compound- and system-specific parameters are separated and can be exchanged, allowing the translation of these models from adults to children by accounting for physiological differences. Owing to these features, PBPK modeling is a valuable approach to support clinical decision making for dosing in children. In this analysis, we evaluate pediatric PBPK models for 10 small-molecule compounds that were applied to support clinical decision processes at Bayer for their predictive power in different age groups. Ratios of PBPK-predicted to observed PK parameters for the evaluated drugs in different pediatric age groups were estimated. Predictive performance was analyzed on the basis of a 2-fold error range and the bioequivalence range (ie, 0.8 ≤ predicted/observed ≤ 1.25). For all 10 compounds, all predicted-to-observed PK ratios were within a 2-fold error range (n = 27), with two-thirds of the ratios within the bioequivalence range (n = 18). The findings demonstrate that the pharmacokinetics of these compounds was successfully and adequately predicted in different pediatric age groups. This illustrates the applicability of PBPK for guiding dosing schemes in the pediatric population.

Pediatric Drug-Drug Interaction Evaluation: Drug, Patient Population, and Methodological Considerations

Hospitalized pediatric patients and those with complex or chronic conditions treated on an outpatient basis are commonly prescribed multiple drugs, resulting in increased risk for drug-drug interactions (DDIs). Although dedicated DDI evaluations are routinely performed in healthy adult volunteers during drug development, they are rarely performed in pediatric patients because of ethical, logistical, and methodological challenges. In the absence of pediatric DDI evaluations, adult DDI data are often extrapolated to pediatric patients. However, the magnitude of a DDI in pediatric patients may differ from adults because of age-dependent physiological changes that can impact drug disposition or response and because of other factors related to the drug (eg, dose, formulation) and the patient population (eg, disease state, obesity). Therefore, the DDI magnitude needs to be assessed in children separately from adults, although a lack of clinical DDI data in pediatric populations makes this evaluation challenging. As a result, pediatric DDI assessment relies on the predictive performance of the pharmacometric approaches used, such as population and physiologically based pharmacokinetic modeling. Therefore, careful consideration needs to be given to adequately account for the age-dependent physiological changes in these models to build high confidence for such untested DDI scenarios. This review article summarizes the key considerations related to the drug, patient population, and methodology, and how they can impact DDI evaluation in the pediatric population.

Preterm Physiologically Based Pharmacokinetic Model. Part II: Applications of the Model to Predict Drug Pharmacokinetics in the Preterm Population

BACKGROUND

Preterm neonates are usually not part of a traditional drug development programme, however they are frequently administered medicines. Developing modelling and simulation tools, such as physiologically based pharmacokinetic (PBPK) models that incorporate developmental physiology and maturation of drug metabolism, can be used to predict drug exposure in this group of patients, and may help to optimize drug dose adjustment.

OBJECTIVE

The aim of this study was to assess and verify the predictability of a preterm PBPK model using compounds that undergo diverse renal and/or hepatic clearance based on the knowledge of their disposition in adults.

METHODS

A PBPK model was developed in the Simcyp Simulator V17 to predict the pharmacokinetics (PK) of drugs in preterm neonates. Drug parameters for alfentanil, midazolam, caffeine, ibuprofen, gentamicin and vancomycin were collated from the literature. Predicted PK parameters and profiles were compared against the observed data.

RESULTS

The preterm PBPK model predicted the PK changes of the six compounds using ontogeny functions for cytochrome P450 (CYP) 1A2, CYP2C9 and CYP3A4 after oral and intravenous administrations. For gentamicin and vancomycin, the maturation of renal function was able to predict the exposure of these two compounds after intravenous administration. All PK parameter predictions were within a twofold error criteria.

CONCLUSION

While the developed preterm model for the prediction of PK behaviour in preterm patients is not intended to replace clinical studies, it can potentially help with deciding on first-time dosing in this population and study design in the absence of clinical data.

Incorporating Breastfeeding-Related Variability with Physiologically Based Pharmacokinetic Modeling to Predict Infant Exposure to Maternal Medication Through Breast Milk: a Workflow Applied to Lamotrigine

Current methods to assess risk in infants exposed to maternal medication through breast milk do not specifically account for infants most vulnerable to high drug exposure. A workflow applied to lamotrigine incorporated variability in infant anatomy and physiology, milk intake volume, and milk concentration to predict infant exposure. An adult physiologically based pharmacokinetic model of lamotrigine was developed and evaluated. The model was scaled to account for growth and maturation of a virtual infant population (n=100). Daily infant doses were simulated using milk intake volume and concentration models described by a nonlinear equation of weight-normalized intake across infant age and a linear function on the relationship of observed milk concentrations and maternal doses, respectively. Average infant plasma concentration at steady state was obtained through simulation. Models were evaluated by comparing observed to simulated infant plasma concentrations from breastfeeding infants based on a 90% prediction interval (PI). Upper AUC ratio (UAR) was defined as a novel risk metric. Twenty-five paired (milk concentrations measured) and 18 unpaired (milk concentrations unknown) infant plasma samples were retrieved from the literature. Forty-four percent and 11% of the paired and unpaired infant plasma concentrations were outside of the 90% PI, respectively. Over all ages (0-7 months), unpaired predictions captured more observed infant plasma concentrations within 90% PI than paired. UAR was 0.18-0.44 when mothers received 200 mg lamotrigine, suggesting that infants can receive 18-44% of the exposure per dose as compared to adults. UARs determined for further medications could reveal trends to better classify at-risk mother-infant pairs.

Developing a physiologically based pharmacokinetic model of apixaban to predict scenarios of drug-drug interactions, renal impairment and paediatric populations

AIMS

To develop a physiologically based pharmacokinetic (PBPK) model for apixaban, an oral anticoagulant with a narrow therapeutic index, and to predict PK profiles and potential drug-drug interactions (DDIs) in patients with renal impairment and paediatrics.

METHODS

A whole-body apixaban PBPK model was developed and validated in SimCYP for healthy adults with or without interacting drugs. The model was extended to renal impairment and paediatrics. Observed PK data in adults were compared with predicted data. The effect of renal function, age and DDIs on apixaban PK was investigated.

RESULTS

The PBPK model successfully predicted the PK of apixaban alone and under the influence of interacting drugs. For patients with renal impairment, the PBPK model successfully predicted the fold change in each impairment group; inhibitory DDI and renal impairment had a synergistic effect on the increase of apixaban exposure (e.g., almost 3-fold increase of AUC in ketoconazole + severe renal impairment group). For infants younger than 1 year, the exposure of apixaban decreased with increased weight-normalized clearance. For newborn infants, AUC of apixaban was >2-fold higher than that in children older than 1 year. Meanwhile, the effect of DDI seems to be weakened while the effect of renal impairment might be enhanced in infants younger than 1 year.

CONCLUSION

Our study provides a reasonable approach to estimate the dose adjustment for the first use of apixaban in special populations with complex situations, which has the opportunity to make the clinical practice much safer.

History and Future Perspectives on the Discipline of Quantitative Systems Pharmacology Modeling and Its Applications

Mathematical biology and pharmacology models have a long and rich history in the fields of medicine and physiology, impacting our understanding of disease mechanisms and the development of novel therapeutics. With an increased focus on the pharmacology application of system models and the advances in data science spanning mechanistic and empirical approaches, there is a significant opportunity and promise to leverage these advancements to enhance the development and application of the systems pharmacology field. In this paper, we will review milestones in the evolution of mathematical biology and pharmacology models, highlight some of the gaps and challenges in developing and applying systems pharmacology models, and provide a vision for an integrated strategy that leverages advances in adjacent fields to overcome these challenges.

Physiologically-based pharmacokinetic modeling of benzo(a)pyrene and the metabolite in humans of different ages

Age-specific differences in the pharmacokinetics of benzo(a)pyrene (BaP) and its metabolite 3-hydroxybenzo(a)pyrene (3-OHBaP) potentially affect time courses of tissue concentration; however, the quantitative impact of these differences is not well characterized. Our objective was to quantify the effect of age-specific differences in physiological and biochemical parameters on the pharmacokinetics of BaP and 3-OHBaP from newborn at birth to adulthood following inhalation exposure. The time courses of BaP and 3-OHBaP were simulated by using a physiologically based pharmacokinetic model with Advanced Continuous Simulation Language (ACSLX). The concentrations of BaP increased with age in the liver but decreased with age in most tissues, urine, and blood. The concentrations of 3-OHBaP were the highest in the newborns. Our results also showed that the concentration of BaP has almost reached a steady state in the kidney, liver, lung, rapidly perfused tissues, slowly perfused tissues, and skin except for adipose tissues. However, the concentration of 3-OHBaP has reached a steady state in all tissues. This study suggests that age-specific parameters have an effect on the pharmacokinetics of BaP and 3-OHBaP. In particular, tissue concentration in the newborns is higher than other age groups, which indicates that the newborns are susceptible to environmental BaP exposure.

Evaluation of models for predicting pediatric fraction unbound in plasma for human health risk assessment

Pediatric physiologically based pharmacokinetic (PBPK) models facilitate the prediction of PK parameters in children under specific exposure conditions. Pharmacokinetic outcomes are highly sensitive to fraction unbound in plasma (fup) as incorporated into PBPK models. Rarely is fup in children (fup_child) experimentally derived and prediction is based upon fup in adults (fup_adult) as well as a ratio of plasma protein concentrations between children and adults. The objectives were to (i) evaluate protein concentration vs. age profile derived from ontogeny models, (ii) assess predictive performances of fup ontogeny models, and (iii) determine overall uncertainty in fup_child prediction resulting from a combination of quantitative structure-property relationship (QSPR) model and ontogeny models. The plasma albumin and alpha-acid glycoprotein (AAG) concentration data for pediatrics and fup_child and fup_adult data were obtained from literature. The protein concentration vs. age profile derived from ontogeny models were compared to observed levels. Fup_child values were calculated according to ontogeny models using both observed and QSPR-predicted fup_adult as inputs and predictive performances of ontogeny models assessed by comparing predicted fup_child to observed values. Protein concentrations vs. age profiles derived from non-linear equations were more congruent with observed albumin levels than linear or step-wise models. When observed fup_adult values were used as input, the fup_child data were under-predicted with average fold error (AFE) amounts ranging 0.79-0.81 and 0.77-0.97 for albumin and AAG ontogeny models, respectively. When QSPR-predicted fup_adult values were used as input, AFE of fup_child ranged 1.2-1.35 and 0.98-1.2 for albumin and AAG models, respectively. The choice of ontogeny model with respect to prediction accuracy is more important for AAG, highly bound compounds and infants. For these compounds and scenarios, experimental determination of fup_child for inclusion into a pediatric PBPK model is necessary to have confidence in PBPK model outputs.

Model-Informed Pediatric Dose Selection for Dapagliflozin by Incorporating Developmental Changes

This analysis reports a quantitative modeling and simulation approach for oral dapagliflozin, a primarily uridine diphosphate-glucuronosyltransferase (UGT)-metabolized human sodium-glucose cotransporter 2 selective inhibitor. A mechanistic dapagliflozin physiologically based pharmacokinetic (PBPK) model was developed using in vitro metabolism and clinical pharmacokinetic (PK) data and verified for context of use (e.g., exposure predictions in pediatric subjects aged 1 month to 18 years). Dapagliflozin exposure is challenging to predict in pediatric populations owing to differences in UGT1A9 ontogeny maturation and paucity of clinical PK data in younger age groups. Based on the exposure-response relationship of dapagliflozin, twofold acceptance criteria were applied between model-predicted and observed drug exposures and PK parameters (area under the curve and maximum drug concentration) in various scenarios, including monotherapy in healthy adults (single/multiple dose), monotherapy in hepatically or renally impaired patients, and drug-drug interactions with UGT1A9 modulators, such as mefenamic acid and rifampin. The PBPK model captured the observed exposure within twofold of the observed monotherapy data in adults and adolescents and in special population. As a guide to determining dosing regimens in pediatric studies, the verified PBPK model, along with UGT enzyme ontogeny maturation understanding, was used for predictions of dapagliflozin monotherapy exposures in pediatric subjects aged 1 month to 18 years that best matched exposure in adult patients with a 10-mg single dose of dapagliflozin.

Pediatric Pharmacokinetics and Dose Predictions: A Report of a Satellite Meeting to the 10th Juvenile Toxicity Symposium

On April 24, 2019, a symposium on Pediatric Pharmacokinetics and Dose Predictions was held as a satellite meeting to the 10th Juvenile Toxicity Symposium. This symposium brought together scientists from academia, industry, and clinical research organizations with the aim to update each other on the current knowledge on pediatric drug development. Through more knowledge on specific ontogeny profiles of drug metabolism and transporter proteins, integrated into physiologically-based pharmacokinetic (PBPK) models, we have gained a more integrated understanding of age-related differences in pharmacokinetics (PKs), Relevant examples were presented during the meeting. PBPK may be considered the gold standard for pediatric PK prediction, but still it is important to know that simpler methods, such as allometry, allometry combined with maturation function, functions based on the elimination pathway, or linear models, also perform well, depending on the age range or the mechanisms involved. Knowledge from different methods and information sources should be combined (e.g., microdosing can reveal early read-out of age-related differences in exposure), and such results can be a value to verify models. To further establish best practices for dose setting in pediatrics, more in vitro and in vivo research is needed on aspects such as age-related changes in the exposure-response relationship and the impact of disease on PK. New information coupled with the refining of model-based drug development approaches will allow faster targeting of intended age groups and allow more efficient design of pediatric clinical trials.

Physiologically Based Pharmacokinetic Modeling for Trimethoprim and Sulfamethoxazole in Children

OBJECTIVE

The aims of this study were to (1) determine whether opportunistically collected data can be used to develop physiologically based pharmacokinetic (PBPK) models in pediatric patients; and (2) characterize age-related maturational changes in drug disposition for the renally eliminated and hepatically metabolized antibiotic trimethoprim (TMP)-sulfamethoxazole (SMX).

METHODS

We developed separate population PBPK models for TMP and SMX in children after oral administration of the combined TMP-SMX product and used sparse and opportunistically collected plasma concentration samples to validate our pediatric model. We evaluated predictability of the pediatric PBPK model based on the number of observed pediatric data out of the 90% prediction interval. We performed dosing simulations to target organ and tissue (skin) concentrations greater than the methicillin-resistant Staphylococcus aureus (MRSA) minimum inhibitory concentration (TMP 2 mg/L; SMX 9.5 mg/L) for at least 50% of the dosing interval.

RESULTS

We found 67-87% and 71-91% of the observed data for TMP and SMX, respectively, were captured within the 90% prediction interval across five age groups, suggesting adequate fit of our model. Our model-rederived optimal dosing of TMP at the target tissue was in the range of recommended dosing for TMP-SMX in children in all age groups by current guidelines for the treatment of MRSA.

CONCLUSION

We successfully developed a pediatric PBPK model of the combination antibiotic TMP-SMX using sparse and opportunistic pediatric pharmacokinetic samples. This novel and efficient approach has the potential to expand the use of PBPK modeling in pediatric drug development.

Precision Dosing Management with Intelligent Computing in Digital Health

Pediatric dosing is not only critical for successful pediatric trials in drug development but also paramount to safety and effective treatment at bedside. Due to the complex pharmacokinetic of children compared to adults, several challenges are posed in managing dosing precisely during drug development and after drug approval to clinicians. In particular, given the real-world practice, understanding the impact of development on the dose-exposure-response relationship is essential in optimizing the dosing to children of different ages. In this paper we propose a novel intelligent computing framework to examine how the growth and maturation create size- and age-dependent variability in pharmacokinetics and pharmacodynamics, and summarize the use of modeling-based approaches for dose finding in pediatric drug development, allowing clinicians to anticipate probable treatment effects and to have a higher likelihood of achieving optimal dose regimens early, as well as reducing the drug development cycling time and cost.

Drug Dosing Recommendations for All Patients: A Roadmap for Change

Most drug labels do not contain dosing recommendations for a significant portion of real‐world patients for whom the drug is prescribed. Current label recommendations predominately reflect the population studied in pivotal trials that typically exclude patients who are very young or old, emaciated or morbidly obese, pregnant, or have multiple characteristics likely to influence dosing. As a result, physicians may need to guess the correct dose and regimen for these patients. It is now feasible to provide dose and regimen recommendations for these patients by integrating available scientific knowledge and by utilizing or modifying current regulatory agency‐industry practices. The purpose of this commentary is to explore several factors that should be considered in creating a process that will provide more effective, safe, and timely drug dosing recommendations for most, if not all, patients. These factors include the availability of real‐world data, development of predictive models, experience with the US Food and Drug Administration (FDA)’s pediatric exclusivity program, development of clinical decision software, funding mechanisms like the Prescription Drug Users Fee Act (PDUFA), and harmonization of global regulatory policies. From an examination of these factors, we recommend a relatively simple, efficient expansion of current practices designed to predict, confirm, and continuously improve drug dosing for more patients. We believe implementing these recommendations will benefit patients, payers, industry, and regulatory agencies.

Physiologically-Based Pharmacokinetic (PBPK) Modeling of Buprenorphine in Adults, Children and Preterm Neonates

Buprenorphine plays a crucial role in the therapeutic management of pain in adults, adolescents and pediatric subpopulations. However, only few pharmacokinetic studies of buprenorphine in children, particularly neonates, are available as conducting clinical trials in this population is especially challenging. Physiologically-based pharmacokinetic (PBPK) modeling allows the prediction of drug exposure in pediatrics based on age-related physiological differences. The aim of this study was to predict the pharmacokinetics of buprenorphine in pediatrics with PBPK modeling. Moreover, the drug-drug interaction (DDI) potential of buprenorphine with CYP3A4 and P-glycoprotein perpetrator drugs should be elucidated. A PBPK model of buprenorphine and norbuprenorphine in adults has been developed and scaled to children and preterm neonates, accounting for age-related changes. One-hundred-percent of the predicted AUC_last values in adults (geometric mean fold error (GMFE): 1.22), 90% of individual AUC_last predictions in children (GMFE: 1.54) and 75% in preterm neonates (GMFE: 1.57) met the 2-fold acceptance criterion. Moreover, the adult model was used to simulate DDI scenarios with clarithromycin, itraconazole and rifampicin. We demonstrate the applicability of scaling adult PBPK models to pediatrics for the prediction of individual plasma profiles. The novel PBPK models could be helpful to further investigate buprenorphine pharmacokinetics in various populations, particularly pediatric subgroups.

Development of a generic lifelong physiologically based biokinetic model for exposome studies

The current study within the frame of the HEALS project aims at the development of a lifelong physiologically based biokinetic (PBBK) model for exposome studies. The aim was to deliver a comprehensive modelling framework for addressing a large chemical space. Towards this aim, the delivered model can easily adapt parameters from existing ad-hoc models or complete the missing compound specific parameters using advanced quantitative structure activity relationship (QSAR). All major human organs are included, as well as arterial, venous, and portal blood compartments. Xenobiotics and their metabolites are linked through the metabolizing tissues. This is mainly the liver, but also other sites of metabolism might be considered (intestine, brain, skin, placenta) based on the presence or not of the enzymes involved in the metabolism of the compound of interest. Each tissue is described by three mass balance equations for (a) red blood cells, (b) plasma and interstitial tissue and (c) cells respectively. The anthropometric parameters of the models are time dependent, so as to provide a lifetime internal dose assessment, as well as to describe the continuously changing physiology of the mother and the developing fetus. An additional component of flexibility is that the biokinetic processes that relate to metabolism are related with either Michaelis-Menten kinetics, as well as intrinsic clearance kinetics. The capability of the model is demonstrated in the assessment of internal exposure and the prediction of expected biomonitored levels in urine for three major compounds within the HEALS project, namely bisphenol A (BPA), Bis(2-ethylhexyl) phthalate (DEHP) and cadmium (Cd). The results indicated that the predicted urinary levels fit very well with the ones from human biomonitoring (HBM) studies; internal exposure to plasticizers is very low (in the range of ng/L), while internal exposure to Cd is in the range of μg/L.

The Ontogeny of UDP-glucuronosyltransferase Enzymes, Recommendations for Future Profiling Studies and Application Through Physiologically Based Pharmacokinetic Modelling

Limited understanding of drug pharmacokinetics in children is one of the major challenges in paediatric drug development. This is most critical in neonates and infants owing to rapid changes in physiological functions, especially in the activity of drug-metabolising enzymes. Paediatric physiologically based pharmacokinetic models that integrate ontogeny functions for cytochrome P450 enzymes have aided our understanding of drug exposure in children, including those under the age of 2 years. Paediatric physiologically based pharmacokinetic models have consequently been recognised by the European Medicines Agency and the US Food and Drug Administration as innovative tools in paediatric drug development and regulatory decision making. However, little is currently known about age-related changes in UDP-glucuronosyltransferase-mediated metabolism, which represents the most important conjugation reaction for xenobiotics. Therefore, the objective of the review was to conduct a thorough literature survey to summarise our current understanding of age-related changes in UDP-glucuronosyltransferases as well as associated clinical and experimental sources of variance. Our findings indicate that there are distinct differences in UDP-glucuronosyltransferase expression and activity between isoforms for different age groups. In addition, there is substantial variability between individuals and laboratories reported for human liver microsomes, which results in part from a lack of standardised experimental conditions. Therefore, we provide a number of best practice recommendations for experimental conditions, which ultimately may help improve the quality of data used for quantitative clinical pharmacology approaches, and thus for safe and effective pharmacotherapy in children.

State-of-the-Art Review on Physiologically Based Pharmacokinetic Modeling in Pediatric Drug Development

Physiologically based pharmacokinetic modeling and simulation is an important tool for predicting the pharmacokinetics, pharmacodynamics, and safety of drugs in pediatrics. Physiologically based pharmacokinetic modeling is applied in pediatric drug development for first-time-in-pediatric dose selection, simulation-based trial design, correlation with target organ toxicities, risk assessment by investigating possible drug-drug interactions, real-time assessment of pharmacokinetic-safety relationships, and assessment of non-systemic biodistribution targets. This review summarizes the details of a physiologically based pharmacokinetic modeling approach in pediatric drug research, emphasizing reports on pediatric physiologically based pharmacokinetic models of individual drugs. We also compare and contrast the strategies employed by various researchers in pediatric physiologically based pharmacokinetic modeling and provide a comprehensive overview of physiologically based pharmacokinetic modeling strategies and approaches in pediatrics. We discuss the impact of physiologically based pharmacokinetic models on regulatory reviews and product labels in the field of pediatric pharmacotherapy. Additionally, we examine in detail the current limitations and future directions of physiologically based pharmacokinetic modeling in pediatrics with regard to the ability to predict plasma concentrations and pharmacokinetic parameters. Despite the skepticism and concern in the pediatric community about the reliability of physiologically based pharmacokinetic models, there is substantial evidence that pediatric physiologically based pharmacokinetic models have been used successfully to predict differences in pharmacokinetics between adults and children for several drugs. It is obvious that the use of physiologically based pharmacokinetic modeling to support various stages of pediatric drug development is highly attractive and will rapidly increase, provided the robustness and reliability of these techniques are well established.

A Physiologically-Based Pharmacokinetic Model to Describe Ciprofloxacin Pharmacokinetics Over the Entire Span of Life

Background

Physiologically-based pharmacokinetic (PBPK) modeling has received growing interest as a useful tool for the assessment of drug pharmacokinetics by continuous knowledge integration.

Objective

The objective of this study was to build a ciprofloxacin PBPK model for intravenous and oral dosing based on a comprehensive literature review, and evaluate the predictive performance towards pediatric and geriatric patients.

Methods

The aim of this report was to establish confidence in simulations of the ciprofloxacin PBPK model along the development process to facilitate reliable predictions outside of the tested adult age range towards the extremes of ages. Therefore, mean data of 69 published clinical trials were identified and integrated into the model building, simulation and verification process. The predictive performance on both ends of the age scale was assessed using individual data of 258 subjects observed in own clinical trials.

Results

Ciprofloxacin model verification demonstrated no concentration-related bias and accurate simulations for the adult age range, with only 4.8% of the mean observed data points for intravenous administration and 12.1% for oral administration being outside the simulated twofold range. Predictions towards the extremes of ages for the area under the plasma concentration–time curve (AUC) and the maximum plasma concentration (C_max) over the entire span of life revealed a reliable estimation, with only two pediatric AUC observations outside the 90% prediction interval.

Conclusion

Overall, this ciprofloxacin PBPK modeling approach demonstrated the predictive power of a thoroughly informed middle-out approach towards age groups of interest to potentially support the decision-making process.

Electronic supplementary material

The online version of this article (10.1007/s40262-018-0661-6) contains supplementary material, which is available to authorized users.