Pediatric Physiologically Based Pharmacokinetic Research Articles

Is the GFR-based scaling approach adequate for predicting pediatric renal clearance of drugs with passive tubular reabsorption? Insights from PBPK modeling.

Empirical maturation models (e.g., Johnson and Rhodin models) for glomerular filtration rate (GFR) are commonly used as scaling factors for predicting pediatric renal clearance, but their predictive performance for drugs featured with tubular reabsorption is poorly understood. This study investigated the adequacy of GFR-based scaling models for predicting pediatric renal clearance in drugs with passive tubular reabsorption by comparing with a mechanistic kidney model (Mech-KiM) that encompasses the physiological processes of glomerular filtration, tubular secretion, and reabsorption. The analysis utilized hypothetical drugs with varying fractions of tubular reabsorption (Freabs), alongside the model drug metronidazole, which has a Freabs of 96%. Our simulations showed that when Freabs is ≤70%, the discrepancies between the GFR-based scaling methods and the Mech-KiM model in predicting pediatric renal clearance were generally within a twofold range throughout childhood. However, for drugs with substantial tubular reabsorption (e.g., Freabs > 70%), discrepancies greater than twofold were observed between the GFR-based scaling methods and the Mech-KiM model in predicting renal clearance for young children. In neonates, the differences ranged from 5- to 10-fold when the adult Freabs was 95%. Pediatric physiologically based pharmacokinetic (PBPK) modeling of metronidazole revealed that using a GFR-based scaling method (Johnson model) significantly overestimated drug concentrations in children under 2 months, whereas utilizing the Mech-KiM model for renal clearance predictions yielded estimates closely aligned with observed concentrations. Our study demonstrates that using GFR-based scaling models to predict pediatric renal clearance might be inadequate for drugs with extensive passive tubular reabsorption (e.g., Freabs > 70%).

Physiologically Based Pharmacokinetic Modelling in Critically Ill Children Receiving Anakinra While on Extracorporeal Life Support.

Because of the pathophysiological changes associated with critical illness and the use of extracorporeal life support (ECLS) such as continuous renal replacement therapy (CRRT) and extracorporeal membrane oxygenation (ECMO), the pharmacokinetics of drugs are often altered. The objective of this study was to develop a physiologically based pharmacokinetic (PBPK) model for anakinra in children that accounts for the physiological changes associated with critical illness and ECLS technology to guide appropriate pharmacotherapy. A PBPK model for anakinra was first developed in healthy individuals prior to extrapolating to critically ill children receiving ECLS. To account for the impact of anakinra clearance by the dialysis circuit, a CRRT compartment was added to the pediatric PBPK model and parameterized using data from a previously published ex-vivo study. Additionally, an ECMO compartment was added to the whole-body structure to create the final anakinra ECLS-PBPK model. The final model structure was validated by comparing predicted concentrations with observed patient data. Due to limited information in guiding anakinra dosing in this population, in-silico dose simulations were conducted to provide baseline recommendations. By accounting for changes in physiology and the addition of ECLS compartments, the final ECLS-PBPK model predicted the observed plasma concentrations in an adolescent receiving subcutaneous anakinra. Furthermore, dosing simulations suggest that anakinra exposure in adolescents receiving ECLS is similar to that in healthy counterparts. The anakinra ECLS-PBPK model developed in this study is the first to predict plasma concentrations in a population receiving simultaneous CRRT and ECMO. Dosing simulations provided may be used to inform anakinra use in critically ill children and guide future clinical trial planning.

Physiologically based pharmacokinetic models for predicting lamotrigine exposure and dose optimization in pediatric patients receiving combination therapy with carbamazepine or valproic acid.

Lamotrigine (LTG) is an antiepileptic drug that has been used in pediatric epilepsy as a combination therapy or monotherapy after stabilization in recent years. However, there are significant drug-drug interactions (DDI) between LTG and combined drugs such as carbamazepine (CBZ) and valproic acid (VPA). It is particularly important to consider the risk of DDI in combination therapy for intractable epilepsy in pediatric patients. Therefore, it is necessary to adjust the dosage of LTG accordingly. The aim of this study was to establish and validate a pediatric physiologically based pharmacokinetic (PBPK) model for predicting LTG exposure. The model is designed to explore the potential for quantifying pharmacokinetic (PK) DDI of LTG when administered concurrently with CBZ or VPA in pediatric patients. Adult and pediatric PBPK models for LTG and VPA were developed using PK-Sim® software in combination with physiological information and drug-specific parameters, and a DDI model was developed in combination with the published CBZ model. The models were validated against available PK data. Predictive and observational results in adults, children, and the DDI model were in good agreement. The recommended doses of LTG for preschool children (2-6 years) and school-aged children (6-12 years) in the absence of drug interactions were 1.47 and 1.2 times higher than those for adults, respectively; 3.1 and 2.6 times higher than those for adults in combination with CBZ; and 0.67 and 0.57 times lower than those for adults in combination with VPA. In addition, plasma exposures in adolescents (12-18 years) were similar to those in adults at the same doses. We have successfully developed PBPK models and DDI models for LTG in adults and children, which provide a reference for rational drug use in the pediatric population.

Simultaneously Predicting Pharmacokinetics of Loratadine and Desloratadine in Children Using a Whole-Body Physiologically Based Pharmacokinetic Model.

Loratadine is metabolized to desloratadine. Both of them have been used for allergy treatment in children. Anatomical, physiological, and biological parameters of children and clearance of drugs vary with age. We aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model to simultaneously predict the pharmacokinetics of loratadine and desloratadine in children. Following validation using 11 adult data sets, the developed PBPK model was extrapolated to children. Plasma concentrations following oral loratadine or desloratadine to children of different ages were simulated and compared with six children data sets. After scaling anatomy/physiology, protein binding, and clearance, pharmacokinetics of the two drugs in pediatric populations were satisfactorily predicted. Most of the observed concentrations fell within the 5th-95th percentile range of the simulations in 1000 virtual children. The predicted area under the concentration-time curve (AUC) and Cmax fell within 0.5-2.0-fold range of the observations. Oral doses of loratadine or desloratadine for children of different ages were simulated based on similar AUCs following 10 mg of loratadine or 5 mg of desloratadine for adults. Pediatric PBPK model was successfully developed to simultaneously predict plasma concentrations of loratadine and desloratadine in children of all ages. The developed pediatric PBPK model may also be applied to optimize pediatric dosage.

Physiologically based pharmacokinetic modelling of cefoperazone in paediatrics.

Cefoperazone is commonly used off-label in the treatment of bacterial meningitis and sepsis in children, and the pharmacokinetic (PK) data are limited in this vulnerable population. The goal of this study was to develop a physiologically based pharmacokinetic (PBPK) model to predict pediatric cefoperazone exposure for rational dosing recommendations. A cefoperazone PBPK model for adults was first constructed using Simcyp V22 simulator. Subsequently, the model was extended to children based on the built in age-dependent physiological parameters, while the drug characteristics remained unchanged. The verified pediatric PBPK model was then utilized to assess the rationality of the common dosing regimens for children at different age groups. Cefoperazone PBPK model included elimination via biliary excretion, glomerular filtration, and organic anion transporter 3 (OAT3)-mediated tubular secretion. 95.2% of the observed mean concentrations and 100% of the area under the plasma drug concentration-time curve (AUC) and peak concentration (Cmax) in adults were within a twofold range of model mean predictions. Good predictive accuracy was also observed in children, including neonates. 50 mg/kg q12h cefoperazone demonstrated effective target attainment in virtual term neonates (<1 month) when the MIC was ≤1 mg/L, adhering to the stringent PK/PD target of 75% fT > MIC. 37.5 mg/kg q12h cefoperazone achieved the common 50% fT > MIC target for an MIC ≤ 0. 25 mg/L in virtual pediatric patients ranging from 1 month to 18 years of age. A pediatric PBPK model was developed for cefoperazone, and it could serve as the basis for deriving rational dosing regimens in children.

Prediction of Pediatric Pharmacokinetics for CYP3A4 Metabolized Drugs: Comparison of the Performance of Two Hepatic Ontogeny Within a Physiologically Based Pharmacokinetic Model.

The rapid growth in the use of pediatric physiologically based pharmacokinetic (PBPK) models, particularly for regulatory applications, has focused emphasis on model verification and ensuring system parameters are robust, including how these change with age. Uncertainty remains regarding the ontogeny of some enzymes and transporters, in this study 2 published ontogeny profiles for hepatic CYP3A4 were compared. Clinical pharmacokinetic data on 4 intravenously administered CYP3A4 substrates (alfentanil, fentanyl, midazolam, and sildenafil) used across the pediatric age range was collected from the literature. The PBPK models were verified in the adult population and then used to compare the Salem and a modified Upreti ontogeny profiles for CYP3A4 in terms of parent drug clearance and area under the curve from birth onward. Overall, the modified Upreti ontogeny profile resulted in 15 out of 17 age-related predictions within 2-fold and 12 out of 17 predictions within 1.5-fold ranges of observed values, for the Salem ontogeny these values were 12 out of 17 and 8 out of 17, respectively. The Upreti ontogeny profile performed better than Salem, average fold error and absolute average fold error were 1.14 and 1.35 compared to 1.56 and 1.90, respectively. Identifying the optimal CYP3A4 ontogeny is important for regulatory use of PBPK especially given the number of drugs cleared by this enzyme. This study broadens the evidence from previous studies that Upreti is more favorable than Salem, but further work is needed especially in the neonatal and early infant age range.

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

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. 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). 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 24h (AUC24). Calculated UAR across infant age groups ranged from 0.0015 to 0.0026. 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.

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.

Ontogeny of Scaling Factors for Pediatric Physiologically Based Pharmacokinetic Modeling and Simulation: Cytosolic Protein Per Gram of Liver.

Scaling factors are necessary for translating in vitro drug biotransformation data to in vivo clearance values in physiologically-based pharmacokinetic modeling and simulation. Values for microsomal protein per gram of liver are available from several sources for use as a scaling factor to estimate hepatic clearance from microsomal drug biotransformation data. However, data regarding the distribution of cytosolic protein per gram of liver (CPPGL) values across the lifespan are limited, and sparse pediatric data have been published to date. Thus, CPPGL was determined in 160 liver samples from pediatric (n = 129) and adult (n = 31) donors obtained from multiple sources: the University of Maryland Brain and Tissue Bank, tissue retrieval services at the University of Minnesota and University of Pittsburgh, and Sekisui-XenoTech. Tissues were homogenized and subjected to differential centrifugation to isolate cytosolic fractions. Cytosolic protein content was determined by BCA assay. CPPGL varied from two- to sixfold within each age group/developmental stage. Tissue source and sex did not contribute substantially to variability in protein content. Regression analyses revealed minimal change in CPPGL over the first two decades of life (logCPPGL increases 0.1 mg/g per decade). A mean ± S.D. CPPGL value of 44.4 ± 17.4 mg/g or median 41.0 mg/g is representative of values observed between birth and early adulthood (0-18 years, n = 129). SIGNIFICANCE STATEMENT: Cytosolic protein per gram of liver (CPPGL) is a scaling factor required for physiologically based pharmacokinetic modeling and simulation of drug biotransformation by cytosolic enzymes, but pediatric data are limited. Although CPPGL varies from two- to sixfold within developmental stages, a value of 44.4 ± 17.4 mg/g (mean ± S.D.) is representative of the pediatric period (0-18 years, n = 129).

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.

Develop adult extrapolation to pediatrics and pediatric dose optimization based on the physiological pharmacokinetic model of azithromycin.

Physiologically-based pharmacokinetic (PBPK) models are more frequently used for supporting pediatric dose selection in small-molecule drugs. Through literature research, drug parameters of azithromycin and clinical data from different studies were obtained. Through parameter optimization of the absorption and dissolution process, the adult intravenous model was extended to the adult oral model. The adult intravenous and oral PBPK models are precise to meet the AAFE<2 standard, and the pharmacokinetic parameters of the predicted values of the model are all within the mean standard deviation of the clinical observations. The values of plasma protein unbound fraction, renal clearance, and gastric juice pH between adults and pediatrics were changed by using the age-dependent pediatric organ maturity formula, and the adult model was extrapolated to the pediatric model. The final developed pediatric PBPK model was used to evaluate optimal dosing for children of different developmental ages. The relationship between the frist dose and age was as follows: 8.8mg/kg/day from 0.5 to 2years old, 9.2mg/kg/day from 3 to 6years old, 9.4mg/kg/day from 7 to 12years old, and 8.2mg/kg/day from 13 to 18years old, taken in half for 2-5days. Simultaneously, the simulated exposures achieved with the dosing regimen proposed were comparable to adult plasma exposures for treatment of community-acquired pneumonia. A reasonable azithromycin pharmacokinetic-pharmacodynamic model for adults and pediatrics has been established, which can be demonstrated by the use of literature pediatric data to develop pediatric PBPK models, expanding the scope of this powerful modeling tool.

Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools.

The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

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.

Leveraging physiologically based pharmacokinetic modeling to optimize dosing for lopinavir/ritonavir with rifampin in pediatric patients.

Treatment of HIV and tuberculosis co-infection leads to significant mortality in pediatric patients, and treatment can be challenging due to the clinically significant drug-drug interaction (DDI) between lopinavir/ritonavir (LPV/RTV) and rifampin. Doubling LPV/RTV results in insufficient lopinavir trough concentrations in pediatric patients. The objective of this study was to leverage physiologically based pharmacokinetic (PBPK) modeling to optimize the adjusted doses of LPV/RTV in children receiving the WHO-revised doses of rifampin (15 mg/kg daily). Adult and pediatric PBPK models for LPV/RTV with rifampin were developed, including CYP3A and P-glycoprotein inhibition and induction. Data for LPV/RTV model development and evaluation were available from the pediatric AIDS Clinical Trials Group. Dosing simulations were next performed to optimize dosing in children (2 months to 8 years of age). Exposure following super-boosted LPV/RTV with 10 and 15 mg/kg PO daily rifampin was simulated. Simulated parameters were within twofold observations for LPV, RTV, and rifampin in adults and children ≥2 weeks old. The model predicted that, in healthy adults receiving 400/100 mg oral LPV/RTV twice daily (BID), co-treatment with 600 mg oral rifampin daily decreased the steady-state area under the concentration vs. time curve of LPV by 79%, in line with the observed change of 75%. Simulated and observed concentration profiles were comparable for LPV/RTV (230/57.5 mg/m2 ) PO BID without rifampin and 230/230 mg/m2 LPV/RTV PO BID with 10 mg/kg PO daily rifampin in pediatric patients. Sixteen mg/kg of super-boosted LPV (LPV/RTV 1:1) PO BID with 15 mg/kg PO daily rifampin achieved simulated LPV troughs >1 mg/L in ≥93% of virtual children weighing 3.0-24.9 kg, which was comparable with 10 mg/kg PO daily rifampin. Super-boosted LPV/RTV with 15 mg/kg rifampin achieves therapeutic LPV troughs in HIV/TB-infected simulated children.

Use of Real-World Data and Physiologically-Based Pharmacokinetic Modeling to Characterize Enoxaparin Disposition in Children With Obesity.

Dosing guidance for children with obesity is often unknown despite the fact that nearly 20% of US children are classified as obese. Enoxaparin, a commonly prescribed low‐molecular‐weight heparin, is dosed based on body weight irrespective of obesity status to achieve maximum concentration within a narrow therapeutic or prophylactic target range. However, whether children with and without obesity experience equivalent enoxaparin exposure remains unclear. To address this clinical question, 2,825 anti–activated factor X (anti‐Xa) surrogate concentrations were collected from the electronic health records of 596 children, including those with obesity. Using linear mixed‐effects regression models, we observed that 4‐hour anti‐Xa concentrations were statistically significantly different in children with and without obesity, even for children with the same absolute dose (P = 0.004). To further mechanistically explore obesity‐associated differences in anti‐Xa concentration, a pediatric physiologically‐based pharmacokinetic (PBPK) model was developed in adults, and then scaled to children with and without obesity. This PBPK model incorporated binding of enoxaparin to antithrombin to form anti‐Xa and elimination via heparinase‐mediated metabolism and glomerular filtration. Following scaling, the PBPK model predicted real‐world pediatric concentrations well, with an average fold error (standard deviation of the fold error) of 0.82 (0.23) and 0.87 (0.26) in children with and without obesity, respectively. PBPK model simulations revealed that children with obesity have at most 20% higher 4‐hour anti‐Xa concentrations under recommended, total body weight–based dosing compared to children without obesity owing to reduced weight‐normalized clearance. Enoxaparin exposure was better matched across age groups and obesity status using fat‐free mass weight‐based dosing.

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 (Cmax) 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.

Physiologically Based Pharmacokinetic Modeling of Metformin in Children and Adolescents With Obesity.

Childhood obesity continues to rise in the United States and, with it, the off-label use of metformin for weight loss. The influence of age and obesity on the drug's disposition and exposure has not previously been studied using a mechanistic framework. Here, an adult physiologically based pharmacokinetic (PBPK) model of metformin was scaled to pediatric populations without obesity, with overweight/obesity, and with severe obesity; a published virtual population of children and adolescents with obesity was leveraged during model evaluation. When the pediatric model was simulated in groups aged 10 to 18 years, oral clearance following 1000mg of metformin was higher (≈1200mL/min) in those with obesity and severe obesity compared to the groups without and with overweight (≈1000mL/min). In addition, simulated area under the concentration-time curve in older children and adolescents with obesity and severe obesity was comparable to that in adults with a similar dose-exposure relationship. Overall, simulations using the pediatric PBPK model support the use of adult doses of metformin in older children and adolescents with obesity. Moreover, the virtual population of children and adolescents with obesity offers a valuable tool to facilitate development of pediatric PBPK models for studying populations with obesity and, in turn, contribute information to inform drug labeling in this special population.

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations.

There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics. The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P‐PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P‐PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P‐PBPK modeling increased 33‐fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P‐PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug–drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P‐PBPK models.

Cytochrome P450 enzymes in the pediatric population: Connecting knowledge on P450 expression with pediatric pharmacokinetics.

Cytochrome P450 enzymes play an important role in the pharmacokinetics, efficacy, and toxicity of drugs. Age-dependent changes in P450 enzyme expression have been studied based on several detection systems, as well as by deconvolution of in vivo pharmacokinetic data observed in pediatric populations. The age-dependent changes in P450 enzyme expression can be important determinants of drug disposition in childhood, in addition to the changes in body size and the other physiological parameters, and effects of pharmacogenetics and disease on organ functions. As a tool incorporating drug-specific and body-specific factors, physiologically-based pharmacokinetic (PBPK) models have become increasingly used to characterize and explore mechanistic insights into drug disposition. Thus, PBPK models can be a bridge between findings from basic science and utilization in predictive science. Pediatric PBPK models incorporate additional system specific information on developmental physiology and ontogeny and have been used to predict pharmacokinetic parameters from preterm neonates onwards. These models have been advocated by regulatory authorities in order to support pediatric clinical trials. The purpose of this chapter is to highlight accumulated knowledge and findings from basic research focusing on P450 enzymes, as well as the current status and future challenges of expanding the utilization of pediatric PBPK modeling.

Development of best practices in physiologically based pharmacokinetic modeling to support clinical pharmacology regulatory decision-making-A workshop summary.

Development of best practices in physiologically based pharmacokinetic modeling to support clinical pharmacology regulatory decision-making-A workshop summary.