Use of physiologically-based pharmacokinetic modeling to inform dosing of the opioid analgesics fentanyl and methadone in children with obesity.

Obesity is an increasingly alarming public health threat, with nearly 20% of children classified as obese in the United States today. Children with obesity are commonly prescribed the opioids fentanyl and methadone, and accurate dosing is critical to reducing the risk of serious adverse events associated with overexposure. However, pharmacokinetic studies in children with obesity are challenging to conduct, so there is limited information to guide fentanyl and methadone dosing in these children. To address this clinical knowledge gap, physiologically-based pharmacokinetic models of fentanyl and methadone were developed in adults and scaled to children with and without obesity to explore the interplay of obesity, age, and pharmacogenomics. These models included key obesity-induced changes in physiology and pharmacogenomic effects. Model predictions captured observed concentrations in children with obesity well, with an overall average fold error of 0.72 and 1.08 for fentanyl and methadone, respectively. Model simulations support a reduced fentanyl dose (1 vs. 2 µg/kg/h) starting at an earlier age (6 years) in virtual children with obesity, highlighting the importance of considering both age and obesity status when selecting an infusion rate most likely to achieve steady-state concentrations within the target range. Methadone dosing simulations highlight the importance of considering genotype in addition to obesity status when possible, as cytochrome P450 (CYP)2B6*6/*6 virtual children with obesity required half the dose to match the exposure of wildtype children without obesity. This physiologically-based pharmacokinetic modeling approach can be applied to explore dosing of other critical drugs in children with obesity.

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 Evaluation of a Virtual Population of Children with Obesity for Physiologically Based Pharmacokinetic Modeling.

BACKGROUND AND OBJECTIVE: While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity. METHODS: To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models. RESULTS: Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens. CONCLUSIONS: Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.

Leveraging Physiologically Based Pharmacokinetic Modeling and Experimental Data to Guide Dosing Modification of CYP3A-Mediated Drug-Drug Interactions in the Pediatric Population.

Solithromycin is a novel fluoroketolide antibiotic that is both a substrate and time-dependent inhibitor of CYP3A. Solithromycin has demonstrated efficacy in adults with community-acquired bacterial pneumonia and has also been investigated in pediatric patients. The objective of this study was to develop a framework for leveraging physiologically based pharmacokinetic (PBPK) modeling to predict CYP3A-mediated drug-drug interaction (DDI) potential in the pediatric population using solithromycin as a case study. To account for age, we performed in vitro metabolism and time-dependent inhibition studies for solithromycin for CYP3A4, CYP3A5, and CYP3A7. The PBPK model included CYP3A4 and CYP3A5 metabolism and time-dependent inhibition, glomerular filtration, P-glycoprotein transport, and enterohepatic recirculation. The average fold error of simulated and observed plasma concentrations of solithromycin in both adults (1966 plasma samples) and pediatric patients from 4 days to 17.9 years (684 plasma samples) were within 0.5- to 2.0-fold. The geometric mean ratios for the simulated area under the concentration versus time curve (AUC) extrapolated to infinity were within 0.75- to 1.25-fold of observed values in healthy adults receiving solithromycin with midazolam or ketoconazole. DDI potential was simulated in pediatric patients (1 month to 17 years of age) and adults. Solithromycin increased the simulated midazolam AUC 4- to 6-fold, and ketoconazole increased the simulated solithromycin AUC 1- to 2-fold in virtual subjects ranging from 1 month to 65 years of age. This study presents a systematic approach for incorporating CYP3A in vitro data into adult and pediatric PBPK models to predict pediatric CYP3A-mediated DDI potential. SIGNIFICANCE STATEMENT: Using solithromycin, this study presents a framework for investigating and incorporating CYP3A4, CYP3A5, and CYP3A7 in vitro data into adult and pediatric physiologically based pharmacokinetic models to predict CYP3A-mediated DDI potential in adult and pediatric subjects during drug development. In this study, minor age-related differences in inhibitor concentration resulted in differences in the magnitude of the DDI. Therefore, age-related differences in DDI potential for substrates metabolized primarily by CYP3A4 can be minimized by closely matching adult and pediatric inhibitor concentrations.