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Dexamethasone is a synthetic glucocorticoid approved for treating disorders of various organ systems in both adult and pediatric populations. Currently, approved pediatric dosing recommendations are weight‐based, but it is unknown whether differences in dexamethasone drug disposition and exposure exist for children with obesity. This study aimed to develop a population pharmacokinetic (PopPK) model for dexamethasone with data collected from children with obesity. Dexamethasone was given as either IV or oral/enteral administration, and a salt factor correction was used for dexamethasone sodium phosphate injection. A PopPK analysis using dexamethasone plasma concentration versus time was performed using the software NONMEM. A virtual population of 1000 children with obesity across three age groups was generated for dosing simulations. Data from 59 study participants with 82 PK plasma samples were used in the PopPK analysis. A one‐compartment model with first‐order absorption and the inclusion of total body weight as a covariate characterized the data. No other covariates were included in the PopPK model. Single and multiple IV dose(s) of 0.5 and 1 mg/kg every 8 h resulted in 68% or more of virtual children with obesity attaining simulated exposures that were within exposure ranges previously reported in adult studies. In conclusion, this was the first study to characterize dexamethasone's PopPK in children with obesity. Simulation results suggest that virtual children with obesity receiving oral doses of 0.5 and 1 mg/kg had generally comparable dexamethasone exposures as adult estimates. Additional studies are needed to characterize the dexamethasone's target exposure in children. [ABSTRACT FROM AUTHOR]

Pantoprazole is a proton pump inhibitor indicated for the treatment of gastroesophageal reflux disease, a condition that disproportionately affects children with obesity. Appropriately dosing pantoprazole in children with obesity requires understanding the body size metric that best guides dosing, but pharmacokinetic (PK) trials using traditional techniques are limited by the need for larger sample sizes and frequent blood sampling. Physiologically‐based PK (PBPK) models are an attractive alternative that can account for physiologic‐, genetic‐, and drug‐specific changes without the need for extensive clinical trial data. In this study, we explored the effect of obesity on pantoprazole PK and evaluated label‐suggested dosing in this population. An adult PBPK model for pantoprazole was developed using data from the literature and accounting for genetic variation in CYP2C19. The adult PBPK model was scaled to children without obesity using age‐associated changes in anatomical and physiological parameters. Lastly, the pediatric PBPK model was expanded to children with obesity. Three pantoprazole dosing strategies were evaluated: 1 mg/kg total body weight, 1.2 mg/kg lean body weight, and US Food and Drug Administration‐recommended weight‐tiered dosing. Simulated concentration–time profiles from our model were compared with data from a prospective cohort study (PAN01; NCT02186652). Weight‐tiered dosing resulted in the most (>90%) children with pantoprazole exposures in the reference range, regardless of obesity status or CYP2C19 phenotype, confirming results from previously published population PK models. PBPK models may allow for the efficient study of physiologic and developmental effects of obesity on PK in special populations where clinical trial data may be limited. [ABSTRACT FROM AUTHOR]

Background and Objective: Pediatric dosing of enoxaparin was derived based on extrapolation of the adult therapeutic range to children. However, a large fraction of children do not achieve therapeutic anticoagulation with initial dosing. We aim to use real-world anti-Xa data obtained from children receiving enoxaparin per standard of care to characterize the population pharmacokinetics (PopPK).Author names: Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Also, kindly confirm the details in the metadata are correct.The author names are accurately presented and the metadata are correct. Methods: A PopPK analysis was performed using NONMEM, and a stepwise covariate modeling approach was applied for the covariate selection. The final PopPK model, developed with data from 1293 patients ranging in age from 1 day to 18 years, was used to simulate enoxaparin subcutaneous dosing for prophylaxis and treatment based on total body weight (0–18 years, TBW) or fat-free mass (2–18 years, FFM). Simulated exposures in children with obesity (body mass index percentile ≥95th percentile) were compared with those without obesity. Results: A linear, one-compartment PopPK model that included allometric scaling using TBW (<2 years) or FFM (≥2 years) characterized the enoxaparin pharmacokinetic data. In addition, serum creatinine was identified as a significant covariate influencing clearance. Simulations indicated that in patients aged <2 years, the recommended 1.5 mg/kg TBW-based dosing achieves therapeutic simulated concentrations. In pediatric patients aged ≥2 years, the recommended 1.0 mg/kg dose resulted in exposures more comparable in children with and without obesity when FFM weight-based dosing was applied. Conclusion: Using real-world data and PopPK modeling, enoxaparin's pharmacokinetics were characterized in pediatric patients. Using FFM and twice-daily dosing might reduce the risk of overdosing, especially in children with obesity. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to evaluate ceftazidime pharmacokinetics (PK) in a cohort that includes a predominate number of children and adolescents with obesity and assess the efficacy of competing dosing strategies. Methods: A population PK model was developed using opportunistically collected plasma samples. For each dosing strategy, model-based probability of target attainment (PTA) estimates were computed for study participants using empirical Bayes estimates. In addition, the effects of body size and renal function on PTA were evaluated using stochastic model simulations with virtually generated subjects. Results: Twenty-nine participants, 24 of whom were obese, contributed data towards the analysis. The median (range) age, body weight, and body mass index of participants were 12.2 years (2.3–20.6), 59.2 kg (8.4–121), and 25.2 kg/m2 (13.8–42.9), respectively. Administration of 50 mg/kg intravenously (IV) every 8 hours (q8h; max 6 g/day) or 40 mg/kg IV q6h (max 6 g/day) resulted in PTA values of ≥ 90% (minimum inhibitory concentration 8 mg/L) for the subset of obese participants with estimated glomerular filtration rates (GFR) ≥ ~ 80 mL/min/1.73 m2. However, for both regimens, stochastic model simulations denoted lower PTA values (< 90%) with increasing body weight for virtual subjects with GFR ≥ 120 mL/min/1.73 m2. Alternatively, permitting for a maximum daily dose of 8 g/day using a 40 mg/kg IV q6h regimen provided PTA values that were near or above target (90%) for virtual subjects between 10 to 120 kg with GFR ≥ 80 mL/min/1.73 m2. Conclusion: Our analysis suggests administration of 40 mg/kg IV q6h (max 8 g/day) maximizes PTA in children and adolescents with obesity and GFR ≥ 80 mL/min/1.73 m2. Trial Registration: Clinicaltrials.gov Identifier: NCT01431326. [ABSTRACT FROM AUTHOR]

Physiologically‐based pharmacokinetic (PBPK) modeling can potentially predict pediatric drug‐drug interactions (DDIs) when clinical DDI data are limited. In infants for whom treatment of pulmonary hypertension and prevention or treatment of invasive candidiasis are indicated, sildenafil with fluconazole may be given concurrently. To account for developmental changes in cytochrome P450 (CYP) 3A, we determined and incorporated fluconazole inhibition constants (KI) for CYP3A4, CYP3A5, and CYP3A7 into a PBPK model developed for sildenafil and its active metabolite, N‐desmethylsildenafil. Pharmacokinetic (PK) data in preterm infants receiving sildenafil with and without fluconazole were used for model development and evaluation. The simulated PK parameters were comparable to observed values. Following fluconazole co‐administration, differences in the fold change for simulated steady‐state area under the plasma concentration vs. time curve from 0 to 24 hours (AUCss,0–24) were observed between virtual adults and infants (2.11‐fold vs. 2.82‐fold change). When given in combination with treatment doses of fluconazole (12 mg/kg i.v. daily), reducing the sildenafil dose by ~ 60% resulted in a geometric mean ratio of 1.01 for simulated AUCss,0–24 relative to virtual infants receiving sildenafil alone. This study highlights the feasibility of PBPK modeling to predict DDIs in infants and the need to include CYP3A7 parameters. [ABSTRACT FROM AUTHOR]

The ubiquinol: cytochrome-c oxidoreductase (cytochrome bc1 complex) is a central component of the mitochondrial respiratory chain as well as the respiratory and/or photosynthetic systems of numerous prokaryotic organisms. In Rhodobacter sphaeroides, the bc1 complex has a dual function. When the cells are grown photosynthetically, the bc1 complex is present in the intracytoplasmic membrane and is a critical component of the cyclic electron transport system. When the cells are grown in the dark in the presence of oxygen, the same bc1 complex is a necessary component of the cytochrome-c2-dependent respiratory chain. The fact that the bc1 complex from R. sphaeroides has been extensively studied, plus the ability to manipulate this organism genetically, makes this an ideal system for using site-directed mutagenesis to address questions relating to the structure and function of the bc1 complex. In the current work, the cloning and complete sequence of the fbc operon from R. sphaeroides is reported. As in other bacteria, this operon contains three genes, encoding the Rieske 2Fe-2S subunit, the cytochrome b subunit, and the cytochrome c1 subunit. Recombination techniques were used to delete the entire fbc operon from the chromosome. The resulting strain cannot grow photosynthetically, but can grow aerobically utilizing a quinol oxidase. Photosynthetic growth is restored by providing fbc operon on a plasmid, and the reappearance of the protein subunits and the spectroscopic features due to the bc1 complex are also demonstrated. Finally, a mutation is introduced within the gene encoding the cytochrome b subunit which is predicted to confer resistance to the inhibitor myxothiazol. It is shown that the resulting strain contains a functional bc1 complex which, as expected, is resistant to the inhibitor. Hence, this system is suitable for the detailed characterization of the bc1 complex, combining site-directed mutagenesis with the biochemical and biophysical techniques which have been previously developed for the study of photosynthetic bacteria. [ABSTRACT FROM AUTHOR]