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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.

The conventional approach to approximating the pharmacokinetics of drugs in patients with chronic kidney disease (CKD) only accounts for changes in the estimated glomerular filtration rate. However, CKD is a systemic and multifaceted disease that alters many body systems. Therefore, the objective of this exercise was to develop and evaluate a whole-body mechanistic approach to predicting pharmacokinetics in patients with CKD. Physiologically based pharmacokinetic models were developed in PK-Sim v8.0 (www.open-systems-pharmacology.org) to mechanistically represent the disposition of 7 compounds in healthy human adults. The 7 compounds selected were eliminated by glomerular filtration and active tubular secretion by the organic cation transport system to varying degrees. After a literature search, the healthy adult models were adapted to patients with CKD by numerically accounting for changes in glomerular filtration rate, kidney volume, renal perfusion, hematocrit, plasma protein concentrations, and gastrointestinal transit. Literature-informed interindividual variability was applied to the physiological parameters to facilitate a population approach. Model performance in CKD was evaluated against pharmacokinetic data from 8 clinical trials in the literature. Overall, integration of the CKD parameterization enabled exposure predictions that were within 1.5-fold error across all compounds and patients with varying stages of renal impairment. Notable improvement was observed over the conventional approach to scaling exposure, which failed in all but 1 scenario in patients with advanced CKD. Further research is required to qualify its use for first-in-CKD dose selection and clinical trial planning for a wider selection of renally eliminated compounds, including those subject to anion transport., (© 2020, The American College of Clinical Pharmacology.)

Pediatric physiologically based pharmacokinetic (PBPK) models facilitate the estimation of pharmacokinetic (PK) parameters in children under specific exposure conditions. In human health risk assessment, PBPK modeling has been used to determine a chemical-specific human kinetic adjustment factor (HKAF). Due to increased demands in regulatory assessment, model evaluation and qualification have gained growing attention. The aim of this study was to undertake model qualification of pediatric PBPK models for compounds that are primarily metabolized by cytochrome P450 (CYP) enzymes. The objectives were to determine the appropriateness of the virtual individual creating algorithm in PK-Sim® in predicting PK parameters and their variability in children and identify critical system-specific inputs. PBPK models in adults were constructed for several pharmaceuticals (grouped by major clearance process such as CYP3A4). Several age groups of virtual individuals were created to represent children in pediatric clinical studies. The mean and variance of clearance (CL) from virtual populations were compared to observed values. Sensitivity analysis on area under the curve (AUC) was performed. System-specific parameters of virtual children that contribute to inter-individual PK properties were assessed. Eighty-one percent of the comparisons between simulated and observed clearance values were within twofold error. The mean fold errors were 1.1, 1, 0.7 and 1.8 in adolescents, children, infants and neonates, respectively. CL variability was reasonably predicted for 70% of the comparisons with comparable coefficients of variation between observed and predicted. The sensitivity analysis revealed that fraction unbound in plasma, parameters related to CYP enzyme-mediated metabolism and liver volumewere most important in the estimation of pediatric exposure. A comparison of variabilities in weight, height and liver volume in virtual children showed reliable agreement with observed data. The presented results of predictive performance and properties of virtual populations provide confidence in the use of PK-Sim for pediatric PBPK modeling in toxicological applications including PBPK-based-HKAF derivation.

Selection of the first dose for neonates in clinical trials is very challenging. The objective of this analysis was to assess if a population pharmacokinetic (PK) model developed with data from infants to adults is predictive of neonatal clearance and to evaluate what age range of prior PK data is needed for informative modeling to predict neonate exposure. Two sources of pharmacokinetic data from 8 drugs were used to develop population models: (1) data from all patients > 2 years of age, and (2) data from all nonneonatal patients aged > 28 days. The prediction error based on the models using data from subjects > 2 years of age showed bias toward overprediction, with median average fold error (AFE) for CL predicted/CLobserved greater than 1.5. The bias for predicting neonatal PK was improved when using all prior PK data including infants as opposed to an assessment without infant PK data, with the median AFE 0.91. As an increased number of pediatric trials are conducted in neonates under the Food and Drug Administration Safety and Innovation Act, dose selection should be based on the best estimates of neonatal pharmacokinetics and pharmacodynamics prior to conducting efficacy and safety studies in neonates., (© 2015, The American College of Clinical Pharmacology.)

Background and Objectives: Pharmacokinetics play an integral role in the pediatric drug development process. The determination of pharmacokinetic parameters, particularly clearance, in different age groups directly informs dosing strategies for subsequent efficacy trials. Allometric scaling for prediction of pediatric clearance from the observed clearance in adults has been used in this effort. Clinical trial simulation, a powerful tool used to inform clinical trial design, requires both an estimate of clearance along with an estimate of the expected pharmacokinetic variability. The standard deviations (SD) of individual clearance values for adults are typically used and may lead to inaccurate predictions by not taking into account the more widespread distribution of factors such as body weight in the pediatric population. The objective of this study was to assess the accuracy of allometric prediction of drug clearance as well as methods for predicting clearance variability in children 6 years of age and older., Methods: US Food and Drug Administration (FDA) clinical pharmacology reviews of pediatric studies conducted from 2002 onwards were reviewed to collate adult and pediatric clearance and clearance variability for studies including children 6 years of age and older. A set of 1,000 virtual adults {A} and a set of 5,000 virtual children (aged 2-17) {P} were generated on the basis of the White American NHANES database. Pediatric clearances were predicted in method 1 by using the geometric mean adult clearance from the in vivo study and calculating pediatric clearance for each virtual child within a subset {P'} of {P} that contained only those children that were within the age range of the in vivo pediatric study. In method 2, adult clearance values were randomly generated from the geometric mean adult clearance and standard deviation and assigned to each virtual adult in {A}. For each adult, allometric clearance scaling was completed with each virtual child within {P'}. The prediction error for the predicted and observed clearance and the clearance variability metric, coefficient of variation (CV), was calculated. The prediction accuracy as a function of the lowest age range (2 years and older) included in the study was also assessed., Results: Thirty-nine unique drugs were included in the study. For both method 1 and method 2, 100 % of predicted pediatric mean clearances were within 2-fold of the observed values and approximately 82 % were within a 30 % prediction error. There was a significant increase in the prediction accuracy of CV using method 2 vs. method 1. There was a major bias towards underprediction of pediatric CV in method 1 whereas method 2 was precise and not biased. Clearance and CV prediction accuracy were not a function of the age range included in the in vivo studies. The observed CV between the adult and pediatric study groups was not significantly different although, on average, the observed pediatric CV was 32 % greater than that from adult studies., Conclusions: Allometric scaling may be a useful tool during pediatric drug development to predict drug clearance and dosing requirements in children 6 years of age and older. A novel methodology is reported that employs virtual adult and pediatric populations and adult pharmacokinetic data to accurately predict clearance variability in specific pediatric subpopulations. This approach has important implications for both clinical trial simulations and sample size determination for pediatric pharmacokinetic studies.

The application of in silico methods for predicting internal dosimetry of a compound has gained attention in the past few years from academia, government and industry. One such method based on both compound- and organism-specific information is physiologically-based pharmacokinetic (PBPK) modeling. Numerous promises surrounding the potential of PBPK models to guide drug development (DD) and human health risk assessment (HHRA) have been made with primary areas of application being incorporation of in vitro data for pharmacokinetic prediction in early drug development, interspecies scaling, intra-human scaling and, of special interest, prediction of drug-drug interaction potential. This article addresses the question 'Have physiologically-based pharmacokinetic models delivered?' through analysis of its promises and accomplishments in real-world situations. Progress on PBPK model use in DD and HHRA has been demonstrated, especially in the area of interspecies and adult-to-children scaling, although its actual application is not reflected in the number of published works. Future advances will depend on continued model development as well as integration of PBPK models with models of response and/or disease. More importantly, increased training along with managerial and regulatory support is imperative to the continued integration of PBPK modeling in both HHRA and DD.

Under extreme conditions of heat exposure and exercise stress, the human body undergoes major physiological changes. Perturbations in organ blood flows, gastrointestinal properties, and vascular physiology may impact the body's ability to absorb, distribute, and eliminate drugs. Clinical studies on the effect of these stressors on drug pharmacokinetics demonstrate that the likelihood of pharmacokinetic alteration is dependent on drug properties and the intensity of the stressor. The objectives of this study were to use literature data to quantify the correlation between exercise and heat exposure intensity to changing physiological parameters and further, to use this information for the parameterization of a whole-body, physiologically based pharmacokinetic model for the purposes of determining those drug properties most likely to demonstrate altered drug pharmacokinetics under stress. Cardiac output and most organ blood flows were correlated with heart rate using regression analysis. Other altered parameters included hematocrit and intravascular albumin concentration. Pharmacokinetic simulations of intravenous and oral administration of hypothetical drugs with either a low or high value of lipophilicity, unbound fraction in plasma, and unbound intrinsic hepatic clearance demonstrated that the area under the curve of those drugs with a high unbound intrinsic clearance was most affected (up to a 130% increase) following intravenous administration, whereas following oral administration, pharmacokinetic changes were smaller (<40% increase in area under the curve) for all hypothetical compounds. A midazolam physiologically based pharmacokinetic model was also used to demonstrate that simulated changes in pharmacokinetic parameters under exercise and heat stress were generally consistent with those reported in the literature.

Objective: To assess pharmacy students' attitudes towards a blended-learning pharmacokinetics course., Design: Narrated visual presentations and animations that illustrated kinetic processes and guided students through the use of software programs used for calculations were created. Other learning techniques used included online self-assessment quizzes, practice problem sets, and weekly face-to-face problem-solving tutorials., Assessment: A precourse questionnaire to assess students' level of enthusiasm towards the blended-learning course and to solicit any concerns they had was administered at the beginning of the course. A postcourse questionnaire that included the same 4 Likert-scale items from the precourse questionnaire and follow-up open-ended questions was administered. Individual changes in level of enthusiasm were compared for individuals who completed both the precourse and postcourse questionnaire. Students' concerns about the blended method of learning had decreased postcourse while their enthusiasm for the benefits of blended learning had increased., Conclusion: Students' initial concerns about the blended learning experience were focused on their ability to communicate with the instructor about the online components, but shifted to their own time management skills at the end of the course. Face-to-face interactions with each other and with the instructor were more highly rated than online interactions in this course.

Background: Whole-body physiologically-based pharmacokinetic (WB-PBPK) models mathematically describe an organism as a closed circulatory system consisting of compartments that represent the organs important for compound absorption, distribution, metabolism and elimination., Objectives: To review the current state of WB-PBPK model use in the clinical phases of drug development., Methods: A qualitative description of the WB-PBPK model structure is included along with a review of the varying methods available for input parameterisation. Current and potential WB-PBPK model application in clinical development is discussed., Conclusions: This modelling tool is at present used for small and large molecule drug development primarily as a means to scale pharmacokinetics from animals to humans based on physiology. The pharmaceutical industry is active in employing these models to clinical drug development although the applications in use now are narrow in comparison to the potential. Expanded integration of WB-PBPK models into the drug development process will only be achieved with staff training, managerial will, success stories and regulatory agency openness.

Purpose: The development and validation of a physiology-based absorption model for orally administered drugs in monkeys is described., Materials and Methods: Physiological parameters affecting intestinal transit and absorption of an orally administered drug in monkeys have been collected from the literature and implemented in a physiological model for passive absorption previously developed for rats and humans. Predicted fractions of dose absorbed have been compared to experimentally observed values for a set of N = 37 chemically diverse drugs. A sensitivity analysis was performed to assess the influence of various physiological model parameters on the predicted fraction dose absorbed., Results: A Pearson's correlation coefficient of 0.94 (95% confidence interval: [0.88, 0.97]; p < 0.0001) between the predicted and observed fraction dose absorbed in monkeys was obtained for compounds undergoing non-solubility limited passive absorption (N = 29). The sensitivity analysis revealed that the predictions of fractions dose absorbed in monkeys are very sensitive with respect to inter-individual variations of the small intestinal transit time., Conclusions: The model is well suited to predict the fraction dose absorbed of passively absorbed compounds after oral administration and to assess the influence of inter-individual physiological variability on oral absorption in monkeys.

In clinical development stages, an a priori assessment of the sensitivity of the pharmacokinetic behavior with respect to physiological and anthropometric properties of human (sub-) populations is desirable. A physiology-based pharmacokinetic (PBPK) population model was developed that makes use of known distributions of physiological and anthropometric properties obtained from the literature for realistic populations. As input parameters, the simulation model requires race, gender, age, and two parameters out of body weight, height and body mass index. From this data, the parameters relevant for PBPK modeling such as organ volumes and blood flows are determined for each virtual individual. The resulting parameters were compared to those derived using a previously published model (P(3)M). Mean organ weights and blood flows were highly correlated between the two models, despite the different methods used to generate these parameters. The inter-individual variability differed greatly especially for organs with a log-normal weight distribution (such as fat and spleen). Two exemplary population pharmacokinetic simulations using ciprofloxacin and paclitaxel as model drugs showed good correlation to observed variability. A sensitivity analysis demonstrated that the physiological differences in the virtual individuals and intrinsic clearance variability were equally influential to the pharmacokinetic variability but were not additive. In conclusion, the new population model is well suited to assess the influence of individual physiological variability on the pharmacokinetics of drugs. It is expected that this new tool can be beneficially applied in the planning of clinical studies.

Background: Clinical trials in children are being encouraged by regulatory authorities in light of the immense off-label and unlicensed use of drugs in the paediatric population. The use of in silico techniques for pharmacokinetic prediction will aid in the development of paediatric clinical trials by guiding dosing regimens, ensuring efficient blood sampling times, maximising therapeutic effect and potentially reducing the number of children required for the study. The goal of this study was to extend an existing physiologically based pharmacokinetic (PBPK) model for adults to reflect the age-related physiological changes in children from birth to 18 years of age and, in conjunction with a previously developed age-specific clearance model, to evaluate the accuracy of the paediatric PBPK model to predict paediatric plasma profiles., Methods: The age-dependence of bodyweight, height, organ weights, blood flows, interstitial space and vascular space were taken from the literature. Physiological parameters that were used in the PBPK model were checked against literature values to ensure consistency. These included cardiac output, portal vein flow, extracellular water, total body water, lipid and protein. Five model compounds (paracetamol [acetaminophen], alfentanil, morphine, theophylline and levofloxacin) were then examined by gathering the plasma concentration-time profiles, volumes of distribution and elimination half-lives from different ages of children and adults. First, the adult data were used to ensure accurate prediction of pharmacokinetic profiles. The model was then scaled to the specific age of children in the study, including the scaling of clearance, and the generated plasma concentration profiles, volumes of distribution and elimination half-lives were compared with literature values., Results: Physiological scaling produced highly age-dependent cardiac output, portal vein flow, extracellular water, total body water, lipid and protein values that well represented literature data. The pharmacokinetic profiles in children for the five compounds were well predicted and the trends associated with age were evident. Thus, young neonates had plasma concentrations greater than the adults and older children had concentrations less than the adults. Eighty-three percent, 97% and 87% of the predicted plasma concentrations, volumes of distribution and elimination half-lives, respectively, were within 50% of the study reported values. There was no age-dependent bias for term neonates to 18 years of age when examining volumes of distribution and elimination half-lives., Conclusion: This study suggests that the developed paediatric PBPK model can be used to scale pharmacokinetics from adults. The accurate prediction of pharmacokinetic parameters in children will aid in the development of dosing regimens and sampling times, thus increasing the efficiency of paediatric clinical trials.

Background and Objective: Clearance is an important pharmacokinetic concept for scaling dosage, understanding the risks of drug-drug interactions and environmental risk assessment in children. Accurate clearance scaling to children requires prior knowledge of adult clearance mechanisms and the age-dependence of physiological and enzymatic development. The objective of this research was to develop and evaluate ontogeny models that would provide an assessment of the age-dependence of clearance., Methods: Using in vitro data and/or in vivo clearance values for children for eight compounds that are eliminated primarily by one process, models for the ontogeny of renal clearance, cytochrome P450 (CYP) 3A4, CYP2E1, CYP1A2, uridine diphosphate glucuronosyltransferase (UGT) 2B7, UGT1A6, sulfonation and biliary clearance were developed. Resulting ontogeny models were evaluated using six compounds that demonstrated elimination via multiple pathways. The proportion of total clearance attributed to each clearance pathway in adults was delineated. Each pathway was individually scaled to the desired age, inclusive of protein-binding prediction, and summed to generate a total plasma clearance for the child under investigation. The paediatric age range included in the study was premature neonates to sub-adults., Results: There was excellent correlation between observed and predicted clearances for the model development (R2 = 0.979) and test sets (Q2 = 0.927). Clearance in premature neonates could also be well predicted (development R2 = 0.951; test Q2 = 0.899)., Conclusion: Paediatric clinical trial development could greatly benefit from clearance scaling, particularly in guiding dosing regimens. Furthermore, since the proportion of clearance via different elimination pathways is age-dependent, information could be gained on the developmental extent of drug-drug interactions.

Introduction: Web‐Accessible Population–Pharmacokinetic Service–Haemophilia (WAPPS‐Hemo) data are available to study factor‐concentrate usage, defined as the required weekly dose to achieve a 3% trough (WD3T), across standard and extended half‐life (SHL/EHL) products. Aim: To provide baseline usage data including (i) differences across plasma‐derived (pdSHL) versus recombinant (rSHL) products, (ii) SHL versus EHL, and (iii) effect of age and positive inhibitor history. Methods: PK profiles (n = 14,416 patients, 0.3–85.2 years) and linear mixed effects models were used to estimate usage versus age, controlling for significant factors, using 95% confidence intervals to perform comparisons across all ages and posthoc tests to assess the differences. Results: Average usage was significantly higher for pdSHL versus rSHL in patients with a positive inhibitor history (PIH; 1.9–2.5 times higher), for SHL versus EHL (4–10 times), and was significantly associated with age. Conclusion: Baseline usage patterns from 2017 to early 2023 provide a benchmark for assessing the impact of emerging technologies in haemophilia. [ABSTRACT FROM AUTHOR]

Introduction: Plasminogen deficiency is an ultra rare disease whose patients may develop ligneous lesions if untreated. Prophylactic replacement therapy with plasma derived plasminogen, Ryplazim, is efficient in treating lesions and could benefit from pharmacokinetic (PK) tailoring. Aim: The objectives of this study are to develop, evaluate and integrate into the WAPPS‐Hemo platform a Population PK model supporting prophylactic replacement therapy for Plasminogen deficient patients. Methods: Population PK modelling and evaluations followed the same protocol performed for factor VIII and IX concentrates. Limited sampling analysis used dosing and sampling scenarios in accordance with recommended treatment for Ryplazim. Results: The population PK model, derived from 16 participants included in previous clinical studies, was a 2‐compartment model whose variability was best described by fat‐free mass. Evaluations showed that the model described well the data and Bayesian forecasting in limited sampling environment led to acceptable precision for PK parameters relevant to plasminogen treatment. Conclusion: The model was integrated into the WAPPS‐Hemo webservice to help individualize prophylactic treatment in plasminogen deficient patients. Prospective PK data to be collected through the WAPPS‐Hemo database will be used to better understand plasminogen PK and improve patient care. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Damoctocog alfa pegol (BAY 94–9027, Jivi®) is an extended half‐life recombinant factor (F)VIII replacement, indicated for the treatment of haemophilia A in patients aged ≥12 years. Following introduction of damoctocog alfa pegol in Canada in 2020, there have been no reports on routine clinical effectiveness and satisfaction, when switching from a previous FVIII product in Canada. Aim: To report changes in pharmacokinetics, effectiveness, utilization and patient satisfaction when switching to damoctocog alfa pegol prophylaxis from previous standard half‐life octocog alfa (BAY 81–8973, Kovaltry®) treatment. Methods: A single‐centre, intra‐patient comparison of pharmacokinetics and clinical outcomes was performed. Blood samples drawn once pre‐dose and ≥2 times post‐dose were measured by a one‐stage assay to assess pharmacokinetic parameters including area under the curve (AUC, primary endpoint). Patient‐reported outcomes data were collected using the Patient‐Reported Outcomes, Burdens and Experiences questionnaire (PROBE). Clinical outcomes included annualized bleeding rate (ABR) and factor utilization. Results: Dose‐normalized AUC was significantly increased after switch to damoctocog alfa pegol from octocog alfa. Median (quartile [Q]1; Q3) annualized bleeding rates were 0.67 (0.00; 1.33) with damoctocog alfa pegol and 1.33 (0.00; 2.67) with octocog alfa. Half of the patients receiving damoctocog alfa pegol prophylaxis experienced zero bleeds (n = 9, 50.0%) versus 38.9% (n = 7) of patients treated with octocog alfa. Patients' good quality of life was maintained. Conclusion: This study provides routine clinical evidence supporting the benefits of switching from octocog alfa to damoctocog alfa pegol for patients with severe haemophilia A. [ABSTRACT FROM AUTHOR]

Physiologically based pharmacokinetic (PBPK) models of skin absorption are a powerful resource for estimating drug delivery and chemical risk of dermatological products. This paper presents a PBPK workflow for the quantification of the mechanistic determinants of skin permeability and the use of these quantities in the prediction of skin absorption in novel contexts. A state-of-the-art mechanistic model of dermal absorption was programmed into an open-source modeling framework. A sensitivity analysis was performed to identify the uncertain compound-specific, individual-specific, and site-specific model parameters that impact permeability. A Bayesian Markov Chain Monte Carlo algorithm was employed to derive distributions of these parameters given in vitro experimental permeability measurements. Extrapolations to novel contexts were generated by simulating the model following its update with samples drawn from the learned distributions as well as parameters that represent the intended scenario. This algorithm was applied multiple times, each using a unique set of permeability measurements sourced under experimental contexts that differ in terms of the compound, vehicle pH, skin sample anatomical site, and the number of compounds under which each subject's skin samples were tested. Among the data sets used in this study, the highest accuracy and precision in the extrapolated permeability was achieved in those that include measurements conducted under multiple vehicle pH levels and in which individual subjects' skin samples are tested under multiple compounds. This work thus identifies factors for consideration in the design of experiments for the purpose of training dermal models to robustly estimate drug delivery and chemical risk. [ABSTRACT FROM AUTHOR]

Spectinamides 1599 and 1810 are lead spectinamide compounds currently under preclinical development to treat multidrug-resistant (MDR) and extensively drug-resistant (XDR) tuberculosis. These compounds have previously been tested at various combinations of dose level, dosing frequency, and route of administration in mouse models of Mycobacterium tuberculosis (Mtb) infection and in healthy animals. Physiologically based pharmacokinetic (PBPK) modeling allows the prediction of the pharmacokinetics of candidate drugs in organs/tissues of interest and extrapolation of their disposition across different species. Here, we have built, qualified, and refined a minimalistic PBPK model that can describe and predict the pharmacokinetics of spectinamides in various tissues, especially those relevant to Mtb infection. The model was expanded and qualified for multiple dose levels, dosing regimens, routes of administration, and various species. The model predictions in mice (healthy and infected) and rats were in reasonable agreement with experimental data, and all predicted AUCs in plasma and tissues met the two-fold acceptance criteria relative to observations. To further explore the distribution of spectinamide 1599 within granuloma substructures as encountered in tuberculosis, we utilized the Simcyp granuloma model combined with model predictions in our PBPK model. Simulation results suggest substantial exposure in all lesion substructures, with particularly high exposure in the rim area and macrophages. The developed model may be leveraged as an effective tool in identifying optimal dose levels and dosing regimens of spectinamides for further preclinical and clinical development. [ABSTRACT FROM AUTHOR]

Cannabidiol (CBD) is approved for treatment of seizures associated with two forms of epilepsy that become apparent in infancy or early childhood. To consider an adult physiologically‐based pharmacokinetic (PBPK) model for pediatric scaling, we assessed in vitro‐derived cytochrome P450 (CYP) and uridine 5′‐diphospho‐glucuronosyltransferase (UGT) enzyme contributions to CBD clearance in human. An i.v. PBPK model was constructed using CBD physicochemical properties and knowledge of disposition. The i.v. datasets were used for model building and evaluation. Oral PBPK models for CBD administered in fasted and fed states were developed using single dose oral datasets and parameters optimized from the i.v. model and evaluated with multiple dose datasets. Relative contributions of CBD metabolizing enzymes were partitioned according to in vitro studies. Clinical drug–drug interaction (DDI) studies were simulated using CBD fed state, itraconazole, fluconazole, and rifampicin PBPK models. Linear mixed effect modeling was used to estimate area under the concentration‐time curve from zero to infinity (AUC0–∞) perpetrator + CBD versus CBD alone. The i.v. and oral datasets used in model evaluation produced acceptable average fold error (AFE) of 1.28 and absolute AFE of 1.65. Relative contributions of drug‐metabolizing enzymes to CBD clearance were proposed from in vitro data: UGT1A7 4%, UGT1A9 16%, UGT2B7 10%, CYP3A4 38%, CYP2C19 21%, and CYP2C9 11%. The simulated DDI studies using the in vitro‐derived values produced AUC0–∞ treatment ratios comparable to observed: itraconazole 1.24 versus 1.07, fluconazole 1.45 versus 1.22, and rifampicin 0.49 versus 0.69. The constructed CBD PBPK models can predict adult exposures and have potential for use in pediatrics where exposure estimates are limited. [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]

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 1000 mg of metformin was higher (≈1200 mL/min) in those with obesity and severe obesity compared to the groups without and with overweight (≈1000 mL/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. [ABSTRACT FROM AUTHOR]

Background and Objective: The renal excretion of drugs via organic anion transporters 1 and 3 (OAT1/3) is significantly decreased in patients with renal impairment. This study uses physiologically based pharmacokinetic models to quantify the reduction in OAT1/3-mediated secretion of drugs throughout varying stages of chronic kidney disease. Methods: Physiologically based pharmacokinetic models were constructed for four OAT1/3 substrates in healthy individuals: acyclovir, meropenem, furosemide, and ciprofloxacin. Observed data from drug–drug interaction studies with probenecid, a potent OAT1/3 inhibitor, were used to parameterize the contribution of OAT1/3 to the renal elimination of each drug. The models were then translated to patients with chronic kidney disease by accounting for changes in glomerular filtration rate, kidney volume, renal blood flow, plasma protein binding, and hematocrit. Additionally, a relationship was derived between the estimated glomerular filtration rate and the reduction in OAT1/3-mediated secretion of drugs based on the renal extraction ratios of ƿ-aminohippuric acid in patients with varying degrees of renal impairment. The relationship was evaluated in silico by evaluating the predictive performance of each final model in describing the pharmacokinetics (PK) of drugs across stages of chronic kidney disease. Results: OAT1/3-mediated renal excretion of drugs was found to be decreased by 27–49%, 50–68%, and 70–96% in stage 3, stage 4, and stage 5 of chronic kidney disease, respectively. In support of the parameterization, physiologically based pharmacokinetic models of four OAT1/3 substrates were able to adequately characterize the PK in patients with different degrees of renal impairment. Total exposure after intravenous administration was predicted within a 1.5-fold error and 85% of the observed data points fell within a 1.5-fold prediction error. The models modestly under-predicted plasma concentrations in patients with end-stage renal disease undergoing intermittent hemodialysis. However, results should be interpreted with caution because of the limited number of molecules analyzed and the sparse sampling in observed chronic kidney disease pharmacokinetic studies. Conclusions: A quantitative understanding of the reduction in OAT1/3-mediated excretion of drugs in differing stages of renal impairment will contribute to better predictive accuracy for physiologically based pharmacokinetic models in drug development, assisting with clinical trial planning and potentially sparing this population from unnecessary toxic exposures. [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]

Childhood obesity is an alarming public health problem. The pediatric obesity rate has quadrupled in the past 30 years, and currently nearly 20% of United States children and 9% of children worldwide are classified as obese. Drug distribution and elimination processes, which determine drug exposure (and thus dosing), can vary significantly between patients with and without obesity. Obesity-related physiological changes, such as increased tissue volume and perfusion, altered blood protein concentrations, and tissue composition can greatly affect a drug's volume of distribution, which might necessitate adjustment in loading doses. Obesity-related changes in the drug eliminating organs, such as altered enzyme activity in the liver and glomerular filtration rate, can affect the rate of drug elimination, which may warrant an adjustment in the maintenance dosing rate. Although weight-based dosing (i.e., in mg/kg) is commonly practiced in pediatrics, choice of the right body size metric (e.g., total body weight, lean body weight, body surface area, etc.) for dosing children with obesity still remains a question. To address this gap, the interplay between obesity-related physiological changes (e.g., altered organ size, composition, and function), and drug-specific properties (e.g., lipophilicity and elimination pathway) needs to be characterized in a quantitative framework. Additionally, methodological considerations, such as adequate sample size and optimal sampling scheme, should also be considered to ensure accurate and precise top-down covariate selection, particularly when designing opportunistic studies in pediatric drug development. Further factors affecting dosing, including existing dosing recommendations, target therapeutic ranges, dose capping, and formulations constraints, are also important to consider when undergoing dose selection for children with obesity. Opportunities to bridge the dosing knowledge gap in children with obesity include modeling and simulating techniques (i.e., population pharmacokinetic and physiologically-based pharmacokinetic [PBPK] modeling), opportunistic clinical data, and real world data. In this review, key considerations related to physiology, drug parameters, patient factors, and methodology that need to be accounted for while studying the influence of obesity on pharmacokinetics in children are highlighted and discussed. Future studies will need to leverage these modeling opportunities to better describe drug exposure in children with obesity as the childhood obesity epidemic continues. [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 and Objective: The use of continuous renal replacement therapy (CRRT) for renal support has increased substantially in critically ill children compared with intermittent modalities owing to its preferential effects on hemodynamic stability. With the expanding role of CRRT, the quantification of extracorporeal clearance and the effect on primary pharmacokinetic parameters is of the utmost importance. Within this review, we aimed to summarize the current state of the literature and compare published pharmacokinetic analyses of commonly used medications in children receiving CRRT to those who are not. Methods: A systematic search of the literature within electronic databases PubMed, EMBASE, Cochrane Library, and Web of Science was conducted. Published studies that were included contained relevant information on the use of commonly administered medications to children, from neonates to adolescents, receiving CRRT. Pharmacokinetic parameters that were analyzed included volume of distribution, total clearance, extracorporeal clearance, area under the curve, and elimination half-life. Information regarding CRRT circuit, flow rates, and membrane components was analyzed to investigate differences in pharmacokinetics between each modality. Results: Forty-five studies met the final inclusion criteria within this systematic review, totaling 833 pediatric patients, with 586 receiving CRRT. Antimicrobials were the most common pharmacological class represented within the literature, representing 81% (35/43) of studies analyzed. Children receiving CRRT largely had similar volume of distribution and total clearance to critically ill children not receiving CRRT, suggesting reno-protective dose adjustments may lead to subtherapeutic dosing regimens in these patients. Overall, there was a tendency for hydrophilic agents, with a low protein binding to undergo elevated total clearance in these children. However, results should be interpreted with caution because of the large variability amongst patient populations and heterogeneity with CRRT modalities, flow rates, and use of extracorporeal membrane oxygenation within studies. This review was able to identify that variation in solute removal, or CRRT modalities, properties (i.e., flow rates), and membrane composition, may have differing effects on the pharmacokinetics of commonly administered medications. Conclusions: The current state of the literature regarding medications administered to children receiving CRRT largely focuses on antimicrobials. Significant gaps remain with other commonly used medications such as sedatives and analgesics. Overall reporting of patient clinical characteristics, CRRT settings, and circuit composition was poor, with only 10% of articles including all relevant information to assess the impact of CRRT on total clearance. Changes in pharmacokinetics because of CRRT often required higher than labeled doses, suggesting renally adjusted or reno-protective doses may lead to subtherapeutic dosing regimens. A thorough understanding of the interplay between patient, drug, and CRRT-circuit factors are required to ensure adequate delivery of dosing regimens to this vulnerable population. [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]

BACKGROUND: Population pharmacokinetics (popPK) has been reliably leveraged to generate individual PK in hemophilia patients. Specific popPK models are suited to predict individual PK under a variety of scenarios that may not be captured by clinical trials, allowing for individualized prophylactic treatment. The Web-Accessible Population Pharmacokinetic Service-Hemophilia (WAPPS-Hemo) project generates individually predicted pharmacokinetic profiles relying on concentrate-specific popPK models used for Bayesian forecasting. OBJECTIVE: Specification of a popPK model for the plasma-derived factor VIII (FVIII) concentrate Koate-DVI and its suitability for pharmacokinetic estimation in low-dose scenarios. METHODS: A popPK model was developed for Koate-DVI WAPPS-Hemo PK data in combination with the existing WAPPS-Hemo Fanhdi/ Alphanate model derivation dataset using nonlinear mixed effects modelling, and was validated via cross-validation and prediction-corrected Visual Predictive Checks (pcVPC). Bootstrap and PK outcomes between the Fanhdi/Alphanate and the Fanhdi/Alphanate/Koate models were compared, and the relative error distributions from a limited sampling analysis (LSA) under the latter model for low and normal doses (10 vs 50 IU/kg) and inclusion/exclusion of pre-dose measurements. RESULTS: A Fanhdi/Alphanate/Koate model was derived (126 patients, ages 1-71 years) after deeming a Koate-brand covariate not clinically significant, resulting in similar parameter estimates than the Fanhdi/Alphanate model with satisfactory goodness of fit, cross-validation and pcVPC results. Low-dose predictions resulted in a higher accuracy and slightly lower precision of half-life (^-phase) and time to 2% trough (TAT2%) estimates than normal dose (median absolute bias for half-life: 0.12 vs 0.5%; median interquartile range, IQR: 11.79% vs 9.95%). Precision improved under pre-dose designs by 2 to 3% and remained similar between 5- and 2-sample designs (IQR reduction<1.8%). CONCLUSIONS: The Fanhdi/Alphanate/Koate model is appropriate for Bayesian forecasting in the WAPPS-Hemo platform, providing a comparable prediction capability for low and normal dosing regimens (10 vs 50 IU/Kg). [ABSTRACT FROM AUTHOR]

Introduction: Emicizumab is dosed as mg/kg and, according to the label, any unused drug left in the vial(s) must be discarded, thereby wasting expensive resources. The aim of this study was to use population pharmacokinetics to illustrate the implications of changing the dosing interval to avoid wastage. Methods: We used a previously published emicizumab PopPK model after extending its validation to children. We simulated PK parameters for labelled dosing regimens and for regimens using full vials with infusion frequency varied to keep the steady‐state drug concentration unchanged. Cost and drug savings were calculated. Results: The model evaluation was successful. When rounding up, the average individual below 53, 47 and 39 has a time‐to‐trough increase of up to 5.7, 7.9 and 5.8 days for the QW, Q2 W and Q4 W regimen, respectively. This resulted in an annual cost reduction of up to $173,136, $75,747 and $61,319 USD per patient. At higher body weights, rounding down the dose to the nearest vial resulted in negligible changes in the steady state concentration and cost savings of up to $93,781, $46,891 and $23,446 USD per patient, respectively. Conclusion: Individuals with a lower body weight may benefit from increasing dose intervals and rounding up dose up to the nearest vial, and individuals with a higher body weight from maintaining the injection frequency and rounding dose down to the nearest vial without significant change in emicizumab levels. Administering the entire vial may result in a reduction of vials used annually and potential cost savings. [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]

Background: The Web‐Accessible Population Pharmacokinetic Service (WAPPS) project generates individually predicted pharmacokinetic (PK) profiles and tailored prophylactic treatment regimens for haemophilic patients, which rely on a set of population PK (PopPK) models providing concentrate‐specific priors for the Bayesian forecasting methodology. Aim: To describe the predictive performance of the WAPPS PopPK models in use on the WAPPS‐Hemo platform. Methods: Data for modelling include dense PK data obtained from industry sponsored and independent PK studies, and dense and sparse data accumulated through WAPPS‐Hemo. WAPPS PopPK models were developed via non‐linear mixed‐effect modelling taking into account the effects of covariates and between‐individual—and sometimes between‐occasion—variability. Model evaluation consisted of (a) prediction‐corrected Visual Predictive Check (pcVPC), (b) Limited Sampling Analysis (LSA) and (c) repeated hold‐out cross‐validation. Results: Thirty‐three WAPPS PopPK models built on data from 3188 patients (ages 1‐78 years) under treatment by factor VIII or IX products (FVIII, FIX) were evaluated. Overall, models exhibit excellent performance characteristics. The pcVPC shows that the observed PK data fall within acceptable 90% interpercentile predictive bands. A slight overprediction beyond the expected half‐life, an anticipated result of using sparse data, occurs for some models. The LSA results in lower than 3% of relative error for FVIII and FIX products and 16% for engineered FIX products. Cross‐Validation analysis yields relative errors lower than 1.5% and 1.4% in estimates of half‐life and time to 0.02 IU/mL, respectively. Conclusion: The WAPPS‐Hemo models consistently showed excellent performance characteristics for the intended use for Bayesian forecasting of individual PK profiles. [ABSTRACT FROM AUTHOR]

An understanding of pediatric pharmacokinetics (PK) is essential for first‐in‐pediatric dose selection and clinical trial design. At present, there is no reliable way to scale the PK of monoclonal antibodies and immunoglobulin G drug products from adults to young children or to premature infants—a vulnerable population with a rapidly growing drug development pipeline. In this work, pediatric physiologically based PK models are constructed in PK‐Sim and Mobi to explore the PK of pagibaximab, palivizumab, MEDI8897, and intravenous immunoglobulin in preterm infants. In addition to considering ontogeny in pediatric organ volumes, organ composition, blood flow rates, and hematocrit, advanced ontogeny is applied for 3 key parameters: capillary surface area, hematopoietic cell concentration, and lymph flow rate. The role and importance of each parameter for determining pediatric clearance (CL) and volume of distribution at steady state (VSS) are quantitatively assessed with a local sensitivity analysis. In addition, the uncertainty around parameters with limited information in pediatrics is addressed (eg, free neonatal Fc receptor concentration). The full ontogeny parameterization yields pediatric PK predictions that are within 1.5‐fold prediction error >90% of the time for preterm infants, with an absolute average fold error of 1.05. This result suggests that many of the key factors related to ontogeny are appropriately addressed. Overall, this study makes a first step toward developing a platform pediatric physiologically based PK model for monoclonal antibodies and immunoglobulin G drug products by solidifying existing parameterizations, integrating new concepts, and drawing attention to unmet needs for physiologic knowledge in children. [ABSTRACT FROM AUTHOR]

Despite the many benefits of breast milk, mothers taking medication are often uncertain about the risks of drug exposure to their infants and decide not to breastfeed. Physiologically based pharmacokinetic models can contribute to drug‐in‐milk safety assessments by predicting the infant exposure and subsequently, risk for toxic effects that would result from continuous breastfeeding. This review aimed to quantify breast milk intake feeding parameters in term and preterm infants using literature data for input into paediatric physiologically based pharmacokinetic models designed for drug‐in‐milk risk assessment. Ovid MEDLINE and Embase were searched up to July 2, 2019. Key study reference lists and grey literature were reviewed. Title, abstract and full text were screened in nonduplicate. Daily weight‐normalized human milk intake (WHMI) and feeding frequency by age were extracted. The review process retrieved 52 studies. A nonlinear regression equation was constructed to describe the WHMI of exclusively breastfed term infants from birth to 1 year of age. In all cases, preterm infants fed with similar feeding parameters to term infants on a weight‐normalized basis. Maximum WHMI was 152.6 ml/kg/day at 19.7 days, and weighted mean feeding frequency was 7.7 feeds/day. Existing methods for approximating breast milk intake were refined by using a comprehensive set of literature data to describe WHMI and feeding frequency. Milk feeding parameters were quantified for preterm infants, a vulnerable population at risk for high drug exposure and toxic effects. A high‐risk period of exposure at 2–4 weeks of age was identified and can inform future drug‐in‐milk risk assessments. [ABSTRACT FROM AUTHOR]

Background: Use of population pharmacokinetics (PopPK) to facilitate PK‐informed prophylaxis in clinical practice has gained momentum among haemophilia providers due to the accessibility of tools such as the Web Accessible Population Pharmacokinetic Service—Hemophilia (WAPPS‐Hemo) and availability of extended half‐life (EHL) factor concentrates. It is unknown how clinicians implement PopPK. Aim: To investigate the evolution of PopPK use in clinical practice by comparing blood sampling strategies, patient features, and factor group between initial and recent periods of WAPPS‐Hemo availability. Methods: PK data for haemophilia A and haemophilia B patients from two time periods were extracted from the WAPPS‐Hemo database: early availability (10/2015‐09/2016) and recent use (10/2017‐09/2018). We compared patient characteristics (age, body weight, haemophilia type), product type and dose, and blood sampling times between the time frames. Results: Over 1900 eligible infusions were submitted to WAPPS‐Hemo during the periods studied, with 85% representing FVIII concentrates. In the recent cohort, PK profiles were requested for younger patients (median age 18 vs 26 years), with increased proportional EHL FVIII use (29% vs 14% of infusions). High‐use centres generally submitted fewer blood samples per infusion than non‐high‐use centres, although the number of samples collected by non‐high‐use centres decreased significantly over time. During both periods, blood sample timing was generally consistent with ISTH recommended windows. Conclusion: The use of WAPPS‐Hemo by haemophilia providers grew by over threefold between the time periods investigated. While sampling times have included key time points proposed first by Björkman since early WAPPS‐Hemo usage, a trend towards minimizing sampling was observed. [ABSTRACT FROM AUTHOR]

The comparative performances of physiologically‐based pharmacokinetic (PBPK) modeling and allometric scaling for predicting the pharmacokinetics (PKs) of large molecules in pediatrics are unknown. Therefore, both methods were evaluated for accuracy in translating knowledge of infliximab PKs from adults to children. PBPK modeling was performed using the base model for large molecules in PK‐Sim version 7.4 with modifications in Mobi. Eight population PK models from literature were reconstructed and scaled by allometry to pediatrics. Evaluation data included seven pediatric studies (~4–18 years). Both methods performed comparably with 66.7% and 68.6% of model‐predicted concentrations falling within twofold of the observed concentrations for PBPK modeling and allometry, respectively. Considerable variability was noted among the allometric models. Therefore, pediatric clinical trial planning would benefit from using approaches that require predictions depending on the specific question i.e., PBPK modeling and allometry. [ABSTRACT FROM AUTHOR]

Physiologically-based pharmacokinetic (PBPK) modeling is a powerful tool used to characterize maturational changes in drug disposition to inform dosing across childhood; however, its use is limited in pediatric drug development. Access to pediatric pharmacokinetic data is a barrier to widespread application of this model, which impedes its development and optimization. To support the development of a pediatric PBPK model, we sought to leverage opportunistically-collected plasma concentrations of the commonly used antibiotic clindamycin. The pediatric PBPK model was optimized following development of an adult PBPK model that adequately described literature data. We evaluated the predictability of the pediatric population PBPK model across four age groups and found that 63-93% of the observed data were captured within the 90% prediction interval of the model. We then used the pediatric PBPK model to optimize intravenous clindamycin dosing for a future prospective validation trial. The optimal dosing proposed by this model was 9 mg/kg/dose in children ≤5 months of age, 12 mg/kg/dose in children >5 months-6 years of age, and 10 mg/kg/dose in children 6-18 years of age, all administered every 8 h. The simulated exposures achieved with the dosing regimen proposed were comparable with adult plasma and tissue exposures for the treatment of community-acquired methicillin-resistant Staphylococcus aureus infections. Our model demonstrated the feasibility of using opportunistic pediatric data to develop pediatric PBPK models, extending the reach of this powerful modeling tool and potentially transforming the pediatric drug development field. [ABSTRACT FROM AUTHOR]

Fluconazole is used to treat hematogenous Candida meningoencephalitis in preterm and term infants. To characterize plasma and central nervous system exposure, an adult fluconazole physiologically‐based pharmacokinetic (PBPK) model was scaled to infants, accounting for age dependencies in glomerular filtration and metabolism. The model was optimized using 760 plasma samples from 166 infants (median postmenstrual age (range) 28 weeks (24–50)) and 27 cerebrospinal fluid (CSF) samples from 22 infants (postmenstrual age 28 weeks (24–33)). Simulations evaluated achievement of the surrogate efficacy target of area under the unbound concentration‐time curve ≥ 400 mg • hour/L over the dosing interval in plasma and CSF using dosing guidelines. Average fold error of predicted concentrations was 0.73 and 1.14 for plasma and CSF, respectively. Target attainment in plasma and CSF was reached faster after incorporating a loading dose of 25 mg/kg. PBPK modeling can be useful in exploring CNS kinetics of drugs in children. [ABSTRACT FROM AUTHOR]

Purpose: This study used uncertainty and sensitivity analysis to evaluate a physiologically based pharmacokinetic (PBPK) model of the complex mechanisms of sorafenib and its two main metabolites, sorafenib glucuronide and sorafenib N-oxide in mice.Methods: A PBPK model for sorafenib and its two main metabolites was developed to explain disposition in mice. It included relevant influx (Oatp) and efflux (Abcc2 and Abcc3) transporters, hepatic metabolic enzymes (CYP3A4 and UGT1A9), and intestinal β-glucuronidase. Parameterization of drug-specific processes was based on in vitro, ex vivo, and in silico data along with plasma and liver pharmacokinetic data from single and multiple transporter knockout mice.Results: Uncertainty analysis demonstrated that the model structure and parameter values could explain the observed variability in the pharmacokinetic data. Global sensitivity analysis demonstrated the global effects of metabolizing enzymes on sorafenib and metabolite disposition and the local effects of transporters on their respective substrate exposures. In addition, through hypothesis testing, the model supported that the influx transporter Oatp is a weak substrate for sorafenib and a strong substrate for sorafenib glucuronide and that the efflux transporter Abcc2 is not the only transporter affected in the Abcc2 knockout mouse.Conclusions: Translation of the mouse model to humans for the purpose of explaining exceptionally high human pharmacokinetic variability and its relationship with exposure-dependent dose-limiting toxicities will require delineation of the importance of these processes on disposition. [ABSTRACT FROM AUTHOR]

Extracorporeal life support (e.g., dialysis, extracorporeal membrane oxygenation (ECMO)) can affect drug disposition, placing patients at risk for therapeutic failure. In this population, dose selection to achieve safe and effective drug exposure is difficult. We developed a novel and flexible approach that uses physiologically based pharmacokinetic (PBPK) modeling to translate results from ECMO ex vivo experiments into bedside dosing recommendations. To determine fluconazole dosing in children on ECMO, we developed a PBPK model, which was validated using fluconazole pharmacokinetic (PK) data in adults and critically ill infants. Next, an ECMO compartment was added to the PBPK model and parameterized using data from a previously published ex vivo study. Simulations using the final ECMO PBPK model reasonably characterized observed PK data in infants on ECMO, and the model was used to derive dosing in children on ECMO across the pediatric age spectrum. This approach can be generalized to other forms of extracorporeal life support (ECLS), such as dialysis. [ABSTRACT FROM AUTHOR]

Background: Differences in plasma protein levels observed between children and adults can alter the extent of xenobiotic binding in plasma, resulting in divergent patterns of exposure.Objective: This study aims to quantify the ontogeny of α1-acid glycoprotein in both healthy and infected subjects.Methods: Data pertaining to α1-acid glycoprotein from healthy subjects were compiled over 26 different publications. For subjects diagnosed or suspected of infection, α1-acid glycoprotein levels were obtained from 214 individuals acquired over three clinical investigations. The analysis evaluated the use of linear, power, exponential, log-linear, and sigmoid E max models to describe the ontogeny of α1-acid glycoprotein. Utility of the derived ontogeny equation for estimation of pediatric fraction unbound was evaluated using average-fold error and absolute average-fold error as measures of bias and precision, respectively. A comparison to fraction unbound estimates derived using a previously proposed linear equation was also instituted.Results: The sigmoid E max model provided the comparatively best depiction of α1-acid glycoprotein ontogeny in both healthy and infected subjects. Despite median α1-acid glycoprotein levels in infected subjects being more than two-fold greater than those observed in healthy subjects, a similar ontogeny pattern was observed when levels were normalized toward adult levels. For estimation of pediatric fraction unbound, the α1-acid glycoprotein ontogeny equation derived from this work (average fold error 0.99; absolute average fold error 1.24) provided a superior predictive performance in comparison to the previous equation (average fold error 0.74; absolute average fold error 1.45).Conclusion: The current investigation depicts a proficient modality for estimation of protein binding in pediatrics and will, therefore, aid in reducing uncertainty associated with pediatric pharmacokinetic predictions. [ABSTRACT FROM AUTHOR]

Solithromycin is a fluoroketolide antibiotic under investigation for community-acquired bacterial pneumonia (CABP). We developed a whole-body physiologically based pharmacokinetic (PBPK) model for solithromycin in adults using PK-Sim and MoBi version 6.2, which incorporated time-dependent CYP3A4 auto-inhibition. The model was developed and evaluated using plasma and epithelial lining fluid (ELF) concentration data from 100 healthy subjects and 22 patients with CABP (1,966 plasma, 30 ELF samples). We performed population simulations and calculated the number of observations falling outside the 90% prediction interval. For the oral regimen (800 mg on day 1 and 400 mg daily on days 2-5) that was evaluated in phase III studies, 11% and 23% of observations from healthy adults fell outside the 90% prediction interval for plasma and ELF, respectively. This regimen should be effective because ≥97% of simulated adults achieved area under the concentration vs. time curve (AUC) to minimum inhibitory concentration ratios associated with a log10 colony forming unit reduction in ELF. [ABSTRACT FROM AUTHOR]

Antibody-drug conjugates (ADCs) are ushering in the next era of targeted therapy against cancer. An ADC for cancer therapy consists of a potent cytotoxic payload that is attached to a tumour-targeted antibody by a chemical linker, usually with an average drug-to-antibody ratio (DAR) of 3.5-4. The theory is to deliver potent cytotoxic payloads directly to tumour cells while sparing healthy cells. However, practical application has proven to be more difficult. At present there are only two ADCs approved for clinical use. Nevertheless, in the last decade there has been an explosion of options for ADC engineering to optimize target selection, Fc receptor interactions, linker, payload and more. Evaluation of these strategies requires an understanding of the mechanistic underpinnings of ADC pharmacokinetics. Development of ADCs for use in cancer further requires an understanding of tumour properties and kinetics within the tumour environment, and how the presence of cancer as a disease will impact distribution and elimination. Key pharmacokinetic considerations for the successful design and clinical application of ADCs in oncology are explored in this review, with a focus on the mechanistic determinants of distribution and elimination. [ABSTRACT FROM AUTHOR]

The total body weight-based dosing strategy currently used in the prophylactic treatment of hemophilia A may not be appropriate for all populations. The assumptions that guide weight-based dosing are not valid in overweight and obese populations, resulting in overdosing and ineffective resource utilization. We explored different weight metrics including lean body weight, ideal body weight, and adjusted body weight to determine an alternative dosing strategy that is both safe and resource-efficient in normal and overweight/obese adult patients. Using a validated population pharmacokinetic model, we simulated a variety of dosing regimens using different doses, weight metrics, and frequencies; we also investigated the implications of assuming various levels of endogenous factor production. Ideal body weight performed the best across all of the regimens explored, maintaining safety while moderating resource consumption for overweight and obese patients. [ABSTRACT FROM AUTHOR]

The article focuses on using physiologically based pharmacokinetic modeling for mechanistic insight. Sorafenib is a multikinase inhibitor that is approved for the treatment of advanced renal cell carcinoma, hepatocellular carcinoma, and advanced thyroid cancer. Sorafenib displays interindividual variability in pharmacokinetics, with hand–foot skin reaction (HFSR) being a significant exposure-related toxicity.

Background and Objective: Human carboxylesterase-1 (CES1) is an enzyme that is primarily expressed in the liver, where it plays an important role in the metabolism of many commonly used medications. Ethanol (alcohol)-mediated inhibition of CES1 and loss-of-function polymorphisms in the CES1 gene can markedly reduce this enzyme's function. Such alterations in CES1 activity may have important effects on the disposition of substrate drugs. The aim of this study is to develop a physiologically based pharmacokinetic (PBPK) model to predict changes in CES1 substrate drug exposure in humans with CES1 activity impaired by ethanol or loss-of-function CES1 genetic polymorphisms. Methods: The antiviral drug oseltamivir, an ethyl ester prodrug that is rapidly converted in vivo to the active metabolite oseltamivir carboxylate (OSC) by CES1 was used as a probe drug for CES1 activity. Oseltamivir PBPK models integrating in vitro and in vivo data were developed and refined. Then the changes in oseltamivir and OSC exposure in humans with CES1 impaired by ethanol or polymorphisms were simulated using a PBPK model incorporating in vitro inhibition and enzyme kinetic data. Model assumptions were verified by comparison of simulations with observed and published data. A sensitivity analysis was performed to gain a mechanistic understanding of the exposure changes of oseltamivir and OSC. Results: The simulated changes in oseltamivir and OSC exposures in humans with CES1 impaired by ethanol or polymorphism were similar to the observed data. The observed exposures to oseltamivir were increased by 46 and 37 % for the area under the plasma concentration-time curve from time zero to 6 h (AUC) and from time zero to 24 h (AUC), respectively, with co-administration of ethanol 0.6 g/kg. In contrast, only a slight change was observed in OSC exposure. The simulated data show the same trend as evidenced by greater change in exposures to oseltamivir (26 and 27 % for AUC and AUC, respectively) than OSC (≤6 %). Conclusions: The PBPK model of impaired CES1 activity correctly predicts observed human data. This model can be extended to predict the effects of drug interactions and other factors affecting the pharmacokinetics of other CES1 substrate drugs. [ABSTRACT FROM AUTHOR]

Physiologically based pharmacokinetic models were developed using MATLAB Simulink® and PK-Sim®. We compared the capability and usefulness of these two models by simulating pharmacokinetic changes of midazolam under exercise and heat stress to verify the usefulness of MATLAB Simulink® as a generic PBPK modeling software. Although both models show good agreement with experimental data obtained under resting condition, their predictions of pharmacokinetics changes are less accurate in the stressful conditions. However, MATLAB Simulink® may be more flexible to include physiologically based processes such as oral absorption and simulate various stress parameters such as stress intensity, duration and timing of drug administration to improve model performance. Further work will be conducted to modify algorithms in our generic model developed using MATLAB Simulink® and to investigate pharmacokinetics under other physiological stress such as trauma. [ABSTRACT FROM AUTHOR]