Development of a Pediatric Physiologically-Based Pharmacokinetic Model of Clindamycin Using Opportunistic Pharmacokinetic Data

Characterization of Pediatric Rectal Absorption, Drug Disposition, and Sedation Level for Midazolam Gel Using Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling

This study aims to explore and characterize the role of pediatric sedation via rectal route. A pediatric physiologically based pharmacokinetic-pharmacodynamic (PBPK/PD) model of midazolam gel was built and validated to support dose selection for pediatric clinical trials. Before developing the rectal PBPK model, an intravenous PBPK model was developed to determine drug disposition, specifically by describing the ontogeny model of the metabolic enzyme. Pediatric rectal absorption was developed based on the rectal PBPK model of adults. The improved Weibull function with permeability, surface area, and fluid volume parameters was used to extrapolate pediatric rectal absorption. A logistic regression model was used to characterize the relationship between the free concentrations of midazolam and the probability of sedation. All models successfully described the PK profiles with absolute average fold error (AAFE) < 2, especially our intravenous PBPK model that extended the predicted age to preterm. The simulation results of the PD model showed that when the free concentrations of midazolam ranged from 3.9 to 18.4 ng/mL, the probability of "Sedation" was greater than that of "Not-sedation" states. Combined with the rectal PBPK model, the recommended sedation doses were in the ranges of 0.44-2.08 mg/kg for children aged 2-3 years, 0.35-1.65 mg/kg for children aged 4-7 years, 0.24-1.27 mg/kg for children aged 8-12 years, and 0.20-1.10 mg/kg for adolescents aged 13-18 years. Overall, this model mechanistically quantified drug disposition and effect of midazolam gel in the pediatric population, accurately predicted the observed clinical data, and simulated the drug exposure for sedation that will inform dose selection for following pediatric clinical trials.

Physiologically Based Pharmacokinetic Modeling in Neonates: Current Status and Future Perspectives

Rational drug use in special populations is a clinical problem that doctors and pharma-cists must consider seriously. Neonates are the most physiologically immature and vulnerable to drug dosing. There is a pronounced difference in the anatomical and physiological profiles be-tween neonates and older people, affecting the absorption, distribution, metabolism, and excretion of drugs in vivo, ultimately leading to changes in drug concentration. Thus, dose adjustments in neonates are necessary to achieve adequate therapeutic concentrations and avoid drug toxicity. Over the past few decades, modeling and simulation techniques, especially physiologically based pharmacokinetic (PBPK) modeling, have been increasingly used in pediatric drug development and clinical therapy. This rigorously designed and verified model can effectively compensate for the deficiencies of clinical trials in neonates, provide a valuable reference for clinical research design, and even replace some clinical trials to predict drug plasma concentrations in newborns. This review introduces previous findings regarding age-dependent physiological changes and pathological factors affecting neonatal pharmacokinetics, along with their research means. The application of PBPK modeling in neonatal pharmacokinetic studies of various medications is also reviewed. Based on this, we propose future perspectives on neonatal PBPK modeling and hope for its broader application.

Physiologically-Based Pharmacokinetic Modeling for Drug Dosing in Pediatric Patients: A Tutorial for a Pragmatic Approach in Clinical Care

It is well-accepted that off-label drug dosing recommendations for pediatric patients should be based on the best available evidence. However, the available traditional evidence is often low. To bridge this gap, physiologically-based pharmacokinetic (PBPK) modeling is a scientifically well-founded tool that can be used to enable model-informed dosing (MID) recommendations in children in clinical practice. In this tutorial, we provide a pragmatic, PBPK-based pediatric modeling workflow. For this approach to be successfully implemented in pediatric clinical practice, a thorough understanding of the model assumptions and limitations is required. More importantly, careful evaluation of an MID approach within the context of overall benefits and the potential risks is crucial. The tutorial is aimed to help modelers, researchers, and clinicians, to effectively use PBPK simulations to support pediatric drug dosing.

Evaluating the Pharmacokinetics of Fentanyl in the Brain Extracellular Fluid, Saliva, Urine, and Plasma of Newborns from Transplacental Exposure from Parturient Mothers Dosed with Epidural Fentanyl Utilizing PBPK Modeling

BACKGROUND AND OBJECTIVE

Fentanyl can mitigate the mother and newborn complications resulting from labor pain. However, fentanyl shows a narrow therapeutic index between its respiratory depressive and analgesic effects. Thus, prenatally acquired high fentanyl levels in the newborn brain extracellular fluid (bECF) may induce respiratory depression which requires therapeutic drug monitoring (TDM). TDM using saliva and urine in newborns can reduce the possibility of infections and distress associated with TDM using blood. The objective of this study was to develop  a physiologically based pharmacokinetic (PBPK) model to predict fentanyl concentrations in different newborn tissues due to intrauterine exposure.

METHODS

A fentanyl PBPK model in adults after intravenous and epidural administration was built, validated, and scaled to pregnancy and newborn populations. The dose that the newborn received transplacentally at birth was calculated using the pregnancy model. Then, the newborn bECF, saliva, plasma, and urine concentrations after such a dose were predicted using the newborn PBPK model.

RESULTS

After a maternal epidural dose of fentanyl 245 µg, the predicted newborn plasma and bECF levels were below the toxicity thresholds. Furthermore, the salivary threshold levels in newborns for fentanyl analgesic and respiratory depression effects were estimated to be 0.39 and 14.7-18.2 ng/ml, respectively.

CONCLUSION

The salivary TDM of fentanyl in newborns can be useful in newborns exposed to intrauterine exposure from parturient females dosed with epidural fentanyl. However, newborn-specific values of µ-opioid receptors IC50 for respiratory depression are needed.

Use of Physiologically Based Pharmacokinetic Modeling for Hepatically Cleared Drugs in Pregnancy: Regulatory Perspective

Physiologically based pharmacokinetic modeling could be used to predict changes in exposure during pregnancy and possibly inform medicine use in pregnancy in situations in which there is currently limited or no available clinical PK data. The Medicines and Healthcare Product Regulatory Agency has been evaluating the available models for a number of medicines cleared by hepatic clearance mechanisms. Models were evaluated for metoprolol, tacrolimus, clindamycin, ondansetron, phenytoin, caffeine, fluoxetine, clozapine, carbamazepine, metronidazole, and paracetamol. The hepatic metabolism through cytochrome P450 (CYP) contributes significantly to the elimination of these drugs, and available knowledge of CYP changes during pregnancy has been implemented in the existing pregnancy physiology models. In general, models were able to capture trends in exposure changes in pregnancy to some extent, but the magnitude of pharmacokinetic change for these hepatically cleared drugs was not captured in each case, nor were models always able to capture overall exposure in the populations. A thorough evaluation was hampered by the lack of clinical data for drugs cleared by a specific clearance pathway. The limited clinical data, as well as complex elimination pathways involving CYPs, uridine 5'-diphospho-glucuronosyltransferase and active transporter for many drugs, currently limit the confidence in the prospective use of the models. Pregnancy-related changes in uridine 5'-diphospho-glucuronosyltransferase and transport functions are emerging, and incorporation of such changes in current physiologically based pharmacokinetic modeling software is in progress. Filling this gap is expected to further enhance predictive performance of models and increase the confidence in predicting PK changes in pregnant women for hepatically cleared drugs.

The Analysis of Pethidine Pharmacokinetics in Newborn Saliva, Plasma, and Brain Extracellular Fluid After Prenatal Intrauterine Exposure from Pregnant Mothers Receiving Intramuscular Dose Using PBPK Modeling

BACKGROUND AND OBJECTIVE

Pethidine (meperidine) can decrease labor pain-associated mother's hyperventilation and high cortisol-induced newborn complications. However, prenatal transplacentally acquired pethidine can cause side effects in newborns. High pethidine concentrations in the newborn brain extracellular fluid (bECF) can cause a serotonin crisis. Therapeutic drug monitoring (TDM) in newborns' blood distresses them and increases infection incidence, which can be overcome by using salivary TDM. Physiologically based pharmacokinetic (PBPK) modeling can predict drug concentrations in newborn plasma, saliva, and bECF after intrauterine pethidine exposure.

METHODS

A healthy adult PBPK model was constructed, verified, and scaled to newborn and pregnant populations after intravenous and intramuscular pethidine administration. The pregnancy PBPK model was used to predict the newborn dose received transplacentally at birth, which was used as input to the newborn PBPK model to predict newborn plasma, saliva, and bECF pethidine concentrations and set correlation equations between them.

RESULTS

Pethidine can be classified as a Salivary Excretion Classification System class II drug. The developed PBPK model predicted that, after maternal pethidine intramuscular doses of 100 mg and 150 mg, the newborn plasma and bECF concentrations were below the toxicity thresholds. Moreover, it was estimated that newborn saliva concentrations of 4.7 µM, 11.4 µM, and 57.7 µM can be used as salivary threshold concentrations for pethidine analgesic effects, side effects, and the risk for serotonin crisis, respectively, in newborns.

CONCLUSION

It was shown that saliva can be used for pethidine TDM in newborns during the first few days after delivery to mothers receiving pethidine.

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

BACKGROUND AND OBJECTIVE

While one in five children in the USA are now obese, and more than three-quarters receive at least one drug during childhood, there is limited dosing guidance for this vulnerable patient population. Physiologically based pharmacokinetic modeling can bridge the gap in the understanding of how pharmacokinetics, including drug distribution and clearance, changes with obesity by incorporating known obesity-related physiological changes in children. The objective of this study was to develop a virtual population of children with obesity to enable physiologically based pharmacokinetic modeling, then use the novel virtual population in conjunction with previously developed models of clindamycin and trimethoprim/sulfamethoxazole to better understand dosing of these drugs in children with obesity.

METHODS

To enable physiologically based pharmacokinetic modeling, a virtual population of children with obesity was developed using national survey, electronic health record, and clinical trial data, as well as data extracted from the literature. The virtual population accounts for key obesity-related changes in physiology relevant to pharmacokinetics, including increased body size, body composition, organ size and blood flow, plasma protein concentrations, and glomerular filtration rate. The virtual population was then used to predict the pharmacokinetics of clindamycin and trimethoprim/sulfamethoxazole in children with obesity using previously developed physiologically based pharmacokinetic models.

RESULTS

Model simulations predicted observed concentrations well, with an overall average fold error of 1.09, 1.24, and 1.53 for clindamycin, trimethoprim, and sulfamethoxazole, respectively. Relative to children without obesity, children with obesity experienced decreased clindamycin and trimethoprim/sulfamethoxazole weight-normalized clearance and volume of distribution, and higher absolute doses under recommended pediatric weight-based dosing regimens.

CONCLUSIONS

Model simulations support current recommended weight-based dosing in children with obesity for clindamycin and trimethoprim/sulfamethoxazole, as they met target exposure despite these changes in clearance and volume of distribution.

Physiologically based pharmacokinetic modelling of acetaminophen in preterm neonates-The impact of metabolising enzyme ontogeny and reduced cardiac output

In preterm neonates, physiologically based pharmacokinetic (PBPK) models are suited for studying the effects of maturational and non-maturational factors on the pharmacokinetics of drugs with complex age-dependent metabolic pathways like acetaminophen (APAP). The aim of this study was to determine the impact of drug metabolising enzymes ontogeny on the pharmacokinetics of APAP in preterm neonates and to study the effect of reduced cardiac output (CO) on its PK using PBPK modelling. A PBPK model for APAP was first developed and validated in adults and then scaled to paediatric age groups to account for the effect of enzyme ontogeny. In preterm neonates, CO was reduced by 10%, 20%, and 30% to determine how this might affect APAP PK in preterm neonates. In all age groups, the predicted concentration-time profiles of APAP were within 5th and 95th percentile of the clinically observed concentration-time profiles and the predicted Cmax and AUC were within 2-folds of the reported parameters in clinical studies. Sulfation accounted for most of APAP metabolism in children, with the highest contribution of 68% in preterm neonates. A reduction in CO by up to 30% did not significantly alter the clearance of APAP in preterm neonates. The model successfully incorporated the ontogeny of drug metabolising enzymes involved in APAP metabolism and adequately predicted the PK of APAP in preterm neonates. A reduction in hepatic perfusion as a result of up to 30% reduction in CO has no effect on the PK of APAP in preterm neonates.

The Role of PK/PD Analysis in the Development and Evaluation of Antimicrobials

Pharmacokinetic/pharmacodynamic (PK/PD) analysis has proved to be very useful to establish rational dosage regimens of antimicrobial agents in human and veterinary medicine. Actually, PK/PD studies are included in the European Medicines Agency (EMA) guidelines for the evaluation of medicinal products. The PK/PD approach implies the use of in vitro, ex vivo, and in vivo models, as well as mathematical models to describe the relationship between the kinetics and the dynamic to determine the optimal dosing regimens of antimicrobials, but also to establish susceptibility breakpoints, and prevention of resistance. The final goal is to optimize therapy in order to maximize efficacy and minimize side effects and emergence of resistance. In this review, we revise the PK/PD principles and the models to investigate the relationship between the PK and the PD of antibiotics. Additionally, we highlight the outstanding role of the PK/PD analysis at different levels, from the development and evaluation of new antibiotics to the optimization of the dosage regimens of currently available drugs, both for human and animal use.

Physiologically-based pharmacokinetic model for alectinib, ruxolitinib, and panobinostat in the presence of cancer, renal impairment, and hepatic impairment

Renal (RIP) and hepatic (HIP) impairments are prevalent conditions in cancer patients. They can cause changes in gastric emptying time, albumin levels, hematocrit, glomerular filtration rate, hepatic functional volume, blood flow rates, and metabolic activity that can modify drug pharmacokinetics. Performing clinical studies in such populations has ethical and practical issues. Using predictive physiologically-based pharmacokinetic (PBPK) models in the evaluation of the PK of alectinib, ruxolitinib, and panobinostat exposures in the presence of cancer, RIP, and HIP can help in using optimal doses with lower toxicity in these populations. Verified PBPK models were customized under scrutiny to account for the pathophysiological changes induced in these diseases. The PBPK model-predicted plasma exposures in patients with different health conditions within average 2-fold error. The PBPK model predicted an area under the curve ratio (AUCR) of 1, and 1.8, for ruxolitinib and panobinostat, respectively, in the presence of severe RIP. On the other hand, the severe HIP was associated with AUCR of 1.4, 2.9, and 1.8 for alectinib, ruxolitinib, and panobinostat, respectively, in agreement with the observed AUCR. Moreover, the PBPK model predicted that alectinib therapeutic cerebrospinal fluid levels are achieved in patients with non-small cell lung cancer, moderate HIP, and severe HIP at 1-, 1.5-, and 1.8-fold that of healthy subjects. The customized PBPK models showed promising ethical alternatives for simulating clinical studies in patients with cancer, RIP, and HIP. More work is needed to quantify other pathophysiological changes induced by simultaneous affliction by cancer and RIP or HIP.

Incorporating Ontogeny in Physiologically Based Pharmacokinetic Modeling to Improve Pediatric Drug Development: What We Know About Developmental Changes in Membrane Transporters

Developmental changes in the biological processes involved in the disposition of drugs, such as membrane transporter expression and activity, may alter the drug exposure and clearance in pediatric patients. Physiologically based pharmacokinetic (PBPK) models take these age-dependent changes into account and may be used to predict drug exposure in children. As a result, this mechanistic-based tool has increasingly been applied to improve pediatric drug development. Under the Prescription Drug User Fee Act VI, the US Food and Drug Administration has committed to facilitate the advancement of PBPK modeling in the drug application review process. Yet, significant knowledge gaps on developmental biology still exist, which must be addressed to increase the confidence of prediction. Recently, more data on ontogeny of transporters have emerged and supplied a missing piece of the puzzle. This article highlights the recent findings on the ontogeny of transporters specifically in the intestine, liver, and kidney. It also provides a case study that illustrates the utility of incorporating this information in predicting drug exposure in children using a PBPK approach. Collaborative work has greatly improved the understanding of the interplay between developmental physiology and drug disposition. Such efforts will continue to be needed to address the remaining knowledge gaps to enhance the application of PBPK modeling in drug development for children.

Physiologically Based Pharmacokinetic Modeling for Trimethoprim and Sulfamethoxazole in Children

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Prediction of lisinopril pediatric dose from the reference adult dose by employing a physiologically based pharmacokinetic model

Background

This study aimed to assess the pediatric lisinopril doses using an adult physiological based pharmacokinetic (PBPK) model. As the empirical rules of dose calculation cannot calculate gender-specific pediatric doses and ignores the age-related physiological differences.

Methods

A PBPK model of lisinopril for the healthy adult population was developed for oral (fed and fasting) and IV administration using PK-Sim MoBI® and was scaled down to a virtual pediatric population for prediction of lisinopril doses in neonates to infants, infants to toddler, children at pre-school age, children at school age and the adolescents. The pharmacokinetic parameters were predicted for the above groups at decremental doses of 20 mg, 10 mg, 5 mg, 2.5 mg, and 1.5 mg in order to accomplish doses producing the pharmacokinetic parameters, similar (or comparable) to that of the adult population. The above simulated pediatric doses were compared to the doses computed using the conventional four methods, such as Young’s rule, Clark’s rule, and weight-based and body surface area-based equations and the dose reported in different studies.

Results

Though the doses predicted for all subpopulations of children were comparable to those calculated by Young’s rule, yet the conventional methods overestimated the pediatric doses when compared to the respective PBPK-predicted doses. The findings of previous real time pharmacokinetic studies in pediatric patients supported the present simulated dose.

Conclusion

Thus, PBPK seems to have predictability potential for pediatric dose since it takes into consideration the physiological changes related to age and gender.

Physiologically Based Population Pharmacokinetic Modeling Approach for Ciprofloxacin in Bone of Patients Undergoing Orthopedic Surgery

Ciprofloxacin is highly active against bacteria that commonly cause bone infections. However, the time-course of ciprofloxacin in bone has not been characterized using population pharmacokinetic modeling. Thirty-nine patients received a 1-h infusion of 400 mg of ciprofloxacin before orthopedic surgery. Blood and bone samples were collected at 0.5 to 20 h following the start of the infusion. Bone samples were separated into cortical and cancellous bone and pulverized under liquid nitrogen using a cryogenic mill. Ciprofloxacin in plasma, and cortical and cancellous bone was quantified by liquid chromatography-tandem mass spectrometry. A physiologically based pharmacokinetic modeling approach was utilized to describe the concentration-time profiles in plasma and bone. Ciprofloxacin concentrations ranged from 0.176 to 5.98 mg/L (median, 1.67; density, 1.99 g/cm³) in cortical, and 0.224 to 14.6 mg/L (median, 1.22; 1.92 g/cm³) in cancellous bone. The average observed cortical bone/plasma concentration ratio was 0.67 at 0.5 to 2 h (n = 7) and 5.1 at 13 to 20 h (n = 9). For cancellous bone the respective average ratios were 0.77 and 4.4. The population PK model included a central (blood) compartment, two peripheral tissue compartments, and compartments for the organic and inorganic (hydroxyapatite) matrix in cortical and cancellous bone. The population mean ciprofloxacin clearance was 20.7 L/h. The estimated partition coefficients of the organic bone matrix were 3.39 for cortical and 5.11 for cancellous bone. Ciprofloxacin achieved higher concentrations in bone than plasma. Slow redistribution from bone to plasma may have been due to binding to the inorganic bone matrix. The developed model presents a step toward optimized antibiotic dosing in osteomyelitis.

Use of normalized prediction distribution errors for assessing population physiologically-based pharmacokinetic model adequacy

Currently employed methods for qualifying population physiologically-based pharmacokinetic (Pop-PBPK) model predictions of continuous outcomes (e.g., concentration-time data) fail to account for within-subject correlations and the presence of residual error. In this study, we propose a new method for evaluating Pop-PBPK model predictions that account for such features. The approach focuses on deriving Pop-PBPK-specific normalized prediction distribution errors (NPDE), a metric that is commonly used for population pharmacokinetic model validation. We describe specific methodological steps for computing NPDE for Pop-PBPK models and define three measures for evaluating model performance: mean of NPDE, goodness-of-fit plots, and the magnitude of residual error. Utility of the proposed evaluation approach was demonstrated using two simulation-based study designs (positive and negative control studies) as well as pharmacokinetic data from a real-world clinical trial. For the positive-control simulation study, where observations and model simulations were generated under the same Pop-PBPK model, the NPDE-based approach denoted a congruency between model predictions and observed data (mean of NPDE =  - 0.01). In contrast, for the negative-control simulation study, where model simulations and observed data were generated under different Pop-PBPK models, the NPDE-based method asserted that model simulations and observed data were incongruent (mean of NPDE =  - 0.29). When employed to evaluate a previously developed clindamycin PBPK model against prospectively collected plasma concentration data from 29 children, the NPDE-based method qualified the model predictions as successful (mean of NPDE = 0). However, when pediatric subpopulations (e.g., infants) were evaluated, the approach revealed potential biases that should be explored.

Utilization of Physiologically Based Pharmacokinetic Modeling in Clinical Pharmacology and Therapeutics: an Overview

The purpose of this review was to assess the advancement of applications for physiologically based pharmacokinetic (PBPK) modeling in various therapeutic areas. We conducted a PubMed search, and 166 articles published between 2012 and 2018 on FDA-approved drug products were selected for further review. Qualifying publications were summarized according to therapeutic area, medication(s) studied, pharmacokinetic model type utilized, simulator program used, and the applications of that modeling. The results showed a 13-fold increase in the number of papers published from 2012 to 2018, with the largest proportion of articles dedicated to the areas of infectious diseases, oncology, and neurology, and application extensions including prediction of drug-drug interactions due to metabolism and/or transporter-mediated effects and understanding drug kinetics in special populations. In addition, we profiled several high-impact studies whose results were used to guide package insert information and formulate dose recommendations. These results show that while utilization of PBPK modeling has drastically increased over the past several years, regulatory support, lack of easy-to-use systems for clinicians, and challenges with model validation remain major challenges for the widespread adoption of this practice in institutional and ambulatory settings. However, PBPK modeling will continue to be a useful tool in the future to assess therapeutic drug monitoring and the growing field of personalized medicine.

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

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

Toward precision medicine in pediatric population using cytochrome P450 phenotyping approaches and physiologically based pharmacokinetic modeling

The activity of drug-metabolizing enzymes (DME) shows high inter- and intra-individual variability. Genetic polymorphisms, exposure to drugs, and environmental toxins are known to significantly alter DME expression. In addition, the activity of these enzymes is highly age-dependent due to maturation processes that occur during development. Currently, there is a vast choice of phenotyping methods in adults using exogenous probes to characterize the activity of these enzymes. However, this can hardly be applied to children since it requires the intake of non-therapeutic xenobiotics. In addition, sampling may be challenging in the pediatric population for a variety of reasons: limited volume (e.g., blood), inappropriate sampling methods for age (e.g., urine), and metric requiring invasive or multiple blood samples. This review covers the main existing methods that can be used in the pediatric population to determine DME activity, with a particular focus on cytochrome P450 enzymes. Less invasive tools are described, including phenotyping using endogenous probes. Finally, the potential of pediatric model-informed precision dosing using physiologically based pharmacokinetic modeling is discussed.

Pitfalls of using numerical predictive checks for population physiologically-based pharmacokinetic model evaluation

Comparisons between observed data and model simulations represent a critical component for establishing confidence in population physiologically-based pharmacokinetic (Pop-PBPK) models. Numerical predictive checks (NPC) that assess the proportion of observed data that correspond to Pop-PBPK model prediction intervals (PIs) are frequently used to qualify such models. We evaluated the effects of three components on the performance of NPC for qualifying Pop-PBPK model concentration-time predictions: (1) correlations (multiple samples per subject), (2) residual error, and (3) discrepancies in the distribution of demographics between observed and virtual subjects. Using a simulation-based study design, we artificially created observed pharmacokinetic (PK) datasets and compared them to model simulations generated under the same Pop-PBPK model. Observed datasets containing uncorrelated and correlated observations (± residual error) were formulated using different random-sampling techniques. In addition, we created observed datasets where the distribution of subject body weights differed from that of the virtual population used to generate model simulations. NPC for each observed dataset were computed based on the Pop-PBPK model's 90% PI. NPC were associated with inflated type-I-error rates (> 0.10) for observed datasets that contained correlated observations, residual error, or both. Additionally, the performance of NPC were sensitive to the demographic distribution of observed subjects. Acceptable use of NPC was only demonstrated for the idealistic case where observed data were uncorrelated, free of residual error, and the demographic distribution of virtual subjects matched that of observed subjects. Considering the restricted applicability of NPC for Pop-PBPK model evaluation, their use in this context should be interpreted with caution.

Mind the Gaps: Ontogeny of Human Brain P-gp and Its Impact on Drug Toxicity

Available data on human brain P-glycoprotein ontogeny during infancy and childhood are limited. This review discusses the current body of data relating to maturation of human brain P-glycoprotein including transporter expression levels in post-mortem human brain samples, in vivo transporter activity using probe substrates, surrogate marker endpoints, and extrapolations from animal models. Overall, the data tend to confirm that human brain P-glycoprotein activity keeps developing after birth, although with a developmental time frame that remains unclear. This knowledge gap is a concern given the critical role of brain P-glycoprotein in drug safety and efficacy, and the vulnerable nature of the pediatric population. Future research could include the measurement of brain P-glycoprotein activity across age groups using positron emission tomography or central pharmacodynamic responses. For now, caution is advised when extrapolating adult data to children aged younger than 2 years for drugs with P-glycoprotein-dependent central nervous system activity.

Mathematical modeling in cancer nanomedicine: a review

Cancer continues to be among the leading healthcare problems worldwide, and efforts continue not just to find better drugs, but also better drug delivery methods. The need for delivering cytotoxic agents selectively to cancerous cells, for improved safety and efficacy, has triggered the application of nanotechnology in medicine. This effort has provided drug delivery systems that can potentially revolutionize cancer treatment. Nanocarriers, due to their capacity for targeted drug delivery, can shift the balance of cytotoxicity from healthy to cancerous cells. The field of cancer nanomedicine has made significant progress, but challenges remain that impede its clinical translation. Several biophysical barriers to the transport of nanocarriers to the tumor exist, and a much deeper understanding of nano-bio interactions is necessary to change the status quo. Mathematical modeling has been instrumental in improving our understanding of the physicochemical and physiological underpinnings of nanomaterial behavior in biological systems. Here, we present a comprehensive review of literature on mathematical modeling works that have been and are being employed towards a better understanding of nano-bio interactions for improved tumor delivery efficacy.

A Retrospective Evaluation of Allometry, Population Pharmacokinetics, and Physiologically-Based Pharmacokinetics for Pediatric Dosing Using Clearance as a Surrogate

Physiologically-based pharmacokinetic models are increasingly applied for pediatric dose selection along with traditional methods such as allometry and population pharmacokinetic models. We report a retrospective evaluation of the three methods. Pediatric population pharmacokinetic models sourced from literature for a subset of eight compounds were used to predict clearances for children < 2 years when they were within the modeled age range (interpolation, N = 11) or including those outside the modeled age range (interpolation and extrapolation, N = 18). Pediatric/adult clearance ratios were evaluated with a strict performance criterion of 0.8-1.25 and with twofold criteria. For children > 2 years, 58-75% of the clinical studies (N = 10) met the strict criteria, and > 80% of the clinical studies were predicted within twofold by all three methods. For children < 2 years, physiologically-based pharmacokinetic, allometry with age-dependent exponents, and pediatric population pharmacokinetic models predict 54%, 82%, and 64% within twofold of the observed, respectively.

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

Almost half of recent pediatric trials failed to achieve labeling indications, in large part because of inadequate study design. Therefore, innovative study methods are crucial to optimizing trial design while also reducing the potential harms inherent with drug investigation. Several methods exist to optimize the amount of pharmacokinetic data collected from the smallest possible volume and with the fewest number of procedures, including the use of opportunistic and sparse sampling, alternative and noninvasive matrices, and microvolume assays. In addition, large research networks using master protocols promote collaboration, reduce regulatory burden, and increase trial efficiency for both early- and late-phase trials. Large pragmatic trials that leverage electronic health records can capitalize on central management strategies to reduce costs, enroll patients with rare diseases on a large scale, and augment study generalizability. Further, trial efficiency and safety can be optimized through Bayesian adaptive techniques that permit planned protocol changes based on analyses of prior and accumulated data. In addition to these trial design features, advances in modeling and simulation have paved the way for systems-based and physiologically based models that individualize pediatric dosing recommendations and support drug approval. Last, given the low prevalence of many pediatric diseases, collecting deidentified genetic and clinical data on a large scale is a potentially transformative way to augment clinical pharmacology research in children.

Clinical pharmacology considerations for children supported with ventricular assist devices

The ventricular assist device is being increasingly used as a "bridge-to-transplant" option in children with heart failure who have failed medical management. Care for this medically complex population must be optimised, including through concomitant pharmacotherapy. Pharmacokinetic/pharmacodynamic alterations affecting pharmacotherapy are increasingly discovered in children supported with extracorporeal membrane oxygenation, another form of mechanical circulatory support. Similarities between extracorporeal membrane oxygenation and ventricular assist devices support the hypothesis that similar alterations may exist in ventricular assist device-supported patients. We conducted a literature review to assess the current data available on pharmacokinetics/pharmacodynamics in children with ventricular assist devices. We found two adult and no paediatric pharmacokinetic/pharmacodynamic studies in ventricular assist device-supported patients. While mechanisms may be partially extrapolated from children supported with extracorporeal membrane oxygenation, dedicated investigation of the paediatric ventricular assist device population is crucial given the inherent differences between the two forms of mechanical circulatory support, and pathophysiology that is unique to these patients. Commonly used drugs such as anticoagulants and antibiotics have narrow therapeutic windows with devastating consequences if under-dosed or over-dosed. Clinical studies are urgently needed to improve outcomes and maximise the potential of ventricular assist devices in this vulnerable population.

Pediatric physiology in relation to the pharmacokinetics of monoclonal antibodies

INTRODUCTION

Dose design for pediatric trials with monoclonal antibodies (mAbs) is often extrapolated from the adult dose according to weight, age, or body surface area. While these methods account for the size differences between adults and children, they do not account for the maturation of processes that may play a key role in the pharmacokinetics and/or pharmacodynamics of mAbs. With the same weight-based dose, infants and young children typically receive lower plasma exposures when compared to adults. Areas covered: The mechanistic features of mAb distribution, elimination, and absorption are explored in detail and literature-based hypotheses are generated to describe their age-dependence. This knowledge can be incorporated into a physiologically based pharmacokinetic (PBPK) modeling approach to pediatric dose determination. Expert opinion: As data from pediatric clinical trials become increasingly available, we have the opportunity to reflect on the physiologic drivers of pharmacokinetics, safety, and efficacy in children with mathematical models. A modeling approach that accounts for the age-related features of mAb disposition can be used to derive first-in-pediatric doses, design optimal sampling schemes for children in clinical trials and even explore new pharmacokinetic end-points as predictors of safety and efficacy in children.