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

Use of population pharmacokinetic-pharmacodynamic modelling to inform antimalarial dose optimization in infants

Infants bear a significant malaria burden but are usually excluded from participating in early dose optimization studies that inform dosing regimens of antimalarial therapy. Unlike older children, infants' exclusion from early-phase trials has resulted in limited evidence to guide accurate dosing of antimalarial treatment for uncomplicated malaria or malaria-preventive treatment in this vulnerable population. Subsequently, doses used in infants are often extrapolated from older children or adults, with the potential for under- or overdosing. Population pharmacokinetic-pharmacodynamic (PK-PD) modelling, a quantitative methodology that applies mathematical and statistical techniques, can aid the design of clinical studies in infants that collect sparse pharmacokinetic data as well as support the analysis of such data to derive optimized antimalarial dosing in this complex and at-risk yet understudied subpopulation. In this review, we reflect on what PK-PD modelling can do in programmatic settings of most malaria-endemic areas and how it can be used to inform antimalarial dose optimization for preventive and curative treatment of uncomplicated malaria in infants. We outline key developmental physiological changes that affect drug exposure in early life, the challenges of conducting dose optimization studies in infants, and examples of how PK-PD modelling has previously informed antimalarial dose optimization in this subgroup. Additionally, we discuss the limitations and gaps of PK-PD modelling when used for dose optimization in infants. To utilize modelling well, there is a need to generate useful, sparse, PK and PD data in this subpopulation to inform antimalarial optimal dosing in infancy.

Ontogeny of Human Liver Aldehyde Oxidase: Developmental Changes and Implications for Drug Metabolism

Despite the increasing importance of aldehyde oxidase (AO) in the drug metabolism of clinical candidates, ontogeny data for AO are limited. The objective of our study was to characterize the age-dependent AO content and activity in the human liver cytosolic fraction (HLC) and human hepatocytes (HH). HLC (n = 121 donors) and HH (n = 50 donors) were analyzed for (1) AO protein content by quantitative proteomics and (2) enzyme activity using carbazeran as a probe substrate. AO activity showed high technical variability and poor correlation with the content in HLC samples, whereas hepatocyte samples showed a strong correlation between the content and activity. Similarly, AO content and activity showed no significant age-dependent differences in HLC samples, whereas the average AO content and activity in hepatocytes increased significantly (∼20-40-fold) from the neonatal levels (0-28 days). Based on the hepatocyte data, the age at which 50% of the adult AO content is reached (age50) was 3.15 years (0.32-13.97 years, 95% CI). Metabolite profiling of carbazeran revealed age-dependent metabolic switching and the role of non-AO mechanisms (glucuronidation and desmethylation) in carbazeran elimination. The content-activity correlation in hepatocytes improved significantly (R2 = 0.95; p < 0.0001) in samples showing <10% contribution of glucuronidation toward the overall metabolism, confirming that AO-mediated oxidation and glucuronidation are the key routes of carbazeran metabolism. Considering the confounding effect of glucuronidation on AO activity, AO content-based ontogeny data are a more direct reflection of developmental changes in protein expression. The comprehensive ontogeny data of AO in HH samples are more reliable than HLC data, which are important for developing robust physiologically based pharmacokinetic models for predicting AO-mediated metabolism in children.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.

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

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

Dose Optimization Informed by PBPK Modeling: State-of-the Art and Future

Model-informed drug development (MIDD) is a powerful quantitative approach that plays an integral role in drug development and regulatory review. While applied throughout the life cycle of the development of new drugs, a key application of MIDD is to inform clinical trial design including dose selection and optimization. To date, physiologically-based pharmacokinetic (PBPK) modeling, an established component of the MIDD toolkit, has mainly been used for assessment of drug-drug interactions (DDIs) and consequential dose adjustments in regulatory submissions. As a result of recent scientific advances and growing confidence in the utility of the approach, PBPK models are being increasingly applied to provide dose recommendations for subjects with differing ages, genetics, and disease states. In this review, we present our perspective on the current landscape of regulatory acceptance of PBPK applications supported by relevant case studies. We also discuss the recent progress and future challenges associated with expanding the utility of PBPK models into emerging areas for regulatory decision making, especially dose optimization in highly vulnerable and understudied populations and facilitating diversity in clinical trials.

Supplementing clinical lactation studies with PBPK modeling to inform drug therapy in lactating mothers: Prediction of primaquine exposure as a case example

Evaluating the safety of primaquine (PQ) during breastfeeding requires an understanding of its pharmacokinetics (PKs) in breast milk and its exposure in the breastfed infant. Physiologically-based PK (PBPK) modeling is primed to assess the complex interplay of factors affecting the exposure of PQ in both the mother and the nursing infant. A published PBPK model for PQ describing the metabolism by monoamine oxidase A (MAO-A; 90% contribution) and cytochrome P450 2D6 (CYP2D6; 10%) in adults was applied to predict the exposure of PQ in mothers and their breastfeeding infants. Plasma exposures following oral daily dosing of 0.5 mg/kg in the nursing mothers in a clinical lactation study were accurately captured, including the observed ranges. Reported infant daily doses based on milk data from the clinical study were used to predict the exposure of PQ in breastfeeding infants greater than or equal to 28 days. On average, the predicted exposures were less than or equal to 0.13% of the mothers. Furthermore, in simulations involving neonates less than 28 days, PQ exposures remain less than 0.16% of the mothers. Assuming that MAO-A increases slowly with age, the predicted relative exposure of PQ remains low in neonates (<0.46%). Thus, the findings of our study support the recommendation made by the authors who reported the results of the clinical lactation study, that is, that when put into context of safety data currently available in children, PQ should not be withheld in lactating women as it is unlikely to cause adverse events in breastfeeding infants greater than or equal to 28 days old.

Development and application of neonatal physiology-based pharmacokinetic models of amikacin and fosfomycin to assess pharmacodynamic target attainment

Antimicrobial resistance increasingly complicates neonatal sepsis in a global context. Fosfomycin and amikacin are two agents being tested in an ongoing multicenter neonatal sepsis trial. Although neonatal pharmacokinetics (PKs) have been described for these drugs, the physiological variability within neonatal populations makes population PKs in this group uncertain. Physiologically-based pharmacokinetic (PBPK) models were developed in Simcyp for fosfomycin and amikacin sequentially for adult, pediatric, and neonatal populations, with visual and quantitative validation compared to observed data at each stage. Simulations were performed using the final validated neonatal models to determine drug exposures for each drug across a demographic range, with probability of target attainment (PTA) assessments. Successfully validated neonatal PBPK models were developed for both fosfomycin and amikacin. PTA analysis demonstrated high probability of target attainment for amikacin 15 mg/kg i.v. q24h and fosfomycin 100 mg/kg (in neonates aged 0-7 days) or 150 mg/kg (in neonates aged 7-28 days) i.v. q12h for Enterobacterales with fosfomycin and amikacin minimum inhibitory concentrations at the adult breakpoints. Repeat analysis in premature populations demonstrated the same result. PTA analysis for a proposed combination fosfomycin-amikacin target was also performed. The simulated regimens, tested in a neonatal sepsis trial, are likely to be adequate for neonates across different postnatal ages and gestational age. This work demonstrates a template for determining target attainment for antimicrobials (alone or in combination) in special populations without sufficient available PK data to otherwise assess with traditional pharmacometric methods.

A Mechanistic Physiologically-Based Pharmacokinetic Platform Model to Guide Adult and Pediatric Intravenous and Subcutaneous Dosing for Bispecific T Cell Engagers

Bispecific T cell engagers (Bi-TCEs) have revolutionized the treatment of oncology indications across both liquid and solid tumors. Bi-TCEs are rapidly evolving from conventional intravenous (i.v.) to more convenient subcutaneous (s.c.) administrations and extending beyond adults to also benefit pediatric patients. Leveraging clinical development experience across three generations of Bi-TCE molecules across both liquid and solid tumor indications from i.v./s.c. dosing in adults and pediatric subjects, we developed a mechanistic-physiologically-based pharmacokinetic (PBPK) platform model for Bi-TCEs. The model utilizes a full PBPK model framework and was successfully validated for PK predictions following i.v. and s.c. dosing across both liquid and solid tumor space in adults for eight Bi-TCEs. After refinement to incorporate physiological ontogeny, the model was successfully validated to predict pediatric PKs in 1 month - < 2 years, 2-11 years, and 12-17 years old subjects following i.v. dosing. Following s.c. dosing in pediatric subjects, the model predicted similar bioavailability, however, a shorter time to maximum concentration (Tmax ) for the three age groups compared with adults. The model was also applied to guide the dosing strategy for first generation of Bi-TCEs for organ impairment, specifically renal impairment, and was able to accurately predict the impact of renal impairment on PK for these relatively small-size Bi-TCEs. This work highlights a novel mechanistic platform model for accurately predicting the PK in adult and pediatric patients across liquid and solid tumor indications from i.v./s.c. dosing and can be used to guide optimal dose and dosing regimen selection and accelerating the clinical development for Bi-TCEs.

Adult and pediatric physiologically-based biopharmaceutics modeling to explain lamotrigine immediate release absorption process

Physiologically-based biopharmaceutics modeling (PBBM) has potential to accelerate the development of new drug and formulations. An important application of PBBM is for special populations such as pediatrics that have pharmacokinetics dependent on the maturation process. Lamotrigine (LTG) is a Biopharmaceutics Classification System (BCS) II drug and is widely prescribed. Therefore, the goal of this study was to assess the biopharmaceutics risk of the low-soluble drug LTG when the ontogeny on gastrointestinal tract (GIT) physiological parameters are considered. An oral physiologically-based pharmacokinetic model and a PBBM were developed and verified using GastroPlus™ software for both adults and children (2-12 years old, 12-52 kg). The biopharmaceutics properties and GIT physiological parameters were evaluated by sensitivity analysis. High doses were simulated assuming a worst case scenario, that is, the dose of 200 mg for adults and 5 mg/kg (up to the maximum of 200 mg) for 2-year-old children. Although several authors have suggested that ontogeny may have an effect on gastrointestinal fluid volume, our study found no evidence of interference between fluid and dose volumes with in vivo dissolution of LTG. The most impactful parameter was found to be the gastric transit time. Therefore, the hypothesis is developed to examine whether LTG exhibits characteristics of a BCS II classification in vitro while showing BCS I-like behavior in vivo. This hypothesis could act as a base for conducting novel studies on model-informed precision dosing, tailored to specific populations and clinical conditions. In addition, it could be instrumental in assessing the influence of various release profiles on in vivo performance for both adult and pediatric populations.

Antiretroviral Drug Exposure and Response in Obese and Morbidly Obese People With Human Immunodeficiency Virus (HIV): A Study Combining Modelling and Swiss HIV Cohort Data

BACKGROUND

Obesity is increasingly prevalent among people with HIV (PWH) and can possibly result in suboptimal antiretroviral drug (ARV) exposure and response. However, this has not been thoroughly evaluated given that obese PWH are underrepresented in clinical trials. We performed virtual trials using physiologically based pharmacokinetic (PBPK) modelling combined with observed clinical data to provide ARV dosing guidance in obese individuals.

METHODS

Each trial included a cohort of virtual adults with a body mass index (BMI) between 18.5 and 60 kg/m2. Therapeutic drug-monitoring data from the Swiss HIV Cohort Study (SHCS) were used to verify the predictive performance of the model. Subsequently, the model was applied to predict the pharmacokinetics of ARVs for different obesity classes. The association between ARV plasma concentrations and virological response was investigated in obese and nonobese individuals.

RESULTS

The PBPK model predicted an average reduction in ARV exposure of ∼20% and trough concentrations of ∼6% in obese (BMI ≥30 kg/m2) compared with nonobese (BMI: 18.5-25 kg/m2) individuals, consistent with observed clinical data. Etravirine and rilpivirine were the most impacted, especially in individuals with BMI >40 kg/m2 whose trough concentrations were below the clinical target threshold. Obese PWH in the SHCS did not have a higher rate of unsuppressed viral load than nonobese PWH.

CONCLUSIONS

The concentrations of ARVs are modestly reduced in obese individuals, with no negative impact on the virological response. Our data provide reassurance that standard doses of ARVs are suitable in obese PWH, including those who gained substantial weight with some of the first-line ARVs.

Interdisciplinary Collaboration on Real World Data to Close the Knowledge Gap: A Reflection on "De Sutter et al. Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling"

This commentary further reflects on the paper of De Sutter et al. on predicting volume of distribution in neonates, and the performance of physiologically based pharmacokinetic models We hereby stressed the add on value to collaborate on real world data to further close this knowledge gap. We illustrated this by weight distribution characteristics in breastfed (physiology) and in asphyxiated (pathophysiology), with additional reflection on their kidney and liver function.

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.

Development and Validation of Physiologically Based Pharmacokinetic Model of Levetiracetam to Predict Exposure and Dose Optimization in Pediatrics

Levetiracetam (Lev) is an antiepileptic drug that has been increasingly used in the epilepsy pediatric population in recent years, but its pharmacokinetic behavior in pediatric population needs to be characterized clearly. Clinical trials for the pediatric drug remain difficult to conduct due to ethical and practical factors. The purpose of this study was to use the physiologically based pharmacokinetic (PBPK) model to predict changes in plasma exposure of Lev in pediatric patients and to provide recommendations for dose adjustment. A PBPK model of Lev in adults was developed using PK-Sim® software and extrapolated to the entire age range of the pediatric population. The model was evaluated using clinical pharmacokinetic data. The results showed the good fit between predictions and observations of the adult and pediatric models. The recommended doses for neonates, infants and children are 0.78, 1.67 and 1.22 times that of adults, respectively. Moreover, at the same dose, plasma exposure in adolescents was similar to that of adults. The PBPK models of Lev for adults and pediatrics were successfully developed and validated to provide a reference for the rational administration of drugs in the pediatric population.

Quantification of drug metabolising enzymes and transporter proteins in the paediatric duodenum via LC-MS/MS proteomics using a QconCAT technique

Characterising the small intestine absorptive membrane is essential to enable prediction of the systemic exposure of oral formulations. In particular, the ontogeny of key intestinal Drug Metabolising Enzymes and Transporter (DMET) proteins involved in drug disposition needs to be elucidated to allow for accurate prediction of the PK profile of drugs in the paediatric cohort. Using pinch biopsies from the paediatric duodenum (n = 36; aged 11 months to 15 years), the abundance of 21 DMET proteins and two enterocyte markers were quantified via LC-MS/MS. An established LCMS nanoflow method was translated to enable analysis on a microflow LC system, and a new stable-isotope-labelled QconCAT standard developed to enable quantification of these proteins. Villin-1 was used to standardise abundancy values. The observed abundancies and ontogeny profiles, agreed with adult LC-MS/MS-based data, and historic paediatric data obtained via western blotting. A linear trend with age was observed for duodenal CYP3A4 and CES2 only. As this work quantified peptides on a pinch biopsy coupled with a microflow method, future studies using a wider population range are very feasible. Furthermore, this DMET ontogeny data can be used to inform paediatric PBPK modelling and to enhance the understanding of oral drug absorption and gut bioavailability in paediatric populations.

Development and Verification of a Japanese Pediatric Physiologically Based Pharmacokinetic Model with Emphasis on Drugs Eliminated by Cytochrome P450 or Renal Excretion

Physiologically based pharmacokinetic (PBPK) models are useful in bridging drug exposure in different ethnic groups, and there is increasing regulatory application of this approach in adults. Reported pediatric PBPK models tend to focus on the North European population, with few examples in other ethnic groups. This study describes the development and verification of a Japanese pediatric PBPK population. The development of the model was based on the existing North European pediatric population. Japanese systems and clinical data were collated from public databases and the literature, and the underlying demographics and equations were optimized so that physiological outputs represented the Japanese pediatric population. The model was tested using 14 different small molecule drugs, eliminated by a variety of pathways, including cytochrome P450 3A4 (CYP3A4) metabolism and renal excretion. Given the limitations of the clinical data, the overall performance of the model was good, with 44/62 predictions for PK parameters (area under the plasma drug concentration-time curve, AUC; maximum serum concentration, Cmax ; clearance, CL) being within 0.8- to 1.25-fold, 56/62 within 0.67- to 1.5-fold, and 61/62 within 0.5- to 2.0-fold of the observed values. Specific results for the 5 CYP3A4 substrates showed 20/31 cases were predicted within 0.8- to 1.25-fold, 27/31 within 0.67- to 1.5-fold, and all were within 0.5- to 2.0-fold of the observed values. Given the increased regulatory use of pediatric PBPK in drug development, expanding these models to other ethnic groups are important. Considering qualifying these models based on the context of use, there is a need to expand on the current research to include a larger range of drugs with different elimination pathways. Collaboration among academic, industry, model providers, and regulators will facilitate further development.

Predicting Volume of Distribution in Neonates: Performance of Physiologically Based Pharmacokinetic Modelling

The volume of distribution at steady state (Vss) in neonates is still often estimated through isometric scaling from adult values, disregarding developmental changes beyond body weight. This study aimed to compare the accuracy of two physiologically based pharmacokinetic (PBPK) Vss prediction methods in neonates (Poulin & Theil with Berezhkovskiy correction (P&T+) and Rodgers & Rowland (R&R)) with isometrical scaling. PBPK models were developed for 24 drugs using in-vitro and in-silico data. Simulations were done in Simcyp (V22) using predefined populations. Clinical data from 86 studies in neonates (including preterms) were used for comparison, and accuracy was assessed using (absolute) average fold errors ((A)AFEs). Isometric scaling resulted in underestimated Vss values in neonates (AFE: 0.61), and both PBPK methods reduced the magnitude of underprediction (AFE: 0.82-0.83). The P&T+ method demonstrated superior overall accuracy compared to isometric scaling (AAFE of 1.68 and 1.77, respectively), while the R&R method exhibited lower overall accuracy (AAFE: 2.03). Drug characteristics (LogP and ionization type) and inclusion of preterm neonates did not significantly impact the magnitude of error associated with isometric scaling or PBPK modeling. These results highlight both the limitations and the applicability of PBPK methods for the prediction of Vss in the absence of clinical data.

A physiologically based pharmacokinetic model of cefepime to predict its pharmacokinetics in healthy, pediatric and disease populations

The physiologically based pharmacokinetic modeling (PBPK) approach can predict drug pharmacokinetics (PK) by combining changes in blood flow and pathophysiological alterations for developing drug-disease models. Cefepime hydrochloride is a parenteral cephalosporin that is used to treat pneumonia, sepsis, and febrile neutropenia, among other things. The current study sought to identify the factors that impact cefepime pharmacokinetics (PK) following dosing in healthy, diseased (CKD and obese), and pediatric populations. For model construction and simulation, the modeling tool PK-SIM was utilized. Estimating cefepime PK following intravenous (IV) application in healthy subjects served as the primary step in the model-building procedure. The prediction of cefepime PK in chronic kidney disease (CKD) and obese populations were performed after the integration of the relevant pathophysiological changes. Visual predictive checks and a comparison of the observed and predicted values of the PK parameters were used to verify the developed model. The results of the PK parameters were consistent with the reported clinical data in healthy subjects. The developed PBPK model successfully predicted cefepime PK as observed from the ratio of the observed and predicted PK parameters as they were within a two-fold error range.

Another Step Toward Qualification of Pediatric Physiologically Based Pharmacokinetic Models to Facilitate Inclusivity and Diversity in Pediatric Clinical Studies

Robust prediction of pharmacokinetics (PKs) in pediatric subjects of diverse ages, ethnicities, and morbidities is critical. Qualification of pediatric physiologically-based pharmacokinetic (P-PBPK) models is an essential step toward enabling precision dosing of these vulnerable groups. Twenty-two manuscripts involving P-PBPK predictions and corresponding observed PK data (e.g., area under the curve and clearance) for 22 small-molecule compounds metabolized by CYP (3A4, 1A2, and 2C9), UGT (1A9 and 2B7), FMO3, renal, non-renal, and complex routes were identified; ratios of mean predicted/observed (P/O) PK parameters were calculated. Seventy-eight of 115 mean predicted PK parameters were within 0.8 to 1.25-fold of observed data, 98 within 0.67 to 1.5-fold, 109 within 2-fold, and only 6 P/O ratios were outside of these bounds. A set of 12 CYP3A4-metabolized compounds and a set of 6 metabolized by other enzymes, CYP1A2 (1 compound), CYP2C9 (2 compounds), UGT1A9 (1 compound) and UGT2B7 (2 compounds) had 56 of 59 and 22 of 25 mean P/O ratios, respectively, that fell within the > 0.5 and < 2.0-fold boundaries. For compounds covering renal, non-renal, complex, and FM03 routes of elimination, 29 of 31 mean P/O ratios fell within the 0.67 to 1.5-fold bounds, including 4 of 5 P/O ratios from newborns. P-PBPK modeling and simulation is a strategic component of the complement of precision dosing methods and has a vital role to play in dose adjustment in vulnerable pediatric populations, such as those with disease or in different ethnic groups. Qualification of such models is an essential step toward acceptance of this methodology by regulators.

PBPK modeling of ivermectin-Considerations for the purpose of developing alternative routes to optimize its safety profile

Although single-dose ivermectin has been widely used in mass-drug administration programs for onchocerciasis and lymphatic filariasis for many years, ivermectin may have utility as an endectocide with mosquito-lethal effects at dosages greater and longer than those used to treat helminths. The final physiologically-based pharmacokinetic (PBPK) model for ivermectin described here was able to capture, with reasonable accuracy, observed plasma drug concentration-time profiles and exposures of ivermectin after a single oral dose of the drug in healthy male (dose range 6-30 mg) and female subjects, in both fasted and fed states, in African patients with onchocerciasis (150 μg/kg) and in African children. The PBPK model can be used for further work on lactation, pediatric dosing (considering CYP3A4 and Pg-p ontogenies), and pregnancy, especially if nonstandard doses will be used. The key findings of our study indicate that absorption of ivermectin may be highly dependent on bile micelle-mediated solubility. The drug is highly lipophilic and permeable, and its plasma exposure appears to be associated with the body mass index of an individual. These are all factors that need to be considered when extrapolating to more complex oral formulations or alternative routes of administration. Administering lower doses over a longer period may attenuate the dependence on bile micelle-mediated solubility. With relevant inputs, the verified PBPK model developed here could be used to simulate plasma exposures following administration of ivermectin by complex generics in development.

The Role of "Physiologically Based Pharmacokinetic Model (PBPK)" New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment

Physiologically Based Pharmacokinetic (PBPK) models are mechanistic tools generally employed in the pharmaceutical industry and environmental health risk assessment. These models are recognized by regulatory authorities for predicting organ concentration-time profiles, pharmacokinetics and daily intake dose of xenobiotics. The extension of PBPK models to capture sensitive populations such as pediatric, geriatric, pregnant females, fetus, etc., and diseased populations such as those with renal impairment, liver cirrhosis, etc., is a must. However, the current modelling practices and existing models are not mature enough to confidently predict the risk in these populations. A multidisciplinary collaboration between clinicians, experimental and modeler scientist is vital to improve the physiology and calculation of biochemical parameters for integrating knowledge and refining existing PBPK models. Specific PBPK covering compartments such as cerebrospinal fluid and the hippocampus are required to gain mechanistic understanding about xenobiotic disposition in these sub-parts. The PBPK model assists in building quantitative adverse outcome pathways (qAOPs) for several endpoints such as developmental neurotoxicity (DNT), hepatotoxicity and cardiotoxicity. Machine learning algorithms can predict physicochemical parameters required to develop in silico models where experimental data are unavailable. Integrating machine learning with PBPK carries the potential to revolutionize the field of drug discovery and development and environmental risk. Overall, this review tried to summarize the recent developments in the in-silico models, building of qAOPs and use of machine learning for improving existing models, along with a regulatory perspective. This review can act as a guide for toxicologists who wish to build their careers in kinetic modeling.

Physiologically Based Pharmacokinetic (PBPK) Model-Informed Dosing Guidelines for Pediatric Clinical Care: A Pragmatic Approach for a Special Population

Physiologically based pharmacokinetic (PBPK) modeling can be an attractive tool to increase the evidence base of pediatric drug dosing recommendations by making optimal use of existing pharmacokinetic (PK) data. A pragmatic approach of combining available compound models with a virtual pediatric physiology model can be a rational solution to predict PK and hence support dosing guidelines for children in real-life clinical care, when it can also be employed by individuals with little experience in PBPK modeling. This comes within reach as user-friendly PBPK modeling platforms exist and, for many drugs and populations, models are ready for use. We have identified a list of drugs that can serve as a starting point for pragmatic PBPK modeling to address current clinical dosing needs.

In-Depth Analysis of Physiologically Based Pharmacokinetic (PBPK) Modeling Utilization in Different Application Fields Using Text Mining Tools

In the past decade, only a small number of papers have elaborated on the application of physiologically based pharmacokinetic (PBPK) modeling across different areas. In this review, an in-depth analysis of the distribution of PBPK modeling in relation to its application in various research topics and model validation was conducted by text mining tools. Orange 3.32.0, an open-source data mining program was used for text mining. PubMed was used for data retrieval, and the collected articles were analyzed by several widgets. A total of 2699 articles related to PBPK modeling met the predefined criteria. The number of publications per year has been rising steadily. Regarding the application areas, the results revealed that 26% of the publications described the use of PBPK modeling in early drug development, risk assessment and toxicity assessment, followed by absorption/formulation modeling (25%), prediction of drug-disease interactions (20%), drug-drug interactions (DDIs) (17%) and pediatric drug development (12%). Furthermore, the analysis showed that only 12% of the publications mentioned model validation, of which 51% referred to literature-based validation and 26% to experimentally validated models. The obtained results present a valuable review of the state-of-the-art regarding PBPK modeling applications in drug discovery and development and related fields.

Development of a pediatric physiologically-based pharmacokinetic model to support recommended dosing of atezolizumab in children with solid tumors

Background: Atezolizumab has been studied in multiple indications for both pediatric and adult patient populations. Generally, clinical studies enrolling pediatric patients may not collect sufficient pharmacokinetic data to characterize the drug exposure and disposition because of operational, ethical, and logistical challenges including burden to children and blood sample volume limitations. Therefore, mechanistic modeling and simulation may serve as a tool to predict and understand the drug exposure in pediatric patients.

Objective: To use mechanistic physiologically-based pharmacokinetic (PBPK) modeling to predict atezolizumab exposure at a dose of 15 mg/kg (max 1,200 mg) in pediatric patients to support dose rationalization and label recommendations.

Methods: A minimal mechanistic PBPK model was used which incorporated age-dependent changes in physiology and biochemistry that are related to atezolizumab disposition such as endogenous IgG concentration and lymph flow. The PBPK model was developed using both in vitro data and clinically observed data in adults and was verified across dose levels obtained from a phase I and multiple phase III studies in both pediatric patients and adults. The verified model was then used to generate PK predictions for pediatric and adult subjects ranging from 2- to 29-year-old.

Results: Individualized verification in children and in adults showed that the simulated concentrations of atezolizumab were comparable (76% within two-fold and 90% within three-fold, respectively) to the observed data with no bias for either over- or under-prediction. Applying the verified model, the predicted exposure metrics including C_min, C_max, and AUC_tau were consistent between pediatric and adult patients with a geometric mean of pediatric exposure metrics between 0.8- to 1.25-fold of the values in adults.

Conclusion: The results show that a 15 mg/kg (max 1,200 mg) atezolizumab dose administered intravenously in pediatric patients provides comparable atezolizumab exposure to a dose of 1,200 mg in adults. This suggests that a dose of 15 mg/kg will provide adequate and effective atezolizumab exposure in pediatric patients from 2- to 18-year-old.

Current and future physiologically based pharmacokinetic (PBPK) modeling approaches to optimize pharmacotherapy in preterm neonates

INTRODUCTION

There is a need for structured approaches to inform on pharmacotherapy in preterm neonates. With their proven track record up to regulatory acceptance, physiologically based pharmacokinetic (PBPK) modeling and simulation provide such a structured approach, and hold the promise to support drug development in preterm neonates.

AREAS COVERED

Compared to the general and pediatric use of PBPK modeling, its use to inform pharmacotherapy in preterms is limited. Using a systematic search (PBPK + preterm), we retained 25 records (20 research papers, 2 letters, 3 abstracts). We subsequently collated the published information on PBPK software packages (PK-Sim®, Simcyp®), and their applications and optimization efforts in preterm neonates. It is encouraging that these applications cover a broad range of scenarios (pharmacokinetic-dynamic analyses, drug-drug interactions, developmental pharmacogenetics, lactation related exposure) and compounds (small molecules, proteins). Furthermore, specific compartments (cerebrospinal fluid, tissue) or (patho)physiologic processes (cardiac output, biliary excretion, first pass metabolism) are considered.

EXPERT OPINION

Knowledge gaps exist, giving rise to various levels of model uncertainty in PBPK applications in preterm neonates. To improve this setting, we need cross talk between clinicians and modelers to generate and integrate knowledge (PK datasets, system knowledge, maturational physiology and pathophysiology) to further refine PBPK models.

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

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