Physiologically Based Pharmacokinetic Modeling and Simulation in Pediatric Drug Development

Dose selection is one of the key decisions made during drug development in pediatrics. There are regulatory initiatives that promote the use of model-based drug development in pediatrics. Pharmacometrics or quantitative clinical pharmacology enables development of models that can describe factors affecting pharmacokinetics and/or pharmacodynamics in pediatric patients. This manuscript describes some examples in which pharmacometric analysis was used to support approval and labeling in pediatrics. In particular, the role of pharmacokinetic (PK) comparison of pediatric PK to adults and utilization of dose/exposure-response analysis for dose selection are highlighted. Dose selection for esomeprazole in pediatrics was based on PK matching to adults, whereas for adalimumab, exposure-response, PK, efficacy, and safety data together were useful to recommend doses for pediatric Crohn's disease. For vigabatrin, demonstration of similar dose-response between pediatrics and adults allowed for selection of a pediatric dose. Based on model-based pharmacokinetic simulations and safety data from darunavir pediatric clinical studies with a twicedaily regimen, different once-daily dosing regimens for treatmentnaïve human immunodeficiency virus 1-infected pediatric subjects 3 to <12 years of age were evaluated. The role of physiologically based pharmacokinetic modeling (PBPK) in predicting pediatric PK is rapidly evolving. However, regulatory review experiences and an understanding of the state of science indicate that there is a lack of established predictive performance of PBPK in pediatric PK prediction. Moving forward, pharmacometrics will continue to play a key role in pediatric drug development contributing toward decisions pertaining to dose selection, trial designs, and assessing disease similarity to adults to support extrapolation of efficacy.

Section: Discussionmentioning

confidence: 99%

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Mehrotra¹,

Bhattaram²,

Earp³

et al. 2016

“…Utilizing the PBPK model framework, literature-based PK studies depicting concentration-time profiles following administration of theophylline either intravenously (Aslaksen et al, 1981;Horai et al, 1983) or orally (Rovei et al, 1982) as an immediate release formulation (assuming fraction absorbed = 1) were used to obtain specific estimates of hepatic and renal clearance in healthy adults. This method of parameter obtainment has been previously described in the literature (Maharaj and Edginton, 2014). In addition, using a similar modality, tissue:plasma partition coefficients were refined using a single global scalar value to ensure simulated results from the adult PBPK model adequately represented observed PK data.…”

Section: Methodsmentioning

confidence: 99%

Examining Small Intestinal Transit Time as a Function of Age: Is There Evidence to Support Age-Dependent Differences among Children?

Maharaj

Edginton

2016

The small intestine represents the region where the majority of drug and nutrient absorption transpires. Among adults, small intestinal transit kinetics is well delineated; however, the applicability of these values toward children remains unclear. This article serves to examine the relationship between age and mean small intestinal transit time (SITT) based on the available literature. In addition, the influence of alterations in intestinal transit time was explored among children using a model-based approach. Primary literature sources depicting SITT from children to adults were ascertained via the PubMed database. Data were limited to subjects without pathologies that could influence intestinal motility. Random-effect meta-regression models with between-study variability were employed to assess the influence of age on SITT. Three separate models with age as a linear or higher-order (i.e., second-and third-order polynomial) regressor were implemented to assess for the potential of both linear and curvilinear relationships. Examination of the influence of altered intestinal transit kinetics on the absorption of a sustained release theophylline preparation was explored among children between 8 and 14 years using physiologically based pharmacokinetic (PBPK) modeling. Age was not found to be a significant modulator of small intestinal transit within either the linear or higher-order polynomial meta-regression models. PBPK simulations indicated a lack of influence of variations in SITT on the absorption of theophylline from the examined sustained release formulation in older children. Based on the current literature, there is no evidence to suggest that mean SITT differs between children and adults.

“…To the best of our knowledge, this alternate approach for obatoclax has not been verified with clinical data from a pediatric population. By contrast, and in line with a recently proposed pediatric PBPK model development workflow (Maharaj and Edginton, 2014), Thai et al (2015) first developed a model for docetaxel from in vitro ADME and intravenous PK data from more than 500 patients with cancer after either single or multiple dosing, to demonstrate how modeling can be applied to optimize dose and sampling times for a pediatric PK bridging study. Docetaxel is highly protein bound, has a high volume of distribution, and is highly metabolized.…”

Section: Case Studies Of Pbpk Modeling In Pediatric Oncologymentioning

confidence: 99%

“…The evaluation of the predictive performance of published PBPK models is an area that is in need of further scrutiny in moving toward a more standardized and systematic reporting of PBPK modeling and simulation efforts, and this issue has been raised by a number of groups from academia, industry, and regulatory authorities (Maharaj and Edginton, 2014;Zhao, 2014;Sager et al, 2015).…”

Section: Current Challenges and Limitations In Pediatric Pbpk Modelingmentioning

confidence: 99%

“…This technological progress has enhanced the number and breadth of robust applications in the area of clinical pharmacology, including first-in-human studies, special populations, drug interactions, and biopharmaceutics/formulations (Jones et al, 2015;Sager et al, 2015). Considerable experience has now accumulated with the development of PBPK models to describe drug concentration-time profiles in adults (Jones et al, 2009;Kostewicz et al, 2014), and, more recently, in cancer drug development (Block, 2015) and special populations such as pediatrics (Khalil and Läer, 2011;Barrett et al, 2012;Maharaj and Edginton, 2014). There have been multiple applications of PBPK in pediatric drug development, many of which are in support of the first pediatric trial, including starting dose selection, prediction of exposures across the age continuum, optimization of blood sampling strategy, prediction of target organ exposure [safety and pharmacodynamics (PD)], and evaluation of drug interaction potential.…”

Section: Introductionmentioning

confidence: 99%

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Physiologically Based Pharmacokinetic Modeling in Pediatric Oncology Drug Development

Rioux

Waters

2016

Childhood cancer represents more than 100 rare and ultra-rare diseases, with an estimated 12,400 new cases diagnosed each year in the United States. As such, this much smaller patient population has led to pediatric oncology drug development lagging behind that for adult cancers. Developing drugs for pediatric malignancies also brings with it a number of unique trial design considerations, including flexible enrollment approaches, ageappropriate formulation, acceptable sampling schedules, and balancing the need for age-stratified dosing regimens, given the smaller patient populations. The regulatory landscape for pediatric pharmacotherapy has evolved with U.S. Food and Drug Administration (FDA) legislation such as the 2012 FDA Safety and Innovation Act. In parallel, regulatory authorities have recommended the application of physiologically based pharmacokinetic (PBPK) modeling, for example, in the recently issued FDA Strategic Plan for Accelerating the Development of Therapies for Pediatric Rare Diseases. PBPK modeling provides a quantitative and systemsbased framework that allows the effects of intrinsic and extrinsic factors on drug exposure to be modeled in a mechanistic fashion. The application of PBPK modeling in drug development for pediatric cancers is relatively nascent, with several retrospective analyses of cytotoxic therapies, and latterly for targeted agents such as obatoclax and imatinib. More recently, we have employed PBPK modeling in a prospective manner to inform the first pediatric trials of pinometostat and tazemetostat in genetically defined populations (mixed lineage leukemia-rearranged and integrase interactor-1-deficient sarcomas, respectively). In this review, we evaluate the application of PBPK modeling in pediatric cancer drug development and discuss the important challenges that lie ahead in this field.