Regulatory Experience With Physiologically Based Pharmacokinetic Modeling for Pediatric Drug Trials

Leong, Ruby; Vieira, Marcel; Zhao, Ping; Mulugeta, Yeruk; Lee, C S; Huang, Suli; Burckart, Gilbert J.

doi:10.1038/clpt.2012.19

Cited by 168 publications

(152 citation statements)

References 25 publications

(27 reference statements)

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“…Several groups reviewed the use of PBPK in pediatric drug development and research, with various versions of workflow being proposed to predict drug PK in pediatrics using PBPK (Barrett et al, 2012;Leong et al, 2012;Jiang et al, 2013;Maharaj and Edginton, 2014;Willmann et al, 2014). All proposals articulate the importance of establishing/ verifying an adult PBPK model, followed by utilizing the most up-todate pediatric physiology models to prospectively predict drug PK in subjects of different pediatric age groups.…”

Section: Discussionmentioning

confidence: 99%

“…The experience with the use of model-based analyses to support regulatory decisions has been previously described (Bhattaram et al, 2005(Bhattaram et al, , 2007Wang et al, 2008;Jadhav et al, 2009;Leong et al, 2012). The objective of this manuscript is to provide detailed examples further highlighting the role of modeling and simulation in the development and approval of drugs and biologic products in pediatric patients.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Mehrotra¹,

Bhattaram²,

Earp³

et al. 2016

Drug Metabolism and Disposition

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Mehrotra¹,

Bhattaram²,

Earp³

et al. 2016

Drug Metabolism and Disposition

View full text Add to dashboard Cite

show abstract

“…Recently, several FDA pediatric submissions have incorporated physiologically based pharmacokinetic (PBPK) models, stimulating an interest in their utility among regulatory authorities (1). In a March 2012 meeting, the majority of the FDA's Pharmaceutical Science and Clinical Pharmacology Advisory Committee voted to support the use of PBPK modeling for pediatric drug development; a decision with potential implications toward the manner in which pediatric drug information is derived.…”

Section: Introductionmentioning

confidence: 99%

“…Amongst the literature, pediatric PBPK models have been utilized in several different capacities: suggesting starting doses for children of different age groups, predictions of environmental contaminant exposure, optimization of clinical drug trial design (sampling schedule, number of patients, etc. ), and assessment of potential drug-drug interactions (1,(4)(5)(6).…”

Section: Introductionmentioning

confidence: 99%

A Workflow Example of PBPK Modeling to Support Pediatric Research and Development: Case Study with Lorazepam

Maharaj

Barrett

Edginton

2013

AAPS J

102

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Abstract. The use of physiologically based pharmacokinetic (PBPK) models in the field of pediatric drug development has garnered much interest of late due to a recent Food and Drug Administration recommendation. The purpose of this study is to illustrate the developmental processes involved in creation of a pediatric PBPK model incorporating existing adult drug data. Lorazepam, a benzodiazepine utilized in both adults and children, was used as an example. A population-PBPK model was developed in PK-Sim v4.2® and scaled to account for age-related changes in size and composition of tissue compartments, protein binding, and growth/maturation of elimination processes. Dose (milligrams per kilogram) requirements for children aged 0-18 years were calculated based on simulations that achieved targeted exposures based on adult references. Predictive accuracy of the PBPK model for producing comparable plasma concentrations among 63 pediatric subjects was assessed using average-fold error (AFE). Estimates of clearance (CL) and volume of distribution (V ss ) were compared with observed values for a subset of 15 children using fold error (FE). Pediatric dose requirements in young children (1-3 years) exceeded adult levels on a linear weight-adjusted (milligrams per kilogram) basis. AFE values for model-derived concentration estimates were within 1.5-and 2-fold deviation from observed values for 73% and 92% of patients, respectively. For CL, 60% and 80% of predictions were within 1.5 and 2 FE, respectively. Comparatively, predictions of V ss were more accurate with 80% and 100% of estimates within 1.5 and 2 FE, respectively. Using the presented workflow, the developed pediatric model estimated lorazepam pharmacokinetics in children as a function of age.

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“…Therefore, tramadol serves as a model drug in our PBPK study to evaluate whether maturation of the clearance is adequately predicted over the pediatric lifespan. In order to make mechanistically sound pediatric tramadol exposure predictions, different elimination pathways in the tramadol clearance should first be validated in an adult PBPK model previous to predicting pediatric exposure (11). In the application of this methodology, these limitations/assumptions should be considered: (i) clearance pathways in children are the same as those observed in adults, (ii) enzyme kinetics of metabolic contributors are first order, (iii) clearance models are perfusion limited (well-stirred), and (iv) no transporters are involved for which ontogeny information is unknown.…”

Section: Introductionmentioning

confidence: 99%

Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

T’jollyn

Snoeys

Vermeulen

et al. 2015

AAPS J

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Abstract. This paper focuses on the retrospective evaluation of physiologically based pharmacokinetic (PBPK) techniques used to mechanistically predict clearance throughout pediatric life. An intravenous tramadol retrograde PBPK model was set up in Simcyp® using adult clearance values, qualified for CYP2D6, CYP3A4, CYP2B6, and renal contributions. Subsequently, the model was evaluated for mechanistic prediction of total, CYP2D6-related, and renal clearance predictions in very early life. In two in vitro pediatric human liver microsomal (HLM) batches (1 and 3 months), O-desmethyltramadol and N-desmethyltramadol formation rates were compared with CYP2D6 and CYP3A4 activity, respectively. O-desmethyltramadol formation was mediated only by CYP2D6, while N-desmethyltramadol was mediated in part by CYP3A4. Additionally, the clearance maturation of the PBPK model predictions was compared to two in vivo maturation models (Hill and exponential) based on plasma concentration data, and to clearance estimations from a WinNonlin® fit of plasma concentration and urinary excretion data. Maturation of renal and CYP2D6 clearance is captured well in the PBPK model predictions, but total tramadol clearance is underpredicted. The most pronounced underprediction of total and CYP2D6-mediated clearance was observed in the age range of 2-13 years. In conclusion, the PBPK technique showed to be a powerful mechanistic tool capable of predicting maturation of CYP2D6 and renal tramadol clearance in early infancy, although some underprediction occurs between 2 and 13 years for total and CYP2D6-mediated tramadol clearance.

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Regulatory Experience With Physiologically Based Pharmacokinetic Modeling for Pediatric Drug Trials

Cited by 168 publications

References 25 publications

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

A Workflow Example of PBPK Modeling to Support Pediatric Research and Development: Case Study with Lorazepam

Physiologically Based Pharmacokinetic Predictions of Tramadol Exposure Throughout Pediatric Life: an Analysis of the Different Clearance Contributors with Emphasis on CYP2D6 Maturation

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