Development and Evaluation of an In Silico Dermal Absorption Model Relevant for Children

Abstract

The higher skin surface area to body weight ratio in children and the prematurity of skin in neonates may lead to higher chemical exposure as compared to adults. The objectives of this study were: (i) to provide a comprehensive review of the age-dependent anatomical and physiological changes in pediatric skin, and (ii) to construct and evaluate an age-dependent pediatric dermal absorption model. A comprehensive review was conducted to gather data quantifying the differences in the anatomy and physiology of child and adult skin. Maturation functions were developed for model parameters that were found to be age-dependent. A pediatric dermal absorption model was constructed by updating a MoBi implementation of the Dancik et al. 2013 skin permeation model with these maturation functions. Using a workflow for adult-to-child model extrapolation, the predictive performance of the model was evaluated by comparing its predicted rates of flux of diamorphine, phenobarbital and buprenorphine against experimental observations using neonatal skin. For diamorphine and phenobarbital, the model provided reasonable predictions. The ratios of predicted:observed flux in neonates for diamorphine ranged from 0.55 to 1.40. For phenobarbital, the ratios ranged from 0.93 to 1.26. For buprenorphine, the model showed acceptable predictive performance. Overall, the physiologically based pediatric dermal absorption model demonstrated satisfactory prediction accuracy. The prediction of dermal absorption in neonates using a model-based approach will be useful for both drug development and human health risk assessment.

Enhancement of Skin Permeability Prediction through PBPK Modeling, Bayesian Inference, and Experiment Design

“…Stratum corneum thickness: Table 6 in [ 27 ] shows inter-site and within-site variability. The abdominal varies between 6 and 13 µm for a partially hydrated SC.…”

“…For a fully hydrated SC, reference [ 10 ] proposes a stratum corneum thickness of 43 µm. To capture the variability in Table 6 in [ 27 ], we applied a similar uncertainty to the fully hydrated case.…”

Update on the advances and challenges in bioequivalence testing methods for complex topical generic products

“…The method considers many intrinsic (e.g., age, genetics, and organ dysfunction) and extrinsic (e.g., drug–drug interactions) factors in a mechanistic manner. More specifically, dermal PBPK models describe skin permeation at or near the site of action and support alternative BE approaches through virtual screening of healthy individuals and patients in special populations (e.g., pediatric and pregnant populations) at the regulatory level ( Hamadeh et al, 2021 ; Yun et al, 2022 ). The particular advantage of the PBPK models in the context of topical formulations lies in their ability to include inter- and intra-subject variability in skin physiology parameters such as skin thickness, blood flow, and skin pH.…”

Mechanistic modeling of drug products applied to the skin: A workshop summary report

“…4,6,7 The overall goal of these grants, listed in Table 1, has been to develop in silico tools that would allow for a mechanistic description of the skin permeation of active pharmaceutical ingredients (APIs) following administration of dermatological drug products in virtual subjects of healthy and diseased populations. [8][9][10][11][12] These PBPK models incorporate drug product attributes allowing for product-specific predictions of the in vivo performance of that drug product. Importantly, by accounting for product quality attributes and the formulation-skin physiology interactions, the application of these models is not only useful in making informed decisions during the product development program, but also supporting alternative BE approaches on a case-by-case basis.…”

“…Quantitative methodologies, such as physiologically‐based PK (PBPK) modeling, have been one of the main areas of focus for FDA's GDUFA research program since its inception, and the first grant in the dermal area was awarded in 2014 with several to follow 4,6,7 . The overall goal of these grants, listed in Table 1, has been to develop in silico tools that would allow for a mechanistic description of the skin permeation of active pharmaceutical ingredients (APIs) following administration of dermatological drug products in virtual subjects of healthy and diseased populations 8–12 . These PBPK models incorporate drug product attributes allowing for product‐specific predictions of the in vivo performance of that drug product.…”