Industry Perspective on Using MIDD for Pediatric Studies Requiring Integration of Ontogeny

Abstract

Joining the Food and Drug Administration/University of Maryland Center of Excellence in Regulatory Science and Innovation Workshop to discuss and identify solutions to optimize pediatric drug development and, in particular, to address the question as to whether we are ready to incorporate pediatric ontogeny into modeling was the opportunity to share learnings, confront ideas, and present examples of studies performed in industry and academia. This was not only the opportunity to reflect on the experience and the knowledge so far within the current regulatory framework but also to look at the future and explore new and future approaches as well as best practices with the use of modeling and simulation and extrapolation as part of pediatric development.

TheMPRINTHub Data, Model, Knowledge and Research Coordination Center: Bridging the gap in maternal–pediatric therapeutics research through data integration and pharmacometrics

“…However, with the paucity of studies providing information on drug exposure to breastfed infants, patients often err on the side of apparent "safety," while inadvertently withholding a valuable resource from their infant. Although the importance of ontogeny of drug metabolizing enzymes and transporters has become widely recognized, [23][24][25][26][27][28][29][30][31] there is little knowledge on ontogeny of drug receptors or mechanism of inter-individual variability in ontogeny functions.…”

Clinical pharmacology and dosing regimen optimization of neonatal opioid withdrawal syndrome treatments

“…119,124 Compared with PKs in pediatrics, there is in general limited information on how developmental changes and their interaction with disease impact PD, and therefore quantifying drug effect in pediatric patients is considered the biggest obstacle. 125 This is particularly true in the case of NOWS, where significant disease heterogeneity and the lack of reliable disease measures could potentially hinder the predictive performance of PK-PD models. In pediatric trials, it is recommended to use functional biomarkers with sufficient accuracy and precision, and adequate sensitivity to distinguish longitudinal changes in disease progression from drug effect.…”

“…Compared with PKs in pediatrics, there is in general limited information on how developmental changes and their interaction with disease impact PD, and therefore quantifying drug effect in pediatric patients is considered the biggest obstacle 125 . This is particularly true in the case of NOWS, where significant disease heterogeneity and the lack of reliable disease measures could potentially hinder the predictive performance of PK‐PD models.…”

“…This is particularly true in the case of NOWS, where significant disease heterogeneity and the lack of reliable disease measures could potentially hinder the predictive performance of PK‐PD models. In pediatric trials, it is recommended to use functional biomarkers with sufficient accuracy and precision, and adequate sensitivity to distinguish longitudinal changes in disease progression from drug effect 125 . Therefore, in addition to the ongoing effort on comparing the efficacy of different therapeutic agents/treatment modalities, more research focus should also be placed on optimizing withdrawal scoring systems as well as identifying objective measurements of disease severity in NOWS.…”

Physiologically Based Pharmacokinetic Modeling in Pregnant Women Suggests Minor Decrease in Maternal Exposure to Olanzapine

“…Physiologically based pharmacokinetic (PBPK) modeling serves as a critical pharmacometrics tool to make reliable pharmacokinetic predictions in special populations. The number of new drug application submissions to the US Food and Drug Administration (FDA) that included PBPK modeling for pediatric drug development has continued to grow over the past decade ( Corriol-Rohou and Cheung, 2019 ) and the role of PBPK modeling for pregnant women in a regulatory context has been discussed recently ( Coppola et al, 2021 ; Green et al, 2021 ). Since PBPK is a mechanism-based modeling method, the combined effects of multiple gestation-related physiological changes on drug disposition can be incorporated.…”