Model-Informed Drug Development in Pediatric Dose Selection

• Published in: Journal of clinical pharmacology Vol. 61 Suppl 1; p. S60
• Main Authors: Bi, Youwei, Liu, Jiang, Li, Fang, Yu, Jingyu, Bhattaram, Atul, Bewernitz, Michael, Li, Ruo-Jing, Ahn, Jihye, Earp, Justin, Ma, Lian, Zhuang, Luning, Yang, Yuching, Zhang, Xinyuan, Zhu, Hao, Wang, Yaning
• Format: Journal Article
• Language: English
• Published: England 01.06.2021
• Subjects: Child; Cytochrome P-450 Enzyme System - metabolism; Data Interpretation, Statistical; Dose-Response Relationship, Drug; Drug Development; Humans; Models, Biological; Pediatrics - methods; Pharmacokinetics; pediatric ontogeny; pediatric drug development; dose selection and optimization; pediatric dose selection; leveraging knowledge; model-informed drug development
• ISSN: 1552-4604
• DOI: 10.1002/jcph.1848

Model-informed drug development (MIDD) has been a powerful and efficient tool applied widely in pediatric drug development due to its ability to integrate and leverage existing knowledge from different sources to narrow knowledge gaps. The dose selection is the most common MIDD application in regulatory submission related to pediatric drug development. This article aims to give an overview of the 3 broad categories of use of MIDD in pediatric dose selection: leveraging from adults to pediatric patients, leveraging from animals to pediatric patients, and integrating mechanism in infants and neonates. Population pharmacokinetic analyses with allometric scaling can reasonably predict the clearance in pediatric patients aged >5 years. A mechanistic-based approach, such as physiologically based pharmacokinetic accounting for ontogeny, or an allometric model with age-dependent exponent, can be applied to select the dose in pediatric patients aged ≤2 years. The exposure-response relationship from adults or from other drugs in the same class may be useful in aiding the pediatric dose selection and benefit-risk assessment. Increasing application and understanding of use of MIDD have contributed greatly to several policy developments in the pediatric field. With the increasing efforts of MIDD under the Prescription Drug User Fee Act VI, bigger impacts of MIDD approaches in pediatric dose selection can be expected. Due to the complexity of model-based analyses, early engagement between drug developers and regulatory agencies to discuss MIDD issues is highly encouraged, as it is expected to increase the efficiency and reduce the uncertainty.