Literature DB >> 34185906

Model-Informed Drug Development in Pediatric Dose Selection.

Youwei Bi1, Jiang Liu1, Fang Li1, Jingyu Yu1, Atul Bhattaram1, Michael Bewernitz1, Ruo-Jing Li1, Jihye Ahn1, Justin Earp1, Lian Ma1, Luning Zhuang1, Yuching Yang1, Xinyuan Zhang1, Hao Zhu1, Yaning Wang1.   

Abstract

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. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

Entities:  

Keywords:  dose selection and optimization; leveraging knowledge; model-informed drug development; pediatric dose selection; pediatric drug development; pediatric ontogeny

Mesh:

Substances:

Year:  2021        PMID: 34185906     DOI: 10.1002/jcph.1848

Source DB:  PubMed          Journal:  J Clin Pharmacol        ISSN: 0091-2700            Impact factor:   3.126


  2 in total

1.  Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations.

Authors:  Trevor N Johnson; Ben G Small; Karen Rowland Yeo
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2022-02-17

Review 2.  Model-Informed Drug Development Approaches to Assist New Drug Development in the COVID-19 Pandemic.

Authors:  Ye Xiong; Jianghong Fan; Eliford Kitabi; Xinyuan Zhang; Youwei Bi; Manuela Grimstein; Yuching Yang; Justin C Earp; Nan Zheng; Jiang Liu; Yaning Wang; Hao Zhu
Journal:  Clin Pharmacol Ther       Date:  2021-12-04       Impact factor: 6.903

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.