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Ye J, Bi Y, Ting N. How to select the initial dose for a pediatric study? J Biopharm Stat 2023; 33:844-858. [PMID: 36476267 DOI: 10.1080/10543406.2022.2149770] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 11/16/2022] [Indexed: 12/13/2022]
Abstract
In typical clinical development programs, a new drug is first developed for the adult use. Drugs are often approved for adult use or in the process of obtaining approval in adults in the target indication before pediatric development is initiated. In designing the first pediatric clinical trial, one of the challenges is to select the initial dose to be tested. The ICH E11 R1 guidance advises that chronologic age alone may not always be the most appropriate categorical determinant to define developmental subgroups in pediatric studies. In this manuscript, the approaches to utilize available data in adults related to those factors beyond age to inform the starting dose selection in pediatric drug development are discussed. Practical considerations and approaches are provided for informing pediatric starting dose. Additional considerations to use pre-clinical information are provided in the case when adult information is limited or not available.
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Affiliation(s)
- Jingjing Ye
- Global Statistics and Data Science (GSDS), Fulton, MD, USA
| | - Youwei Bi
- Division of Pharmacometrics, Office of Translational Sciences (OTS), Center for Drug Evaluation and Research (CDER), US Food and Drug Administration (FDA), Silver Spring, MD, USA
| | - Naitee Ting
- Biostatistics and Data Science, Boehringer Ingelheim Pharmaceuticals, Inc, Ridgefield, CT, USA
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Wang K, Jiang K, Wei X, Li Y, Wang T, Song Y. Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development. AAPS PharmSciTech 2021; 22:208. [PMID: 34312742 PMCID: PMC8312709 DOI: 10.1208/s12249-021-02076-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 06/16/2021] [Indexed: 12/30/2022] Open
Abstract
Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.
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Bi Y, Liu J, Li F, Yu J, Bhattaram A, Bewernitz M, Li RJ, Ahn J, Earp J, Ma L, Zhuang L, Yang Y, Zhang X, Zhu H, Wang Y. Model-Informed Drug Development in Pediatric Dose Selection. J Clin Pharmacol 2021; 61 Suppl 1:S60-S69. [PMID: 34185906 DOI: 10.1002/jcph.1848] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 02/18/2021] [Indexed: 01/12/2023]
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.
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Affiliation(s)
- Youwei Bi
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Jiang Liu
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Fang Li
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Jingyu Yu
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Atul Bhattaram
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Michael Bewernitz
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Ruo-Jing Li
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Jihye Ahn
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Justin Earp
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Lian Ma
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Luning Zhuang
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Yuching Yang
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Xinyuan Zhang
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Hao Zhu
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
| | - Yaning Wang
- Office of Clinical Pharmacology, Food and Drug Administration, Silver Spring, Maryland, USA
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