Application of size and maturation functions to population pharmacokinetic modeling of pediatric patients

Hyun Moon Back, Jong Bong Lee, Nayoung Han, Sungwoo Goo, Eben Jung, Junyeong Kim, Byungjeong Song, Sook Hee An, Jung Tae Kim, Sandy Jeong Rhie, Yoon Sun Ree, Jung Woo Chae, Jaewoo Kim, Hwi Yeol Yun

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14 Scopus citations


Traditionally, dosage for pediatric patients has been optimized using simple weight-scaled methods, but these methods do not always meet the requirements of children. To overcome this discrepancy, population pharmacokinetic (PK) modeling of size and maturation functions has been proposed. The main objective of the present study was to evaluate a new modeling method for pediatric patients using clinical data from three different clinical studies. To develop the PK models, a nonlinear mixed effect modeling method was employed, and to explore PK differences in pediatric patients, size with allometric and maturation with Michaelis–Menten type functions were evaluated. Goodness of fit plots, visual predictive check and bootstrap were used for model evaluation. Single application of size scaling to PK parameters was statistically significant for the over one year old group. On the other hand, simultaneous use of size and maturation functions was statistically significant for infants younger than one year old. In conclusion, population PK modeling for pediatric patients was successfully performed using clinical data. Size and maturation functions were applied according to established criteria, and single use of size function was applicable for over one year ages, while size and maturation functions were more effective for PK analysis of neonates and infants.

Original languageEnglish
Article number259
Issue number6
StatePublished - Jun 2019

Bibliographical note

Funding Information:
Funding: This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT and Future Planning (Grant number 2009-0093815 and 2014R1A1A1006006) and supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health and Welfare, Republic of Korea (Grant number: HI17C0927). This work was also supported by research funds from Chungnam National University.

Publisher Copyright:
© 2019 by the authors. Licensee MDPI, Basel, Switzerland


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