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Development of a physiologically-based pharmacokinetic model for cyclosporine in Asian children with renal impairment

This study aimed to assess the pharmacokinetics of cyclosporine A (CsA) in Asian children with renal impairment (RI) by developing a physiologically-based pharmacokinetic (PBPK) model with Simcyp Simulator. The PBPK model of Asian children with RI was developed by modifying the physiological paramet...

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Detalles Bibliográficos
Autores principales: Yoon, Sumin, Yi, Sojeong, Rhee, Su-jin, Lee, Hyun A, Kim, Yun, Yu, Kyung-Sang, Chung, Jae-Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Clinical Pharmacology and Therapeutics 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6989237/
https://www.ncbi.nlm.nih.gov/pubmed/32055591
http://dx.doi.org/10.12793/tcp.2019.27.3.107
Descripción
Sumario:This study aimed to assess the pharmacokinetics of cyclosporine A (CsA) in Asian children with renal impairment (RI) by developing a physiologically-based pharmacokinetic (PBPK) model with Simcyp Simulator. The PBPK model of Asian children with RI was developed by modifying the physiological parameters of the built-in population libraries in Simcyp Simulator. The ratio of healthy and RI populations was obtained for each parameter showing a difference between the populations. Each ratio was multiplied by the corresponding parameter in healthy Asian children. The model verification was performed with published data of Korean children with kidney disease given multiple CsA administrations. Simulations were performed with different combinations of ethnicity, age, and renal function to identify the net impact of each factor. The simulated results suggested that the effect of RI was higher in children than adults for both Caucasian and Asian. In conclusion, the constructed model adequately characterized CsA pharmacokinetics in Korean children with RI. Simulations with populations categorized by ethnicity, age, and renal function enabled to assess the net impact of each factor on specific populations.