Liang Zheng1, Miao Xu1, Shi-Wei Tang2, Hao-Xin Song3, Xue-Hua Jiang1, Ling Wang4. 1. Department of Clinical Pharmacy and Pharmacy Administration, West China School of Pharmacy, Sichuan University, Chengdu, China. 2. Department of Pharmacy, People's Hospital of Dujiangyan City, Dujiangyan, China. 3. Department of Pharmacy, West China Second Hospital of Sichuan University, Chengdu, China. 4. Department of Clinical Pharmacy and Pharmacy Administration, West China School of Pharmacy, Sichuan University, Chengdu, China. rebeccawang312@gmail.com.
Abstract
PURPOSE: Physiologically-based pharmacokinetic (PBPK) modeling offers a unique modality to predict age-specific pharmacokinetics. The objective of this study was to assess the ability of PBPK model to predict plasma exposure of oxycodone, a widely used opioid for pain management, in adults and children. METHODS: A full PBPK model of oxycodone following intravenous and oral administration was developed using a 'bottom-up' and 'top-down' combined strategy. The model was then extrapolated to pediatrics through a reasonable scaling method. The adult and pediatric model was evaluated using data from 17 clinical PK studies by testing predicted/observed goodness of fit. The mean fold error for PK parameters was calculated. Finally, we used the validated PBPK model to visualize adult-children dose conversion for oxycodone. RESULTS: The developed PBPK model successfully predicted the oxycodone disposition in adults, wherein the predicted versus observed AUC, Cmax, and tmax were within 0.90 to 1.20-fold difference. After scaling anatomy/physiology, protein binding, and clearance, the model showed satisfactory prediction performance for pediatric populations as predicted AUC were within the 1.50-fold range of the observed values. According to the application of PBPK model, we found that different intravenous doses should be given in children of different ages compared to a standard 0.1 mg/kg in adults, while a progressive increasing dose with age growth following oral administration is recommended for children. CONCLUSIONS: The current example provides the opportunity for using the PBPK model to guide dose adjustment of oxycodone in the design of future pediatric clinical studies.
PURPOSE: Physiologically-based pharmacokinetic (PBPK) modeling offers a unique modality to predict age-specific pharmacokinetics. The objective of this study was to assess the ability of PBPK model to predict plasma exposure of oxycodone, a widely used opioid for pain management, in adults and children. METHODS: A full PBPK model of oxycodone following intravenous and oral administration was developed using a 'bottom-up' and 'top-down' combined strategy. The model was then extrapolated to pediatrics through a reasonable scaling method. The adult and pediatric model was evaluated using data from 17 clinical PK studies by testing predicted/observed goodness of fit. The mean fold error for PK parameters was calculated. Finally, we used the validated PBPK model to visualize adult-children dose conversion for oxycodone. RESULTS: The developed PBPK model successfully predicted the oxycodone disposition in adults, wherein the predicted versus observed AUC, Cmax, and tmax were within 0.90 to 1.20-fold difference. After scaling anatomy/physiology, protein binding, and clearance, the model showed satisfactory prediction performance for pediatric populations as predicted AUC were within the 1.50-fold range of the observed values. According to the application of PBPK model, we found that different intravenous doses should be given in children of different ages compared to a standard 0.1 mg/kg in adults, while a progressive increasing dose with age growth following oral administration is recommended for children. CONCLUSIONS: The current example provides the opportunity for using the PBPK model to guide dose adjustment of oxycodone in the design of future pediatric clinical studies.
Authors: Nora M Hagelberg; Tuija H Nieminen; Teijo I Saari; Mikko Neuvonen; Pertti J Neuvonen; Kari Laine; Klaus T Olkkola Journal: Eur J Clin Pharmacol Date: 2008-10-03 Impact factor: 2.953
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