Drug clearance in neonates: A combination of population pharmacokinetic modelling and machine learning approaches to improve individual prediction

• Main Authors: Tang, Bo-Hao, Guan, Zheng, Allegaert, Karel, Wu, Yue-E., Manolis, Efthymios, Leroux, Stephanie, Yao, Bu-Fan, Shi, Hai-Yan, Li, Xiao, Huang, Xin, Wang, Wen-Qi, Shen, A. -Dong, Wang, Xiao-Ling, Wang, Tian-You, Kou, Chen, Xu, Hai-Yan, Zhou, Yue, Zheng, Yi, Hao, Guo-Xiang, Xu, Bao-Ping, Thomson, Alison H., Capparelli, Edmund V., Biran, Valerie, Simon, Nicolas, Meibohm, Bernd, Lo, Yoke-Lin, Marques, Remedios, Peris, Jose-Esteban, Lutsar, Irja, Saito, Jumpei, Burggraaf, Jacobus, Jacqz-Aigrain, Evelyne, van den Anker, John, Zhao, Wei
• Format: Article
• Published: Adis 2021
• Subjects: R Medicine (General)
• Online Access: http://eprints.um.edu.my/34712/

Background Population pharmacokinetic evaluations have been widely used in neonatal pharmacokinetic studies, while machine learning has become a popular approach to solving complex problems in the current era of big data. Objective The aim of this proof-of-concept study was to evaluate whether combi...