Bo-Hao Tang, Jin-Yuan Zhang, Karel Allegaert, Guo-Xiang Hao, Bu-Fan Yao, Stephanie Leroux, Alison H Thomson, Ze Yu, Fei Gao, Yi Zheng, Yue Zhou, Edmund V Capparelli, Valerie Biran, Nicolas Simon, Bernd Meibohm, Yoke-Lin Lo, Remedios Marques, Jose-Esteban Peris, Irja Lutsar, Jumpei Saito, Evelyne Jacqz-Aigrain, John van den Anker, Yue-E Wu, Wei Zhao
BACKGROUND AND OBJECTIVE: High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0 ) and steady-state area-under-curve (AUC0-24 ) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions. METHODS: C0 were retrieved from a large neonatal vancomycin dataset...
June 10, 2023: Clinical Pharmacokinetics