Exposure prediction and dose optimization of polymyxin B based on bayesian and machine learning

ObjectivesTo explore the application scenarios of maximum a posteriori Bayesian estimation (MAP-BE) and eXtreme Gradient Boosting (XGBoost) in the prediction of polymyxin B (PMB) exposure.MethodsTwo sets of simulations based on the population pharmacokinetic (PopPK) model developed for PMB were used...

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Principais autores:	Qihan Xu, Xuanyi Li, Shuqi Huang, Qin Ding, Yaqian Li, Nan Yang, Chenhui Deng, Bin Tang, Guoping Yang, Qi Pei
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2026-06-01
coleção:	Frontiers in Pharmacology
Assuntos:	limited sampling strategy maximum a posteriori Bayesian estimators polymyxin B population pharmacokinetics model XGBoost
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fphar.2026.1859709/full
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