Machine learning approach for dosage individualization of azithromycin in children with community-acquired pneumonia.

Journal: British journal of clinical pharmacology
Published Date: Apr 3, 2025

Abstract

AIMS: The uncertainty about the efficacy and safety of currently used azithromycin dosing regimens in children warrants individualized therapy. The area under the plasma concentration-time curve over 24 h (AUC) of azithromycin correlates best with its effectiveness. The aim of this study was to evaluate the ability of machine learning (ML) to predict the AUC of azithromycin in children with community-acquired pneumonia.

Authors

  • Bo-Hao Tang
    Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education),NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Shu-Meng Fu
    Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Li-Yuan Tian
    Department of Respiratory Care, Children's Hospital of Hebei Province affiliated to Hebei Medical University, Shijiazhuang, China.
  • Xin-Fang Zhang
    Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education), NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Bu-Fan Yao
    Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education),NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Wei Zhang
    The First Affiliated Hospital of Nanchang University, Nanchang, China.
  • Yue-E Wu
    Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education),NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • Yue Zhou
    State Key Laboratory of Bioactive Substances and Functions of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, 2A Nanwei Road, Beijing 100050, China. zhouyue@imm.ac.cn.
  • Ya-Kun Wang
    Department of Respiratory Care, Children's Hospital of Hebei Province affiliated to Hebei Medical University, Shijiazhuang, China.
  • Guo-Xiang Hao
    Department of Clinical Pharmacy, Institute of Clinical Pharmacology, Key Laboratory of Chemical Biology (Ministry of Education),NMPA Key Laboratory for Clinical Research and Evaluation of Innovative Drug, School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan, China.
  • John van den Anker
    Division of Clinical Pharmacology, Children's National Hospital, Washington, DC, USA.
  • Yi Zheng
    Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, 300211 Tianjin, China.
  • Wei Zhao
    Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, Jiangnan University, Wuxi 214122, Jiangsu Province, P. R. China. lxy@jiangnan.edu.cn zhuye@jiangnan.edu.cn.

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