Long short-term memory recurrent neural network for pharmacokinetic-pharmacodynamic modeling.

Journal: International journal of clinical pharmacology and therapeutics
Published Date: Feb 1, 2021

Abstract

OBJECTIVE: Recurrent neural network (RNN) has been demonstrated as a powerful tool for analyzing various types of time series data. There is limited knowledge about the application of the RNN model in the area of pharmacokinetic (PK) and pharmacodynamic (PD) analysis. In this paper, a specific variation of RNN, long short-term memory (LSTM) network, is presented to analyze the simulated PK/PD data of a hypothetical drug.

Authors

  • Xiangyu Liu
    School of Pharmacy, Shenyang Medical College, Shenyang 110034, People's Republic of China.
  • Chao Liu
    Anti-Drug Technology Center of Guangdong Province, National Anti-Drug Laboratory Guangdong Regional Center, Guangzhou 510230, China.
  • Ruihao Huang
    Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, USA.
  • Hao Zhu
    State Key Laboratory of Advanced Technology for Materials Synthesis and Processing, Wuhan University of Technology Wuhan 430070 PR China chang@whut.edu.cn suntl@whut.edu.cn.
  • Qi Liu
    National Institute of Traditional Chinese Medicine Constitution and Preventive Medicine, Beijing University of Chinese Medicine, Beijing, China.
  • Sunanda Mitra
  • Yaning Wang
    Department of Radiology, The First Hospital of Jilin University, No.1, Xinmin Street, Changchun 130021, China (Y.W., M.L., Z.M., J.W., K.H., Q.Y., L.Z., L.M., H.Z.).

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