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

International Journal of Clinical Pharmacology and Therapeutics
Xiangyu LiuYaning Wang

Abstract

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. The plasma concentration and effect level under one dosing regimen were used to train the LSTM model. The developed LSTM model was used to predict the individual PK/PD data under other dosing regimens. The optimized LSTM model captured temporal dependencies and predicted PD profiles accurately for the simulated indirect PK-PD relationship. The results demonstrated that the generic LSTM model can approximate the complex underlying mechanistic biological processes.

Citations

Jul 27, 2021·Clinical Pharmacology and Therapeutics·Teun van Gelder, Alexander A Vinks

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