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PU Chengtao, GU Lingqian, CHEN Xingye, ZHANG Yanmin. Prediction of human intestinal absorption properties based on artificial intelligence[J]. Journal of China Pharmaceutical University, 2023, 54(3): 355-362. DOI: 10.11665/j.issn.1000-5048.2023032102
Citation: PU Chengtao, GU Lingqian, CHEN Xingye, ZHANG Yanmin. Prediction of human intestinal absorption properties based on artificial intelligence[J]. Journal of China Pharmaceutical University, 2023, 54(3): 355-362. DOI: 10.11665/j.issn.1000-5048.2023032102
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Prediction of human intestinal absorption properties based on artificial intelligence

  • Institute of Medical Big Data and Artificial Intelligence, School of Science, China Pharmaceutical University, Nanjing 211198, China

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  • Received Date: March 20, 2023
  • Revised Date: June 12, 2023
    Graphical Abstract
    • Abstract
  • Human intestinal absorption (HIA) is a crucial indicator for measuring the oral bioavailability of drugs.This study aims to use artificial intelligence methods to predict and evaluate the HIA of drugs in the early stages of drug discovery, thus accelerating the drug discovery process and reducing costs.This study used MOE''s 2D, 3D descriptors, and ECFP4 (extended connectivity fingerprints) to characterize the molecules and established eight models, including support vector machine (SVM), random forest (RF), and deep neural network (DNN).The results showed that the SVM model constructed using a combination of 2D, 3D descriptors and ECFP4 fingerprints was the optimal model according to comprehensive evaluation of various evaluation indicators.The area under the receiver operating characteristic curve (AUC), Matthews correlation coefficient, and Kappa coefficient of the optimal model were 0.94, 0.75, and 0.74, respectively.In conclusion, this study established a robust and generalizable machine learning model for predicting HIA properties, which can provide guidance for early molecular screening and the study of pharmacokinetic properties of drugs.
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    • References (21)
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