•  "Prediction of the Contribution Ratio of a Target Metabolic Enzyme to Clearance from Chemical Structure Information"     

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•  "Utilizing public and private sector data to build better machine learning models for the prediction of pharmacokinetic parameters"     

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•  "TargetMine 2022: A new vision into drug target analysi"     

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•  "Integrative Network Modeling Highlights the Crucial Roles of Rho-GDI Signaling Pathway in the Progression of Non-Small Cell Lung Cancer"     

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•  "Structure–Activity Relationships of Anti-microRNA Oligonucleotides Containing Cationic Guanidine-Modified Nucleic Acids"     

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•  "Deep Learning Prediction of Adverse Drug Reactions in Drug Discovery Using Open TG–GATEs and FAERS Databases"     

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Poster Title： ”Development of a pharmacokinetics prediction system using multiscale integrated modeling:15. Development of an in silico prediction system of human renal excretion and clearance from chemical structure information”

Author: Reiko Watanabe, Rikiya Ohashi, Tsuyoshi Esaki, Hitoshi Kawashima,
Yayoi Natsume-Kitatani, Chioko Nagao, Kenji Mizuguchi

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