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Koichi Handa

Showing results (1-10 of 17) with videos related to

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Molecular Pharmaceutics|May 9, 2025
Machine Learning Prediction and Validation of Plasma Concentration-Time ProfilesHiroaki Iwata, Michiharu Kageyama, Koichi Handa
Journal of Chemical Information and Modeling|April 19, 2024
Development of Novel Methods for QSAR Modeling by Machine Learning Repeatedly: A Case Study on Drug Distribution to Each TissueKoichi Handa, Saki Yoshimura, Michiharu Kageyama, et al.
Pharmaceutical Research|September 10, 2025
Fraction-based Linear Extrapolation (FLEX) Method for Predicting Human Pharmacokinetic Clearance: Advanced Allometric Scaling Method and Machine Learning ApproachYuki Umemori, Koichi Handa, Saki Yoshimura, et al.
Drug Discovery Today|July 2, 2025
Computational approaches to DMPK: A realistic assessment of current methods and their practical impact. Part I: Physicochemical and in vitro propertiesKoichi Handa, Mariko Hirano, Michiharu Kageyama, et al.
European Journal of Drug Metabolism and Pharmacokinetics|June 2, 2023
Development of a 2D-QSAR Model for Tissue-to-Plasma Partition Coefficient Value with High Accuracy Using Machine Learning Method, Minimum Required Experimental Values, and Physicochemical DescriptorsKoichi Handa, Seishiro Sakamoto, Michiharu Kageyama, et al.
Drug Metabolism and Pharmacokinetics|January 30, 2013
Three-dimensional quantitative structure-activity relationship analysis of inhibitors of human and rat cytochrome P4503A enzymesKoichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, et al.
Biomolecules|May 24, 2024
Development of a Novel In Silico Classification Model to Assess Reactive Metabolite Formation in the Cysteine Trapping Assay and Investigation of Important SubstructuresYuki Umemori, Koichi Handa, Saki Yoshimura, et al.
Drug Metabolism and Pharmacokinetics|July 17, 2013
In silico study on the inhibitory interaction of drugs with wild-type CYP2D6.1 and the natural variant CYP2D6.17Koichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, et al.
Journal of Pharmaceutical Sciences|November 11, 2014
Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysisKoichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, et al.
Journal of Cheminformatics|November 22, 2023
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary dataKoichi Handa, Morgan C Thomas, Michiharu Kageyama, et al.
Pageof 2

Showing results (1-10 of 17) with videos related to

Sort By:
Pageof 2
Molecular Pharmaceutics|May 9, 2025
Machine Learning Prediction and Validation of Plasma Concentration-Time ProfilesHiroaki Iwata, Michiharu Kageyama, Koichi Handa
Journal of Chemical Information and Modeling|April 19, 2024
Development of Novel Methods for QSAR Modeling by Machine Learning Repeatedly: A Case Study on Drug Distribution to Each TissueKoichi Handa, Saki Yoshimura, Michiharu Kageyama, et al.
Pharmaceutical Research|September 10, 2025
Fraction-based Linear Extrapolation (FLEX) Method for Predicting Human Pharmacokinetic Clearance: Advanced Allometric Scaling Method and Machine Learning ApproachYuki Umemori, Koichi Handa, Saki Yoshimura, et al.
Drug Discovery Today|July 2, 2025
Computational approaches to DMPK: A realistic assessment of current methods and their practical impact. Part I: Physicochemical and in vitro propertiesKoichi Handa, Mariko Hirano, Michiharu Kageyama, et al.
European Journal of Drug Metabolism and Pharmacokinetics|June 2, 2023
Development of a 2D-QSAR Model for Tissue-to-Plasma Partition Coefficient Value with High Accuracy Using Machine Learning Method, Minimum Required Experimental Values, and Physicochemical DescriptorsKoichi Handa, Seishiro Sakamoto, Michiharu Kageyama, et al.
Drug Metabolism and Pharmacokinetics|January 30, 2013
Three-dimensional quantitative structure-activity relationship analysis of inhibitors of human and rat cytochrome P4503A enzymesKoichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, et al.
Biomolecules|May 24, 2024
Development of a Novel In Silico Classification Model to Assess Reactive Metabolite Formation in the Cysteine Trapping Assay and Investigation of Important SubstructuresYuki Umemori, Koichi Handa, Saki Yoshimura, et al.
Drug Metabolism and Pharmacokinetics|July 17, 2013
In silico study on the inhibitory interaction of drugs with wild-type CYP2D6.1 and the natural variant CYP2D6.17Koichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, et al.
Journal of Pharmaceutical Sciences|November 11, 2014
Three-dimensional quantitative structure-activity relationship analysis for human pregnane X receptor for the prediction of CYP3A4 induction in human hepatocytes: structure-based comparative molecular field analysisKoichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, et al.
Journal of Cheminformatics|November 22, 2023
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary dataKoichi Handa, Morgan C Thomas, Michiharu Kageyama, et al.
Pageof 2