Publications by authors named "Koichi Handa"

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Fraction-based Linear Extrapolation (FLEX) Method for Predicting Human Pharmacokinetic Clearance: Advanced Allometric Scaling Method and Machine Learning Approach.
Yuki Umemori, Koichi Handa, Saki Yoshimura, Michiharu Kageyama

Pharm Res· September 2025

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Computational approaches to DMPK: A realistic assessment of current methods and their practical impact. Part I: Physicochemical and in vitro properties.
Koichi Handa, Mariko Hirano, Michiharu Kageyama, Andreas Bender

Drug Discov Today· August 2025

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Machine Learning Prediction and Validation of Plasma Concentration-Time Profiles.
Hiroaki Iwata, Michiharu Kageyama, Koichi Handa

Mol Pharm· June 2025

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A Practical Method for Predicting Compound Brain Concentration-Time Profiles: Combination of PK Modeling and Machine Learning.
Koichi Handa, Daichi Fujita, Mariko Hirano, Saki Yoshimura, Michiharu Kageyama

Mol Pharm· October 2024

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Prediction of Inhibitory Activity against the MATE1 Transporter via Combined Fingerprint- and Physics-Based Machine Learning Models.
Koichi Handa, Shunta Sasaki, Satoshi Asano, Michiharu Kageyama, Takeshi Iijima

J Chem Inf Model· September 2024

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Development of Novel Methods for QSAR Modeling by Machine Learning Repeatedly: A Case Study on Drug Distribution to Each Tissue.
Koichi Handa, Saki Yoshimura, Michiharu Kageyama, Takeshi Iijima

J Chem Inf Model· May 2024

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Development of a Novel In Silico Classification Model to Assess Reactive Metabolite Formation in the Cysteine Trapping Assay and Investigation of Important Substructures.
Yuki Umemori, Koichi Handa, Saki Yoshimura, Michiharu Kageyama, Takeshi Iijima

Biomolecules· April 2024

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On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data.
Koichi Handa, Morgan C Thomas, Michiharu Kageyama, Takeshi Iijima, Andreas Bender

J Cheminform· November 2023

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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 Descriptors.
Koichi Handa, Seishiro Sakamoto, Michiharu Kageyama, Takeshi Iijima

Eur J Drug Metab Pharmacokinet· July 2023

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Prediction of Compound Plasma Concentration-Time Profiles in Mice Using Random Forest.
Koichi Handa, Peter Wright, Saki Yoshimura, Michiharu Kageyama, Takeshi Iijima

Mol Pharm· June 2023

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Predicting Total Drug Clearance and Volumes of Distribution Using the Machine Learning-Mediated Multimodal Method through the Imputation of Various Nonclinical Data.
Hiroaki Iwata, Tatsuru Matsuo, Hideaki Mamada, Takahisa Motomura, Mayumi Matsushita, Koichi Handa

J Chem Inf Model· September 2022

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Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning.
Hiroaki Iwata, Tatsuru Matsuo, Hideaki Mamada, Takahisa Motomura, Mayumi Matsushita, Koichi Handa

J Pharm Sci· April 2021

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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 analysis.
Koichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, Hiroaki Gouda, Shuichi Hirono

J Pharm Sci· January 2015

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In silico study on the inhibitory interaction of drugs with wild-type CYP2D6.1 and the natural variant CYP2D6.17.
Koichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, Hiroaki Gouda, Shuichi Hirono

Drug Metab Pharmacokinet· October 2014

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Three-dimensional quantitative structure-activity relationship analysis of inhibitors of human and rat cytochrome P4503A enzymes.
Koichi Handa, Izumi Nakagome, Noriyuki Yamaotsu, Hiroaki Gouda, Shuichi Hirono

Drug Metab Pharmacokinet· April 2014

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Calcium ions are involved in the delay of plant cell cycle progression by abiotic stresses.
Toshio Sano, Takumi Higaki, Koichi Handa, Yasuhiro Kadota, Kazuyuki Kuchitsu

FEBS Lett· January 2006

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