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AI-Driven Prediction of Bitterness and Sweetness and Analysis of Receptor Interactions , Hiroaki Iwata , Current Research in Food Science , vol.10 (101090) , 2025.05 , There is Review , The Simple Work , English
Machine Learning Prediction and Validation of Plasma Concentration Time Profiles , Hiroaki Iwata, Michiharu Kageyama, Koichi Handa , Molecular Pharmaceutics , vol.22 (6) (p.2976 - 2984) , 2025.05 , There is Review , The Multiple Authorship , English
Precision Spatiotemporal Analysis of Large-scale Compound–Protein Interactions through Molecular Dynamics Simulation , Shigeyuki Matsumoto, Yuta Isaka, Ryo Kanada, Biao Ma, Mitsugu Araki, Shuntaro Chiba, Atsushi Tokuhisa, Hiroaki Iwata, Shoichi Ishida, Yoshinobu Akinaga, Kei Terayama, Ryosuke Kojima, Yohei Harada, Kazuhiro Takemura, Teruki Honma, Akio Kitao, Yasushi Okuno , PNAS Nexus , vol.4 (3) , 2025.02 , There is Review , The Multiple Authorship , English
kMoL: an open-source machine and federated learning library for drug discovery , Romeo Cozac, Haris Hasic, Jun Jin Choong, Vincent Richard, Loic Beheshti, Cyrille Froehlich, Shigeyuki Matsumoto, Ryosuke Kojima, Hiroaki Iwata, Aki Hasegawa, Takao Otsuka, Takuto Koyama, Yasushi Okuno , Journal of Cheminformatics , vol.17 (1) , 2025.02 , There is Review , The Multiple Authorship , English
Transforming Drug Discovery: The Impact of AI and Molecular Simulation on R&D Efficiency , Hiroaki Iwata , Bioanalysis , vol.16 (23-24) (p.1211 - 1217) , 2024.12 , There is Review , The Simple Work , English
Accelerating Virtual Patient Generation with a Bayesian Optimization and Machine Learning Surrogate Model , Hiroaki Iwata, Ryuta Saito , CPT: Pharmacometrics & Systems Pharmacology , vol.14 (3) (p.486 - 494) , 2024.12 , There is Review , The Multiple Authorship , English
Constructing a graph neural network-based artificial intelligence model to predict drug-induced phospholipidosis potential , Yoshinobu Igarashi, Aki Hasegawa, Shigeyuki Matsumoto, Hiroaki Iwata, Ryosuke Kojima, Yasushi Okuno, and Hiroshi Yamada , Fundamental Toxicological Sciences , vol.11 (6) (p.279 - 288) , 2024.11 , There is Review , The Multiple Authorship , English
Developing a GNN-based AI model to predict mitochondrial toxicity using the bagging method , Igarashi Y, Kojima R, Matsumoto S, Iwata H, Okuno Y, Yamada H , The Journal of Toxicological Sciences , 2024.03 , There is Review , The Multiple Authorship , English
Feature extraction of particle morphologies of pharmaceutical excipients from scanning electron microscope images using convolutional neural networks , Iwata H, Hayashi Y, Koyama T, Hasegawa A, Ohgi K, Kobayashi I, Okuno Y , International Journal of Pharmaceutics , 2024.02 , There is Review , The Multiple Authorship , English
VGAE-MCTS: a New Molecular Generative Model combining Variational Graph Auto-Encoder and Monte Carlo Tree Search , Hiroaki Iwata, Taichi Nakai, Takuto Koyama, Shigeyuki Matsumoto, Ryosuke Kojima, Yasushi Okuno , Journal of chemical information and modeling , 2023.11 , There is Review , The Multiple Authorship , English
Improving Compound-Protein Interaction Prediction by Self-Training with Augmenting Negative Samples , Koyama T, Matsumoto S, Iwata H, Kojima R, Okuno Y , Journal of chemical information and modeling , 2023.07 , There is Review , The Multiple Authorship , English
Classification of scanning electron microscope images of pharmaceutical excipients using deep convolutional neural networks with transfer learning , Iwata H, Hayashi Y, Hasegawa A, Terayama K, Okuno Y , International Journal of Pharmaceutics: X , 2022.10 , There is Review , The Multiple Authorship , English
Predicting total drug clearance and volumes of distribution using the machine learning mediated multimodal method through the imputation of various non-clinical data , Iwata H, Matsuo T, Mamada H, Motomura T, Matsushita M, Fujiwara T, Maeda K, Handa K , Journal of chemical information and modeling , 2022.08 , There is Review , The Multiple Authorship , English
Structure-based de novo molecular generator combined with artificial intelligence and docking simulations , Ma B, Terayama K, Matsumoto S, Isaka Y, Sasakura Y, Iwata H, Araki M, Okuno Y , Journal of chemical information and modeling , 2021.07 , There is Review , The Multiple Authorship , English
Prediction of Total Drug Clearance in Humans Using Animal Data: Proposal of a Multimodal Learning Method Based on Deep Learning , Iwata H, Matsuo T, Mamada H, Motomura T, Matsushita M, Fujiwara T, Maeda K, Handa K , Journal of Pharmaceutical Sciences , 2021.03 , There is Review , The Multiple Authorship , English
Discovery of Natural TRPA1 Activators through Pharmacophore-based Virtual Screening and a Biological Assay , Iwata H, Kanda N, Araki M, Sagae Y, Masuda K, Okuno Y , Bioorganic & Medicinal Chemistry Letters , 2020.10 , There is Review , The Multiple Authorship , English
An in silico approach for integrating phenotypic and target-based approaches in drug discovery , Iwata H, Kojima R, Okuno Y , Molecular Informatics , 2020.10 , There is Review , The Multiple Authorship , English
Novel Orexin Antagonist from a Natural Plant was Discovered using Zebrafish Behavioural Analysis , Yamanaka M, Iwata H, Masuda K, Araki M, Okuno Y, Okamura M, Koiwa J, Tanaka T , European Review for Medical and Pharmacological Sciences , 2020.05 , There is Review , The Multiple Authorship , English
Identification of a new class of non-electrophilic TRPA1 agonists by a structure-based virtual screening approach , Araki M, Kanda N, Iwata H, Sagae Y, Masuda K, Okuno Y , Bioorganic & Medicinal Chemistry Letters , 2020.04 , There is Review , The Multiple Authorship , English
kGCN: a graph convolutional network framework for chemical structures , Kojima R, Ishida S, Ohta M, Iwata H, Honma T, Okuno Y , Cheminformatics , 2020.03 , There is Review , The Multiple Authorship , English