Chemoinformatics / Materials Science
Discover new materials/drugs with computational science.
Finding new materials by deep learning and computational simulations*
Material analysis based on computational simulation can be a promising solution to reduce experimental costs and promote new material developments. Current simulation technology is, however, not mature enough to handle tremendous numbers of candidate compounds and materials thoroughly because of its computational cost.
Our goal is to accelerate the process of material developments by high-performance material analysis system based on state-of-the-art deep learning and computational simulation technologies.
Especially, we are engaging R&D activities to achieve such material analysis technology for application to drug and material discovery.
Chemistry Letters, 47, 1431-1434, 2018
By : Naruki Yoshikawa, Kei Terayama, Masato Sumita, Teruki Homma, Kenta Oono, Koji Tsuda
Machine Learning for Molecules and Materials in NIPS 2017
AI based Drug Design using Variational Autoencoder and Weighted Retraining
By : Ryuichiro Ishitani
Discovery of SARS-CoV-2 protease inhibitors using AI drug discovery technology
By : Kentaro Rikimaru