Release date: 2020.06.26

Rapid safety prediction of antiviral drugs using machine learning with ES/iPS cells (Kyoto University)

Author: Kyoto University

Research classification

Detecting and treating infection by AI

Stages of technologies

Research and development stage

Applied AI technologies

Bayesian networks and machine learning

Related web pag

https://scchemrisc.stemcellinformatics.org/

  We have a consortium, scChemRISC, that develops a system for predicting the toxicity of compounds using ES cells. In the development of antiviral drugs, many products have side effects in clinical trials, and conventional safety evaluations require a huge budget and time, but using this system, we offer a technology that can predict toxicity risk rapidly, accurately and inexpensively. With this technology, we believe that it is possible to examine the differences in the reactions using iPS cells with ACE2 gene polymorphism.

 

  Laboratories, researchers, and contact address

   Prof. Wataru FUJIBUCHI, 
   Center for iPS Cell Research and Application (CiRA), Kyoto University
   53 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, JAPAN
   fujibuchi-g[atmark]cira.kyoto-u.ac.jp