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

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Research classification

  • Detecting and treating infection by AI

Stages of technologies

  • Research and development stage

Applied AI technologies

  • Bayesian networks and machine learning

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

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