Mission

Accelerating drug development process via digital transformation and open innovation

The Problem : Only 1/9000 success rate after 10~15 years

The Solution : Digital transformation of drug development process

Benchwork vs HITS digital solution

Technology

Innovation via fusion of physics and deep learning

Hit discovery

Hit-to-lead

More about HITS technology

Reference

Hit Discovery

Predicting drug-target interaction using graph neural network

Journal of chemical information and modeling, 59 (9), 3981-3988

Jaechang Lim, Seongok Ryu, Kyubyong Park, Yo Joong Choe, Jiyeon Ham, and Woo Youn Kim
Hit Discovery

Attention- and gate-augmented graph convolutional network

arXiv:1805.10988

Seongok Ryu, Jaechang Lim, Seung Hwan Hong, and Woo Youn Kim
Hit Discovery

Rational discovery of antimetastatic agents targeting the intrinsically disordered region of MBD2

Science Advances 5 (11), eaav9810

Min Young Kim, Insung Na, Ji Sook Kim, Seung Han Son, Sungwoo Choi, Seol Eui Lee, Ji-Hun Kim, Kiseok Jang, Gil Alterovitz, Yu Chen, Arjan van der Vaart, Hyung-Sik Won,Vladimir N. Uversky and Chul Geun Kim
Hit Discovery

A Bayesian graph convolutional network for reliable prediction of molecular properties with uncertainty quantification

Chemical Science, 2019, 10, 8438-8446

Seongok Ryu, Yongchan Kwon, and Woo Youn Kim
Hit-to-lead

Scaffold-based molecular design with graph generative model

Chemical Science, 2020,11, 1153-1164

Jaechang Lim, Sang-Yeon Hwang, Seokhyun Moon, Seungsu Kim, and Woo Youn Kim
Hit-to-lead

Molecular generative model with conditional variational autoencoder

Journal of Cheminformatics 10 (1), 31

Jaechang Lim, Seongok Ryu, Jin Woo Kim, and Woo Youn Kim
Hit-to-lead

Molecular generative model based on adversarially regularized autoencoder

Journal of Chemical Information and Modeling, 2020, 60, 1, 29-36

Seung Hwan Hong, Seongok Ryu, Jaechang Lim, and Woo Youn Kim

Team

Woo Youn Kim

CEO (cofounder)

  • B.S. in Chemistry and Physics, POSTECH
  • Ph.D. in Chemistry, POSTECH
  • Assistant and Associate professor, KAIST (2011~)

Jaechang Lim

Scientist (cofounder)

  • B.S. in Chemistry, KAIST
  • Ph.D. in Chemistry, KAIST
  • Development of deep learning techniques for drug discovery

Insung Na

Scientist (cofounder)

  • B.S. in Biology, Kyung Hee university
  • Staff. Microbiology analysis, QC, Celltrion
  • Ph.D. in Medical Sciences (concentration: molecular medicine), University of South Florida
  • Post doc, Boston Children’s Hospital / Harvard Medical School
  • Computational biology application for drug discovery

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서울특별시 강남구 테헤란로 124 삼원타워 902호
Send an email to [email protected] for collaboration or job application

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