The first South Korean data challenge for drug discovery using human and mouse liver microsomal stability data

The Korea Chemical Bank (KCB) has generated a dataset containing metabolic stability data for approximately 4,000 compounds that have been tested on human and mouse liver microsomes. The first South Korea Data Challenge, named the Jump AI Challenge for Drug Discovery (JUMP AI 2023), was opened using the metabolic stability data of KCB in 2023. The objective of the JUMP AI 2023 was to promote and encourage the development of new drugs using artificial intelligence (AI) technology in South Korea. A total of 1254 teams participated in the competition, developing algorithms to estimate the remaining percentage of compounds after 30 min of incubation with human and mouse liver microsomes. The data set comprised training and test sets of 3498 and 483 compounds, respectively. This paper provides an overview of the JUMP AI 2023 and its outcomes, highlighting the diverse range of algorithms and artificial intelligence technologies employed by the competing teams. Among these, five teams stood out by utilizing GNN-based approaches winning awards. This competition was the first AI competition for drug discovery in South Korea, attracting numerous researchers and playing a key role in promoting drug research through the application of artificial intelligence technologies.

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Publication Details

Journal
Journal of Cheminformatics
Published
2025-09-03
DOI
https://doi.org/10.1186/s13321-025-01047-8
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

The first South Korean data challenge for drug discovery using human and mouse liver microsomal stability data

Jin Sook Song, Eugenia L.L. Yeo, Yuno Lee, Sung Woo Jung et al.
Journal of Cheminformatics
Computational Drug Discovery Methods
article

The first South Korean data challenge for drug discovery using human and mouse liver microsomal stability data

Jin Sook Song, Eugenia L.L. Yeo, Yuno Lee, Sung Woo Jung, Su Jin Kang, Jae‐Sung Hwang, Sung Hyun Hong, Tae-Eun Jin, Nam-Chul Cho, Seul Gee Hwang
article en

Abstract

The Korea Chemical Bank (KCB) has generated a dataset containing metabolic stability data for approximately 4,000 compounds that have been tested on human and mouse liver microsomes. The first South Korea Data Challenge, named the Jump AI Challenge for Drug Discovery (JUMP AI 2023), was opened using the metabolic stability data of KCB in 2023. The objective of the JUMP AI 2023 was to promote and encourage the development of new drugs using artificial intelligence (AI) technology in South Korea. A total of 1254 teams participated in the competition, developing algorithms to estimate the remaining percentage of compounds after 30 min of incubation with human and mouse liver microsomes. The data set comprised training and test sets of 3498 and 483 compounds, respectively. This paper provides an overview of the JUMP AI 2023 and its outcomes, highlighting the diverse range of algorithms and artificial intelligence technologies employed by the competing teams. Among these, five teams stood out by utilizing GNN-based approaches winning awards. This competition was the first AI competition for drug discovery in South Korea, attracting numerous researchers and playing a key role in promoting drug research through the application of artificial intelligence technologies.

Journal of CheminformaticsVol. 17(1)
Institute of Chemical Technology (IN), Korea Pharma (South Korea) (KR), Korea Research Institute of Chemical Technology (KR), Korea Pharmaceutical and Bio-Pharma Manufacturers Association (KR), Korea Research Institute of Bioscience and Biotechnology (KR), Korea Institute of Science & Technology Information (KR), Bank of Korea (KR)
National Research Foundation, Korea Health Industry Development Institute, National Research Foundation of Korea
Openalex Percentile: Top 75%
Computational Drug Discovery Methods
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