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- Title
- The first South Korean data challenge for drug discovery using human and mouse liver microsomal stability data
- Author(s)
- N C Cho; S E Hong; J S Song; E J Yeo; S Jung; Y Lee; S G Hwang; S M Kang; J S Hwang; Tae-Eun Jin
- Bibliographic Citation
- Journal of Cheminformatics, vol. 17, pp. 139-139
- Publication Year
- 2025
- 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.
- Keyword
- Korea data challengeJUMP AI 2023Metabolic stability
- ISSN
- 1758-2946
- Publisher
- Springer-BMC
- Full Text Link
- http://dx.doi.org/10.1186/s13321-025-01047-8
- Type
- Article
- Appears in Collections:
- 1. Journal Articles > Journal Articles
- Files in This Item:
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