Evidence map›Paper›PMID 40903765›Full record

ArticleJournal of cheminformatics2025

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

Nam-Chul Cho, SeongEun Hong, Jin Sook Song, EuiJu Yeo, SoI Jung, Yuno Lee, Seul Gee Hwang, Su Min Kang, JaeSung Hwang, Tae-Eun Jin

Abstract read
In one paragraph

Article in Journal of cheminformatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Nam-Chul ChoDrug Information Platform Center, Korea Research Institute of Chemical Technology, Daejeon, 34114, Republic of Korea. nccho@krict.re.kr.
SeongEun HongKorea Pharmaceutical and Bio-Pharma Manufacturers Association, Seoul, 06666, Republic of Korea.
Jin Sook SongData Convergence Drug Research Center, Korea Research Institute of Chemical Technology, Daejeon, 34114, Republic of Korea.
EuiJu YeoKorea Pharmaceutical and Bio-Pharma Manufacturers Association, Seoul, 06666, Republic of Korea.
SoI JungKorea Pharmaceutical and Bio-Pharma Manufacturers Association, Seoul, 06666, Republic of Korea.
Yuno LeeDrug Information Platform Center, Korea Research Institute of Chemical Technology, Daejeon, 34114, Republic of Korea.
Seul Gee HwangDrug Information Platform Center, Korea Research Institute of Chemical Technology, Daejeon, 34114, Republic of Korea.
Su Min KangDrug Information Platform Center, Korea Research Institute of Chemical Technology, Daejeon, 34114, Republic of Korea.
JaeSung HwangKorea Pharmaceutical and Bio-Pharma Manufacturers Association, Seoul, 06666, Republic of Korea.
Tae-Eun JinKorea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, 34141, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

JUMP AI 2023Korea data challengeMetabolic stability

Identifiers

PMID40903765
PMCPMC12409929

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.