Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future

Michael G. Diemar; Cyrille A. M. Krul; Marc Teunis; Francois Busquet; Helena Kandarova; Julia D. Zajac; Mathieu Vinken; Erwin L. Roggen

doi:10.1177/02611929241305112

Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future

Michael G. Diemar
, Cyrille A. M. Krul
, Marc Teunis
, Francois Busquet
, Helena Kandarova
, Julia D. Zajac
, Mathieu Vinken
, Erwin L. Roggen

Research output: Contribution to journal › Article › peer-review

3 Citations (Scopus)

96 Downloads (Pure)

Abstract

The first ONTOX Hackathon of the EU Horizon 2020-funded ONTOX project was held on 21–23 April 2024 in Utrecht, The Netherlands (https://ontox-project.eu/hackathon/). This participatory event aimed to collectively advance innovation for human safety through the use of Artificial Intelligence (AI), and hence significantly reduce reliance on animal-based testing. Expert scientists, industry leaders, young investigators, members of animal welfare organisations and academics alike, joined the hackathon. Eight teams were stimulated to find innovative solutions for challenging themes, that were selected based on previous discussions between stakeholders, namely: How to drive the use of AI in chemical risk assessment?; To predict or protect?; How can we secure human health and environmental protection at the same time?; and How can we facilitate the transition from animal tests to full implementation of human-relevant methods? The hackathon ended with a pitching contest, where the teams presented their solutions to a jury. The most promising solutions will be presented to regulatory authorities, industry, academia and non-governmental organisations at the next ONTOX Stakeholder Network meeting and taken up by the ONTOX project in order to tackle the above-mentioned challenges further. This report comprises two parts: The first part highlights some of the lessons learnt during the planning and execution of the hackathon; the second part presents the outcome of the ONTOX Hackathon, which resulted in several innovative and promising solutions based on New Approach Methodologies (NAMs), and outlines ONTOX’s intended way forward.

Original language	English
Pages (from-to)	42-61
Number of pages	20
Journal	ATLA. Alternatives to Laboratory Animals
Volume	53
Issue number	1
DOIs	https://doi.org/10.1177/02611929241305112 https://doi.org/10.1177/02611929241305112
Publication status	Published - Jan 2025

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: European Union\u2019s Horizon 2020 Research and Innovation programme, 963845.

Funding Information:
ONTOX expresses a great thank you to all participants and facilitators for a very enthusiastic involvement (Appendix, ). This work was performed in the context of the ONTOX project ( https://ontoxproject.eu/ ) that has received funding from the European Union\u2019s Horizon 2020 Research and Innovation programme under Grant Agreement No. 963845. ONTOX is part of the ASPIS project cluster ( https://aspiscluster.eu/ ). The credits for the photographs used by Breakout Group H for their presentation slide () are: bus couple, from the EC website (\u00A9 iStock); man in suit, model photograph on bucco.us; grad couple, Cumberland University, Lebanon, TN, USA ( https://www.cumberland.edu/academics/ ); meeting table ( https://www.cleanpng.com/png-round-table-meeting-clip-art-meeting-675504/ ).

Publisher Copyright:
© The Author(s) 2024.

Keywords

Ai
NAMs
New Approach Methodologies
Ontox
Artificial intelligence
Hackathon
Probabilistic risk assessment
Reduction
Replacement
Toxicology

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EUAR61: H2020: Ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment
Vinken, M. (Administrative Promotor), Vanhaecke, T. (CoI (Co-Promotor)) & Rogiers, V. (CoI (Co-Promotor))
1/05/21 → 31/10/26
Project: Fundamental

Cite this

Diemar, M. G., Krul, C. A. M., Teunis, M., Busquet, F., Kandarova, H., Zajac, J. D., Vinken, M., & Roggen, E. L. (2025). Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future. ATLA. Alternatives to Laboratory Animals, 53(1), 42-61. https://doi.org/10.1177/02611929241305112, https://doi.org/10.1177/02611929241305112

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abstract = "The first ONTOX Hackathon of the EU Horizon 2020-funded ONTOX project was held on 21–23 April 2024 in Utrecht, The Netherlands (https://ontox-project.eu/hackathon/). This participatory event aimed to collectively advance innovation for human safety through the use of Artificial Intelligence (AI), and hence significantly reduce reliance on animal-based testing. Expert scientists, industry leaders, young investigators, members of animal welfare organisations and academics alike, joined the hackathon. Eight teams were stimulated to find innovative solutions for challenging themes, that were selected based on previous discussions between stakeholders, namely: How to drive the use of AI in chemical risk assessment?; To predict or protect?; How can we secure human health and environmental protection at the same time?; and How can we facilitate the transition from animal tests to full implementation of human-relevant methods? The hackathon ended with a pitching contest, where the teams presented their solutions to a jury. The most promising solutions will be presented to regulatory authorities, industry, academia and non-governmental organisations at the next ONTOX Stakeholder Network meeting and taken up by the ONTOX project in order to tackle the above-mentioned challenges further. This report comprises two parts: The first part highlights some of the lessons learnt during the planning and execution of the hackathon; the second part presents the outcome of the ONTOX Hackathon, which resulted in several innovative and promising solutions based on New Approach Methodologies (NAMs), and outlines ONTOX{\textquoteright}s intended way forward.",

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author = "Diemar, \{Michael G.\} and Krul, \{Cyrille A. M.\} and Marc Teunis and Francois Busquet and Helena Kandarova and Zajac, \{Julia D.\} and Mathieu Vinken and Roggen, \{Erwin L.\}",

note = "Funding Information: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: European Union\textbackslash{}u2019s Horizon 2020 Research and Innovation programme, 963845. Funding Information: ONTOX expresses a great thank you to all participants and facilitators for a very enthusiastic involvement (Appendix, ). This work was performed in the context of the ONTOX project ( https://ontoxproject.eu/ ) that has received funding from the European Union\textbackslash{}u2019s Horizon 2020 Research and Innovation programme under Grant Agreement No. 963845. ONTOX is part of the ASPIS project cluster ( https://aspiscluster.eu/ ). The credits for the photographs used by Breakout Group H for their presentation slide () are: bus couple, from the EC website (\textbackslash{}u00A9 iStock); man in suit, model photograph on bucco.us; grad couple, Cumberland University, Lebanon, TN, USA ( https://www.cumberland.edu/academics/ ); meeting table ( https://www.cleanpng.com/png-round-table-meeting-clip-art-meeting-675504/ ). Publisher Copyright: {\textcopyright} The Author(s) 2024.",

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Diemar, MG, Krul, CAM, Teunis, M, Busquet, F, Kandarova, H, Zajac, JD , Vinken, M & Roggen, EL 2025, 'Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future', ATLA. Alternatives to Laboratory Animals, vol. 53, no. 1, pp. 42-61. https://doi.org/10.1177/02611929241305112, https://doi.org/10.1177/02611929241305112

Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future. / Diemar, Michael G.; Krul, Cyrille A. M.; Teunis, Marc et al.
In: ATLA. Alternatives to Laboratory Animals, Vol. 53, No. 1, 01.2025, p. 42-61.

Research output: Contribution to journal › Article › peer-review

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Diemar MG, Krul CAM, Teunis M, Busquet F, Kandarova H, Zajac JD et al. Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future. ATLA. Alternatives to Laboratory Animals. 2025 Jan;53(1):42-61. doi: 10.1177/02611929241305112, 10.1177/02611929241305112

Report of the First ONTOX Hackathon: Hack to Save Lives and Avoid Animal Suffering. The Use of Artificial Intelligence in Toxicology - A Potential Driver for Reducing/Replacing Laboratory Animals in the Future

Abstract

Bibliographical note

Keywords

Access to Document

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Projects

EUAR61: H2020: Ontology-driven and artificial intelligence-based repeated dose toxicity testing of chemicals for next generation risk assessment

Cite this