ONTOX: predicting toxicity with artificial intelligence
ONTOX aims to deliver a generic strategy for using artificial intelligence (AI) that can be applied to predict toxicity in humans of any chemical at any dose. With the use of big data, novel predictive algorithms will be used to effectively indicate whether a compound of interest provides a risk for human health.
Objective
The vision of the ONTOX consortium is to provide a functional and sustainable solution for advancing human risk assessment of chemicals without the use of animals in line with the principles of 21st century toxicity testing and next generation risk assessment.
Results
ONTOX will deliver a generic strategy to create innovative new approach methodologies (NAMs) in order to predict systemic repeated dose toxicity effects. Upon combination with tailored exposure assessment, these will enable human risk assessment. This strategy can be applied to any type of chemical and systemic repeated dose toxicity effect. Application of AI is at the heart of this project.
Approach
Focus will be put on 6 specific new approach methodologies addressing adversities in the liver, kidney and the developing brain induced by a variety of chemicals. Including pharmaceuticals, cosmetics, and food ingredients and biocides.
Education impact
ONTOX will have a deep and long-lasting impact on many levels. In particular by consolidating Europe’s world-leading position regarding the development, exploitation, regulation and application of animal-free methods for human risk assessment of chemicals.
Projectupdates
HU researchers involved in the research
Collaboration with knowledge partners
The project consortium consists of a broad range of European and other research institutes and businesses. For a full overview, please refer to the project's website.
Co-funding
This project has received a grant of 17,211,050 euro under the European Union's Horizon 2020 programme under grant agreement number 963845.
