Project description
Improved predictive models to assess drug and chemical toxicity
The toxicology field is facing a critical need for fast, efficient and accurate technologies to assess the effects of an increasing number of drugs and chemicals. While computational toxicology offers cost-effective and fast testing methods, it faces limitations. Current predictive models, such as quantitative structure-activity relationship models, rely on large sets of molecular descriptors. However, this methodology can assess chemicals similar to those used in developing the models, while the large number of descriptors is hard to interpret. The EIC-funded QUANTUM-TOX project will develop a new type of descriptor based on quantum mechanics that can cover the entire chemical space with easily interpretable parameters. By creating specific electronic signatures and leveraging AI, QUANTUM-TOX's innovative approach could significantly improve computational toxicology.
Objective
Toxicology is at a crossroads. With ever more drugs going to market and more chemicals having an environmental impact, the need for fast, cheap and accurate technologies to assess toxic effects is pressing. Computational toxicology provides an array of tools and methods for toxicity prediction only using computer approaches. Conceptually, computational toxicology has significant advantages since testing is fast and cheaper than in vitro. However, currently computational toxicology has severe limitations. Predictions typically use Quantitative Structure-Activity Relationship (QSAR) models that rely on large sets of molecular descriptors. This causes severe problems since the methodologies cannot assess chemicals different than the ones used to develop the QSAR models, and when that is possible, the very large number of descriptors limits understandability. Therefore, new methodologies are needed to address those shortcomings. This project will develop a new type of descriptor, totally based on quantum mechanics that can cover the whole chemical space and relies on a small number of parameters that are easily interpretable. Starting with meaningful chemical perturbations, that extract the behaviour of the chemicals in assumed mechanisms of toxic action, the approach will develop specific Electronic SIGNatures (ESigns). ESigns are mathematical invariants that map the results of the quantum chemical calculations. Using Artificial Intelligence, the ESigns will relate to toxicity. The new approach introduces a momentous change in computational toxicology. It can cover the whole chemical space, since we are abandoning predictions based on molecular structures, uses fewer parameters, and can be related to the new trends in toxicology regarding use of pathways information. In fact, it is a powerful tool to allow accurate toxicology predictions solely on the basis of biochemical and chemical insight.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been validated by the project's team.
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC - HORIZON EIC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2023-PATHFINDEROPEN-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
20156 MILANO
Italy
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