Project description
Advancing AI for safer chemical development
In the chemical industry, developing compounds requires balancing biological activity, physico-chemical properties, and minimal toxicity. Advanced machine learning is crucial in identifying harmful environmental and human impacts. However, traditional machine learning methods are limited to predicting compounds similar to their training sets, narrowing their applicability domain (AD). Emerging representation learning approaches offer the potential for broader AD by efficiently modelling molecular interactions, matching the accuracy of physics-based methods in a fraction of the time. Supported by the Marie Skłodowska-Curie Actions programme, the AiChemist project will use both public and in-house data to enhance predictions across chemical reactions and toxicity endpoints. It also provides structured training to foster European innovation in AI methods for chemistry.
Objective
Optimising biological activity and physico-chemical properties, while minimising their toxicity, are objectives when developing new compounds in chemical industries. Advanced machine learning (AI) methods are indispensable to this process. They are also increasingly used in environmental chemistry to identify compounds damaging to the environment and humans. Traditional machine learning (ML) methods provide reliable predictions though only for compounds similar to the training set, thus defining their applicability domain (AD). Emerging representation learning approaches can efficiently approximate the physical interactions of molecules with an accuracy comparable to physics-based methods in only fractions of time. Models based on these representations should have much larger AD due to pre-training on large chemical sets of theoretical values. Here we will develop and benchmark representation learning approaches, addressing their accuracy and ADs, using public and in-house data for endpoints ranging from chemical reactions to toxicity. While explainable AI (XAI) methods are actively developing in the ML community, there is a gap with their use in chemistry, i.e. there is a need to translate their results to the end users, chemists and regulatory bodies. Since the research program is tightly coupled with the target users - large companies, regulatory agencies and SMEs - it provides a clear path for technology transfer from academia to industry. AiChemist will provide structured training to its fellows through a combination of online courses and schools, strengthening European innovation capacity in the education of specialists in AI methods. The fellows will receive comprehensive training in transferable skills. The complementary expertise and strong commitment of the partners make this ambitious innovative research program realistic via the proper allocation of individual tasks and resources, as described below.
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.
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.
- natural sciences computer and information sciences artificial intelligence machine learning
- natural sciences chemical sciences
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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.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
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.
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
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.
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-TMA-MSCA-DN-ID - HORIZON TMA MSCA Doctoral Networks - Industrial Doctorates
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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-MSCA-2022-DN-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.
85764 Neuherberg
Germany
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Participants (14)
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151 85 Sodertaelje
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51373 Leverkusen
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10785 Berlin
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94250 Gentilly
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90411 Nurnberg
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1165 KOBENHAVN
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67081 Strasbourg
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2311 EZ Leiden
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20156 MILANO
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Participation ended
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28006 Madrid
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80333 Muenchen
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5612 AE Eindhoven
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75230 Paris
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08003 Barcelona
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Partners (14)
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6900 Lugano
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1015 Lausanne
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08007 Barcelona
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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80803 Munich
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
6900 Lugano
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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.
20993 Silver Spring
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20892 Bethesda
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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33150 Cenon
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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305606 DAEJEON
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00121 Helsinki
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43235 1623 Columbus Oh
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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4058 Basel
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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75006 Paris
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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85716 Unterschleiheim
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The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.