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Accelerating SUStainable TECHnological trajectories with computational chemistry and machine learning

Objective

SUSTECH addresses a critical paradox at the heart of modern society: synthetic chemicals have been instrumental in societal advancement in their manifold uses ranging from materials to fertilizers and pharmaceuticals. Yet, they pose escalating risks to human health and environmental sustainability. There is an urgent need to reorient technological development toward safer and more sustainable alternatives. This project aims to generate a comprehensive understanding of the technological pathways that lead to the commercialization of hazardous compounds to inform policy-makers how to redirect innovation in ways that align with societal and environmental well-being. SUSTECH investigates the decision-making processes and incentive structures that drive the development and the market approval of hazardous compounds to identify potentially misguided incentives. The interdisciplinary project integrates methodologies from computational chemistry and machine learning, with frameworks rooted in the economics of innovation. SUSTECH forecasts various characteristics, including toxicity profiles, of molecular structures disclosed in archival sources such as patents, linking these to related innovation activities and underlying incentives. This approach offers a robust foundation for evidence-based policy interventions. Moreover, SUSTECH will craft predictive tools for early hazard assessment in the innovation process, with key data and algorithms accessible via an open platform. The potential impact is immense: informing regulatory approaches to steer early-stage innovation towards sustainability. SUSTECH represents a paradigm shift, applying predictive chemistry methods to address this challenge. The PIs are leaders with complementary expertise: predictive algorithms using molecular data (OI), innovation studies and patent analyses in chemistry (AM) and pharmaceuticals (SW), and sustainability and science & technology policy (EG).

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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Keywords

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.

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.

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.

HORIZON-ERC-SYG - HORIZON ERC Synergy Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2025-SyG

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Host institution

UNIVERSITA DI PISA
Net EU contribution

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.

€ 2 456 963,85
Address
LUNGARNO PACINOTTI 43/44
56126 PISA
Italy

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Region
Centro (IT) Toscana Pisa
Activity type
Higher or Secondary Education Establishments
Links
Total cost

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.

€ 2 456 963,85

Beneficiaries (4)

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