La Trobe

INSIGHT: An Integrated Framework for Safe and Sustainable Chemical and Material Assessment

journal contribution
posted on 2025-04-29, 02:34 authored by Angela Serra, Dimitrios Zouraris, Alexandra Schaffert, Marcella Torres Maia, Periklis Tsiros, Ishita Virmani, Emanuele Di Lieto, Laura Aliisa Saarimaki, Jack Morikka, Rafael Riudavets-Puig, Dimitra-Danai Varsou, Konstantinos D Papavasileiou, Panagiotis D Kolokathis, Dimitris G Mintis, Haralampos Tzoupis, Andreas Tsoumanis, Georgia Melagraki, Alex Arvanitidis, Philip Doganis, Vasileios Minadakis, Giannis Savvas, Adrien Perello-y-bestard, Stefano Cucurachi, Marija Buljan, Fotini Nikiforou, Achilleas Karakoltzidis, Spyros Karakitsios, Dimosthenis A Sarigiannis, Steffi Friedrichs, Christian Seitz, Tomas Navarrete Gutierrez, Panagiotis Isigonis, Sebastien Cambier, Antonino Marvuglia, Gottlieb Georg Lindner, Jacques-Aurelien Sergent, L Cristiana Gheorghe, Laura-Jayne A Bradford, Seung-Geun Park, Seung Min Ha, Zayakhuu Gerelkhuu, Tae Hyun Yoon, Romana Petry, Diego Stefani Teodoro Martinez, David WinklerDavid Winkler, Peter Wick, Thomas E Exner, Francesco Dondero, Tommaso Serchi, Willie Peijnenburg, Haralambos Sarimveis, Martin Paparella, Iseult Lynch, Antreas Afantitis, Dario Greco
The assessment of chemicals and materials has traditionally been fragmented, with health, environmental, social, and economic impacts evaluated independently. This disjointed approach limits the ability to capture trade-offs and synergies necessary for comprehensive decision-making under the Safe and Sustainable by Design (SSbD) framework. The EU INSIGHT project addresses this challenge by developing a novel computational framework for integrated impact assessment, based on the Impact Outcome Pathway (IOP) approach. Extending the Adverse Outcome Pathway (AOP) concept, IOPs establish mechanistic links between chemical and material properties and their environmental, health, and socio-economic consequences. The project integrates multi-source datasets (including omics, life cycle inventories, and exposure models) into a structured knowledge graph (KG), ensuring FAIR (Findable, Accessible, Interoperable, Reusable) data principles are met. INSIGHT is being developed and validated through four case studies targeting per- and polyfluoroalkyl substances (PFAS), graphene oxide (GO), bio-based synthetic amorphous silica (SAS), and antimicrobial coatings. These studies demonstrate how multi-model simulations, decision-support tools, and artificial intelligence-driven knowledge extraction can enhance the predictability and interpretability of chemical and material impacts. Additionally, INSIGHT incorporates interactive, web-based decision maps to provide stakeholders with accessible, regulatory-compliant risk and sustainability assessments. By bridging mechanistic toxicology, exposure modeling, life cycle assessment, and socio-economic analysis, INSIGHT advances a scalable, transparent, and data-driven approach to SSbD. This project aligns with the European Green Deal and global sustainability goals, promoting safer, more sustainable innovation in chemicals and materials through an integrated, mechanistic, and computationally advanced framework.

Funding

INSIGHT (Grant Agreement No. 101137742) is co-funded by the European Union’s Horizon Europe programme under the call HORIZON-CL4–2023-RESILIENCE-01, managed by the European Health and Digital Executive Agency (HADEA), with a total grant of €4,130,318.75 supporting the project from January 2024 to December 2027. Co-funding from UKRI Innovate UK for UoB participation via grant no. 10097888. EMPA also acknowledge the State Secretariat for Education, Research and Innovation (SERI) no 24.00030. Nano Material Technology Development Program (Grant number RS-2024–00452934) and Basic Science Research Program (Grant number 2020R1A6A1A06046728) through the National Research Foundation of Korea (NRF).

History

Publication Date

2025-01-01

Journal

Computational and Structural Biotechnology Journal

Volume

29

Pagination

13p. (p. 125-137)

Publisher

Elsevier

ISSN

2001-0370

Rights Statement

© 2025 The Author(s). Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).