CHIASMA: Advancing chemicals and materials safety and sustainability assessments through innovative integration of in vitro and in silico (new approach) methodologiesopen access
- Authors
- Weber, Pamina; Arnesdotter, Emma; Attar, Nour; Friedrichs, Steffi; Seitz, Christian; Chowdhury, Riju Roy; Koch, Katharina; Buerki-Thurnherr, Tina; Brugger, Beatrice; Wick, Peter; Morikka, Jack; Serra, Angela; Capini, Lorenzo; Greco, Dario; Lacconii, Valentina; Marchesei, Adriana Scattareggia; Campagnoloi, Luisa; Exnerj, Thomas E.; Brajnikj, Maja; Brun, Emilie; Lynch, Iseult; Zouraris, Dimitris; Mintis, Dimitris; Tsoumanis, Andreas; Afantitis, Antreas; Melagraki, Georgia; Minadakis, Vasileios; Papakyriakopoulou, Paraskevi; Tsiros, Periklis; Thepaut, Elisa; Sarimveis, Haralambos; Majo, Marc; Hischier, Roland; Virmani, Ishita; Paparella, Martin; Kavaliauskiene, Simona; Sayyari, Amin; Fontaine, Romain; Muller, Mette Helen Bjorge; Lee, Eunseo; Gerelkhuu, Zayakhuu; Yoon, Tae Hyun; Turan-Sorhun, Duygu; Neuhaus, Winfried; Serchi, Tommaso
- Issue Date
- Jan-2025
- Publisher
- Research Network of Computational and Structural Biotechnology
- Keywords
- New Approach Methodologies (NAMs); Next generation Safety Assessment (NGSA); 3Rs (Replacement; Reduction; Refinement); chemical safety assessment; Safe and Sustainable by Design (SSbD); PFAS; (nano-)pesticides; advanced materials; European Green Deal
- Citation
- Computational and Structural Biotechnology Journal, v.29, pp 305 - 327
- Pages
- 23
- Indexed
- SCIE
SCOPUS
- Journal Title
- Computational and Structural Biotechnology Journal
- Volume
- 29
- Start Page
- 305
- End Page
- 327
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/209849
- DOI
- 10.1016/j.csbj.2025.11.032
- ISSN
- 2001-0370
2001-0370
- Abstract
- Traditional in vivo methodologies have long formed the foundation of chemical and material safety assessment, yet they are increasingly inadequate to meet modern regulatory, ethical, and sustainability demands. These conventional approaches are resource-intensive, ethically questionable, and often fail to accurately predict human or environmental toxicity, particularly for emerging pollutants such as PFAS, (nano-) pesticides, and 2D materials. In response, the EU has launched initiatives like the Chemical Strategy for Sustainability and the Zero Pollution Action Plan under the European Green Deal to promote innovation in safer, and more sustainable chemicals. Central to this transformation is the Safe and Sustainable by Design (SSbD) framework, developed by the European Commission's Joint Research Center, which provides structured methodologies and metrics to integrate safety and sustainability into material innovation from the earliest stages of design. Building on this vision, the CHIASMA project aims to advance Next generation Safety Assessment (NGSA) by developing innovative New Approach Methodologies (NAMs) that combine experimental, computational, and Life Cycle Assessment (LCA) tools. Focusing on key biological systems and exposure routes, CHIASMA integrates Artificial Intelligence (AI), Machine Learning (ML), and Knowledge Graph (KG) technologies to enhance data interoperability and predictive accuracy. By embedding FAIR data principles and aligning with Good Laboratory Practice (GLP) standards, CHIASMA promotes transparency and regulatory acceptance. Fully aligned with SSbD principles, CHIASMA establishes a digital, interoperable infrastructure for predictive safety evaluation, that leverage on state-of-art experimental New Approach Methodologies (NAMs) bridging critical data gaps and supporting the transition towards sustainable, science-driven, and ethically responsible chemical and material innovation in Europe and beyond.
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