CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials

The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced <i>in vitro</i> models, <i>in silico</i> approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems. Significant progress has been made in generating atomistic and quantum-mechanical descriptors for various NMs, evaluating their interactions with biological systems (from small molecules or metabolites, to proteins, cells, organisms, animals, humans and ecosystems), and in developing predictive models for NMs risk assessment. The CompSafeNano project has also focused on implementing and further standardising data reporting templates and enhancing data management practices, ensuring adherence to the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Despite challenges, such as limited regulatory acceptance of New Approach Methodologies (NAMs) currently, which has implications for predictive nanosafety assessment, CompSafeNano has successfully developed tools and models that are integral to the safety evaluation of NMs, and that enable the extensive datasets on NMs safety to be utilised for the re-design of NMs that are inherently safer, including through prediction of the acquired biomolecule coronas which provide the biological or environmental identities to NMs, promoting their sustainable use in diverse applications. Future efforts will concentrate on further refining these models, expanding the NanoPharos Database, and working with regulatory stakeholders thereby fostering the widespread adoption of SbD practices across the nanotechnology sector. CompSafeNano's integrative approach, multidisciplinary collaboration and extensive stakeholder engagement, position the project as a critical driver of innovation in NMs SbD methodologies and in the development and implementation of computational nanosafety.

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Publication Details

Journal
Computational and Structural Biotechnology Journal
Published
2024-12-25
DOI
https://doi.org/10.1016/j.csbj.2024.12.024
Citations
13
Primary Topic
Nanoparticles: synthesis and applications
Type
article
Field-Weighted Citation Impact
1.52

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article

CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials

Laura Aliisa Saarimäki, Dimitrios Zouraris, Naouale El Yamani, Andreas Tsoumanis et al.
13 citations
Computational and Structural Biotechnology Journal
Nanoparticles: synthesis and applications
1.52
article

CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials

Laura Aliisa Saarimäki, Dimitrios Zouraris, Naouale El Yamani, Andreas Tsoumanis, L Cristiana Gheorghe, Alicja Mikołajczyk, Sébastien Cambier, Haralambos Sarimveis, Muhammad Moazam Fraz, Katie Reilly, Romana Petry, Sergey Shaposhnikov, Periklis Tsiros, Karolina Jagiełło, Dario Greco, Tomasz Puzyn, Sivakumar Murugadoss, Francesco Dondero, Krzesimir Ciura, Mary Gulumian, Candida Lorusso, Angela Serra, Ian Rouse, Eleonora Longhin, Diego Stéfani T. Martinez, Elise Rundén‐Pran, Georgia Melagraki, Anita Sosnowska, Giusy del Giudice, Julia Subbotina, Vladimir Lobaskin, Mária Dušinská, Peter Hutár, Anastasios G. Papadiamantis, Beata Judzińska, Tommaso Serchi, Ann‐Karin Olsen, Tanima SenGupta, Émilie Brun, Victor Wepener, Iseult Lynch, Sami Ullah, Antreas Afantitis, Kaido Tämm, Vasileios Minadakis, Antonio Federico, Angelos Mavrogiorgis, Viera Skakalova, Evangelos Melagrakis
article en
13 citations

Abstract

The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced <i>in vitro</i> models, <i>in silico</i> approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems. Significant progress has been made in generating atomistic and quantum-mechanical descriptors for various NMs, evaluating their interactions with biological systems (from small molecules or metabolites, to proteins, cells, organisms, animals, humans and ecosystems), and in developing predictive models for NMs risk assessment. The CompSafeNano project has also focused on implementing and further standardising data reporting templates and enhancing data management practices, ensuring adherence to the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Despite challenges, such as limited regulatory acceptance of New Approach Methodologies (NAMs) currently, which has implications for predictive nanosafety assessment, CompSafeNano has successfully developed tools and models that are integral to the safety evaluation of NMs, and that enable the extensive datasets on NMs safety to be utilised for the re-design of NMs that are inherently safer, including through prediction of the acquired biomolecule coronas which provide the biological or environmental identities to NMs, promoting their sustainable use in diverse applications. Future efforts will concentrate on further refining these models, expanding the NanoPharos Database, and working with regulatory stakeholders thereby fostering the widespread adoption of SbD practices across the nanotechnology sector. CompSafeNano's integrative approach, multidisciplinary collaboration and extensive stakeholder engagement, position the project as a critical driver of innovation in NMs SbD methodologies and in the development and implementation of computational nanosafety.

Computational and Structural Biotechnology JournalVol. 29
University College Dublin (IE), Università degli Studi del Piemonte Orientale “Amedeo Avogadro” (IT), Tampere University of Applied Sciences (FI), National Technical University of Athens (GR), Hellenic Military Academy (GR), North-West University (ZA), Hellenic Statistical Authority (GR), University of Gdańsk (PL), Larnaca College (CY), Danubia NanoTech (Slovakia) (SK), Luxembourg Institute of Science and Technology (LU), NovaMechanics (Cyprus) (CY), Brazilian Center for Research in Energy and Materials (BR), University of Tartu (EE), Atotech (United States) (US), NILU (NO), University of Birmingham (GB), National University of Sciences and Technology (PK)
European Commission, H2020 Marie Skłodowska-Curie Actions
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Nanoparticles: synthesis and applications
1.52
DOIOpen Access PDFOpenAlex
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