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

Dimitrios Zouraris, Angelos Mavrogiorgis, Andreas Tsoumanis, Laura Aliisa Saarimäki, Giusy del Giudice, Antonio Federico, Angela Serra, Dario Greco, Ian Rouse, Julia Subbotina, Vladimir Lobaskin, Karolina Jagiello, Krzesimir Ciura, Beata Judzinska, Alicja Mikolajczyk, Anita Sosnowska, Tomasz Puzyn, Mary Gulumian, Victor Wepener, Diego S.T. MartinezRomana Petry, Naouale El Yamani, Elise Rundén-Pran, Sivakumar Murugadoss, Sergey Shaposhnikov, Vasileios Minadakis, Periklis Tsiros, Harry Sarimveis, Eleonora Marta Longhin, Tanima SenGupta, Ann Karin Hardie Olsen, Viera Skakalova, Peter Hutar, Maria Dusinska, Anastasios G. Papadiamantis, L. Cristiana Gheorghe, Katie Reilly, Emilie Brun, Sami Ullah, Sebastien Cambier, Tommaso Serchi, Kaido Tämm, Candida Lorusso, Francesco Dondero, Evangelos Melagrakis, Muhammad Moazam Fraz, Georgia Melagraki, Iseult Lynch, Antreas Afantitis

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
135 Downloads (Pure)

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 in vitro models, in silico 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.

Original languageEnglish
Pages (from-to)13-28
Number of pages16
JournalComputational and structural biotechnology journal
Volume29
Early online date25 Dec 2024
DOIs
Publication statusPublished - Jan 2025
Publication typeA1 Journal article-refereed

Keywords

  • biomolecule interactions
  • cloud platform
  • Computational approaches
  • nanoinformatics
  • nanomaterials safety

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Biotechnology
  • Biophysics
  • Structural Biology
  • Biochemistry
  • Genetics
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials'. Together they form a unique fingerprint.

Cite this