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Home / Resources / Presentations / Innovative Nanoinformatics models and tools: towards a Solid, verified and Integrated Approach to Predictive (eco)Toxicology (NanoSolveIT) / About

Innovative Nanoinformatics models and tools: towards a Solid, verified and Integrated Approach to Predictive (eco)Toxicology (NanoSolveIT)

By Antreas Afantitis, Mervi Heiskanen1

1. National Cancer Institute

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Abstract

Nano WG January 17, 2019

NanoSolveIT (a new H2020 nanoinformatics project) aspires to introduce a ground-breaking in silico Integrated Approach to Testing and Assessment (IATA) for the environmental health and safety of Nanomaterials (NM), implemented through a decision support system packaged as both a stand-alone open software and via a Cloud platform. NanoSolveIT will develop and deliver: (i) a reliable user friendly knowledge-based infrastructure for data hosting, sharing and exploitation, (ii) NM fingerprints, sets of nanodescriptors and properties that can be predictively linked to NM functionality, exposure and hazard, thereby supporting NM grouping, safe-by-design (SbD) and regulatory risk assessment (RA), (iii) innovative methodologies for NMs predictive (eco)toxicology underpinned by artificial intelligence (AI) and state-of-the-art in silico techniques, and, (iv) integration with currently developing multi-scale modelling, RA and governance frameworks developing in EU H2020 funded projects including caLIBRAte and expected in the forthcoming NMBP-13 project(s). NanoSolveIT will deliver a validated, sustainable, multi-scale nanoinformatics IATA, tested and demonstrated at TLR6 via OECD-style case studies, to serve the needs of diverse stakeholders at each stage of the NMs value chain, for assessment of potential adverse effects of NM on human health and the environment.

 

 

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Researchers should cite this work as follows:

  • Antreas Afantitis; Mervi Heiskanen (2019), "Innovative Nanoinformatics models and tools: towards a Solid, verified and Integrated Approach to Predictive (eco)Toxicology (NanoSolveIT)," https://nciphub.org/resources/2187.

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