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

Periodic Reporting for period 3 - NanoSolveIT (Innovative Nanoinformatics models and tools: towards a Solid, verified and Integrated Approach to Predictive (eco)Toxicology (NanoSolveIT))

Período documentado: 2022-03-01 hasta 2023-08-31

Nanotechnology is a key enabling technology, capable of delivering a wide range of technological breakthroughs, through a multitude of novel and emerging engineered nanomaterials (NMs) whose unique features serve applications across all EU priority sectors. Although many benefits of NMs have been identified, concerns are also arising as risk assessment is lagging behind product development, as current approaches to assessing exposure, hazard and risk are expensive, time-consuming, and frequently involve testing in animal models.

To overcome these challenges, NanoSolveIT (Figure 1) introduced a ground-breaking in silico Integrated Approach to Testing and Assessment (IATA) for environmental health and safety evaluation of NMs. The IATA was implemented through a decision support system packaged as a stand-alone open software and via a Cloud platform (Figure 2). The NanoSolveIT partners (Figure 3) designed and integrated a clear plan of model development, integration, testing and validation via case studies. This resulted in the provision of user-friendly graphical user interfaces, complemented by detailed training documentation to support uptake and application by industry and regulators (Figure 4). The ultimate outcome is a validated, sustainable, multi-scale nanoinformatics IATA, tested and demonstrated at TRL6 via OECD-style case studies selected to serve the needs of stakeholders at different stages of the NM value chain, for the assessment of potential adverse effects of NMs on human

The specific objectives of NanoSolveIT were to:

1.Collect curate, harmonize and integrate existing and emerging data on NMs characterization, release, exposure and biological/toxicological effects on human health and the environment;
2.Deliver targeted datasets to gap-fill incomplete datasets and models;
3.Develop validated and robust in silico methodologies for prediction of NM toxicity from biological descriptors and using Adverse Outcome Pathways, and for evaluation of quantitative characteristics of the bionano interface via coupled materials models at different scales;
4. Implement the concept of NM fingerprints, a set of nanodescriptors (physicochemical, omics, and computational)that can be used to predict NM release, exposure and hazard, and thus overall risk;
5. Develop and apply innovative nanoinformatics methods that are less reliant on animal testing;
6. Establish the NanoSolveIT IATA ( as a sustainable multi-scale modelling framework for predicting NMs risk, benchmark it via Round Robin testing and experimental validation, and demonstrate its utility at TRL6 via OECD IATA case studies;
7. Integrate the developed nanoinformatics tools into the NanoSolveIT e-platform.
NanoSolveIT has had a very successful third period, delivering high-quality outcomes and insights. Extensive cross-WP and cross-project collaboration took place, including with NanoCommons, RiskGONE, NanoInformaTIX, and the Marie Curie RISE project CompSafeNano (coordinated by NovaMechanics also). CompsafeNano was designed to reuse and integrate outcomes across NanoSolveIT, RiskGONE, and NanoCommons, and to align their e-tools and cloud platform. NanoSolveIT partners have generated more than 50 models for predicting the properties and behaviour of NMs in various environments. The produced models have been provided as user-friendly interfaces, via the NanoSolveIT Cloud platform, and disseminated to key stakeholders, i.e. industry, regulators, scientists, for exposure, hazard and risk assessment of NMs and safe and sustainable by design strategies. These tools are also integrated into the overall IATA toolbox. The delivered version of the IATA allows the determination of NMs lung exposure, translocation, biodistribution and potential toxicity to the exposed tissue. A complete overview is provided at the dedicated services page of the NanoSolveIT Cloud platform: https://cloud.nanosolveit.eu/services/.

The NanoSolveIT consortium made the overwhelming majority of data produced and project deliverables openly and publicly available for reuse and exploitation by stakeholders, via the NanoSolveIT Knowledge Base (https://ssl.biomax.de/nanosolveit/cgi/login_bioxm_portal.cgi) in a ready-for-modelling format in the NanoPharos database (https://db.nanopharos.eu/) and via Zenodo (https://zenodo.org/communities/nanosolveit/). NanoSolveIT is actively promoting Open Data from publicly funded research and contributing to data-driven innovation and the expansion of the digital single market.

NanoSolveIT partners have lproduced >100 peer-reviewed publications and editorials to date (https://nanosolveit.eu/resources/library/) 35 in the final reporting period. Many are in advanced stages of preparation and will maintain increase impact and visibility of the project and its outputs in the long term. Almost all publications are gold open access, with others made available via the green open access route, in accordance with the Open Data requirements.
NanoSolveIT has demonstrated the potential for removing barriers from nanosafety-related regulatory and industrial processes by revolutionising modelling across scales and model types, integrating multi-scale physics-based and data-driven (AI) approaches, offering a more comprehensive understanding of NMs behaviour and effects. NanoSolveIT has also demonstrated the potential of advanced modelling approaches for improving the safety and sustainability of nanotechnology and NMs, creating a “roadmap” of best practices in integrating diverse modelling techniques.

NanoSolveIT contains an extensive breadth of sophisticated integrated models ranging from NM-biomolecule and cell interactions, models for omics analysis and AOP generation, release and exposure models, toxicokinetics and PBPK, and ecotoxicity prediction models. All of the models are delivered as publicly available and user-friendly webtools within a benchmarked IATA for nanosafety assessment, to enable safe-by-design NM development and NM Risk Governance. Demonstration of the IATA functionality via case studies (aligned to the OECD IATA case studies approach), and benchmarking of the approaches utility to address specific Safe-by-design and regulatory questions, maximise uptake and implementation by industry and regulatory stakeholders.

By advancing nanomaterial safety knowledge, NanoSolveIT’s outcomes have contributed towards improved NMs safety and regulatory standards. Furthermore, this acquired knowledge and the produced data can drive EU data-driven innovation, increase industrial confidence in nanotechnology, lead to better protection of public health and the environment, and remove regulatory barriers to commercialisation of NMs and nano-enabled products leading to higher investment and positive socio-economic impact from publicly funded research. The NanoSolveIT results and insights can be used as part of the ongoing discussions on the ethical and sustainable use of nanotechnology and its societal acceptance. NanoSolveIT has been actively disseminating its results not only through peer-reviewed publications but through press releases, editorials, and articles in online scientific news media, as well as through its mobile apps (for iOS https://apps.apple.com/pl/app/nanosolveit-cloud-platform/id6451151044 and android https://play.google.com/store/apps/details?id=com.novamechanics.NanoSolveIT_Cloud_Platform&pli=1) to reach the widest possible audience.
Figure 2: Schematic representation of the NanoSolveIT Integrated Approach for Testing and Assessment
Figure 5: NanoSolveIT’s deep learning model for assessment of the chronic and multi-generational to
Figure 1: NanoSolveIT project logo
Figure 3: NanoSolveIT consortium partners
Figure 4: NanoSolveIT positioning vis-à-vis other ongoing activities and efforts in nanoinformatics