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

Période du rapport: 2020-09-01 au 2022-02-28

Nanotechnology is a key enabling technology (KET), capable of delivering a wide range of technological breakthroughs, through the production of a multitude of novel and emerging engineered and manufactured nanomaterials (NMs) whose unique features serve numerous applications across all EU priority sectors. Although numerous benefits of NMs have been identified over the years, concerns are also arising as risk assessment is lagging behind product development, mainly because current approaches to assessing exposure, hazard and risk are expensive and time-consuming, and frequently involve testing in animal models.
To overcome these challenges, NanoSolveIT (Figure 1) aspires to introduce a ground-breaking in silico Integrated Approach to Testing and Assessment (IATA) for the environmental health and safety of NMs, implemented through a decision support system packaged as both a stand-alone open software and via a Cloud platform (Figure 2). To achieve this, NanoSolveIT partners (Figure 3) have a clear plan of model development, model integration, model testing and validation via case studies, and provision of user friendly graphical user interfaces and training documentation to support implementation of the IATA and its uptake and application by industry and regulators (Figure 4). The ultimate outcome will be a validated, sustainable, multi-scale nanoinformatics IATA, tested and demonstrated at TLR6 via OECD-style case studies, to serve the needs of stakeholders at each stage of the NM value chain, for the assessment of potential adverse effects of NMs on human health and the environment.
The specific objectives of NanoSolveIT are thus 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 to ensure its exploitation for in silico nanosafety assessment;
2. Deliver targeted datasets to gap-fill incomplete datasets and models;
3. Develop validated and robust in silico methodologies for prediction (https://cloud.nanosolveit.eu/services/qsars/) of NM toxicity from biological descriptors and for AOP-based models, 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) and properties that can be predictively linked to NM release/exposure (https://cloud.nanosolveit.eu/services/exposure-models/) and hazard, and thus overall risk;
5. Develop and apply innovative nanoinformatics methods less reliant on animal testing;
6. Establish the NanoSolveIT IATA (https://cloud.nanosolveit.eu/services/iatas/) as a sustainable multi-scale modelling framework for predictive NMs RA, benchmark it via Round Robin testing and experimental validation, and demonstrate its utility at Technology Readiness Level 6 via OECD IATA case studies, illustrating time/cost efficiency and reduced need for animal studies;
7. Integrate the developed nanoinformatics tools into the NanoSolveIT e-platform (https://cloud.nanosolveit.eu/)
NanoSolveIT has had a very successful second period, with all partners engaging and integrating very well, leading to extensive cross-WP collaboration and cross-project collaboration, especially with the research infrastructure project, NanoCommons, the risk governance project, RiskGONE, our sister nanoinformatics project, NanoInformaTIX, and the Marie Curie RISE project CompSafeNano (which was designed to integrate across NanoSolveIT, RiskGONE and NanoCommons) and align and supplement their e-tools and cloud platform (CompSafeNano is coordinated by NovaMechanics also).
During the second period NanoSolveIT partners have generated 19 new models (total 30 models), provided user-friendly interfaces for all the models as a key step towards their integration into the overall IATA and cloud platform, and worked extensively on the specifications for the cloud platform. A complete overview is provided at the dedicated services page of the NanoSolveIT Cloud platform https://cloud.nanosolveit.eu/services/

NanoSolveIT partners have led or contributed to 53 peer-reviewed publications and editorials to date (https://nanosolveit.eu/resources/library/) of which 38 were published within this reporting period, and many more in advanced stages of preparation, leading to a high visibility of the project and its outputs. Almost all of these publications are in gold open access, with any others deposited in the relevant institutional repository and made available via the green open access route, in accordance with the Open Data pilot. All datasets underpinning the models are being assigned DOIs via UoB’s DataCite partnership, or Zenodo, and are available through the NanoSolveIT KnowledgeBase (https://ssl.biomax.de/nanosolveit/) and in modelling-ready format via the nanoPharos database (https://db.nanopharos.eu/Queries/Datasets.zul).
NanoSolveIT has the unique potential to deliver a step-changing impact for the emerging nanoinformatics in nanosafety community. It will remove 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. NanoSolveIT will contain an extensive breadth of 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, all delivered within a benchmarked IATA for nanosafety assessment, to enable safe-by-design NM development and NMs Risk Governance. Demonstration of the 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 will maximise uptake and implementation by industry and regulatory stakeholders.
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