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.
