The SABYDOMA programme addresses developments in the safety by design (SbD) paradigm by examining four industrial case studies in detail where the TRLs will advance from 4 to 6. Each TRL activity will progress from being lab based at TRL4 to being industry based at TRL6. The TRL4 activity will involve only innovation with regular industrial communication whereas the TRL6 activity will involve industrially located activities with innovation communication. One of the novel themes of this study is to use system control and optimisation theory including the Model Predictive Control (MPC) philosophy to bind the whole subject of SbD from laboratory innovation to the industrial production line and from decision making processes to project governance. An equally important innovative step is the building of high throughput online platforms where nanomaterial (NM) is manufactured and screened at the point of production. The screening signal controls the NM redesign and production in a feedback loop. Screens will involve (a) physiochemical sensing elements (b) in-vitro targets of increasing complexity from the 2D biomembrane to cell-line and more complex cell-line elements; and, (c) multiple in-vitro targets with multiple end-points; developed in current H2020 projects. Two of the industrial studies include composite coating manufacture where the coating’s stability and toxicity will be tested using a flow through microfluidic flow cell system coupled to online screens. This is part of the release and ageing investigations on the NM and NM coatings and the results of these will feed back to the production line design. At every step on the TRL ladder the in-silico modelling will be applied to optimise and redefine the relevant activities. By the same token regulatory and governance principles of SbD will be used to refine the technological development. The final deliverable will be four distinct technologies applying SbD to the four industrial processes respectively.

The objective of the caLIBRAte project is to establish a state-of-the-art versatile Risk Governance framework for assessment and management of human and environmental risks of MN and MN-enabled products. The framework will be a web-based “system-of-systems” linking different models and methods for: 1) screening of apparent and perceived risks and trends in nanotechnology, 2) control banding, qualitative and fully integrated predictive quantitative risk assessment operational at different information levels, 3) safety-by-design and multi-criteria decision support methods, 4) risk surveillance, -management and -guidance documents. The risk management framework will support assessments of emerging and existing MN and MN-enabled products following the recent ISO31000 risk governance framework, as well as safety in innovation by matching models to the principle innovation steps in the “Cooper Stage-Gate®” product innovation model Control banding tools and quantitative models will be subject to sensitivity analysis and performance testing followed by a revision as needed. After revision the models will again be analyzed by sensitivity testing, calibration, performance tested to establish the uncertainties. After calibration, the models will be part of the framework, which will be demonstrated by case studies. Stakeholders will be involved for defining the user requirements of the framework and will receive training in the framework at the end. The caLIBRAte project proposal answers to the call of NMP30-2015: Next generation tools for risk governance of MNs. The project is specifically designed to address the key challenges defined in the scope of the call text. There is particular focus on model revision, calibration and demonstration of existing models and methods that support the risk governance framework in regards to safe innovation and already implemented nanomaterials. Next generation computational exposure assessment and -toxicology is anticipated in the framework

Next generation nanomaterials are a challenge for the established risk assessment and management paradigm. The regulatory frameworks have just been modified to address risk assessment of primary nanomaterials with simple coatings and are currently in the first phase of implementing methods and tools adequate for simple nanomaterials. Next generation nanomaterials and products thereof, are multiconstuent materials which exhibit much more complex behaviour, potentially including mixture toxicology. The morphologies and stoichiometry of next generation advanced nanomaterials are not harmless, as designs including high aspect ratio shapes and heavy metal content are abundant. By elucidating the role of nanostructures, their transformation and initiation of adverse outcome pathways, HARMLESS will provide novel tools, guidance and decision support for balancing functionality versus risk to ensure that the next generation nanomaterials will be harmless.

NanoSolveIT will introduce a ground-breaking in silico Integrated Approach to Testing and Assessment (IATA) for the environmental health and safety of Nanomaterials (NM), implemented as a decision support system packaged as a standalone open software and 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 and state-of-the-art in silico techniques, and, (iv) integration with multi-scale modelling, RA and governance frameworks developed in EU H2020 funded and 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 IATA case studies, serving 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. NanoSolveIT is fully aligned to the objectives of the EU-US Nanoinformactics Roadmap, addressing all 13 of its short, medium and long term milestones, and supports the recommendations of the EMMC on standards for developing material modelling software and OECD best practice. The NanoSolveIT consortium (EU and international partners) is the only grouping capable of delivering the ambitious goals of the NMBP-14-2018 call, since they have collectively driven most of the current progress in nanoinformatics: 81% of the nanoinormatics papers cited in the EU-US nanoinformatics roadmap had NanoSolveIT authors. NanoSolveIT will integrate across the consortium-wide modelling approaches to provide the IATA platform for in silico NMs RA.

The goal of PrecisionTox is to advance safety assessment of chemicals without the use of animal testing by establishing a new, 3Rs-compliant, cost-effective testing paradigm for chemical safety assessment — Precision Toxicology — that identifies molecular key event (KE) biomarkers predictive of chemically induced adverse health effects in humans and facilitates their uptake into regulatory and industry practice. This goal is supported by three core concepts: PhyloToxicology, which replaces mammal models with an evolutionarily diverse suite of non-sentient animal species from across the tree of life; Quantitative Susceptibility, which determines safety factors based on genetic variability; and Embedded Translation, which engages key stakeholders in project planning, selection of chemicals for investigation, and case studies for regulatory application. We accomplish this goal through six objectives: ● Stakeholder Integration, embedding the Stakeholder Advisory Group in project management (WP1); ● Comparative Toxicology, utilising high-throughput testing methods across five non-sentient species and human cell lines to observe toxic response (WP2); ● Molecular Data Production, applying metabolomics and transcriptomics to comparative toxicology samples to trace adverse outcomes via the molecular key events preceding them (WP3); ● Quantitative Susceptibility, applying quantitative genetics and gene expression profiling to understand variation in individual susceptibility and develop empirical exposure thresholds (WP4); ● Biomarker Discovery, PrecisionTox Data Commons, and NAM Toolbox, using machine learning to identify biomarkers for molecular key events and creating the dissemination and translation products for their use (WP5); and ● Regulatory Analysis and Application, partnering with JRC and regulatory agencies to identify opportunities for applying Precision Toxicology within existing regulatory structures and develop draft guidance for industry use and reporting (WP6).