The field of toxicology is evolving from purely descriptive to a highly data‐rich science. To structure this large amount of data and in this way make the usage more effective for the safety assessors, the concept of adverse outcome pathways was established providing a means of understanding how chemicals induce adverse effects through their toxicity pathways and modes of action. However, there are some doubts if the one initiating event - one adverse outcome relationship enforced on AOPs by the OECD guideline is able to cover more complex adverse effects like hepatocellular carcinoma resulting from non-mutagenic chemical exposure. Therefore, the ADVaNCE project will demonstrate based on the just mentioned example that combining all existing knowledge into an adverse outcome network formed by interlinked AOPs is needed to cover all the pathways and intervention points activated in order to contribute to the development of hepatocellular carcinomas. Computational approaches will be used to extract important key events and their relationships from existing data sources and the relevant literature. These will be compared with existing AOPs and further experimental validation will be started. The computational and experimental result will finally guide the development of an integrated testing strategy completely based on in silico and in vitro data, which development and validation regarding regulatory usage will be continued after the project.

Toxicology and risk assessment are undergoing a paradigm shift, from a phenomenological to a mechanistic discipline based on in vitro and in silico approaches that represent an important alternative to classical animal testing applied to the evaluation of chronic and systemic toxicity risks. Large databases and highly sophisticated methods, algorithms and tools are available for different tasks such as hazard prediction, toxicokinetics, and in vitro – in vivo extrapolations to support this transition. However, since these services are developed independently and provided by different groups world-wide, there is no standardized way how to access the data or run modelling workflows. To overcome the fragmentation of data and tools, OpenRiskNet will provide open e-Infrastructure resources and services to a variety of communities requiring chemical risk assessment, including chemicals, cosmetic ingredients, therapeutic agents, and nanomaterials. OpenRiskNet will combine the achievements from earlier projects for generating modeling and validation workflows, knowledge integration and data management as well as include all ongoing projects and important stakeholders through an associated partner programme. The main components of the infrastructure will be an interoperability layer added to every service to describe the functionality and guaranteeing technical and semantic interoperability, a discovery service, deployment options based on container technology, and packaging of the infrastructure into virtual instances. This will be complemented by training and support on integration of specific services based on prototype implementation, usage of standard file formats for data sharing including the generation of templates for data and metadata, as well as the harmonized usage of ontologies. Case studies will demonstrate the applicability of the infrastructure in productive settings supporting research and innovation in safer product design and risk assessment.

All chemicals whether they are drugs, cosmetics, agrochemicals or others need to be tested for their safety to man and the environment. The use of whole animal studies for the prediction of adverse effects in man, is problematic due to species dependent effects, high costs and a large burden to animals in terms of numbers and suffering. While there have been major improvements in human in vitro and in silico techniques, there is still a lack of an integrated risk assessment platform. The in3 proposal aims to significantly further the development of animal-free chemical and nanomaterial (NM) safety evaluation by creating a scientific and training program aimed at integrating human in vitro testing with computational approaches. The project will focus on human induced pluripotent stem cells (hiPSC) derived tissues, including liver, kidney, brain, lung and vasculature and to utilise mechanistic toxicology, quantitative adverse outcome pathways, biokinetics, cheminformatics and modelling approaches to derive testable prediction models. hiPSC present the major advantages provide non-cancerous derived tissues with identical genetic backgrounds. All Early Stage Researchers (ESRs) will work towards the same goal, utilising the same chemicals, donor cells, assays and software packages. All data will be centrally housed in standardised formats, appropriately annotated and linked with protocols and material information. While ESRs will hone their skills in their own field of expertise, they will also collaborate to create an in depth safety evaluation testing platform for the chosen test compounds. By interaction, problem solving, training and secondments over the three years, they will acquire a unique set of interdisciplinary skills for chemical and NM safety assessment. The project aims to accelerate the realisation of animal-free safety assessment and to graduate 15 PhD students with the ideal skill sets to carry out the strategy designed in in3 in the near future.

The unique properties of nanomaterials (NMs), relative to their bulk form, has seen them used in a rapidly increasing number of commercial applications. However, with these useful new properties of NMs come potential health and environmental hazards. Thus, as part of a responsible innovation approach, NMs potential risks must be assessed in parallel to exploitation of their benefits. Due to their enormous variability, NM risk assessment urgently needs advanced in silico methodologies capable of machine learning from limited experimental datasets. These in silico tools for NMs characterisation, exposure, hazard and risk assessment and sustainability and life cycle assessment, need to support implementation of existing regulatory guidelines and extend regulatory risk assessment to integrate the extensive new knowledge generated computationally. CompSafeNano’s overarching objective is thus to drive the development of integrated and universally applicable nanoinformatics models, with broad domains of applicability across NMs compositions and forms, that are directly usable by industry, especially SMEs, and regulators for NMs risk assessment and decision making. CompSafeNano will establish an extended safe-by-design paradigm that includes environmental sustainability (life cycle assessment) based on in silico predictions with experimental testing to validate the results. CompSafeNano has a clear set of objectives to deliver this vision of an in silico safe-by-design computational platform and will be in close communication with other EU projects to access existing data on NM hazard and integrate existing nanoinformatics and NMs risk governance platforms (i.e. within NanoCommons, NanoSolveIT & RiskGONE). Training activities will benefit both ESRs and ERs from participating organizations, with a strong focus on inter-sectoral exchange (SME-academia) and international collaboration, filling the well-recognised current skills gap in nanoinformatics and big data analytics.

Nanotechnologies and the resulting novel and emerging materials (NEMs) represent major areas of investment and growth for the European economy. Recent advances have enabled confidence in the understanding of what constitutes toxicity of NEMs in relation to health and environmental hazards. However, the nanotechnology and nanosafety communities remain disparate and unconnected, whilst knowledge and data remain fragmented and inaccessible, such that from a data integrating and mining perspective it is clearly a “starting community”. The field, and indeed the European open knowledge economy, requires conversion of these scientific discoveries into legislative frameworks and industrial applications, which can only be achieved through concerted efforts to integrate, consolidate, annotate and facilitate access to the disparate datasets. NanoCommons brings together academia, industry and regulators to facilitate pooling and harmonising of methods and data for modelling, safe-by-design product development and regulatory approval purposes, thereby driving best practice and ensuring maximum access to data and tools. Networking Activities span community needs assessment through development of demonstration case studies (e.g. exemplar regulatory dossiers). Joint Research Activities will integrate existing resources and organise efficient curation, preservation and facilitate access to data/models. Transnational Access will focus on standardisation of data generation workflows across the disparate communities and establishment of a common access procedure for transnational and/or virtual access to the data, and modelling and risk prediction/management tools developed and integrated. Given the extremely rapid pace of development of nanoinformatics, NanoCommons’s detailed workplan will be prescribed for the first 18 months, beyond which it will be co-developed with stakeholders on a rolling call basis to ensure maximum responsiveness to community needs.