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.

Five leading European supercomputing centres are committed to develop, within their respective national programs and service portfolios, a set of services that will be federated across a consortium. The work will be undertaken by the following supercomputing centres, which form the High Performance Analytics and Computing (HPAC) Platform of the Human Brain Project (HBP): ▪ Barcelona Supercomputing Centre (BSC) in Spain, ▪ The Italian supercomputing centre CINECA, ▪ The Swiss National Supercomputing Centre CSCS, ▪ The Jülich Supercomputing Centre in Germany, and ▪ Commissariat à l'énergie atomique et aux énergies alternatives (CEA), France (joining in April 2018). The new consortium will be called Fenix and it aims at providing scalable compute and data services in a federated manner. The neuroscience community is of particular interest in this context and the HBP represents a prioritised driver for the Fenix infrastructure design and implementation. The Interactive Computing E-Infrastructure for the HBP (ICEI) project will realise key elements of this Fenix infrastructure that are targeted to meet the needs of the neuroscience community. The participating sites plan for cloud-like services that are compatible with the work cultures of scientific computing and data science. Specifically, this entails developing interactive supercomputing capabilities on the available extreme computing and data systems. Key features of the ICEI infrastructure are: ▪ Scalable compute resources; ▪ A federated data infrastructure; and ▪ Interactive Compute Services providing access to the federated data infrastructure as well as elastic access to the scalable compute resources. The ICEI e-infrastructure will be realised through a coordinated procurement of equipment and R&D services. Furthermore, significant additional parts of the infrastructure and R&D services will be realised within the ICEI project through in-kind contributions from the participating supercomputing centres.

Melanoma cases and deaths are expected to increase in the coming years, representing a significant burden for the European economy and healthcare system. Metastatic melanoma (MM) is the most serious form of skin cancer and is characterised by uncontrolled metastatic spread of melanocytes to distant sites. Although standard treatments exist, significant clinical challenges remain, resulting in limited response and high MM recurrence rates. As a result of these limited treatment options, the quality of life of MM patients is dramatically compromised. Emerging immunotherapies, such as adoptive cell therapy (ACT), are promising but have significant obstacles, including long manufacturing times, high costs and, most critically, rapid exhaustion of infused cells due to the tumour immune microenvironment (TIME). Research in Gottfried Baier's lab has identified a unique way to effectively stimulate the immune system with an ACT by inhibiting NR2F6, an intrinsic immune checkpoint of T lymphocytes. This is done through our NR2F6 blockade-based adoptive immune cell therapy for metastatic melanoma (NR2F6-AIM) approach, where T cells are engineered for enhanced immune fitness prior to infusion. This greatly sensitises the patient's immune system to currently available immune checkpoint inhibitor therapy (ICT). This approach will permit us to deliver a combinatorial treatment that can overcome TIME immunosuppression, providing curative potential against MM. NR2F6-AIM will block NR2F6 by a non-viral, time-boxed gene silencing through a synthetic small interfering RNA (siRNA) transfection method. This method will allow us to overcome therapeutic manufacturing hurdles through a one-day in-hospital preparation of the ACT. NR2F6-AIM will verify and optimise the technology in relevant in vivo and ex vivo study models to validate the potential of this innovative ACT. It will also develop and execute an IP strategy and a commercial feasibility analysis to enter the MM market.

This proposal unites researchers from Canada, Europe, Island Southeast Asia and Oceania to re-evaluate our understanding of the Austronesian expansion. It does so using new high-density data from archaeology, biological anthropology, linguistics and genetics, and aims to unite them within a common statistical framework. OCSEAN achieves a true synthesis of disciplines using state-of-the-art computational and statistical methods to interrogate the structural relationship between joint data sets. The research contextualizes the expansion of the Austronesian language family within the growing evidence for social and political complexity across Island Southeast Asia and coastal mainland regions prior to the arrival of rice and millet agriculture to Taiwan during the mid 5th millennium BP. It also takes into account the rich history of interaction since the spread of the Malayo-Polynesian branch of Austronesian outside of Taiwan. OCSEAN brings together leading researchers from the humanities and sciences and combines the resources of multiple laboratories to tackle questions that can only be addressed with this extensive network of cooperation. We will embrace the complexities of the archaeological, genetic and linguistic records, providing an alternative to directional, progressive and technological deterministic models, whilst recognizing the difficulties inherent in identifying concepts of culture or ethnicity with archaeological evidence, because of the very fluidity of these constructs. Through our combined expertise, we will demonstrate that a new way of working with big data leads to new insights at the small scale. In doing so, it will fundamentally change the way people do research.