The connectome is a map of all neural connections in the brain that can provide information about the brain’s (re)wiring in neurological diseases, injuries, or drugs responses. The use of connectomes in clinical practice has enormous potential to improve treatment efficacy, enhance patient stratification, disease characterization, and ultimately diagnosis. However, the means to clinically utilize connectomes are limited. Therefore neurologists still rely on subjective analysis of brain scans. Although the use of big data tools in neuro-diagnostics is growing, no commercial application for clinical practice is available yet. Biomax developed the first commercial solution to translate big connectome data into clinically relevant information: NeuroXM. In combination with patients’ clinical data this can be valorized to improve neuro-diagnosis. NeuroXM has successfully undergone pilot studies at two major institutes. The proprietary NeuroXM platform includes all features and security levels that are required in the clinic. Biomax is a strong bioinformatic SME with 20 years’ experience, including >25 European grants, 5 successful bioinformatic products, and a pioneering reputation. NeuroXM targets a very large and diverse neurology market with multiple clinical applications, e.g. diagnosis of dementia using brain imaging, detecting brain wiring “disconnections” in schizophrenia, and establishing treatment efficacy (longitudinal assessments of the connectome). This SME Phase 1 project will assess the feasibility of these different applications, which will help Biomax to establish a Go/No-go for further clinical validation for the specific clinical applications. With a strong first mover advantage and freedom to operate, NeuroXM has the potential to become the gold standard for working with connectome data. Commercialization of NeuroXM will provide Biomax a cumulative revenue of €47,4 million (2025) and further company growth.

The toxicological impact of exposure to chemical mixtures is a matter of undisputed concern, but mixtures are only slowly making their way into regulatory risk assessment. Critical knowledge gaps are which and how many chemicals drive mixture effects in the environment and in humans. Scientific uncertainty remains on the validity of the dose addition principle for complex mixtures of large numbers of chemicals at low concentrations as they occur in our bodies. The PANORAMIX consortium addresses these challenges by showcasing a novel experimental path based on whole mixture assessments for identifying and quantifying the risk of chemical mixtures extracted from real-life samples representing environment and food as well as humans. We provide ready-to-use and practical tools for mixture risk assessment of several chemicals with a diverse range of adverse health outcomes. The applied methodologies, including a panel of in vitro assays coupled with effect-directed analyses and large-scale suspect and non-targeted chemical profiling are innovative in their combinatorial approach. Specifically, we will take advantage of a well-studied human cohort of new-borns, in whom adverse health outcomes related to developmental toxicity originating from chemical mixture exposure will be identified. PANORAMIX will use mixture modelling, case studies and experimental data to deliver a web-based interface for calculating risks to chemical mixtures and to define effect-based trigger values for in vitro effects that can be directly measured in water, food, and blood to identify when mixture exposure is posing a health threat. By involving regulatory and scientific stakeholders throughout the project, we support the implementation of existing mixture risk assessment and management approaches to reduce the most critical exposures and assist in optimizing regulatory approaches to yield evidence-based policies, contributing to EU's zero-pollution ambition for a toxic free environment in the future.

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.

The last of four multi-year work plans will take the HBP to the end of its original incarnation as an EU Future and Emerging Technology Flagship. The plan is that the end of the Flagship will see the start of a new, enduring European scientific research infrastructure, EBRAINS, hopefully on the European Strategy Forum on Research Infrastructures (ESFRI) roadmap. The SGA3 work plan builds on the strong scientific foundations laid in the preceding phases, makes structural adaptations to profit from lessons learned along the way (e.g. transforming the previous Subprojects and Co-Design Projects into fewer, stronger, well-integrated Work Packages) and introduces new participants, with additional capabilities. The SGA3 work plan is built around improved integration and a sharpening of focus, to ensure a strong HBP legacy at the end of this last SGA. In previous phases, the HBP laid the foundation for empowering empirical and theoretical neuroscience to approaching the different spatial and temporal scales using state-of-the-art neuroinformatics, simulation, neuromorphic computing, neurorobotics, as well as high-performance analytics and computing. While these disciplines have been evolving for some years, we now see a convergence in this field and a dramatic speeding-up of progress. Data is driving a scientific revolution that relies heavily on computing to analyse data and to provide the results to the research community. Only with strong computer support, is it possible to translate information into knowledge, into a deeper understanding of brain organisation and diseases, and into technological innovation. In this respect, the underlying Fenix HPC and data e-infrastructure, co-designed with the HBP, will be key. The services offered by EBRAINS will be grouped in six Service Categories: SC1: Curated and shared data: EBRAINS FAIR data services - neuroscience data publishing SC2: Brain atlas services: navigate the brain in 3D - find, contribute and analyse brain data, based on location SC3: Brain modelling and simulation workflows: integrated tools to create and investigate models of the brain SC4: Closed loop AI and robotics workflows: design, test and implement robotic and AI solutions SC5: Medical Data Analytics SC6: Interactive workflows on HPC or NMC: Europe-wide access to scalable and interactive compute services Their users are to be supported with High-Level Support Teams and Vouchers, as well as Engagement and Facility Hubs located around Europe, at which additional services, unique equipment and compute infrastructure will be offered by local HBP Partners. Significant outcomes in relevant scientific communities are expected to materialise rapidly. Association with new Partnering Projects is still sought, along with wider international cooperation. The SGA3 objectives can be summarised as: 1) Establish a sustainable European scientific research infrastructure, EBRAINS, leading to an increased use and adoption of FAIR data, web-based analyses, model building, simulation, atlasing, and virtual experiments for brain research and brain-inspired sciences. 2) Provide a multi-level atlas of the human brain - the first of its kind that links microstructural detail and inter-subject variability. 3) Increase the capacity of neuroscientists for multiscale neural activity modelling of the human brain network. 4) Increase the availability of integrated multiscale data and computational models supporting brain states transitions, network complexity and cognitive functions. 5) Enhance real-world task performance through biologically plausible adaptive cognitive architectures running on neuromorphic hardware and a closed-loop Neurorobotics Platform. 6) Ensure that neuroscientific insights at the interface of neuro-inspired computing and technology are being translated into a benefit for patients with brain diseases. 7) Ensure an ethically and legally compliant infrastructure and promote embedding of Responsible Research and Innovation, a

TranSYS will recruit 15 ESRs to highly skilled jobs in the new area of Systems Health developing tools and approaches to exploit large and complex datasets, to advance Precision (Personalised) Medicine in several disease areas. The training programme and experience of different international research environments cuts across traditional data and life sciences silos. The emphasis on translational research will support new collaborations between academics and the pharma and health analytics sectors. Our ESR projects will advance the state of the art on biomarker discovery, improve understanding of disease-specific molecular mechanism and target identification for optimal diagnostics, disease risk and treatment management, refine data generation and their management (including warehousing, disease specific and standardised approaches for data processing, visualisation and model development) leading to improved clinical study design, clinical sampling and more targeted therapeutics. This ETN will internationalise participants, and leverage EC and industry sponsorship, to structure and expand the unique training programme and advance emerging research areas, combining wet-lab, clinical and Big Data resources with computational and modelling know-how. To achieve a paradigm shift in research training this ETN brings together international leaders in Preclinical Science & Molecular Medicine, Systems Analytics, and Targeted Therapeutics, from academia and industry. These experts are ideally positioned to develop the proposed training programme and deliver a highly-trained workforce of next generation scientists, with the right mind-set, knowledge and skills, at the interface of Translational and Systems Medicine. The TranSYS training programme is designed to address a critical skills gap that is currently a bottle neck to advancing Precision Medicine.