Myasthenia Gravis (MG) is a prototypic autoimmune disease causing muscle weakness and fatigability, mostly treated by chronic immunosuppressive (IS) therapy. MG clinical heterogeneity, fluctuating symptoms with unpredictable disease course, and inter-individual variation in response to treatments, including conventional IS and the emerging biological drugs, highlight the need to adopt safe, predictive and preventive personalised medicine (PM) strategies, still lacking in MG. The MG-PerMed project will employ an interdisciplinary approach, combining pre-clinical, clinical, artificial intelligence (AI) and bioethic research, to achieve PM for MG. Pharmacogenetic, pharmaco-miR and serological biomarkers associated with clinical features and response to therapies will be validated in three different MG populations (Italian, French and Israeli). Integration of biological and real-world clinical data by AI will lead to the development of a clinical decision support tool (MG-CDST), to guide clinicians in the choice of the best therapeutic program for individual patients/patient subgroups, enabling both early prediction of the optimal therapy and on-treatment disease monitoring to prevent MG symptom worsening and crisis. For the first time, a MG-CDST-based PM approach will be prospectively validated. The project outcomes promise to significantly change the MG treatment flow-chart, shifting from the “one-fits-all” approach to personalised care. MG-CDST adoption into the clinical practice should prospectively lead to: treatment failure prevention, prevention of IS drug-related adverse events, prevention of disease exacerbations, and in turn an improved MG patient compliance to treatment and a better quality of life. MG-dedicated Apps will allow patient/caregiver involvement in therapeutic decisions. Data dissemination will promote PM adoption in consensus guidelines for MG, and potentially other autoimmune diseases in which current treatment is chronic immunosuppression.

Topological quantum computing (TQC) is an emerging field with strong benefits for prospective applications, since it provides an elegant way around decoherence. The theory of TQC progressed very rapidly during the last decade from various qubit realizations to scalable computational protocols. However, experimental realization of these concepts lags behind. Important experimental milestones have been achieved recently, by demonstrating the first signatures of Majorana states which are the simplest non-Abelian anyons. However, to realize fully topologically protected universal quantum computation, more exotic anyons, such as parafermions are required. Thus, the unambiguous demonstration of parafermion states will have a great impact on the development of universal quantum computation. The experimental realization of parafermions is challenging, since they are based on the combination of various ingredients, such as crossed Andreev reflection, electron-electron or spin-orbit interaction, and high quality quantum conductors. Thus, the investigation of all these ingredients is essential and timely to achieve further experimental progress. The team of SuperTop is composed of six leading groups with strong and complementary experimental background in these areas with the aim to realize parafermions in double nanowire-based hybrid devices (DNW) for the first time. The main objectives of SuperTop are: a) development of different DNW geometries, which consist of two parallel 1D spin-orbit nanowires coupled by a thin superconductor stripe and b) investigation of the emerging exotic bound states at the superconductor/semiconductor interface of the DNW. SuperTop first grows state-of-the-art InAs and InSb based nanostructures, in particular InAs nanowires (NWs) with in-situ grown epitaxial superconducting layer, NWs with built-in InP barriers and InSb nanoflakes. Based on these high quality materials, different device geometries of DNW are fabricated and the emerging novel states are investigated. The topological character, quantum phase transition, coherence time, coupling strength to QED as key features of the engineered new states are planned to be addressed by various cutting-edge low temperature measurement techniques (e.g. non-local spectroscopy, noise, current-phase relationship measurement or integration into coplanar resonators). The experimental team of SuperTop is supported by in-house theoretical experts of TQC, who will contribute to the interpretation of the results and development of technologically feasible topologically protected quantum architectures. The research project of SuperTop is strongly linked to various targeted outcomes of the QuantERA call (see the related outcomes in ). Our advanced multidisciplinary work aims to engineer the central building block of a new architecture of quantum computation , so called parafermions. In order to do so, SuperTop investigates novel superconductor/semiconductor hybrid devices to realize engineered topologically protected quantum systems. . Thereby our activity will contribute to develop novel ideas in quantum science , which could lead to built-in protection of quantum information as a radically enhanced functionality. The expected topological protection will be a game changer and will help to realize universal quantum computing, which is one of the pillars of the EU Quantum Manifesto.

AMERISKA: Analysis of Multivariate Extremes and RISKs Assessment. An international research network on food and environmental risks assessment. The project AMERISKA aims at encouraging interactions of people of different backgrounds and from different countries to assess risks of different kinds. In particular, the project focuses on the assessment of risks in the contexts of food, hydrology and climatology which are major issues of concern for society. • Food risks assessments: The use of chemical products and the degradation of the natural environment are responsible for the presence of contaminants in food usually accumulated by human body. The degree of toxicity of the products and the consequences for human health require better stochastic modeling of the accumulation process. • Environmental risks assessments: modeling accurately the spatio-temporal structures of some atmospheric extreme variables like heavy rainfall, storms, still remains a statistical challenge. This is due to the complex multivariate structure within and between rare events. Inferring in space and time will be at the core of this environmental applications. To assess the aforementioned risks, a careful use of statistics is required. One major difficulty is that extremal events are often not well modeled due to the lack of observations. It is a major challenge for applied mathematicians to understand heavy tail phenomena observed. In particular, it appears that the importance of the events requires a global point of view, involving many researchers form different disciplines. It seems possible to use more information on extremal events because of the emergence of bigger mass of data. A major problem is to deal with the interaction (dependence) of extremes which necessarily leads to a multivariate context. Suitable mathematical tools have been developed only recently: multivariate regular variation processes are suitable new concepts for dealing with extremes and dependence in space and time. The literature on stochastic models for spatio-temporal extremal phenomena is still rather sparse. Statistical inference on these phenomena has just started and convincing applications are still missing. It is necessary to bundle the working forces of various researchers to face the challenges. AMERISKA will be a project where applied mathematicians concerns on issues of extremal risks will met; they will discuss the problems mentioned and and collaborate on their solution. One of the goals is the organization of a semester on risks that could be partly funded by Labex MME-DII. The research will be coordinated and led by 4 principal investigators: Olivier Wintenberger, Patrice Bertail, Philippe Naveau and Thomas Mikosch. They will manage a team of 8 experts from different countries, 12 french professors with strong experiments, 9 young french researchers and 2 PhD students, all working in the domain of quantitative risk analysis.