Autoimmune disease affects 10% of adults, most of whom are women, and two of the top five medications with the highest cost globally are used to maintain these recurring conditions in remission. These medications act by suppressing the immune system, leaving the patient exposed to severe infection and at risk of cancer. Affected individuals receive standard treatment regimens for long periods of time, even though, in some cases, the autoimmune response may no longer be detectable. The general requirement for these medications, and their side effects, has been raised as a key target for research by the PARADISE consortium patient groups. Therefore, we aim to develop and validate a deployable personalised predictive tool that will accurately define the individual’s degree of immune system activation so that the medication dose can be tailored and, in some cases, stopped safely. We use systemic vasculitis as an archetypal autoimmune disease, integrating clinical, innovative biomarker and smartphone app-derived patient wellbeing data through a novel semantic web platform to inform predictive algorithms that will underpin a physician-facing tool. Such artificial intelligence (AI) applications are coming under intense scrutiny in the EU, so we will co-develop an “AI transparency notice” with the patient arm of the European Reference Network for immune disorders through a series of multi-stakeholder workshops, which will make explicit and explainable the full provenance of the PARADISE tool clinical outputs.

The proposed IGCT initiative stems from results obtained within the FP7-HEALTH Project LEUKOTREAT (www.leukotreat.eu), coordinated by Odile Boespflug-Tanguy (IGCT initiator) which aims to develop therapeutic strategies in inherited neurodegenerative disorders affecting the white matter (leukodystrophies) In particular, two LEUKOTREAT work packages were dedicated to the identification of pharmacological strategies and the development of innovative gene and cell therapies. In this context, IGCT aims to capitalise on these first works performed within LEUKOTREAT, and to pursue research activities on both topics in the framework of the Horizon 2020 Programme by extending to neurodegenerative disorders affecting the axon (spastic paraplegia and ataxia). To this end, several interesting calls for proposals have been identified in the 2016-2017 Health programme draft: • PM 202 – 2016 – “Solving the unsolved"- Genomic Diagnostic characterisation of undiagnosed rare diseases [RTD] – 10 m€; • PM 707 – 2017 - New therapies for rare diseases – 6 m€; • PM 808 – 2016 - Patient-centred new therapies for chronic diseases [RTD] – 6 m€; • PM 10 – 2016+2017 - Clinical research on regenerative medicine [RTD] – 6 m€. Based on these different calls, IGCT already gathers a network of several teams involved in gene and cell therapies as well as in neuroprotection, led by Pr. Boespflug-Tanguy: • French INSERM research units: UMR 1141 – Neuroprotection of the developing brain (Odile Boespflug-Tanguy), UMR 1169 – Thérapie Génique, Génétique, Epigénétique en neurologie, Endocrinologie et Développement de l'enfant (Patrick Aubourg), UMRS 975-Centre de Recherche de l’ Institut du Cerveau et de la Moelle épinière (CRICM) (Anne Baron-Van Evercooren), ; UMR 1107-NeuroDol (Melina Begou) • Two Italian research teams: the San Raffaele Telethon Institute for Gene Therapy (Alessandra Biffi and Angela Gritti) and the laboratory of molecular medicine of Ospedale Pediatrico Bambino Gesu (Enrico Bertini); • One Spanish research team: Bellvitge Biomedical Research Institute (Aurora Pujol), • One Danish-USA research team: Center for Translationnal Neuromedecine (CTN) Copenhagen and Rochester Universities (Steven Goldman). Furthermore, IGCT plans to integrate several other partners possessing different know-how, with the objective to guarantee transdisciplinary expertise and experience. Among targeted fields, one can cite clinical sites (at the EU level), CROs, patients’ associations, partners skilled in other types of diseases than the ones currently tackled, etc. The successful achievement of IGCT should lead to the submission of four complete proposals in the framework of H2020 Health Programme 2016-2017, all coordinated by a group of French teams (INSERM).

Pancreatic cancer (PC) has the lowest survival rate of all cancers in Europe, with no early detection strategies available. The IMAGene project will develop, implement and test a comprehensive Cancer Risk Prediction Algorithm (CRPA) to predict PC in high-risk (HR) asymptomatic subjects; it will investigate the potential for DNA methylation biomarkers to improve currently available risk indexes, and validate the feasibility of using liquid biopsies for early detection of cancer in such HR individuals. A sample of 200 healthy first-degree relatives of PC patients will be recruited, and their epidemiological factors related to PC risks assessed through initial interviews. Subjects will receive medical and psychological visits, and will undergo screening for germline mutations, DNA methylation profiling plus Whole-body MRI at baseline. Biostatistical analysis of data will be performed to develop algorithms able to extract risk profiles from biological and imaging data. All subjects will undergo epigenetic follow-ups plus radiological exam at 1 year after baseline. Participants’ lifestyle, epidemiological and psycho-decisional assessment will be performed through a monitoring process over the 3 years of the project. HR subjects’ lifestyle data will be correlated with DNA methylation profiles. All data collected will feed the supervised machine learning CRPA. Assuming the risk assessment through CRPA and DNA methylation profiling allows a two or three-fold enrichment in early detection of suspicious cancer in HR individuals (compared to the detection rate of pancreatic cysts with malignant potential observed in non-stratified asymptomatic population, 9.3%), we expect a detection rate of suspicious lesions of 20-25% in the selected population. A cost-utility and a detailed ethical analysis will be conducted. The IMAGene project will adopt a transnational, multi-level, multidisciplinary and multi-methodological approach to achieve its aims.