Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Culture, Heritage and Identities: Impacts of Climate Change in North West Europe (CHICC)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Standard European Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Denmark
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2021-02-01
End date: 2023-09-21
Duration (months): 24.0
Total project cost (EUR): 207312.0
EU funding (EUR): 207312.0
Participants: 1
Project status: SIGNED

CHICC aims to understand the impact of climate-change driven heritage loss on local communities. The widespread impacts of climate change are acknowledged in the UN’s Sustainable Development Goal 13: Climate Action; however, the full scale of the impacts on heritage and associated communities is currently unknown but knowable. Three damaged or lost heritage sites will be explored through CHICC: Mårup, Denmark; Dunbeag, Ireland; Brora, Scotland. Each has been altered by climate change, creating an impact on the lives and livelihoods of local communities, their sense of place and belonging, their perception of climate change; overall, impacting their cultural identities. As North-West Europe is expected to experience greater and more widespread heritage loss due to climate change, CHICC will use these sites to understand the complexity of loss, and the impact on communities and their cultural identities. Through adopting a Citizen Science approach, CHICC will include the often-omitted voice of local communities to understand how climate change impacts them, which may include an upsurge in engagement with climate change mitigation, greater energy for preservation or forgetting. Communities will be active participants within the research, contributing their views, ideas and resources. Through co-creation, CHICC will launch an online, deepmap for three damaged or lost heritage sites. The deepmap will collate and democratise multidisciplinary, primary and secondary data to interrogate the relationship between climate change, heritage and culture. This open-access resource will be created in-line with a Digital Preservation Strategy to ensure reuse of data for future researchers and varied stakeholder groups. The methodology developed includes co-creation and Citizen Science, underpinned by well-integrated interdisciplinarity, thus allows for impact and relevance for the numerous stakeholder groups with vested interested in heritage, climate change and the future.

Keywords: climate change,deep mapping,heritage loss,citizen science,co creation,interdisciplinary,local communities,climate change impacts
Precise and non-GMO Engineering of Nutritional Factors for Breeding High Quality Crops (MetKnock)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Israel
Call: ERC Proof of Concept Grant (ERC-2014-PoC, 2014)
Start date: 2015-02-01
End date: 2016-07-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

While great attention has been given to increase nutritional substances in food plants only limited efforts have been made for using biotechnology to reduce the level of endogenous, anti-nutritional factors (e.g. toxic compounds) in existing crops. Anti-nutritional substances not only affect the digestion and absorption of nutrients, but can also be lethal to humans or feeding animals and are responsible for food spoilage. Glycoalkaloids (GLAs) produced by crops of the Solanacea family, namely, potato and eggplant, are a major problem for breeders and farmers, as their level must be tightly regulated. Worldwide, between 13 and 27% of the potato crops are discarded because GLA levels are above the maximum currently deemed to be safe. In this PoC project we propose to redesign the potato GLAs metabolic pathway in a precise manner without the insertion of foreign genes, through targeted gene knockouts. Our strategy will be based on the discovery and intellectual property of genes part of the GLAs biosynthetic pathway obtained in the course of the ERC SAMIT project (Aharoni lab; ID-204575) that will be targets for precise, non-GMO metabolic engineering of potato. Know-how from TRACTAR, an ERC project (ID-268646) in the collaborating lab (A. Levy), will serve as the base for generating custom-designed nucleases (i.e. CRISPR/Cas) to be employed for targeted knockouts of potato GLAs genes. We will develop new potato cultivars with low GLAs content and with minimum impact on other plant characteristics, providing a proof-of-concept for potato breeding. In parallel to the technical testing, we will build a strategy to commercialize the IP and prototypes that have been or will be developed in the course of this project. We will identify and contact the relevant partners or investors who have an interest in potato quality and/or in the production of functional health food.

Keywords: antinutritional,crispr,non gmo,alkaloids,crops,potato,gene targeting
Printable Strain Sensors - Nanomaterial based Inks for High Performance Sensing Applications (Print-SENSE)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Synthetic Chemistry and Materials
Panel description: New materials and new synthetic approaches, structure-properties relations, solid state chemistry, molecular architecture, organic chemistry
Countries involved: Ireland
Call: Call for proposals for ERC Proof of Concept Grant (ERC-2020-PoC, 2020)
Start date: 2021-08-01
End date: 2023-01-31
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Strain gauges are devices that are used to measure a variety of forces. The broad nature of these devices means that they have applications in industries ranging from construction and aerospace to medical and automotive fields. Our project looks to develop a new approach to strain sensing devices by utilizing the unique properties of nanomaterial based composites. Through the expertise gained through the previously awarded ERC FUTURE-PRINT grant we look to develop the next generation of commercial strain sensing technology. The invention described is an ink blend consisting of a polymer (PDMS) and a nanomaterial (graphene) deposited to form a flexible, polymer-nanomaterial composite film with unique electro-mechanical properties suitable for high performance strain sensing applications This ink can be deposited using a variety of printing methods (screen printing, aerosol and mechanical deposition) resulting, once the ink dries, in the formation of a flexible, polymer-nanomaterial composite film which is extremely sensitive to any external forces - ~ 50 x more sensitive than standard industry strain gauges. We have started the patent process to establish the technology and underlying processes as the IP of the inventors and Trinity College Dublin. This IP would form the basis of an eventual spin-out launched by inventors should the application to the ERC PoC be successful. The objectives necessary to achieve this are the identification of an appropriate market based on the unique selling points of our technology, developing a prototype to be tested in real world applications, engage industry and take the further necessary steps towards commercialization. To accomplish these objectives, we have established an experienced team of researchers, IP/tech transfer and commercialization specialists with a prior track record of working effectively and efficiently together in achieving the outlined objectives in the area of research commercialization.

Keywords: strain sensors,graphene,nancomposites,2d materials,commercialization,medical diagnostics,spin out
A Wearable Electronics Approach To Reduce Mortality in Epilepsy (NOSUDEP)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Systems and communication engineering
Panel description: Electrical, electronic, communication, optical and systems engineering
Countries involved: United Kingdom
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-09-01
End date: 2024-12-31
Duration (months): 88.0
Total project cost (EUR): 1999999.0
EU funding (EUR): 1999999.0
Participants: 1
Project status: SIGNED

Epilepsy is a neurological condition that affects approximately 1% of the population (or over 50 million people in the world). Europe alone is home to 6 million people that suffer from epilepsy with one new case every minute. In certain cases, healthy patients with epilepsy can die suddenly and unexpectedly. This is known as Sudden Unexpected Death in Epilepsy (SUDEP). SUDEP kills thousands of people in Europe every year. Unfortunately the mechanisms of SUDEP are not known, which makes it unpredictable Individuals with refractory tonic-clonic or complex-partial seizures are at the highest risk of SUDEP. These comprise approximately one third of the population affected by epilepsy, i.e. in the order of 2 million people in Europe. The focus of this research project is to carry out multidisciplinary research on wearable medical technologies with the ultimate aim of helping to protect epilepsy patients from SUDEP, by automatically and reliably alerting carers of physiologically dangerous indicators that are known to be precursors of it. These technologies will also have the potential to facilitate clinical research that is not possible with existing physiological monitoring systems. This could further current understanding of the mechanisms as well as individual risks factors of SUDEP, and consequently lead to specific disease management, treatment and prevention strategies targeted to the individual patient. Additionally, the research work carried out in this project will be beneficial in a number of clinical contexts, including but not limited to: diagnosis of paediatric and adult sleep apnoea (affects 2-10% of the population, but less than 20% are diagnosed in developed countries due to lack of in-clinic resources), early warning scoring in hospitals (i.e. 80% of patients in hospital), asthma (334 million people in the world, ), Chronic Obstructive Pulmonary Disease (64 million people in the world. 4th leading cause of death), and neonatal cot death (0.41% of babies)

Keywords: wearable technologies,low power electronics
Decoding the molecular mechanisms driving host adaptation of yellow rust on cereal crops and grasses (DeMMYR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Biotechnology and Biosystems Engineering
Panel description: Biotechnology using all organisms, biotechnology for environment and food applications, applied plant and animal sciences, bioengineering and synthetic biology, biomass and biofuels, biohazards
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-03-01
End date: 2023-02-28
Duration (months): 72.0
Total project cost (EUR): 1714779.0
EU funding (EUR): 1714779.0
Participants: 1
Project status: CLOSED

Yellow rust (YR) disease is a major threat to cereal crops and grasses worldwide, causing significant losses to the global wheat harvest each year. The long-term aim of this research is to develop new varieties of wheat with enhanced resistance to YR. To do this, it is essential to understand host specificity - the ability of the pathogen to specialize on particular grass hosts, coupled with the ability of the host to resist infection by different strains of YR. I recently pioneered a field-based 'pathogenomics' approach to enable a comprehensive evaluation of the genetic diversity of YR. This new method provides unparalleled resolution of the pathogen population that can identify gene families associated with the ability to cause disease on all the major hosts of YR in Europe, namely wheat barley, rye, triticale and cocksfoot grass. Using this approach, I previously uncovered a genetically distinct population of YR on triticale and showed that these isolates contained gene clusters that were specifically expressed in all isolates identified on triticale and had no or negligible levels of expression in all wheat YR isolates. In this ERC project, I will use the pathogenomics approach to collect an extensive dataset of YR on all its major hosts, aiming to characterise genomic regions and the genes they encode to understand the underlying regulatory mechanisms that drive host specialization and adaptation. I will then assess changes at the transcriptomic level in closely related host-specialized YR races to provide insights into how pathogens adapt to new hosts. In parallel, I will identify host targets of effectors from YR to resolve the underlying molecular processes that are targeted by the pathogen to enable successful host-specific colonization. I will then disrupt the function of these host targets using precision genome editing to determine their contribution to YR pathogenicity and reveal novel susceptibility genes that are essential for pathogen progression.
Cloud collaborative open platform for advanced brain analytics (Neuromapper)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Spain
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-1-2016-2017, 2017)
Start date: 2017-05-01
End date: 2017-10-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Understanding brain’s anatomy is one of the biggest challenges in science due to the difficulty to observe it in vivo and its enormous complexity. Neuroimaging is the only available tool for non-invasive quantification of brain pathology and injury. However, a single neuroimaging dataset can measure in the terabytes. As a result, big data analysis in neurology is an epically big challenge. Despite the advances in computer infrastructure, data transmission and imaging techniques cracking the brain requires a collective effort. However, collaborative research is severely limited due to bureaucracy and privacy issues regarding patients’ data. Additionally, existing visualization systems for brain images have serious interoperability issues and lack advanced quantification and image visualization tools that can help researchers better identify disease biomarkers and study large datasets. This greatly hinders our understanding of the brain and our capabilities to develop new treatments for brain disorders, which is critical considering that 165 million people are affected by brain disorders in the EU, with an estimated cost of €798 billion each year. The objective of Neuromapper is to create a new gold standard for collaborative research on neuroscience by providing an environment for secure data sharing in the cloud as well advanced data management, analytics and visualization tools. In addition, the platform will be open to external researchers so that they can develop new data visualization and image processing tools and share them with the community. As the community grows and the database of brain images reaches a critical mass, Mint Labs will be able to implement big data and deep learning techniques. This will allow the development of a decision support system able to automate the diagnosis process and find new biomarkers of brain disorders, leading to earlier diagnosis and the development of new treatments.

Keywords: big data,deep learning,decision support system,cloud computing,open platform,image processing
Printable Perovskite Solar Cells with High Efficiency and Stable Performance (PRINTSolar)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Countries involved: Switzerland
Call: ERC-Proof of Concept-2016 (ERC-2016-PoC, 2016)
Start date: 2016-09-01
End date: 2018-02-28
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

The unique ability of perovskite solar cells (PSCs) to harvest very efficiently incident solar radiation even with films of only a few hundred nm thickness that can be infiltrated by solution processing onto planar substrates and into screen printable scaffold structures provides strong and unprecedented innovation potential in photovoltaics. Demonstration of high power conversion efficiency at very low cost along with the requisite durability metrics will form a persuasive argument for large investments in this new technology. Drawing from concepts developed as well as the latest advancements and discoveries made under our MESOLIGHT project (ERC grant 247404), we shall employ novel designs to gain further advantages over competing technologies. Particularly, mixed A cation –X formulations will be used to in ABX3 perovskite formulations along with inorganic hole conductors such as lithium doped NiMgO designed and developed as part of MESOLIGHT task will be utilized in the construction of PSCs for testing under solar light conditions. We have recently reached a certified solar conversion efficiency of 21% under standard AM 1.5 solar illumination with small laboratory cells. This POC will focus on upscaling to industrial PSC architecture on the module level and demonstrate long term stability for large scale deployment.

Keywords: metal halide perovskite solar cells,high efficiency modules,scaleup printable modules
Restoring competitiveness – Information system for the 21st Century Manufacturing (PPROI)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Czechia
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-09-01
End date: 2019-02-28
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

PPROI is a revolutionary information system supporting lean management of manufacturing processes by providing users within the firm (from planners to senior executives) with real-time data on capital employed in every process or product in order to increase its manufacturing productivity, overall operational effectiveness, and return on capital. No other system at the market today can supply this kind of detailed information. Commercializing the PPROI IS within EU can have significant economic and social impacts derived from increasing competitiveness of PPROI users mainly through employment retention and employment gains in areas in which European companies – for cost reason - could not compete and where 1.3 mil jobs and European prosperity are at risk. The proposed project is a strategic initiative for growth and transformation of the company from a small innovation-driven entity, to a market-oriented SME with scale-up business model based on a network of implementation partners. The specific aim of the Phase 1 is to check the feasibility of scaling-up the PPROI concept for a broad commercialization, to be realized e.g. by the SME Instrument Phase 2 funding. The feasibility study will have three components: 1. comprehensive business plan providing a blueprint for business expansion in the CEE region 2 Detailed evaluation of alternative “go-to-market” approaches, including IP protection implications. 3. Designing and testing the technological platform to enhance scalability. The company has already signed long-term service contract with four customers (two subsidiaries of large MNCs, two local SME), reaching TRL 6, and the next stage of company development is focused on business expansion first within the region and then within EU. It aims to reach turnover of 3,6 million EUR by the end of 2020 focusing on two industrial sectors critical to Europe’s competitiveness – automotive and electronics.

Keywords: lean manufacturing,balanced production planning,workflow optimisation,return on investments,workforce,productivity,factory efficiency,enterprise resource planning,financial control,levelling
RESISTANCE UNDER COMBINATORIAL TREATMENT IN ER+ AND ER- BREAST CANCER. (RESCUER)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Understanding health, wellbeing and disease
Action type: Research and Innovation actions
Countries involved: Germany,Spain,Israel,Spain,Norway,Norway,Finland,Sweden,Belgium,France,United States,United Kingdom
Call: Systems approaches for the discovery of combinatorial therapies for complex disorders (H2020-SC1-2019-Two-Stage-RTD, 2019)
Start date: 2020-01-01
End date: 2025-12-31
Duration (months): 72.0
Total project cost (EUR): 6283250.0
EU funding (EUR): 6000000.0
Participants: 18
Project status: SIGNED

Breast Cancer (BC) is the first cause of cancer-related death in women worldwide. Breast cancer is classified into well-recognized molecular subtypes. Despite solid pre-clinical evidence, only some patients benefit from administering drug combinations, an indication that patient and tumor heterogeneity is still present in the current stratification. Out of the numerous possible combinations of approved drugs, only a few have been actually tried, and the choice of tested combinations has been to some degree arbitrary. This proposal seeks to develop new approaches and identify mechanisms of treatment resistance at systems level, exploring how the effectiveness of specific targeted therapies applied in different clinical trials is affected by patient- and tumor-specific conditions. For this purpose, the project will gather and integrate longitudinal multidimensional data from ongoing clinical trials and newly generated --omics using systems approaches, which combine sub-cellular/cellular and/or organ level in-silico models and network analysis to build computational frameworks able to discover molecular signatures of resistance and predict patient response to combinatorial therapies. We aim to identify the physiological characteristics of non-responders vs. responders from existing and newly generated multi-omic data and biological samples from in-vivo and ex-vivo clinical studies of specific subtypes of BC patients treated with combination therapy. This new knowledge will be used to investigate the curative potential of new personalized drugs combinations. The overreaching goal is to develop computer “xenograft model” as a cost-efficient and better alternative in terms of ethics, availability to everyone, and animal use. The framework will include optimization algorithms to identify combinations of approved drugs with a high probability to work on individual or thin strata of patients. The project is endowed with a “legal” framework addressing ethical aspects

Keywords: combinatorial therapies,systems approaches,discovery,complex disorders,personalized medicine,breast cancer subclasses,pdx mouse models,longitudinal omics data from clinical trials