Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Support services to IMProve innovation and competitiveness of business in Lombardia and Emilia-Romagna (KAMINLER)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: Specific Grant agreement
Countries involved: Italy,Italy,Italy,Italy
Call: Enhancing the innovation management capacity of SMEs (H2020-Adhoc-2014-20, 2014)
Start date: 2015-01-01
End date: 2016-12-31
Duration (months): 24.0
Total project cost (EUR): 522974.0
EU funding (EUR): 522974.0
Participants: 13
Project status: CLOSED

The objective of the present action is the establishment and delivery of a specific Enterprise Europe Network service designed to enhance the innovation management capacity of SMEs, by providing in-depth support in the areas where these services are absent or unaffordable on local markets. The service will also aim at supporting beneficiaries of the SME Instrument (H2020) dealing with coaching assignments and addressing specific innovation weaknesses.

Keywords: innovation,technology transfer,coaching,sme instrument
Central Repository for Digital Pathology (BIGPICTURE)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Public-private partnerships
Destination: Innovative Medicines Initiative 2
Action type: Research and Innovation actions
Partnership: IMI2 (Art-187)
Countries involved: Germany,Austria,Austria,Germany,Germany,Italy,Germany,Germany,Italy,Germany,Ireland,Belgium,Finland,Switzerland,Belgium,Belgium,Finland,Hungary,Sweden,Sweden,Sweden,Switzerland,Belgium,Belgium,France,France,France,United States,Netherlands,Netherlands,Netherlands,Netherlands,Netherlands,United Kingdom,Denmark,United Kingdom,United Kingdom
Call: Central repository of digital pathology slides to support the development of artificial intelligence tools (H2020-JTI-IMI2-2019-18-two-stage, 2019)
Start date: 2021-02-01
End date: 2027-01-31
Duration (months): 72.0
Total project cost (EUR): 70081907.0
EU funding (EUR): 32319825.0
Participants: 51
Project status: SIGNED

BIGPICTURE, a pathology-led consortium, has the vision to become the catalyst in digital transformation in Pathology. Our mission is to create the first European GDPR compliant platform, in which both quality-controlled Whole Slide Imaging (WSI) data and advanced Artificial intelligence (AI) algorithms will exist. The BIGPICTURE platform will be built on existing assets of ELIXIR EU data infrastructure, including the federated European Genome-phenome Archive (EGA) technology for managing the exchange of confidential information between contributors and users. The consortium will use Cytomine, an established open-source, cross-platform framework to develop unique tools for access to WSI, including annotations and visualisation of algorithm results, while we will develop new and generic models to facilitate AI development and mining of WSI data. By engaging and building consensus with all the relevant stakeholders, we will contribute to the development of a regulatory framework for digital slides and AI-based methods. Finally, BIGPICTURE envisions sustainability of its platform through a community- based model which relies on reciprocity, value creation and inclusiveness. To achieve our vision, we have brought together Europe’s leaders in the field of computational pathology who have access to national and European high-performance computing infrastructures as well as Europe’s fully digitalised pathology departments. Additionally, the consortium has currently access to approximately 4.5 million clinical WSI covering a wider range of indications through 17 partners and 23 third parties from the largest European and international pathology and trial groups. Our consortium is further strengthened by the presence of the European Society of Pathology, Digital Pathology Association, FDA and 9 SMEs as partners, while we are further supported by professional societies, and patient advocates.

Keywords: artificial intelligence,digital pathology
A Humanized Monoclonal Anti-Claudin1 Antibody (anti-CLDN1 mAb) for Treatment of Hepatocellular Carcinoma (HCC) (HEPCAN)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Proof of concept grants
Action type: ERC actions
Panel: Prevention, Diagnosis and Treatment of Human Diseases
Panel description: Medical technologies and tools for prevention, diagnosis and treatment of human diseases, therapeutic approaches and interventions, pharmacology, preventative medicine, epidemiology and public health, digital medicine
Countries involved: France
Call: ERC Proof of Concept Grant (ERC-2019-PoC, 2019)
Start date: 2019-10-01
End date: 2021-09-30
Duration (months): 24.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Hepatocellular carcinoma is the most frequent primary liver cancer and owing to its very aggressive nature is amongst the leading cause of cancer mortality worldwide (IARC). The number of liver cancer-related deaths in Europe in 2018 amounted to 77 375, and this number is expected to keep rising, reaching an estimated number of more than 100 000 deaths in 2040 (IARC). Major causes include the hepatitis B and C viruses, alcoholism, Non-Alcoholic Fatty Liver Disease and Non-Alcoholic Steatohepatitis. All of these medical conditions trigger liver fibrosis by damaging the liver and are closely associated with the development of HCC. As a matter of fact, more than 80% of HCC develop in fibrotic or cirrhotic livers. Early stages of liver cancer do not usually produce symptoms, and many challenges are associated with the screening of HCC, leading to its late diagnosis. The absence of effective drug treatment for HCC makes its resection the first curative option with most of the patients experiencing HCC recurrence within 5 years. All these factors contribute to the poor prognosis of the HCC patients. Sorafenib is the only currently approved systemic therapy for advanced HCC in the EU, only prolonging survival by an average of 3 months, the treatment often leads to drug resistance. Indeed, intra-tumor heterogeneity strongly constrains the therapeutic benefit of precision medicine and triggers drug-resistant sub-population of cells. Consequently, persistent treatment of drug-resistant tumor cells may accelerate tumor progression, suggesting that inappropriate and continual use of a compound on drug-resistant cancer cells is not recommended. Thus, there is an urgent unmet medical need to identify and to validate the therapeutic efficacy of new valuable molecules – i.e. targeting the existing drug-resistant cell populations -that could be used in monotherapy or in combination therapy with FDA-approved drugs to improve HCC treatment responses.

Keywords: liver disease,cancer,hepatocellular carcinoma,drug development,liver cancer model,antibody,cancer treatment
A Unified Theory of Algorithmic Relaxations (AUTAR)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Computer science and informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Spain
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-06-01
End date: 2020-09-30
Duration (months): 64.0
Total project cost (EUR): 1725656.0
EU funding (EUR): 1725656.0
Participants: 1
Project status: CLOSED

For a large family of computational problems collectively known as constrained optimization and satisfaction problems (CSPs), four decades of research in algorithms and computational complexity have led to a theory that tries to classify them as algorithmically tractable vs. intractable, i.e. polynomial-time solvable vs. NP-hard. However, there remains an important gap in our knowledge in that many CSPs of interest resist classification by this theory. Some such problems of practical relevance include fundamental partition problems in graph theory, isomorphism problems in combinatorics, and strategy-design problems in mathematical game theory. To tackle this gap in our knowledge, the research of the last decade has been driven either by finding hard instances for algorithms that solve tighter and tighter relaxations of the original problem, or by formulating new hardness-hypotheses that are stronger but admittedly less robust than NP-hardness. The ultimate goal of this project is closing the gap between the partial progress that these approaches represent and the original classification project into tractable vs. intractable problems. Our thesis is that the field has reached a point where, in many cases of interest, the analysis of the current candidate algorithms that appear to solve all instances could suffice to classify the problem one way or the other, without the need for alternative hardness-hypotheses. The novelty in our approach is a program to develop our recent discovery that, in some cases of interest, two methods from different areas match in strength: indistinguishability pebble games from mathematical logic, and hierarchies of convex relaxations from mathematical programming. Thus, we aim at making significant advances in the status of important algorithmic problems by looking for a general theory that unifies and goes beyond the current understanding of its components.

Keywords: logic in computer science,computational complexity,algorithms
Antibiotics reduction with early mastitis pathogens detection for @ point of animal care usages (Pathogens detection)

Framework: Horizon 2020 — Societal Challenges
Programme: Food security, sustainable agriculture and forestry, marine and maritime and inland water research and the bioeconomy
Action type: SME instrument
Countries involved: Netherlands
Call: Resource-efficient eco-innovative food production and processing (H2020-SMEINST-1-2014, 2014)
Start date: 2015-03-01
End date: 2015-08-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Blue4Green will develop a portable sample handling/sensing system for DNA and/or RNA fragments. The input to such a system is a raw sample of milk, containing the bacteria to be analysed that causes mastitis. Most of the time treatment starts without knowing the responsible pathogen. Often, the wrong (or not most optimal) antibiotic is used as treatment. When therapy fails, new mastitis incidences and prevalence’s are rising. To test, at this moment farmers collect their samples in testing tubes. These tubes should be transported and send to a laboratory. Within the laboratory, the fluid is tested and the farmer receives the results within three (or more) days. The new technology, concerns a more rapid detection method. Within the technique of B4G, it is possible to know which pathogen is responsible for the inflammation to treat mastitis infection within three minutes instead of three days (or more) since the farmer can test it by himself. With a rapid mastitis pathogen test: - less mastitis incidences occur - reduce of revenue losses (less new infection) - there will be less use of unnecessary antibiotic - more milk will be produced - a better dairy cattle lifetime will be developed, resulting in a better return on investment for the farmer per cow Detecting mastitis at an early stage is a new competitive eco-innovative process that contributes to a more resource-efficient, sustainable circular economy. Continuing population and consumption growth will mean that the global demand for food will increase for at least another 40 years. Growing competition for land, water, and energy, will affect our ability to produce food, as will the urgent requirement to reduce the impact of the food system on the environment. Extending the lifespan of dairy cattle by combating mastitis with better insights @ point of animal care using innovative diagnostics tools will lead to a proper use of resources hence a more the efficiency use of raw materials.

Keywords: innovation,food,animals,cows,milk,technology,green,partnership,europe,institutes
Comorbid Conditions of Attention deficit / hyperactivity disorder (CoCA)

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,Germany,Germany,Spain,Spain,Estonia,Germany,Germany,Germany,Norway,Sweden,United States,Netherlands,Netherlands,Denmark,United Kingdom
Call: Understanding common mechanisms of diseases and their relevance in co-morbidities (H2020-PHC-2015-two-stage, 2015)
Start date: 2016-01-01
End date: 2021-06-30
Duration (months): 66.0
Total project cost (EUR): 6192770.5
EU funding (EUR): 5999020.5
Participants: 18
Project status: CLOSED

Understanding mechanisms underlying comorbid disorders poses a challenge for developing precision medicine tools. Psychiatric disorders are highly comorbid, and are among the last areas of medicine, where classification is driven by phenomenology rather than pathophysiology. We will study comorbidity between the most frequent psychiatric conditions, ADHD, mood/anxiety, and substance use disorders, and a highly prevalent somatic disease, obesity. ADHD, a childhood-onset disorder, forms the entry into a lifelong negative trajectory characterized by these comorbidities. Common mechanisms underlying this course are unknown, despite their relevance for early detection, prevention, and treatment. Our interdisciplinary team of experts will integrate epidemiologic/genetic approaches with experimental designs to address those issues. We will determine disease burden of comorbidity, calculate its socioeconomic impact, and reveal risk factors. We will study biological pathways of comorbidity and derive biomarkers, prioritizing two candidate mechanisms (circadian rhythm and dopaminergic neurotransmission), but also leveraging large existing data sets to identify new ones. A pilot clinical trial to study non-pharmacologic, dopamine-based and chronobiological treatments will be performed, employing innovative mHealth to monitor and support patients’ daily life. Integration of findings will lead to prediction algorithms enhancing early diagnosis and prevention of comorbidity. Finally, we will screen to repurpose existing pharmacological compounds. Integrating complementary approaches based on large-scale, existing data and innovative data collection, we maximize value for money in this project, leading to insight into the mechanisms underlying this comorbidity triad with its huge burden for healthcare, economy, and society. This will facilitate early detection and non-invasive, scalable, and low-cost treatment, creating opportunities for substantial and immediate societal impact.

Keywords: adhd,mood disorders,depression,anxiety,substance use,obesity,dopamine,circadian rhythm,mhealth,mobile health,clinical trial,biomarker,epidemiology,gwas,repurposing,precision med
Remote Sensing Science Center for Cultural Heritage (ATHENA)

Framework: Horizon 2020 — Spreading excellence and widening participation
Programme: Widening participation and spreading excellence
Theme: Improved access to Excellence
Action type: Coordination and support actions
Countries involved: Germany,Italy,Cyprus
Call: Twinning (H2020-TWINN-2015, 2015)
Start date: 2015-12-01
End date: 2018-11-30
Duration (months): 36.0
Total project cost (EUR): 972841.25
EU funding (EUR): 972841.25
Participants: 3
Project status: CLOSED

The “ATHENA” proposal aims to establish a Center of Excellence in the field of Remote Sensing for Cultural Heritage in the areas of Archaeology and Cultural Heritage through the development of an enhanced knowledge base and innovative methods. This center will be established by twinning the existing Remote Sensing and Geo-environment Research Laboratory at the Cyprus University of Technology (CUT) with internationally-leading counterparts from other Member States of the EU, such as the Institute of Archaeological and Architectural Heritage of the National Research Council of Italy (IBAM- CNR) and the German Aerospace Centre (DLR). The goals of the Center will be aligned with the Smart Specialization Strategy of Cyprus. The close collaboration between CUT and other experts in the field of Remote Sensing for Cultural Heritage in the EU will form a synergic network that will permit the transfer of knowledge and training of the existing personnel of CUT. As a result, the ATHENA project will have both direct and indirect social, scientific, and economic outcomes. In addition, the implementation of the project will facilitate future collaborations with experts of the Archaeology and Cultural Heritage sector in an EU level, increase the Centers’ research capabilities, as well as enhance the research and academic profile of all participants. It is noteworthy to underline the importance of the geographical position of the Center in the region of eastern Mediterranean, a region inhabited thousands of years before and therefore abound in archaeological residues.

Keywords: remote sensing archaeology,cultural heritage preservation
METRO High bandwidth, 5G Application-aware optical network, with edge storage, compUte and low Latency (METRO-HAUL)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: Research and Innovation actions
Partnership: 5G PPP (cPPP)
Countries involved: Spain,Spain,Italy,Italy,Germany,Italy,Germany,Germany,France,Netherlands,United Kingdom,Portugal,United Kingdom,United Kingdom,United Kingdom,United Kingdom
Call: 5G PPP Research and Validation of critical technologies and systems (H2020-ICT-2016-2, 2016)
Start date: 2017-06-01
End date: 2020-09-30
Duration (months): 40.0
Total project cost (EUR): 7784859.75
EU funding (EUR): 7784859.75
Participants: 23
Project status: CLOSED

METRO-HAUL is a project proposal addressing the Horizon 2020 ICT-07 5G PPP call; it is an RIA, focusing on strand 2 (high capacity elastic – optical networks) and strand 3 (software networks). The central topic is cost-efficient optical metro networks for 5G backhaul. The aim of this project is to design and build a smart, but cost-effective, optical metro infrastructure able to support traffic originating from heterogeneous 5G access networks, addressing the anticipated capacity increase and its specific characteristics such as mobility, low latency, and high bandwidth. This infrastructure will be able to also support a wide variety of 5G applications with special emphasis on services from various industries vertical to the ICT. This will be achieved by architecting new access-facing and core-facing nodes, complete with storage and compute facilities, interconnected by novel, spectrally efficient, and adaptive optical transmission networks. Advanced concepts, such as hardware disaggregation and virtualisation, will assist in hitting challenging cost targets whilst enabling automation and programmability – all supported by a purpose-designed SDN-based control plane which will interface with client applications, intelligently catering for the wide range of 5G KPIs. METRO-HAUL will coordinate the disparate elements of transmission, switching, networking, compute, and storage, orchestrating dynamic solutions for multiple 5G applications. METRO-HAUL will carry out Proof of Concept demonstrations of its networking solution involving the interconnection of metro node prototypes, the use of the project's transmission technologies, and the associated control plane and orchestration software. The final project demonstrations will also involve the demonstration of actual 5G and vertical services across the METRO-HAUL test-bed. Additionally, the project will actively participate in the relevant standardization bodies, promoting METRO-HAUL solutions to the wider community.

Keywords: metro networks,software defined networks,5g aware networks
Pushing the frontiers of biological imaging with genetically encoded fluorescence switches (FLUOSWITCH)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator 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: France
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-05-01
End date: 2023-04-30
Duration (months): 72.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 851562.5
Participants: 2
Project status: SIGNED

Biological imaging is essential for revealing the inner workings of living systems. Among the numerous imaging modalities, light microscopy has revolutionized biological research. In addition to advances in optics and detectors, imaging has benefited from the development of molecular tools to observe biomolecules in action. Although the last decade’s breakthroughs in imaging have led to new discoveries in biology, there are still extraordinary opportunities for basic and clinical research in further advancing imaging capabilities. This project proposes to develop new classes of probes to advance biological imaging and allow the study of biological processes in all their complexity. First, I propose to push the boundaries of multiplexing and super-resolution imaging in living cells developing a new class of fluorogenic probes that act as genetically encoded fluorescence on/off switches. Highly multiplexed images will be built up over sequential activation of orthogonal fluorescence on/off switches, while continuous switching will allow implementing innovative dynamic super-resolution techniques in living cells. Then, I will develop dynamic fluorescence on/off switches enabling to reveal the dynamics of intracellular processes, focusing in particular on the visualization of interaction dynamics in real-time, and the dynamic detection of endogenous molecules (e.g. proteins, nucleic acids) in living cells. The final part will be dedicated to the development of probes acting as molecular integrator switches to identify active cell circuits in whole tissues or organisms through permanent labeling of transiently activated cells. Overall, this project will enable to push back the frontiers of biological imaging providing innovative tools to interrogate quantitatively and comprehensively living systems at the molecular, cellular and network levels.

Keywords: biomolecular imaging,fluorescence,probe and biosensor design