Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Ultra-efficient Multi-phase Sequential Waste Water Treatment Technology (Anaergy)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain,Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-08-01
End date: 2018-11-30
Duration (months): 4.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 2
Project status: CLOSED

The agro-food industrial sector is required to treat large quantities of wastewater (20,000 l /product kg) rich in organic matter content (30 kg Chemical Oxygen Demand – COD – per m3 wastewater). Anaerobic digesters treat high COD wastewater and produce biogas used as a renewable energy source. Nevertheless, even the most advanced high-rate systems present important technical and economic limitations: 1) Post-treatment (usually aerobic) is still required for wastewater discharge on surface water (COD elimination rates are in the range of 60-80% for current technologies), 2) Digester investment costs are high (€300,000 for the smallest reactors), 3) The efficiency of biogas production is low (35-50%). The above confirms that the industry is on demand of low price digesters and high efficiency biogas production solutions that will increase COD elimination rates. Through the launch of ANAERGY, Ingeobras and Proycon consortium aim to respond to these demands by introducing a proprietary Multiphase Sequential Anaerobic Digester, being the first demonstrated solution able to combine anaerobic, aerobic and photocatalysis in one digester. Our current prototype was built in-house and has been tested under relevant industrial conditions in 4 pilot plants, offering very high COD elimination rates (up to 99.8%) allowing for direct discharge to the land and a 60% increase in biogas production efficiency. At a low price (€150,000) and with very low operational cost we are offering a extremely efficient solution for the agro-food industry to treat water without need of post-treatment (60% reduction in operational costs). Furthermore, the production of biogas will cover industry energy needs up to 80%, enabling a return of investment of 12-20 months. We target commercialisation by 2021Q1, starting with 26 units sold going up to 80 in 2024, and expecting to achieve an accumulated profits of more than €17,9M over first four years.

Keywords: anaerobic digestion,aerobic,photocatalysis,biogas,agro food industry,water treatment costs,high organic water content,digester,cod elimination rate
Rapid and easy- test for Coronavirus infections (Corona-Quick)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-EIC-SMEInst-2018-2020-3, 2020)
Start date: 2020-08-01
End date: 2022-10-31
Duration (months): 27.0
Total project cost (EUR): 2574750.0
EU funding (EUR): 1439900.0
Participants: 1
Project status: SIGNED

The coronavirus outbreak in 2019 (Cov-19) has challenged the global healthcare system to contain a virus with unprecedented contagious capabilities. A major aspect for controlling the Coronavirus pandemic is the implementation of tools that allow rapid screening of patients at the healthcare centers and not only. Fast and accurate diagnosis of early infections will facilitate the clinical management of the virus, and will improve patients' prognosis. The diagnostic gold standard for Coronavirus is the RNA detection of pharyngeal swab specimen by RT-PCR. However, the limitations of time, need of devices and specialized personnel to perform RT-PCR, combined with the rapid spread and universal susceptibility to the general population, make this diagnostic technique incompatible with the urgent medical needs. Moreover, the number of RT PCR kits available are limited and the production cannot cope with the high demand. The main objective of this study is to develop a rapid, easy and economical screening test for Coronavirus with the capability to achieve results in less than one hour, with high sensitivity and specificity. The test will be used to screen asymptomatic or mildly symptomatic individuals, which can risk community transmission to population categories at a higher risk (elderly with underlying conditions, among others). Corona-Test is a lateral flow strip test similar to the well-known pregnancy test. Herein, we are aiming to validate the diagnostic accuracy and screening efficacy of Corona-Test. This strategy could provide the means to prevent and control the disease. The objective of this project will be to bring two different applications of the test to market within 20 months.

Keywords: coronavirus
FRICTION OPTIMISATION OF SEALS THROUGH ADVANCED LASER SURFACE TEXTURING OF MOULDS (MouldTex)

Framework: Horizon 2020 — Industrial Leadership
Programme: Nanotechnologies, Advanced Materials, Advanced Manufacturing and Processing, and Biotechnology
Theme: Technologies for Factories of the Future
Action type: Research and Innovation actions
Countries involved: Spain,Germany,Spain,Italy,Israel,Spain,Greece,Hungary,France
Call: New product functionalities through advanced surface manufacturing processes for mass production (H2020-FOF-2017, 2017)
Start date: 2017-11-01
End date: 2021-04-30
Duration (months): 42.0
Total project cost (EUR): 5133871.25
EU funding (EUR): 5133871.25
Participants: 10
Project status: CLOSED

Polymeric seals are essential components in almost every industrial and mechanical process enabling the effective containment and movement of liquids and gases under extremes of environment. Friction is intrinsically related to seal performance. High friction accelerates wear of the seal leading to leakage and/or premature failure, and increases the energy consumption of industrial processes. Surface (micro-) texturing is a proven technique for reducing friction across lubricated rigid materials such as metal and ceramic materials. Within recent years this technique has been applied and demonstrated for polymeric and elastomeric materials at laboratory level. The project will develop and demonstrate a novel methodology for the design and high volume manufacture of surface textured polymeric components tailored to the (friction) environment within which the component operates, achieving a friction reduction of >20% at a cost premium of <10%. The novel methodology combines: •advanced modelling software for the identification of surface texture patterns that lead to significant friction reduction for target rubber and plastic seals and applications •software for the design of mould tools that enable the reliable transfer of texture patterns onto the seal surface •novel automated laser system for the application of hierarchical laser induced micro- texture patterns to the mould tool surface •best practice for moulding and de-moulding using surface textured moulds •inline optical inspection for surface texture pattern quality control The project will establish three pilot lines for demonstration of: 1) mould tool design and manufacture; and the design and manufacture of 2) rotary seals for engine applications; and 3) reciprocating seals for industrial processes.

Keywords: rotary hydraulic piston seals,laser induced surface texture,mould transfer,friction modelling,reduced order modelling,design software,optical inspection
Enhacing TRANslational SAFEty Assessment through Integrative Knowledge Management (eTRANSAFE)

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: Austria,Spain,Germany,Germany,Germany,Germany,Germany,Spain,Germany,Germany,Germany,Switzerland,Belgium,Sweden,France,France,Netherlands,Netherlands,United States,Denmark,United Kingdom,United Kingdom,Japan,United Kingdom,United Kingdom,United Kingdom
Call: NEXT GENERATION OF ELECTRONIC TRANSLATIONAL SAFETY – NEXGETS (H2020-JTI-IMI2-2016-09-two-stage, 2016)
Start date: 2017-09-01
End date: 2023-02-28
Duration (months): 66.0
Total project cost (EUR): 40882349.5
EU funding (EUR): 20000000.0
Participants: 32
Project status: SIGNED

Drug safety assessment is a knowledge-intensive process that demands advancement in data handling methods and tools for facilitating data sharing, mining, analysis and predictive modelling. This need is not restricted to any specific type of data and real advancement requires integrating information of different types and from different sources (e.g. publicly available biomedical knowledge, proprietary preclinical and clinical data, evidence from post-marketing studies) for addressing drug safety assessment from a holistic perspective. The eTRANSAFE project will address these needs by developing a powerful data integration infrastructure (Knowledge Hub) and a collection of computational tools (exploitation modules) for making optimal use of these data. The proposed system will be a flexible and expandable framework, built on previous experience and applying state-of-the-art methods and technologies for providing the most advanced solutions for data sharing, interoperability and exploitation. An experienced honest broker will guarantee the confidentiality of any proprietary data. The project will develop in silico tools for data mining, visualisation, and prediction of potential toxicity, with specific attention to the assessment of the preclinical to clinical predictivity and the discovery of safety biomarkers. The CDISC-SEND format will be supported, facilitating the preparation of regulatory-compliant documentation. This infrastructure will be underpinned by development of open standards and guidelines recognised by regulatory agencies and international organisations. The eTRANSAFE consortium brings together 13 organizations that mobilize an unprecedented capacity and resources, uniquely placed to leverage the experience of eTOX and other EU projects and initiatives. The project partners are six prestigious academic institutions, six highly skilled small-medium enterprises (SME) and one European infrastructure (ELIXIR), bringing in this way a perfect balance.

Keywords: drug safety,translational safety,toxicology,pre clinical data,send data,data sharing,data integration,data interoperability,computational toxicology,predictive models,read across
Origami-based Microfluidic Interface for Cell Signalling (OMICS)

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: Chemistry
Countries involved: Germany
Call: Individual Fellowships (H2020-MSCA-IF-2016, 2016)
Start date: 2017-03-15
End date: 2019-03-14
Duration (months): 24.0
Total project cost (EUR): 159460.8
EU funding (EUR): 159460.8
Participants: 1
Project status: CLOSED

Cell surface receptors react to a multitude of signal molecules that trigger cellular responses and regulate cell fate. The malfunction of receptors and signals in cells may lead to the development of many diseases, including cancer, diabetes, neurodegeneration or autoimmune disorders. Thus, understanding complex signal pathways is key for future therapeutic approaches and drug development. This project concerns the development of a high throughput microfluidic device for the investigation of early cell signalling, which is triggered by ligand-decorated DNA origami nanostructures, immobilized on a microarray-patterned surface inside the microfluidic device. By combining state-of-the-art top-down microstructuring and bottom-up self-assembly, this approach allows to present ligands on surfaces with a full control of their absolute number, stoichiometry and nanoscale orientation, enabling to closer mimic the natural cell environment. While the principal functioning of origami-based ligand presentation has very recently been demonstrated by the beneficiary, the here proposed implementation in a microfluidic chip will improve surface stability and robustness, as well as allow automated, on-surface assembly and cell culture processes to open the door to multiplexing and high throughput analyses.

Keywords: microfluidics,dna origami,cell signalling,biomimetic interface,egfr,nanoscale organization,breast cancer cells
Geodetic data assimilation: Forecasting Deformation with InSAR (GEO-4D)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Earth system science
Panel description: Physical geography, geology, geophysics, atmospheric sciences, oceanography, climatology, cryology, ecology, global environmental change, biogeochemical cycles, natural resources management
Countries involved: France
Call: ERC Starting Grant (ERC-2017-STG, 2017)
Start date: 2018-01-01
End date: 2023-12-31
Duration (months): 72.0
Total project cost (EUR): 1499125.0
EU funding (EUR): 1499125.0
Participants: 1
Project status: SIGNED

Recent space-based geodetic measurements of ground deformation suggest a paradigm shift is required in our understanding of the behaviour of active tectonic faults. The classic view of faults classified in two groups – the locked faults prone to generate earthquakes and the creeping faults releasing stress through continuous aseismic slip – is now obscured by more and more studies shedding light on a wide variety of seismic and aseismic slip events of variable duration and size. What physical mechanism controls whether a tectonic fault will generate a dynamic, catastrophic rupture or gently release energy aseismically? Answering such a fundamental question requires a tool for systematic and global detection of all modes of slip along active faults. The launch of the Sentinel 1 constellation is a game changer as it provides, from now on, systematic Radar mapping of all actively deforming regions in the world with a 6-day return period. Such wealth of data represents an opportunity as well as a challenge we need to meet today. In order to expand the detection and characterization of all slip events to a global scale, I will develop a tool based on machine learning procedures merging the detection capabilities of all data types, including Sentinel 1 data, to build time series of ground motion. The first step is the development of a geodetic data assimilation method with forecasting ability toward the first re-analysis of active fault motion and tectonic phenomena. The second step is a validation of the method on three faults, including the well-instrumented San Andreas (USA) and Longitudinal Valley faults (Taiwan) and the North Anatolian Fault (NAF, Turkey). I will deploy a specifically designed GPS network along the NAF to compare with outputs of our method. The third step is the intensive use of the algorithm on a global scale to detect slip events of all temporal and spatial scales for a better understanding of the slip behaviour along all active continental faults.
A pan-national collaborative analytics platform for the exploration and improvement of population health (AtmoHealth)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: United Kingdom
Call: Open Disruptive Innovation Scheme (H2020-SMEINST-2-2016-2017, 2016)
Start date: 2016-10-01
End date: 2018-03-31
Duration (months): 18.0
Total project cost (EUR): 1798316.13
EU funding (EUR): 1258821.29
Participants: 1
Project status: CLOSED

Healthcare data analysis has become an integral part of public health policy making, medical research, the development of new treatments and medical innovation. Governments, pharmaceutical industries, insurance companies, medical research groups and hospitals increasingly use population-based healthcare data as a critical support to research and decisionmaking. Citizens are also increasingly keen to learn about the distribution and outcome of conditions which they may be suffering from. However, an affordable, user-friendly platform that brings together population health and research data from multiple sources and enables it to be easily presented and ‘mined’ for this wide range of purposes does not currently exist. iMoHEALTH will meet this need. The completed iMoHEALTH SMEI Phase 1 feasibility study enabled developers, FACE Recording and Measurement Systems Ltd, to conduct a number of research and development activities to build a detailed business plan. This, combined with the exceptionally enthusiastic response of both prospective users and potential commercial partners, confirmed that the product meets a clear market need and will have major perceived benefits to healthcare stakeholders across Europe. Indeed, the level of response suggested that the need is even greater and more keenly felt than had been previously anticipated. To build on the current TRL6, this project sets out to refine and improve the iMoHEALTH platform by both evolution of the back-end architecture and additional front-end functionality to reach TRL9, as well as performance verification in a broader range of healthcare contexts. FACE has over 20 years of experience in the health and social care sectors, developing solutions that meet the collective needs of practitioners, patients/service users and their carers, managers, policymakers and researchers. FACE has a national reputation for delivering high quality solutions, producing nationally accredited and awarding winning products.

Keywords: healthcare analytics,population health,research collaboration,data management,healthcare,health research,data analysis
High-Pressure High-Temperature Superconductivity (HPSuper)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Condensed matter physics
Panel description: Structure, electronic properties, fluids, nanosciences, biological physics
Countries involved: United Kingdom
Call: ERC Starting Grant (ERC-2016-STG, 2016)
Start date: 2017-02-01
End date: 2023-01-31
Duration (months): 72.0
Total project cost (EUR): 1809752.0
EU funding (EUR): 1809752.0
Participants: 1
Project status: SIGNED

Superconductors promote electrical currents without loss and are exploited for applications like magnets in medical imaging. Further applications like large scale usage in electrical power generation and transmission, however, are limited by the need to cool materials below a critical temperature Tc. Thus, novel superconductors with higher Tc are highly desirable. High Tc has been predicted almost 50 years ago for hydrogen and hydrogen compounds but was only confirmed in 2015 with the discovery of superconductivity at a record temperature of 203K in hydrogen sulphide H3S at high pressures. This long term effort highlights that finding new superconductors remains challenging as theory is very limited in predicting specific compounds for high-temperature superconductivity. The reason for this is that a favourable combination of materials and electronic properties is needed. This project will unravel the mechanism of high-temperature superconductivity in H3S, derive design principles, and find new high-temperature superconductors. We will measure key parameters of the superconducting state in H3S including the London penetration depth, coherence length, superconducting gap, charge carrier concentration, electron-phonon coupling, and Fermi surface topology as well as the isotope effect on these. This will be achieved through measurements of the critical field, Hall effect, quantum oscillations, and tunnelling spectroscopy. This insight will be used to derive design principles for new superconductors with increased Tc and at lower pressures. We will work together with theory and materials science to predict, synthesise and test novel superconductors working towards hydrogen based high-temperature superconductivity at ambient pressure. We will focus on two materials classes with high hydrogen content: i) phosphanes with excellent control of complementary elements and ii) hydrogen storage materials alanates and borohydrades with light complementary elements.

Keywords: high pressure,superconductivity,electronic structure,electron phonon coupling
Modeling the pharmacokinetics profiles of therapeutic peptides by chemoinformatics methods (PeptiMOL)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Society and Enterprise panel
Action type: Marie Skłodowska-Curie actions
Panel: Chemistry
Countries involved: Spain
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-05-01
End date: 2022-04-30
Duration (months): 24.0
Total project cost (EUR): 160932.48
EU funding (EUR): 160932.48
Participants: 1
Project status: CLOSED

Peptides have been acclaimed as the drugs of the future, thanks to their high specificity and activity, as well as their easy degradation. This implies that they generally possess reduced toxicity, few secondary effects, and are thus administered in small doses. Peptides possess multiple therapeutic applications, which include: antivirals, antifungals, antibiotics, modulators of the immune, cardiovascular and nervous systems, etc. However, it has been demonstrated that therapeutically relevant peptides generally exhibit limited capacity to diffuse across biomembranes such as the human gastrointestinal epithelium, in addition to their low stability. Moreover, due the short plasmatic half-life and low stability of these peptides, they are administered through injections, often several times a day. It is essential to develop methods for modeling the bioactivity of peptides, predict their pharmacokinetic profiles and ultimately allow for the design of novel peptide chains adapted to predetermined bioactivity profiles. Such modeling systems will allow for the design of peptides with favorable therapeutic efficacy, and above all, ensure their adequate bioavailability and (preferably oral) administration. Based on this background, the objectives of PeptiMOL are: • Define parameters (numerical molecular descriptors) for characterizing the structural, compositional and physicochemical properties of peptides and develop a user-friendly Java-based tool for their computation. • Construct mathematical models to predict the PK properties of peptides using the state of the art statistical and machine learning techniques. • Implement the developed models in a Java-based chemoinformatic platform which will enable potential end-users to virtually screen peptide libraries or design novel peptide structures with desirable physicochemical and PK profiles.

Keywords: therapeutic peptides,quantitative structure pharmacokinetic relationships qspkr,computational chemistry,pharmacokinetics,drug discovery