Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly (OPERAM)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Treating and managing disease
Action type: Research and Innovation actions
Countries involved: Ireland,Italy,Germany,Switzerland,Belgium,Greece,Belgium,Switzerland,Netherlands
Call: Comparing the effectiveness of existing healthcare interventions in the elderly (H2020-PHC-2014-two-stage, 2014)
Start date: 2015-05-01
End date: 2020-04-30
Duration (months): 60.0
Total project cost (EUR): 3930277.25
EU funding (EUR): 3735608.25
Participants: 10
Project status: CLOSED

Most older adults have multiple chronic diseases (multimorbidity) and multiple medications (polypharmacy). However, multimorbid patients are often excluded from clinical trials and most guidelines address diseases in isolation. Inappropriate drug prescription and poor drug compliance are common and contribute to up to 30% of hospital admissions. OPERAM investigators developed STOPP/START criteria to detect inappropriate drug use, both over- and underuse. Applying these criteria limits unnecessary polypharmacy and reduces underuse of indicated medications, but it remains uncertain whether systematic pharmacotherapy optimisation can improve clinical outcomes and reduce costs.We propose a multicentre randomised controlled trial to assess the impact of a userfriendly software-assisted intervention to optimise pharmacotherapy and to enhance compliance in 1900 multimorbid patients aged ≥75 years. Outcomes will include drug-related hospital admissions, health care utilisation, quality of life, patient preferences and cost-effectiveness. We will also perform several network meta-analyses (NMA) to provide new comparative evidence on the most effective and safest pharmacological and non-pharmacological interventions to reduce common causes of preventable hospital admissions (e.g. falls, fractures, bleeding). Therapy optimisation in the multimorbid elderly, enhanced compliance and discontinuation of less effective interventions have the potential to improve clinical, quality of life and safety outcomes, while reducing costs. We will provide a structured method with practical software solutions for optimal prescribing and new comparative evidence from NMAs for addressing multimorbidity and polypharmacy by means of customised, patient-centred guidelines. OPERAM ultimately aims at better healthcare delivery in primary and hospital care, based on effective, safe, personalised and cost-effective interventions that can be applied to the rapidly growing older population in Europe.

Keywords: polypharmacy,inappropriate prescribing,drug related side effects and adverse reactions
Commercialising a novel glioblastoma targeted therapy and a companion diagnostic compound (GLIOGUIDE)

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: Estonia
Call: ERC-Proof of Concept (ERC-2017-PoC, 2017)
Start date: 2018-06-01
End date: 2019-11-30
Duration (months): 18.0
Total project cost (EUR): 150000.0
EU funding (EUR): 150000.0
Participants: 1
Project status: CLOSED

Glioblastoma (GBM), is the most aggressive form of primary brain cancer and is diagnosed in 22,000 people per year in the EU. GBM is the most aggressive primary brain cancer and, by annual incidence, the most common type of malignant brain tumour. Despite aggressive treatment, the cancer always recurs. The average survival after diagnosis is 12 to 15 months, with less than 3% to 5% of patients surviving longer than 5 years. The current standard of care extends overall survival to ~14 -16 months. Current valuation of the global GBM treatment market is estimated to be €615 million per year, and it is predicted to increase to over €3.08 billion by 2024 (compound annual growth rate of 17%), based on the projected approval of new therapies including Opdivo and Optune. The main aim of this ERC PoC proposal is to probe the commercial viability of two types of tumour-targeted payload hybrids, one as an improved chemotherapeutic treatment, and the other as a precision-guided imaging agent for PET/MRI-based diagnosis. Our goal is for the former to become the clinician’s chemotherapy of choice in the adjuvant phase of GBM treatment; and for the latter to be incorporated into PET and MR-imaging procedures as a method for identifying and diagnosing GBM, as well as a companion test for stratification of patients for therapy.

Keywords: glioblastoma,targeted therapy,peptide conjugated compound,companion diagnostic
Defining the BUilding Basic BLocks for a U-Space SEparation Management Service (BUBBLES)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Theme: Public-private partnerships
Destination: Single European Sky Air Traffic Management Research
Action type: Research and Innovation actions
Partnership: SESAR (Art-187)
Countries involved: Italy,Spain,Spain,Belgium,Portugal
Call: U-space (H2020-SESAR-2019-2, 2019)
Start date: 2020-05-01
End date: 2022-10-31
Duration (months): 30.0
Total project cost (EUR): 1893197.5
EU funding (EUR): 1606108.75
Participants: 5
Project status: CLOSED

BUBBLES is a project targeting the formulation and validation of a concept of a U-Space advanced (U3) ‘separation management service’ at TRL3. BUBBLES will develop algorithms to compute the collision risk of UAS (taking into account all the involved risk sources), allowing to define separation minima and methods (procedural, tactical self-separated or tactical ground-based) so that a safety level stated in terms of overall probability of collision can be defined and maintained. The project will apply these algorithms to a set of generic CONOPs for UAS Operations defined by BUBBLES. These CONOPs will be detailed enough to cover all envisaged applications, but generic enough not to be linked to any particular one. The generic CONOPs will be classified in terms of risk using the SORA methodology. Afterwards, separation minima and methods will be assigned to them, leading to the definition of a set of generic OSED from which safety and performance requirements for the CNS systems will be derived through a safety assessment and based on the Performance-based Navigation (PBN) and Performance-based Communication and Surveillance (PBCS) concepts, including performance monitoring. To contribute the use of highly automated and digitalised systems in the U-Space, BUBBLES will also investigate the use of Artificial Intelligence (AI) to support the separation management, both for centralised and distributed systems. Moreover, BUBBLES will contribute to the standardisation of the U-Space by drafting required performance specifications for the CNS and AI-based systems involved in the provision of the Separation Management service. Lastly, the project will exploit the similarity between the U-Space Separation Management service and the Air Traffic Control (ATC) and the widespread confidence on the latter to improve the perception of safety regarding the UAS operations among the general public, thus contributing to their social acceptance.

Keywords: separation minima and methods,u space services,artifcial intelligence for utm,performance based communication and surveillance,u space cns infratructure performance monitoring
Noncausal time series models for the forecasting of speculative bubbles (NONCAUSALBubble)

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: Economic Sciences
Countries involved: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-07-01
End date: 2022-06-30
Duration (months): 24.0
Total project cost (EUR): 187572.48
EU funding (EUR): 187572.48
Participants: 1
Project status: CLOSED

Speculative bubbles on financial markets, viewed as short-term explosive deviations of prices from a typical historical level and ending in an abrupt correction, have become common events across all major asset classes. They can have a dramatic impact on portfolio performances, financial institutions solvability and can compromise the stability of the financial system. Because of their ability to reproduce stylized facts from speculative bubbles such as locally explosive trajectories, noncausal time series models -autoregressive (AR) and moving average (MA) processes with roots located inside the unit circle- have been at the center of a recent fast-emerging literature in econometrics and finance. Provided their dynamics is better understood, they will enable to formulate forecasts of future bubble trajectories. If rapid progress is being achieved on estimation and fitting problematics, prediction theory of noncausal processes remains particularly scarce and limited to special elementary cases – mostly the univariate noncausal AR(1) with independent and identically distributed Cauchy errors. The NONCAUSALBubble project aims at specifically addressing the lack of theoretical foundations for the forecasting of heavy-tailed noncausal processes. Building on recent tools from extreme value and alpha-stable distribution theories, NONCAUSALBubble will characterise the conditional distribution of future paths given the past observed trajectory during explosive episodes for 1) higher-order and 2) multivariate noncausal ARMA models. Closed-form formulations of the predictive distribution during bubble episodes will be derived alongside analytical quantification of the crash odds, and an intuitive prediction framework in terms of bubble pattern-recognition will be developed. The project is hosted by VU Amsterdam, one of the top research groups in time series econometrics and forecasting.

Keywords: noncausal processes,explosive bubbles,forecasting,econometric theory
An integrated appRoach To improve the Environmental perforMance of smart cItieS (ARTEMIS)

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: Environment and Geosciences
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-09-06
End date: 2023-09-05
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: CLOSED

The smart city concept has received increased attention from researchers and decision-makers across the EU. However, there is a gap between smart city research & practice, and environmental sustainability: to date, smart city projects have not adequately assessed the environmental impacts of their strategies, which remain largely unknown. Research is needed to provide empirical evidence, advanced tools and metrics that can support the design, implementation and evaluation of smart city strategies to improve urban environmental sustainability. RESEARCH GOALS ARTEMIS will investigate whether and how the smart city can improve the environmental performance of urban systems. The research aims to provide insight on key aspects in smart city strategies that can effectively reduce environmental impacts; a novel environmental impact assessment framework to support decision-making in smart city projects; and improved key performance indicators (KPIs) on environmental sustainability and circularity for smart cities. ACHIEVING THE GOALS ARTEMIS will develop an integrated framework coupling urban metabolism and life-cycle assessment, to estimate how strategies implemented in two EU-funded smart city projects (in Lisbon, Portugal, and Trento, Italy) have affected a wide set of environmental impacts, associated with urban systems. Drawing on the framework and results, KPIs will be provided to evaluate environmental sustainability in smart cities. The framework, recommendations and KPIs will be replicable across EU cities. RELEVANCE TO THE WORK PROGRAMME ARTEMIS will support the EU’s vision for smart cities and its aim of becoming a role model in sustainable development. My expertise in environmental impact assessment and the supervisor’s in smart cities bond effectively to pursue the research plan. The fellowship is a unique opportunity for me to obtain enhanced knowledge and skills on the development of environmental assessment tools and metrics for smart cities.

Keywords: smart city,environmental impacts,life cycle assessment lca,urban metabolism um,energy,greenhouse gas ghg emissions,key performance indicators kpis,sustainable urban development
Pursuing Efficient Reliability of Object Detection for automotive and aerospace applications (PERIOD)

Framework: Horizon 2020 — Excellent Science
Programme: Marie-Sklodowska-Curie Actions
Theme: Marie Skłodowska-Curie
Destination: Individual Fellowships (IF)-Reintegration panel
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Italy
Call: Individual Fellowships (H2020-MSCA-IF-2019, 2019)
Start date: 2020-10-16
End date: 2022-10-15
Duration (months): 24.0
Total project cost (EUR): 171473.28
EU funding (EUR): 171473.28
Participants: 1
Project status: CLOSED

Autonomous vehicles are about to change completely the transportation systems, the automotive and military markets, and burst deep space exploration. However, while autonomous cars are expected to reduce of two-three orders of magnitude the number of traffic accidents and burst space exploration, the current self-driving systems are not yet compliant with ISO26262 dependability requirements to be adopted in large-scale and are not yet sufficiently reliable to be part of a space mission. In particular object detection, a critical task in autonomous vehicles, has been demonstrated to be highly undependable and to be responsible for the great majority of accidents in current self-driving cars prototypes. “Pursuing Efficient Reliability of Object Detection for automotive and aerospace applications” (PERIOD) challenge is to improve the dependability of object detection frameworks in an effective and efficient way. PERIOD aims at analyzing and proposing solutions to overcome the software and hardware dependability issues of object detection. By correlating computing architectures and software reliability analyses with the impact of faults in the vehicle behavior, PERIOD aims at reducing the probability of misdetection without the time, power, and cost overheads that make traditional fault-tolerance solutions unsuitable for automotive or aerospace real-time systems. The proposed action will enable a highly interdisciplinary collaboration between the experienced researcher, a talented associate professor with a significant track record in computer science and computer engineering, and the supervisor, a world leader in test, embedded systems, and computing architectures for automotive/space applications whose group is embedded systems in one of Europe’s leading research institutions.

Keywords: reliability,dependability,transient errors,autonomous vehicles
First-in-class implants for bone regeneration surgery after a bone, ligament or tendon injury (REBOOT)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: France
Call: SME instrument (H2020-SMEInst-2018-2020-2, 2019)
Start date: 2019-11-01
End date: 2023-10-31
Duration (months): 48.0
Total project cost (EUR): 3545000.0
EU funding (EUR): 2481500.0
Participants: 1
Project status: SIGNED

NORAKER develops first-in-class implants for regenerative orthopaedic surgery to offer full healing to patients suffering from a bone, ligament or tendon injury. With project REBOOT, NORAKER will create the market of bone regeneration surgery. Each year in Europe, 1,6 million people require orthopaedic surgery after a bone, ligament or tendon injury, with many more cases expected as population ages. The current implants (made of metallic or bioresorbable materials) show imperfect healing outcomes, leaving millions of patients with fragile bones and poor quality of life (with 30% of inflammation, 20% of revision surgery and millions suffering from chronic pain and musculoskeletal disorders, MSDs). It weights billions of follow-up costs on the community. Enter NORAKER’s biocomposite surgical implants, made of bioactive glass – a revolutionary ceramic – mixed with a synthetic polymer, both bioabsorbable. This technology shows disruptive regeneration action: it can recreate up to 100% of the native-like functional bone structure with no inflammation, no abnormal pain, no MSD and a very low re-operation rate (4%). Today this patented technology is adapted to knee cruciate ligaments regeneration (with a world-first biocomposite screw marketed in 2015). In a SME Instrument Phase 1 project (2018), NORAKER has validated the feasibility of a new biocomposite formula with broader perspectives of regeneration for tendon, ligament and bone injuries. The Phase 2 project will do the industrial scale-up of this biocomposite and launch the industrial production of the first range of implants for the bone trauma market. Their adoption will support the transition toward regenerative orthopaedic surgery and break the spiral of pain and MSDs, which too many patients are experiencing these days. With this disruptive offer, NORAKER will become a scale-up operating worldwide, with a large manufacturing capablity, international sales and turnover multiplied by 15 in five years.

Keywords: orthopaedic regenerative medicine,bioactive glass,biocomposite,orthopaedic implant,bone regeneration
RISK assessment of chemicals integrating HUman centric Next generation Testing strategies promoting the 3Rs (RISK-HUNT3R)

Framework: Horizon 2020 — Societal Challenges
Programme: Health, demographic change and wellbeing
Theme: Methods and data
Action type: Research and Innovation actions
Countries involved: Austria,Germany,Spain,Germany,Germany,Germany,Spain,Germany,Germany,Germany,Belgium,Belgium,Sweden,Sweden,Sweden,Sweden,Switzerland,Latvia,France,France,Netherlands,Netherlands,Netherlands,Netherlands,Netherlands,Denmark,Denmark,United Kingdom,United Kingdom,United Kingdom
Call: Advancing the safety assessment of chemicals without the use of animal testing (H2020-SC1-2020-Single-Stage-RTD, 2020)
Start date: 2021-06-01
End date: 2026-05-31
Duration (months): 60.0
Total project cost (EUR): 23177768.75
EU funding (EUR): 22927768.75
Participants: 38
Project status: SIGNED

The vision of the RISK-HUNT3R consortium is to develop a reliable, efficient and cost-effective chemical safety assessment approach. It will be based entirely on non-animal methods and provide improved protection of the human population against systemic health effects caused by (chronic) chemical exposure. The major innovation provided by RISK-HUNT3R is a complete and truly human-centric risk assessment strategy. RISK-HUNT3R will establish, optimize and assemble all essential safety testing elements: exposure assessment, information on chemical distribution in the body, hazard characterization, adverse outcome prediction and determination of actual risk in defined scenarios. RISK-HUNT3R integrates cutting-edge in silico (computational) and in vitro (experimental testing) technologies. Human (disease) genetics and exposome data will ensure anchoring of test results to the human situation. The project will ensure regulatory relevance by testing the applicability of the critical test systems integrated in the next generation risk assessment strategy. The ambitious overall deliverable will be a comprehensive computational framework for the prediction of human adverse outcomes, and a set of stringently evaluated assays to feed the required data into this framework. RISK-HUNT3R will engage with all key stakeholders from different industry sectors and international regulatory agencies to critically evaluate and warrant genuine acceptance of the novel safety testing framework. This unique interaction of these key stakeholders working together on real-world case studies, will result in a ready-to-apply strategy to ensure societal protection against hazardous chemicals fully in concordance with the European Commission’s “Green Deal”. Importantly, the project will push commercial exploitation of the validated safety assessment approaches, thereby ensuring sustainability of the project outcomes and fortifying the innovation capacity of the industry sectors involved.

Keywords: exposure modelling,toxicokinetics,toxicodynamics,quantitative aop networks,systems toxicology,systemic human health effects,case studies,next generation risk assessment,regulatory acceptance
Architecture for EurOpean Logistics Information eXchange (AEOLIX)

Framework: Horizon 2020 — Societal Challenges
Programme: Smart, green and integrated transport
Action type: Research and Innovation actions
Countries involved: Germany,Italy,Italy,Italy,Austria,Germany,Germany,Germany,Spain,Germany,Spain,Italy,Serbia,Greece,Greece,Romania,Sweden,Greece,Romania,Slovakia,Sweden,Greece,Belgium,France,France,France,Czechia,Netherlands,Netherlands,Netherlands,Netherlands,United Kingdom,United Kingdom
Call: Common communication and navigation platforms for pan-European logistics applications (H2020-MG-2015_TwoStages, 2015)
Start date: 2016-09-01
End date: 2019-08-31
Duration (months): 36.0
Total project cost (EUR): 16220106.25
EU funding (EUR): 16220106.25
Participants: 47
Project status: CLOSED

Supply chain visibility supported by easy access to, and exchange and use of relevant and abundant logistics-related information is an important prerequisite for the deployment of pan-European logistics solutions that are needed to increase efficiency and productivity, and to reduce environmental impact. Although there is a proliferative development of logistics-related data stores, information channels, information management systems and data mining facilities, with both international and intermodal focus, this multitude of solutions exhibits a high degree of fragmentation, due to differences in user requirements, data models, system specification and business models. This legacy situation severely hampers the optimal use of logistics-related information. To overcome this fragmentation and lack of connectivity of ICT-based information systems for logistics decision making, AEOLIX will establish a cloud-based collaborative logistics ecosystem for configuring and managing (logistics-related) information pipelines. This digital business ecosystem will create visibility across the supply chain, enabling more sustainable and efficient transport of goods cross Europe. An essential element of the approach is to ensure that for logistics actors connecting to and using the ecosystem in undemanding and has a low level of complexity. We envision the ecosystem enabling the integration of supply-chain-related transport business processes through logistics software solutions for cloud-based connectivity and interaction, in order to support more efficient collaboration in the logistics supply chain than exists today. By enabling low-complexity and low cost connectivity of local ICT platforms and systems and thereby scalable, trusted and secure exchange of information, AEOLIX will improve the overall competitiveness of goods transport in the supply chain, while simultaneously targeting sustainability from environmental, economic and social perspectives.

Keywords: digital business ecosystem,sustainability,cloud based open ecosystem,intelligent hubs,horizontal and vertical collaboration,multi,syncromodal transport