Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Precision Cancer Medicine Pipeline and Services (PCMPS)

Framework: Horizon 2020 — Industrial Leadership
Programme: Information and Communication Technologies
Action type: SME instrument
Countries involved: Norway
Call: Open Disruptive Innovation Scheme (implemented through the SME instrument) (H2020-SMEINST-1-2014, 2014)
Start date: 2015-05-01
End date: 2015-10-31
Duration (months): 6.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Cancer cost the EU €126 billion in 2009, while in 2010 the US spent a staggering $124.6 billion on treating cancer. This cost is set to rise as the effects of an aging population and increasing life expectancy take their toll. These market drivers will put an intolerable strain on health services across the western world, forcing governments to streamline their health services. Current cancer treatment is based on the "average cancer patient", meaning some cancer patients may not respond to the treatment while others do. Thus it is clearly is a need for solutions that offer precision cancer medicine. PubGene AS aims to pursue a major market opportunity by developing a complete pipeline for precision cancer medicine (PCMPS), that include the necessary steps from Next Generation Sequencing to clinical treatment support for cancer patients. The biggest beneficiary of PCMPS will be the patient, who will receive a personalized treatment rather than a “hit and miss” approach to therapy. This will improve patient outcomes and ensure patients no longer have to suffer harsh side effects from non-efficacious treatments. The second beneficiaries will be the health providers and payers, as doctors will no longer waste time and money prescribing ineffective treatments. Nevertheless, despite the benefits of personalized cancer medicine, it is crucial to validate and demonstrate the benefits of this type of cancer medicine before large-scale commercialization. PMCPS is an opportunity for PubGene to expand our suite of applications and enter into complete new market for PubGene - targeting the treatment market. The project will give us a head start in providing tools in the field of personalized cancer medicine, ensuring us strong positions in the future European and worldwide markets. Accomplishment of the project will represent a significant business opportunity with an expected annual turnover of €17 million with a 25-30% annual increase, 3 years after commercialization.

Keywords: personalized medicine,precision cancer medicine,biomarker,tumor panel,bio informatics
Generation and manipulation of magnonic Schrödinger cat states for quantum information science (SPINCAT)

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: Physics
Countries involved: Netherlands
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2021-05-01
End date: 2023-04-30
Duration (months): 24.0
Total project cost (EUR): 187572.48
EU funding (EUR): 187572.48
Participants: 1
Project status: CLOSED

Given the rapid development of information-based society, it becomes more important and urgent to find efficient means to store and process huge amount of information. While the traditional transistor technology is becoming a bottleneck, spintronics and quantum information science stand out as two promising candidates to innovate our current computing and storage concepts. The combination of these two fields can allow us to take advantages of both fields to build solid-state platforms for studying quantum phenomena and performing multi-functional quantum information tasks. However, their interaction was limited because of the different properties of classical magnetization in spintronics and quantum qubit in the quantum information. The situation is changing with the progress of magnonic spintronics, which manipulates the collective magnetic excitation so-called magnons, and fits neatly with continuous variable quantum information. In the SPINCAT project, I will provide a route to bridge the two fields by examining the generation and manipulation of the magnonic Schrödinger cat state in the continuous variable quantum information science. In particular, I will (i) generate and manipulate of magnonic cat state in magnetic ordered systems driven by parametric pumping, (ii) ascertain its robustness under the influence of magnon-photon and magnon-magnon scattering, (iii) detect this nonclassical state by coupling it to the cavity photons, and (iv) identify its applications in quantum computing and quantum teleportation. The SPINCAT is an original, novel and highly interdisciplinary project covering spintronics, quantum optics and quantum information. The successful implementation of this project will significantly broaden the horizon of each subfield, and fertilize the on-going topics in magnonic spintronics in particular. Further, the training and skills acquired in this project would increase my competence in academics and boost myself to become a mature researcher.

Keywords: magnons,schr dinger cat
iMOTED Platform Built to improve Clinical Trial outcomes (iMOTED)

Framework: Horizon 2020 — Industrial Leadership
Programme: Innovation in SMEs
Action type: SME instrument
Countries involved: Spain
Call: SME instrument (H2020-SMEInst-2018-2020-1, 2018)
Start date: 2018-08-01
End date: 2018-12-31
Duration (months): 5.0
Total project cost (EUR): 71429.0
EU funding (EUR): 50000.0
Participants: 1
Project status: CLOSED

Clinical Trials (CT) are designed to prove if a drug, device or therapy is safe and effective in the human body, so they are already tested in individuals. The CT investigators and sponsors spend great amount of resources on data management and project and data quality control. In 2017 more than 120,000 CT have been registered, of which near 31,000 are carried out in the EU. Usually the average duration of CT from start to marketing is 7.5 years, however, more than 80% of CT are delayed from 1 to 6 month costing to the companies upwards of 30,000 € per day per trial. In most of the cases, this delay is due to inefficient management systems. With CT conducted in over 140 countries, the complexity and rate of change in trials is increasing. Considering this huge business opportunity, we have been working in a customizable software system to manage and simplify CT development. iMOTED platform will ensure high quality data, collected from multiple sources by using real time analysis of data, a simple and intuitive interface, generation of real time alarms employing estimations, predictions & simulations In this way, we expect to reduce the economic losses that pharma industry has when launching a new drug, for whom only 2 out of 10 marketed drugs return revenues that exceed R&D costs. iMOTED belongs to the e-clinic market, which is forecasted to reach €7.6 Bn by 2022 growing at a CARG of 12.4% over the period 2017-2022. We will initially target Europe as our domestic market, to start selling the IMOTED licenses. We expect to have our breakeven point two years after the beginning of the project, a cumulative turnover of €13 M by 2022, that will give us a ROI of 560% in 2024. Hence, at this stage of development we believe that we need to perform a through feasibility study to assess for the challenges and tasks that we still must accomplish to launch iMOTED for what we are asking for EC support.

Keywords: clinical trials management system,mathematical methods
Retina Organoid Mechanobiology (ROMB)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Products and processes engineering
Panel description: Product and process design, chemical, civil, environmental, mechanical, vehicle engineering, energy processes and relevant computational methods
Countries involved: Germany
Call: ERC Starting Grant (ERC-2019-STG, 2019)
Start date: 2020-09-01
End date: 2025-08-31
Duration (months): 60.0
Total project cost (EUR): 1497175.0
EU funding (EUR): 1497175.0
Participants: 1
Project status: SIGNED

The retina carries signatures of neuronal diseases which have been linked to mechanical abnormalities, including Glaucoma and Alzheimer’s disease. Yet no biophysical retina model exists due to a cross-disciplinary challenge: While stem cell derived organoids mimic the retina in vitro, organoid research has been limited by large variations in cell and tissue organization. Mechanobiology, in turn, has revealed mechanical signals as essential players in regulating cellular behavior to guide organogenesis. Accordingly, the ball is in the court of physicists and bioengineers to quantify those mechanical signals and shape tissue growth by tailoring the physical interactions of cells with their environment. Finally, the functionality of the retina has to be quantified via neuroscience techniques. This multifaceted challenge has prevented the establishment of the retina organoid as a biophysical model. ROMB introduces a biophysical model for the retina which I will use to model Alzheimer’s disease in vitro. It will be built on 4 cross-disciplinary posts: (i) retina organoids as a physiological in vitro model, (ii) tissue mechanics measurements, (iii) neuronal activity readout and (iv) disease modeling. First, I will reveal the mechanical building plan of retina organoids using ferrofluid droplets as mechanical actuators, hereby opening the field of organoid mechanobiology. In a second step, the organoid’s 3D neuronal function will be recorded using lightsheet microscopy. Mechanical, functional and genetic access will allow me in a final step to detect and manipulate Alzheimer’s disease: using mouse retina organoids with a mutation in the App gene, I will mechanically characterize the formation of those peptide aggregates which are the hallmark of disease onset. ROMB opens the door to engineering functional retinas in vitro. Moreover, it will be uniquely suited to tackle mechanically related neuronal diseases and promises a breakthrough for basic and applied research.

Keywords: tissue mechanics,neuronal network,retina organoid,alzheimer s disease
Analysis of the European energy system under the aspects of flexibility and technological progress (REFLEX)

Framework: Horizon 2020 — Societal Challenges
Programme: Secure, clean and efficient energy
Theme: Robust decision making and public engagement
Action type: Research and Innovation actions
Countries involved: Germany,Germany,Italy,Germany,Poland,Sweden,Switzerland,Netherlands
Call: Modelling and analysing the energy system, its transformation and impacts (H2020-LCE-2015-2, 2015)
Start date: 2016-05-01
End date: 2019-04-30
Duration (months): 36.0
Total project cost (EUR): 3285530.0
EU funding (EUR): 2779700.0
Participants: 9
Project status: CLOSED

The future energy system is challenged by the intermittent nature of renewables and requires therefore several flexibility options. Still, the interaction between different options, the optimal portfolio and the impact on environment and society are unknown. It is thus the core objective of REFLEX to analyse and evaluate the development towards a low-carbon energy system with focus on flexibility options in the EU to support the implementation of the SET-Plan. The analysis are based on a modelling environment that considers the full extent to which current and future energy technologies and policies interfere and how they affect the environment and society while considering technological learning of low-carbon and flexibility technologies. For this purpose, REFLEX brings together the comprehensive expertise and competences of known European experts from six different countries. Each partner focusses on one of the research fields techno-economic learning, fundamental energy system modelling or environmental and social life cycle assessment. To link and apply these three research fields in a compatible way, an innovative and comprehensive energy models system (EMS) is developed, which couples the models and tools from all REFLEX-Partners. It is based on a common database and scenario framework. The results from the EMS will help to understand the complex links, interactions and interdependencies between different actors, available technologies and impact of the different interventions on all levels from the individual to the whole energy system. In this way, the knowledge base for decision-making concerning feasibility, effectiveness, costs and impacts of different policy measures will be strengthened, which will assist policy makers and support the implementation of the SET-Plan. Stakeholders will be actively involved during the entire project from definition of scenarios to dissemination and exploitation of results via workshops, publications and a project website.

Keywords: set plan,policy measures,modelling tool,environmental and social life cycle assessment,experience curve,electricity,heat,mobility,low carbon technologies,flexibility option,energy scenario assessment
Translational and Transdisciplinary research in Modeling Infectious Diseases (TransMID)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator 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: Belgium,Belgium
Call: ERC Consolidator Grant (ERC-2015-CoG, 2015)
Start date: 2016-10-01
End date: 2021-09-30
Duration (months): 60.0
Total project cost (EUR): 1639168.0
EU funding (EUR): 1203485.0
Participants: 2
Project status: CLOSED

TransMID focuses on the development of novel methods to estimate key epidemiological parameters from both serological and social contact data, with the aim to significantly expand the range of public health questions that can be adequately addressed using such data. Using new statistical and mathematical theory and newly collected as well as readily available serological and social contact data (mainly from Europe), fundamental mathematical and epidemiological challenges as outlined in the following work packages will be addressed: (a) frequency and density dependent mass action relating potential effective contacts to transmission dynamics in (sub)populations of different sizes with an empirical assessment using readily available contact data, (b) behavioural and temporal variations in contact patterns and their impact on the dynamics of infectious diseases, (c) close contact household networks and the assumption of homogeneous mixing within households, (d) estimating parameters from multivariate and serial cross-sectional serological data taking temporal effects and heterogeneity in acquisition into account in combination with the use of social contact data, and (e) finally the design of sero- and social contact surveys with specific focus on serial cross-sectional surveys. TransMID is transdisciplinary in nature with applications on diseases of major public health interest, such as pertussis, cytomegalovirus and measles. Translational methodology is placed at the heart of TransMID resulting in the development of a unifying methodology for other diseases and settings. The development of a toolbox and accompanying software allow easy and effective application of these fundamentally improved techniques on many infectious diseases and in different geographic contexts, which should maximize TransMID’s impact on public health in Europe and beyond.

Keywords: infectious disease epidemiology,vaccination,outbreak risk
3D Reloaded: Novel Algorithms for 3D Shape Inference and Analysis (3D Reloaded)

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: Germany
Call: ERC Consolidator Grant (ERC-2014-CoG, 2014)
Start date: 2015-09-01
End date: 2020-08-31
Duration (months): 60.0
Total project cost (EUR): 2000000.0
EU funding (EUR): 2000000.0
Participants: 1
Project status: CLOSED

Despite their amazing success, we believe that computer vision algorithms have only scratched the surface of what can be done in terms of modeling and understanding our world from images. We believe that novel image analysis techniques will be a major enabler and driving force behind next-generation technologies, enhancing everyday life and opening up radically new possibilities. And we believe that the key to achieving this is to develop algorithms for reconstructing and analyzing the 3D structure of our world. In this project, we will focus on three lines of research: A) We will develop algorithms for 3D reconstruction from standard color cameras and from RGB-D cameras. In particular, we will promote real-time-capable direct and dense methods. In contrast to the classical two-stage approach of sparse feature-point based motion estimation and subsequent dense reconstruction, these methods optimally exploit all color information to jointly estimate dense geometry and camera motion. B) We will develop algorithms for 3D shape analysis, including rigid and non-rigid matching, decomposition and interpretation of 3D shapes. We will focus on algorithms which are optimal or near-optimal. One of the major computational challenges lies in generalizing existing 2D shape analysis techniques to shapes in 3D and 4D (temporal evolutions of 3D shape). C) We will develop shape priors for 3D reconstruction. These can be learned from sample shapes or acquired during the reconstruction process. For example, when reconstructing a larger office algorithms may exploit the geometric self-similarity of the scene, storing a model of a chair and its multiple instances only once rather than multiple times. Advancing the state of the art in geometric reconstruction and geometric analysis will have a profound impact well beyond computer vision. We strongly believe that we have the necessary competence to pursue this project. Preliminary results have been well received by the community.

Keywords: 3d reconstruction,shape analysis,optimization
Regulation of membraneless organelles through phosphatase-DYRK kinase feedback (PhosphoMLO)

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: Life Sciences
Countries involved: Switzerland
Call: Individual Fellowships (H2020-MSCA-IF-2020, 2020)
Start date: 2022-09-01
End date: 2024-08-31
Duration (months): 24.0
Total project cost (EUR): 191149.44
EU funding (EUR): 191149.44
Participants: 1
Project status: SIGNED

As the demographics of Europe and other developed countries shift ever older, neurodegenerative diseases involving aberrant protein aggregation grow more common but still lack effective treatment options. In healthy eukaryotic cells, the reversible weak aggregation of proteins and RNAs is necessary for the formation of condensates known as membraneless organelles. The roles of these condensates are still under investigation but may include concentrating proteins to facilitate reactions and buffering protein availability in a variety of cellular pathways. Identifying the molecular regulators of condensate assembly and maintenance is important to understand the transition from reversible to irreversible aggregation during disease and to determine potential therapeutic targets. The host lab has found that sufficient concentrations of the kinase DYRK3 trigger the dissolution of condensates, including splicing speckles, the pericentriolar matrix, and stress granules, by phosphorylating their component proteins. While in C. elegans, the serine/threonine phosphatase PP2A plays a crucial role in the assembly of membraneless organelles by dephosphorylating the substrates of the DYRK family kinase MBK-2, little is known about dephosphorylation of DYRK3 substrates in human cells or the regulation of DYRK3 activity. I hypothesize that feedback between DYRK3 and a phosphatase controls cycling of DYRK3 and its substrates between membraneless organelles and a dilute phase. I will apply interdisciplinary approaches including genetic perturbations, biochemical experiments, imaging, and mathematical modelling to address this hypothesis, in the process uncovering key regulators of condensate formation, emergent properties of feedback regulation, and a new mechanism for the regulation of phase-separated compartments.

Keywords: membraneless organelles,systems biology,mathematical modelling,phosphorylation,phase separation,feedback network,protein aggregation
The evolutionary dynamics of pathogen emergence and establishment: from Reservoir Detection to Outbreak Control (ReservoirDOCs)

Framework: Horizon 2020 — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: Environmental Biology, Ecology and Evolution
Panel description: Ecology, biodiversity, environmental change, evolutionary biology, behavioural ecology, microbial ecology, marine biology, ecophysiology, theoretical developments and modelling
Countries involved: Belgium,United States,United Kingdom
Call: ERC Consolidator Grant (ERC-2016-COG, 2016)
Start date: 2017-08-01
End date: 2023-07-31
Duration (months): 72.0
Total project cost (EUR): 1810576.0
EU funding (EUR): 1311279.14
Participants: 3
Project status: SIGNED

Extracted evolutionary and epidemiological information from pathogen genomes has grown into an important instrument across infectious disease research. By harnessing such information, molecular epidemiologists aim to shed light on the origin and epidemic history of pathogens, from reservoir dynamics to emergence and adaptation to new hosts, and their spatiotemporal spread. However, despite the revolution in genome sequencing technologies and advances in statistical methodology, key questions about pathogen emergence and establishment in human populations remain unresolved for major viral epidemics. When confronted with new viral outbreaks, such as the recent devastating Ebola virus epidemic, we also struggle to deploy these technologies in a systematic and concerted way despite a critical need to support public health interventions. In this project, we propose to unravel crucial steps in the emergence and establishment of key viral pathogens. We will scrutinise the reservoir dynamics of HCV by sequencing complete hepacivirus genomes from infected samples emerging from a large-scale screening of African rodents, and analyze the cross-species transmission history using novel evolutionary methods that accommodate spatial and temporal variability in selective pressures. To test hypotheses about the early establishment of HIV-1, we will carve a genomic window into the past epidemic history of the virus by integrating molecular work on archival samples from Central Africa and on samples representative of the current HIV-1 diversity, with the development of ancestral recombination graphs that accommodate dated tips and spatial diffusion, as well as population dynamic models that incorporate epidemiological information. Finally, we will take the recent Ebola epidemic in West Africa as a model to develop high-performance statistical approaches for extracting practical and timely epidemiological information from virus genome sequences during epidemics as they unfold.

Keywords: emerging infectious diseases,molecular epidemiology,bayesian inference