Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
Revolutionary Accuracy in waVeguide- and photoacoustic-ENabled atmospheric sensors (RAVEN) (RAVEN)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Digital
Destination: Digital & Emerging Technologies for Competitiveness and Fit for the Green Deal
Action type: Research and Innovation actions
Partnership: Photonics (co-programmed)
Countries involved: Finland,France,Italy,Poland,Spain,United Kingdom
Call: Pervasive photonics - multi-technology integration for digital infrastructure, sensors and internet of things (Photonics partnership)(RIA) (HORIZON-CL4-2023-DIGITAL-EMERGING-01, 2023)
Start date: 2024-06-01
End date: 2028-05-31
Duration (months): 48.0
Total project cost (EUR): 4813147.5
EU funding (EUR): 4813147.5
Participants: 18
Project status: SIGNED

Anthropogenic greenhouse gas (GHG) emissions and deteriorating air quality are driving climate change and severely impacting human and ecosystem health, respectively. To combat these issues, new and more stringent green regulations are being implemented globally, which existing air monitoring systems are not well equipped to handle. Currently available commercial sensors are expensive, bulky, and frequently require shelter and power from the mains. Field performance also often falls lower than required due to high signal noise and drift. Consequently, there is a need for new air pollution and GHG monitoring systems that offer improved sensitivity, precision, and accuracy while also being inexpensive, compact, and energy efficient. RAVEN will develop the next generation of gas sensing systems, consisting of two miniaturised gas sensors implementing cutting-edge PIC technology, one in the VIS-SWIR range and one in the MIR range. These sensors will work in tandem across a broad wavelength range (600-3000 nm) to measure concentrations of multiple pollutants and GHGs, including CO2, CO, O3, CH4, N2O, CH3OH, NH3, NO2 in 1-25 ppb LOD range. The sensors will leverage cutting-edge science, including developing a high-power compact dual-supercontinuum source on a chip and on-chip data analysis using a quantum-inspired approach for improved LOD and selectivity of gases and to satisfy the performance, power consumption, size, and cost requirements of end users. RAVEN will offer an unparalleled, high-performance multi-sensing solution that can be packaged into a single near-universally applicable miniaturised system. The implementation of RAVEN technology will provide Europe with the necessary resources to ensure compliance with the EU Green Deal and enhance the photonic technology capabilities of the EU.

Keywords: photonics,mid ir,vis swir,ghg,air quality monitoring,air pollution,data processing,supercontinuum source,photoacoustics,waveguides
Best-in-class canceR dIaGnostic cHip for patient sTratification. (BRIGHT)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Challenges
Action type: EIC actions
Countries involved: Portugal
Call: Strategic Digital and Health Technologies (HORIZON-EIC-2021-ACCELERATORCHALLENGES-01, 2021)
Start date: 2022-08-01
End date: 2025-12-31
Duration (months): 41.0
Total project cost (EUR): 3568401.25
EU funding (EUR): 2497880.88
Participants: 1
Project status: SIGNED

Through advanced microengineering and nanotechnology, we have developed a proprietary microfluidic-based liquid biopsy device, the RUBYchip™ (PCT/EP2016/078406). This technology allows for the isolation of all types of CTCs, keeping them viable and enabling the analysis of their phenotypic, genetic and functional characteristics, enabling unprecedented frequent monitoring of cancer progression in a minimally invasive and cost-efficient way. Our chip isolates 70% of the very scarce CTCs from a 7.5mL blood sample of a cancer patient in less than 3 h and without the need of sample pre‐processing. This dramatic improvement in the sensitivity compared to competition is enabled by a unique microfilter network embedded in a microfluidic device that separates the CTCs from the healthy cells based on their size and deformability. Furthermore, the RUBYchip enables automation reducing inter-laboratory and inter-user dependence and ensuring reproducible analysis of CTCs.

Keywords: personalised medicine,microfluids,liquid biopsy,circulating tumour cells,non invasive monitoring,companion diagnostics,metastasis,cancer
Transformative Pediatric Brain Cancer Imaging using Integrated Biophysics-AI Molecular MRI (BabyMagnet)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Starting grants
Action type: ERC actions
Panel: Prevention,  Diagnosis and T reatment 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: Israel
Call: ERC STARTING GRANTS (ERC-2023-STG, 2023)
Start date: 2024-04-01
End date: 2029-03-31
Duration (months): 60.0
Total project cost (EUR): 1497669.0
EU funding (EUR): 1497669.0
Participants: 1
Project status: SIGNED

Despite vast drug development efforts, brain tumors remain the leading cause of pediatric cancer deaths. Noninvasive monitoring of treatment response is crucial to reveal the mechanisms behind tumor-drug interactions and optimize patient care. However, standard magnetic resonance imaging (MRI) methods involve injecting metals, have severe difficulties in differentiating treatment response from tumor progression, are qualitative, and mandate prolonged anesthesia due to the lengthy acquisition. I propose to develop a transformative molecular MRI technology, based on the chemical exchange saturation transfer (CEST) contrast mechanism that will enable specific, quantitative, rapid, contrast-material free, treatment monitoring of pediatric brain cancer. Recently I revealed that a combination of mathematical CEST models and AI can generate quantitative biomarker maps of pH and protein concentration changes across the brain, two known hallmarks of cancer. Inspired by these results, I now propose to adopt a previously unconsidered perspective and to represent the underlying physics of CEST MRI as a computational graph, enabling an automatic AI-based optimization of molecular imaging. I hypothesize that the combination of biophysical models with a new AI framework, and their synergetic integration throughout the entire imaging pipeline will provide accurate noninvasive treatment monitoring. First, I will establish a method for automated optimization of MRI protocols for early determination of the tumor response to mainstream chemotherapy. Next, I will shorten the 3D scan time by an order of magnitude and quantify the response to next generation immunotherapy. Third, I will translate the method to clinical scanners and validate it in a human pediatric pilot study. This research will yield a fundamental understanding of the molecular mechanisms underlying treatment response and establish an innovative precision medicine methodology that will transform pediatric cancer imaging.

Keywords: medical imaging,machine learning,cancer imaging,treatment response,ai,mri,chemical exchange saturation transfer,molecular imaging,quantitative imaging,ph,car t cell,chemotherapy
The MANOSphere Pill: Pathways of Boys and Men into Online Male Supremacism in Portugal and Ireland (MANOS)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Ireland,Portugal,Brazil
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2025-08-01
End date: 2028-01-31
Duration (months): 30.0
Total project cost (EUR): 249618.0
EU funding (EUR): 249618.0
Participants: 4
Project status: SIGNED

This research intends to explore the discourses and social dynamics constructed on social media by manosphere groups, particularly Pickup Artist, InCel, and MGTOW communities, as well as its roots and if these discourses are successfully imported to the Portuguese and the Irish contexts, comparing both. The study will focus on the gender identity narratives created by men who identify with these groups or singular influencers with similar discourses. Pickup Artists and MGTOWs share the red pill theory which is characterized by a rejection of “the mainstream beliefs around gender”, i.e., the views of liberal feminists whom they believe are marginalizing men. To deal with it, they advocate for individual self-improvement and reject political correctness, and INCELs use the term "black pill" to describe the belief that there is no hope for them to have a romantic/sexual relationship, which can lead to radicalisation and support for violence against women. The main goal of this research project is to examine the construction of narratives about gender in Portuguese and Irish communities of men online; to explore how these communities represent and construct their identity, often through discourses of anti-feminism and misogyny, and how these representations vary across social media platforms and geographical contexts. MANOS will be informed by Critical Theory (Discourse, Narrative, Gender & Media Studies). The project will use a mixed-method approach that combines systematic literature review, critical discourse analysis & digital ethnography (non-participant observation, in-depth interviews & focus groups) to analyse the data collected from both online & offline environments. The research will ultimately identify and develop strategies to counteract the negative effects of these communities, promote gender equality, and the prevention of misogynistic violence by informing public educational policies about internet usage.

Keywords: masculinities,online communities,anti feminism misogyny sexual violence
Artificial Intelligence for early detection of non-communicable disease risk in people with breast cancer (ARTILLERY)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Health
Theme: Health
Destination: Staying Healthy in a rapidly changing society
Action type: Research and Innovation actions
Countries involved: Netherlands,Denmark,Slovenia,Germany,Portugal
Call: Trustworthy artificial intelligence (AI) tools to predict the risk of chronic non-communicable diseases and/or their progression (HORIZON-HLTH-2022-STAYHLTH-01-two-stage, 2022)
Start date: 2023-05-01
End date: 2028-04-30
Duration (months): 60.0
Total project cost (EUR): 5704756.25
EU funding (EUR): 5704756.25
Participants: 12
Project status: SIGNED

The ultimate ambition of the ARTILLERY consortium is to enhance long term health of the growing population of breast cancer survivors by making optimal use of routine imaging for timely detection of actionable chronic conditions or their risk factors. ARTILLERY will develop trustworthy AI systems that allow robust and accurate risk prediction of common chronic conditions, including cardiovascular disease, chronic obstructive pulmonary disease, unfavorable body composition and osteoporosis. Implementation of these AI systems in routine care will provide healthcare professionals with objective and quantitative parameters of their patients’ individual chronic disease risks, permitting them to start prompt treatment and implement risk reducing strategies. Unique aspects of ARTILLERY include the continuous and close interaction between renowned computational scientists, influential breast cancer professionals and the largest breast cancer patient advocacy organisation in Europe, as well as direct access to a large and comprehensive Real-World Data infrastructure that includes CT scans and clinical data from >26.000 patients with breast cancer. This partnership will result in trustworthy AI systems for prevalent chronic conditions, relevant to breast cancer patients and physicians, and ready for implementation at radiotherapy workstations across Europe. ARTILLERY-manuals will be developed and made available to multidisciplinary tumour boards and will contain recommendations on how and when (not) to use AI systems in routine breast cancer care, and on optimal management of breast cancer patients identified to be at high risk of chronic conditions. At the end of the project, we will have augmented the understanding and perception of the public towards the use of AI systems in routine healthcare and empowered breast cancer patients to make targeted lifestyle changes based on their individual risk profile, thus improving their life expectancy and quality of life.

Keywords: breast cancer patients,breast cancer survivors,risk factors,prevention,cardiovascular disease,osteoporosis,lung disease,body composition,ct scans
Near-Infrared Photothermal Nano-CAR Immunotherapy mediated by engineered exosomes targeted to pancreatic cancer with mutated KRAS (NIR-NanoCAR)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Spain,Portugal
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2024-01-01
End date: 2025-12-31
Duration (months): 24.0
Total project cost (EUR): 165312.96
EU funding (EUR): 165312.96
Participants: 2
Project status: SIGNED

Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancers with a 5-year survival rate under 10%. Current treatments for PDAC are based on ineffective and unspecific drugs that cause hard side effects. Besides, new T cell-based immunotherapies are toxic and unsuccessful in most solid tumors, including PDAC. Activating KRAS mutations occur in almost all patients, but unfortunately, KRAS is difficult to target. This discouraging situation highlights the need to design orthogonal and innovative strategies that target different pro-tumoral axes, in order to increase the antitumor effect minimizing side effects. In NIR-NanoCAR project, we will develop a new concept of therapy, Near-Infrared (NIR) Photothermal Nano-CAR Immunotherapy (NIR-PNCI). To test this concept, we will fuse i) thermosensitive liposomes capable to mediate photothermal therapy by NIR, with ii) exosomes derived from mesothelin-CAR T cells armored with IL-12 (which maintain effector molecules from their parental cells) and loaded with siRNA targeted to mutated KRAS. We will explore the antitumor capability and the tumor microenvironment-reprograming mediated by the hybrid nanotherapy in a relevant murine PDAC model. If successful, this nanosystem will be a breakthrough with a paradigm shift in the strategy to design the next generation of nanoimmunotherapies for solid tumors.

Keywords: exosomes,liposomes,immunotherapy,nanomedicine,car t cells,mutated kras,pancreatic cancer
Dynamic control of Gaussian morphing structures via embedded fluidic networks (DynaMorph)

Framework: Horizon Europe — 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: France
Call: ERC STARTING GRANTS (ERC-2024-STG, 2024)
Start date: 2025-01-01
End date: 2029-12-31
Duration (months): 60.0
Total project cost (EUR): 1499601.0
EU funding (EUR): 1499601.0
Participants: 1
Project status: SIGNED

Transforming a flat plate into a doubly curved shell is not possible without distorting in-plane distances, as stated by Gauss in his seminal theorem. In natural morphogenesis, this strong geometrical constraint is overcome by differential growth in the tissues, which induces mechanical stresses and thus the buckling in a rich variety of shapes. Over the last decade, emerging approaches have embraced this paradigm to develop bioinspired synthetic responsive materials with in-plane distortions, and hence shape-morphing capabilities. However, despite rapid developments, current efforts primarily focus on programming the final equilibrium shape, overseeing the dynamical trajectory of the transformation but also the mechanics of the morphed structure. As a result, exciting biomedical applications perspective in minimally invasive surgery, rehabilitation and soft robotics remain so far elusive. Here, I aim to develop structures in which the shape, but also the mechanics and the dynamical deformation trajectory may be programmed in time. To do so, I propose to develop hybrid elastic plates embedding a network of fluid-filled cavities. First, I will generalise design principles to create unit cells that dispose of all six deformation modes (both in-plane and out-of-plane) when pressurized. Assembling such cells will enable univocal shape selection but also internal degrees of freedom to control the frustrated mechanics. Then, I will unravel the coupling between fluid viscosity and cavity geometry to spatially control the homogenized viscoelastic property of the material. The subsequent timescales will be finally used to program the dynamical deformation trajectory of the structure when submitted to a mechanical or fluidic load. Taken together, I propose to develop new experimental standards and theoretical frameworks to pave the way for the first fully controllable shape-morphing materials, with applications for adaptive peristaltic endotracheal cuffs in view.

Keywords: shape morphing,slender structures,mechanical instabilities,incompatible elasticity
Growing Europe's global tech Companies (EIC Scaling Club)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: Elevating the scalability potential of European business
Destination: Other destinations
Action type: Coordination and support actions
Countries involved: Bulgaria,Belgium,France,Portugal,Germany,Spain,Türkiye,United Kingdom
Call: EIC Scale Up 100 (HORIZON-EIC-2022-SCALEUP-01, 2022)
Start date: 2023-05-01
End date: 2026-10-31
Duration (months): 42.0
Total project cost (EUR): 7261952.09
EU funding (EUR): 6999452.1
Participants: 9
Project status: SIGNED

The EIC Scaling Club’s mission is to grow Europe’s tech success stories. It is to be the home where 100 selected European deep-tech scale-ups, their investors and stakeholders collaborate to develop market opportunities and contribute to a better world. It will deliver 6 sets of services to its members over a period of 3.5 years: - Engage the most active investors, corporations, agencies, clusters and media and mentors - Grow the value of the 100 selected member companies with a best-in-class venture mentoring programme; - Facilitate the financing, partnering and hiring of talent through a curated roadshow of events - Share the inspirational success stories of the scale-ups - Develop relationships with the key institutions at EU and Member States - Manage the Club to a self-sustainable future The Club is led by 6 complementary partners who believe that Europe is a technology and unicorn powerhouse with a purpose. Its deep tech sale-ups are at work to bring solutions to the world’s biggest challenges.

Keywords: scaleup,growth,unicorn
e-powerTrain prEdictive mAintenance using physics inforMed learnING (TEAMING)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Staff Exchanges
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: France,Denmark,Germany,Italy,Canada,United Kingdom,Portugal,Tunisia,Sweden,Estonia,Türkiye,United States
Call: MSCA Staff Exchanges 2022 (HORIZON-MSCA-2022-SE-01, 2022)
Start date: 2024-01-01
End date: 2027-12-31
Duration (months): 48.0
Total project cost (EUR): 1395771.43
EU funding (EUR): 1283400.0
Participants: 16
Project status: SIGNED

Mobility electrification plays a critical role in the economy decarbonisation, and we are on the edge of an industrial revolution linked to the massive deployment of the electric vehicle (EV). Their technologies readiness level has significantly increased, and the EV can now replace the thermal vehicle in terms of service provided, supporting the EU decarbonisation effort. Besides the reduction of critical material, and decrease of cost, optimising the lifetime of the EV components is essential to ease their adoption, especially the powertrain sub-components that have the major impact on EV cost and CO2 emissions. A new-generation of diagnostic and prognostic systems for the powertrain will be a game changer to ensure EV adoption, because they will estimate its degradation, anticipate failures, and ease reparability thus extending its lifespan. With significant improvement of sensors, complex modelling and data processing methods such as Artificial Intelligence (AI), predictive maintenance (PdM) has gained a lot of interest in different fields. Development of PdM methods for the sub-components of the EV powertrain (battery, fuel cell, e-motor, power electronics) is at the heart of TEAMING. Thanks to international staff exchanges, TEAMING will significantly improve the different facets of the PdM solution: sensors, modelling, Digital Twins, adapted AI, and Physics-Informed Machine Learning methods are at the centre of the studies and present a major potential in term of innovation. TEAMING will advance PdM system to better diagnose the internal physical phenomena of the different EV powertrain components and optimise their performance, lifetime, safety, and reliability.”

Keywords: predictive maintenance,powertrain,battery,fuel cell,e motor,electrical motor,sensors,electrical vehicle,life cycle assessment,lca,physics informed ai,digital twin,dt,modeling