Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PolaritonPixels (Horizon Europe, appel 2025, Proof of concept grants)
Entité participante : Université de St Andrews — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Fluorescence microscopy is a fundamental tool in biomedical research, pharmaceutical development, and clinical diagnostics, yet conventional systems remain costly, bulky, and impractical for scalable or portable applications. PolaritonPixels introduces a lensless multicolour fluorescence imaging platform that integrates arrays of narrow-band polariton filters directly onto CMOS imaging chips, eliminating the need for traditional bulky optics and filter wheels. This breakthrough enables simultaneous spectral discrimination of multiple fluorophores in a compact, cost-effective, and scalable format, making high-quality multicolour fluorescence imaging more accessible for emerging applications such as high-throughput screening and point-of-care diagnostics. This 18-month project will advance PolaritonPixels from TRL 2-3 to TRL 4, demonstrating a fully functional prototype with validated multicolour fluorescence imaging performance. The system will be optimized to ensure precise spectral separation, high signal-to-noise ratio, and stable imaging performance across diverse biological applications, including live-cell imaging, tissue-scale fluorescence analysis, and multiplexed assays. By addressing key technical challenges and validating the technology’s real-world applicability, the project will position PolaritonPixels as a novel alternative to traditional fluorescence microscopy. By significantly reducing cost, complexity, and footprint while maintaining high imaging performance, PolaritonPixels has the potential to democratize microscopy, enabling broader adoption in biomedical research, pharmaceutical development, and decentralized diagnostics. The project will lay the foundation for further commercialization and scale-up, supporting an EIC Transition application to bring this disruptive imaging technology to market.
Projet ERC : HYMATE (Horizon Europe, appel 2025, Proof of concept grants)
Entité participante : Université de Saragosse — Pays : Espagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Tissue decellularization is a well-established technique in tissue engineering to preserve the biochemical complexity of native tissues. However, its application in recreating the tumor stroma for in vitro studies remains limited, with current models often relying on non-specific extracellular matrices that lack the unique characteristics of the tumor microenvironment. Here, we present a novel technology to develop hydrogels from decellularized tumor tissue using a tumor cell culture-derived matrix. This new technology, developed as part of the ERC project ICoMICS, improves the preservation of the composition of the matrix, in contrast to currently available alternatives. Hence, this technology creates a market opportunity to improve the development of hydrogels not only for cancer modeling, but also for a wide range of potential applications in disease modeling and regenerative medicine. In addition, by leveraging our extensive expertise in hydrogel characterization, we will expand our products not only for the production of specific hydrogels, but also for the characterization of all types of hydrogels according to the specific needs of potential users. Therefore, the main objective of this proof of concept is to assess the potential of this project to evolve into a spin-off company focused on: 1) commercializing novel hydrogels for tumor and disease modeling, and 2) providing potential customers with a wide range of accessible and thorough characterization methods. In addition, we aim to assess the market opportunities for both the commercialization of our hydrogel products and the establishment of a specialized characterization service providing in-depth physicochemical analysis of biomaterials for research groups and industry stakeholders.
Projet ERC : NutriCells (Horizon Europe, appel 2022, Proof of concept grants)
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Global food shortage together with economical stress poses a nutritional threat to various populations. For elders, food shortage affects health and well-being and is directly associated with immune and neurological deficiencies. Synthetic cells (SC) – lipid-based vesicles composed of essential fatty acids and loaded with immune-supporting vitamins and nutrients have been suggested as economical nutritional supplements that can be produced at large-scale and integrated into generic food matrices to improve their nutritional value. In this research program, we propose to develop nourishing SC targeted to deficiencies of the immune and neurological systems, to support the aging body.
Projet ERC : easi-IPMN (Horizon Europe, appel 2023, Proof of concept grants)
Entité participante : Université Vie-Santé Saint-Raphaël — Pays : Italie — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 115000.0 €

Pancreatic Ductal Adenocarcinoma (PDAC) is a lethal cancer with rising global incidence and poor survival rates. Early PDAC diagnosis is hampered by non-specific symptoms and by the absence of reliable early biomarkers. On the other hand, intraductal papillary mucinous neoplasms (IPMNs), precursor lesions of PDAC, are commonly found during abdominal imaging. IPMN management lacks consensus, leading to inefficient decisions decisions on empirical assessments of high-risk stigmata (HRS) and worrisome features (WF). There is an urgent need for precise IPMN patient classification to guide personalized treatment decisions, reducing unnecessary surgeries and late interventions.  Our ERC-StG project identified a gene signature marking pre-neoplastic cells in PDAC precursor lesions. We propose testing this signature as a biomarker for PDAC in IPMN patients, to distinguish those at high-risk or low-risk of progressing to invasive carcinoma. Successful validation of the signature as a biomarker holds benefit clinical management of IPMN patients, mitigating the economic and societal consequences of over-treatment and under-treatment. At the same time, these activities should advance early detection in pancreatic cancer. Our multidisciplinary approach and groundbreaking discoveries put us in the best position to tackle this key challenge in immuno-oncology.
Projet ERC : UR4energy (Horizon Europe, appel 2024, Proof of concept grants)
Entité participante : NTNU Technology Transfer (Norway) — Pays : Norvège — Rôle : Partner
Type d'entité : Organismes privés (hors enseignement)
Financement ERC de l'entité : 10000.0 €

The renewable energy input in the grid is not sufficient to cover the European energy demand, which largely still depends on fossil fuels. To reach the goal of climate neutrality by 2050, Europe needs to diversify and improve the adoption of renewable energy technologies. A yet-untapped source of energy can be found in the ocean. While wave and tidal energy have been explored, the reliable and predictable vortex wake energy has not been harvested yet as a renewable energy source. UR4energy will tap into this energy source by developing an efficient way to harvest it by using Underwater Robots. In this project, Prof. Pettersen will prove the technical and commercial feasibility of an underwater robot for ocean energy harvesting. Prof. Pettersen’s group will integrate the expertise of two partners, i.e., Inventas AS and NTNU Technology Transfer AS, for the development of the prototype and the monitoring of the patent landscape, respectively. UR4energy contributes to the ocean energy market, one of the fastest growing renewable energy markets (CAGR 2022-2030 = 33.5%) with a versatile technology that has the potential to support the EU’s independence from fossil fuels, while contributing to research on robotics and autonomy for underwater robots.
Projet ERC : Real-Database-PIM (Horizon Europe, appel 2023, Proof of concept grants)
Entité participante : Technion - Institut de technologie d'Israël — Pays : Israël — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

In the contemporary digital era, relational databases play a pivotal role in business applications, facilitating the management and analysis of intricate data sets in diverse sectors including healthcare, finance, and social media platforms. These databases comprise relations represented as sets of records and attributes, allowing for detailed data scrutiny and insightful business decision-making. However, the prevalent model of data analysis is beleaguered by lengthy execution times and considerable energy consumption due to the separation of data processing and storage, necessitating hefty computational investments.  Addressing this, we propose an innovative approach leveraging processing-in-memory (PIM) techniques, specifically bulk-bitwise PIM, to hasten analytical processing in relational databases. Grounded in emergent nonvolatile memristive memory technologies, this method capitalizes on memory cell arrays for concurrent data processing and result storage, markedly diminishing data movement and consequently, time and energy expenditure. Our endeavor is to craft the memristive memory processing unit (mMPU), originally developed during the PI's ERC StG Real-PIM-System project, adept at accelerating relational database analysis, promising to deliver a computing system that is tenfold faster and a hundred times more energy-efficient at a fraction of the current cost, revolutionizing data analysis and offering substantial savings in both time and financial resources.
Projet ERC : IMMUNO-MONITORING (Horizon Europe, appel 2022, Proof of concept grants)
Entité participante : Istituto Nazionale Biostrutture e Biosistemi — Pays : Italie — Rôle : PI
Acronyme de l'entité : INBB
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

During the initial part of the ERC-Consolidator Grant PRO-TOOLKITS we have successfully demonstrated a novel approach for antibodies detection. The platform uses antigen-conjugated synthetic DNA strand to achieve the rapid and inexpensive detection of target antibodies. Our platform offers several advantages (low-cost, single-step, rapid) in comparison of other methods for antibody detection and is so versatile that can be used also for the detection of Bispecific Antibodies (BsAb). On the basis of interactions with pharmaceutical companies and following a market analysis we have found that there is a growing need for similar approaches that can allow to monitor the efficacy of immunotherapies. This is especially true for immunotherapies using BsAb as there are no standard analytical methods for these targets. Given these considerations, the goal of this project is to evaluate the commercial potential of our innovative platform for immunotherapy efficacy monitoring with particular focus on the detection and characterization of BsAb. During the project we will 1) Fully characterize the DNA-based antibody sensor for the detection of a model BsAb (Anti EGFR/Anti HER2 BsAb) in terms of analytical performances (i.e. sensitivity, specificity, stability etc.) with direct comparison with other used techniques; 2) Prepare a Manufacturing Plan for producing/testing the Ab-switch; 3) Establish an IP strategy for patent filing and maintenance; 4) Determine a business and commercialization planning.
Projet ERC : EOFLIM (Horizon Europe, appel 2022, Proof of concept grants)
Entité participante : Université de Vienne — Pays : Autriche — Rôle : PI
Acronyme de l'entité : Uni Wien
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Fluorescence Lifetime Imaging Microscopy (FLIM) is a powerful method for monitoring physicochemical parameters of cells and tissues, as well as biomolecular interactions, with applications in science, medicine, and industry. However, its use is currently limited due to technological constraints regarding frame rate and sensitivity.  We have developed a FLIM detector that enables highly sensitive, high-speed FLIM. It is based on the use of electro-optical elements as temporal gating units. Electro-optical FLIM (EOFLIM) enables frame rates beyond 100 Hz for megapixel images, single-molecule sensitivity, and high-resolution imaging (numerical aperture > 1.3).  We will demonstrate the innovation potential of our detector in two key applications: Super-resolution FLIM and Surgical FLIM. Super-resolution FLIM will be done in collaboration with Prof. Huser (Univ. of Bielefeld). We will apply our EOFLIM detector to super-resolution microscopy at high frame rates in live cells and tissues. Surgical FLIM will be done in collaboration with Prof Unterhuber (Medical Univ. of Vienna) and will aim at diagnosing cancerous tissue in brain biopsies. Super-resolution FLIM and Surgical FLIM will demonstrate the wide applicability of EOFLIM in research and medicine.
Projet ERC : FORTE (Horizon Europe, appel 2024, Proof of concept grants)
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : ICL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Software is the driving force of today's world. Used in almost any system, it has a wide-ranging impact on every area of private and public life, from health, to finance, education, entertainment, business, and government.  Developing software is a cognitively demanding task. Coming up with a software solution for a problem is already challenging, and continuous changes in requirements and in the environment where software is used make it even harder. As a result, bugs and security vulnerabilities are often introduced during software development. To make things worse, even when these issues are discovered and reported, many of them remain unfixed due to a lack of developer time.  Generative AI promises to change the game by being able to automatically repair code, but requires developers to validate that the proposed software fixes correctly address the issues, while simultaneously checking that they do not introduce unintended behaviour.  FORTE combines automated change-impact analysis with automated root cause analysis and AI-based repair to enable an AI-augmented process of developing software. Our goal with FORTE is to help developers confidently change software without breaking it in unexpected ways, and embrace generative AI to simplify the process of writing and fixing code. To demonstrate the usefulness of FORTE, we plan to use it with real-world software that is publicly available.
Projet ERC : STEDGate (Horizon Europe, appel 2023, Proof of concept grants)
Entité participante : Leibniz-Gemeinschaft — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : WLG
Type d'entité : Recherche
Financement ERC de l'entité : 50000.0 €

Neurological disorders have emerged as a significant global societal burden, exemplified by afflictions like Alzheimer's and Parkinson's, impacting over one billion individuals globally and surpassing the combined economic burden of cancer and diabetes. This has spurred a concerted global effort, with increased support for neuroscience research. These disorders often target deep brain regions and profoundly influence the structural connectivity of neuronal cells within functional circuits. Synapses, where neurons exchange information, exhibit plasticity, altering information transmission efficiency, shape, and position. Understanding the mechanisms underlying these structural changes, especially in neuronal circuits, remains limited in both healthy and affected individuals. The ERC PoC project STEDGate seeks to advance our understanding of neuronal connectivity and plasticity by developing STED-enabled holographic endo-nanoscopy for neuroscience. This ground-breaking technology promises atraumatic nanoscale in-vivo imaging of deep brain structures reaching depths up to 5 mm beneath the brain's surface. Collaborating with the start-up endeavour DeepEn, the team aims to facilitate the commercial transition of this technology. Making deep-tisue nanoscopy available globally will revolutionize our ability to monitor and understand neurological disorders and, ultimately, offer new avenues for intervention and treatment..
Projet ERC : CHARMS (Horizon Europe, appel 2025, Proof of concept grants)
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : ICL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

CHARMS aims to transform prenatal screening by developing novel normative representation learning (NRL) algorithms for ultrasound imaging and introducing them into clinical workflows, to enhance early detection of congenital heart anomalies. Addressing disparities in maternity outcomes and global shortages in sonography expertise, the project targets improving the detection of congenital heart disease (CHD), a common and often fatal congenital malformation with low antenatal detection rates. Building on the ERC MIA-NORMAL project, we will create robust out-of-distribution detectors specifically for ultrasound imaging and CHD, utilising comprehensive data, including videos, images, and patient characteristics. CHARMS tools will identify subtle abnormalities in motion patterns or anatomical changes, significantly enhancing CHD detection in practice. We will develop normality-focused models to confidently confirm normal development and malformations using ultrasound video data, design self-supervised anomaly detectors to identify 'unknown unknowns’ and equip models with generative capabilities to ensure trustworthiness and robustness against covariate shifts such as poor image quality or varying ultrasound scanners. Through generative techniques we will also validate and refine 3D+time representations of fetal cardiac anatomy, facilitating a comparative analysis with MRI data, further enhancing model precision. Additionally, CHARMS will explore correlations between non-imaging and imaging phenotypes, utilising knowledge distillation to align features with physiological textbook knowledge. This will generate synthetic scan variants that match clinical phenotypes, enabling a deeper understanding of disease mechanisms and the development of new image-based biomarkers. A Quality Assurance framework will be established to ensure model safety and robustness, complying with the EU AI Act, including protocols for rigorous validation against known physiological facts.
Projet ERC : Megabouts (Horizon Europe, appel 2025, Proof of concept grants)
Entité participante : Champalimaud Foundation — Pays : Portugal — Rôle : PI
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Thorough, quantitative analysis of behaviour is essential for advancing neuroscience and neurological disorder research and has the potential to significantly improve the characterization of phenotypes in genetic, pharmacological and toxicological screens commonly employed in the pharmaceutical and biotech industries. Achieving high-throughput screening, without compromising the richness of phenotypic data requires scalable, standardized and cost-effective solutions for behavioral recording that also allow seamless integration across labs. To address this need, we developed megabouts.ai (Jouary et al., Biorxiv, 2024) an AI-based pipeline for behavioral analysis capable of reliably inferring high-speed behavioral kinematics from diverse and low-resolution data sources. Complementing this, we have designed a low-cost, modular behavioral testing system optimized to leverage the strengths of the megabouts.ai pipeline, and enable sophisticated behavioral experiments compatible with high-throughput screening approaches. In this proposal, we will develop and validate these tools across a range of behavioral screening paradigms, exploring their potential applications in both basic and translational research. Our goal is to disseminate these innovations, promoting their effective use in academic and industry settings, unlocking new experimental possibilities and enhancing the capabilities of existing commercial and custom-built solutions.
Projet ERC : DART (Horizon Europe, appel 2025, Proof of concept grants)
Entité participante : Imperial College London — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : ICL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Capturing nature’s most fleeting moments, such as a lemur leaping, a peregrine falcon striking, or dragonflies dueling over water, has always relied on a mix of skill and luck. It also demands extensive setup and long waits in harsh environments. With Dynamic Automatic Region Tracking (DART), these moments become routine and much easier to capture.  DART revolutionizes nature cinematography with bioinspired algorithms and cutting-edge hardware. Using motorized mirrors to steer a camera’s view, it enables ultra-fast, high-resolution tracking of unpredictable subjects. The system integrates two cameras: a wide-angle search camera to detect action and a telephoto homing camera to capture it in stunning detail. Its bioinspired vision algorithm and controller enable low-latency, data-efficient, and energy-efficient continuous operation.  This project will refine DART’s tracking algorithms and hardware controls to create a modular, plug-and-play solution for applications in agri-tech, environmental monitoring, industrial automation, entertainment, and wildlife documentary production. Building on our strong academic expertise in robotics and biomechanics, DART is now advancing toward real-world demonstrations with early partners. By capturing what once seemed unfilmable, DART opens new frontiers in motion analysis and visual storytelling.

Mots-clés : visual tracking,bioinspired vision,nature documentary,motion capture,unmanned aerial system research