Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : EUDAIMONIA (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Liège — Pays : Belgique — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1497687.0 €

Despite significant advancements in European integration, the institutional design and organisation of administrative structures implementing and enforcing EU law had traditionally remained the responsibility of EU Member States. Over the past decade, however, EU legislation has increasingly come to impose more organisational requirements on those Member States’ administrative structures. That evolution is most remarkable as EU law has long recognised the existence of a principle of national institutional/administrative autonomy. That principle is to guarantee Member States’ freedom to designate and structure the administrative bodies responsible for the application and enforcement of EU rules. How far does the EU’s more extensive involvement in Member States’ administrative design decisions actually reach and can one find parallels between different fields of regulation? If so or if not, what are the implications for our understanding of institutional autonomy as a principle of EU (administrative) law? So far, legal scholarship, including the PI’s previous work on EU market supervision, has paid only scarce attention to those important questions. The principal objective of this project will be to analyse the scope of Member States’ administrative autonomy and to uncover, explain and conceptualise the limits that are imposed on it by EU law. To do so, it will first of all map and compare EU law’s influence over Member States’ administrative designs across 18 domains of regulation influenced by the EU. Since the traditional legal scholarship toolkit insufficiently allows to grasp the different factors having given rise to Member States’ administrative design decisions, the project will subsequently rely on actor-network theory (ANT) to uncover those factors. Using that particular research methodology, new and more extensive data obtained through in-depth case studies and questionnaires will allow to formulate theoretical modifications and policy recommendations.

Mots-clés : european union law,institutional,administrative autonomy,relationship with member states,principles of law,actor network theory,comparative law
Projet ERC : con-PDmode (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Technical University of Munich — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : TUM
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Despite the fact that there has been some progress in developing methods for estimating Parkinson’s disease (PD) symptoms using wearable sensors, these technologies have not sufficiently penetrated the market due to the usability of the system and its cost; existing technologies are constrained by specific hardware requirements or user activities, therefore aversively affecting the cost and usability of the technologies, respectively. Thus, Con-PDmode delivers a software prototype for control-oriented modelling and estimation of PD symptoms that are transparent and platform agnostic. The excellence in innovation potential for successfully bringing the PD assessment tool to the market is the capability to account for inaccuracies and uncertainty in the data collected from low-cost wearable sensors. To this purpose, we will adapt and implement advanced stochastic techniques for improved robustness in state estimation, the confidence level of the model estimation will be transparently communicated to its users. We will perform iterative tests in various environmental and sensor configurations to refine our algorithms as well as the user interface.

Mots-clés : machine learning,parkinson s disease,wearables,mhealth
Projet ERC : Cluster-Buster (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Physiology in Health, Disease and Ageing
Entité participante : University of Basel — Pays : Suisse — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Despite the great progress that has been made in treating cancer, metastasis remains incurable. Metastasis accounts for 8 million deaths per year worldwide and no agents are currently available to prevent the metastatic spread of cancer. The metastatic process begins with cancer cells leaving the primary tumor site and entering the blood circulation. In circulation, cancer cells are defined as circulating tumor cells (CTCs), and are typically found in the form of single CTCs or small CTC aggregates (CTC clusters). Upon dissemination and survival into distant organs, cancer cells give rise to proliferating metastatic lesions, which in turn can shed other CTCs and form additional metastases. While virtually all oncology-related drugs aim to kill cancer cells within a tumor, no drugs are available to target metastatic cells in circulation. As a consequence, no drugs are available to block or prevent the metastatic cascade. We recently discovered that CTC clusters are exceptionally efficient metastatic precursors, capable to initiate a metastasis 50-times better than single CTCs. Within our ERC Starting Grant Project Holding-Hands, through a screen with 2’456 FDA-approved compounds, we discovered those that enable the disaggregation of CTC clusters in breast cancer mouse models and consequently, lead to metastasis suppression. This exciting new discovery implies that targeting CTC clusters is now feasible, and that this approach is likely to delay or prevent metastasis formation in cancer patients. Thus, within this Proof of Concept application, we aim to screen and patent additional cluster-targeting compounds with higher efficacy and better safety profile, to establish a new company whose aim is to commercialize cluster-targeting molecules, and to prepare for clinical trials.

Mots-clés : circulating tumor cell clusters,cell cell junctions,signaling,drug screening
Projet ERC : IN2DIAG (Horizon 2020, appel 2016, Proof of concept grants)
Entité participante : Autonomous University of Barcelona — Pays : Espagne — Rôle : PI
Acronyme de l'entité : UAB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Despite the initial high expectations of genome variation studies, only a small proportion of the genetic risk of common and complex diseases has been identified so far. Most of the work has focused on single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). Inversions, on the other hand, are a type of structural variant that affects a large fraction of the human genome and is implicated in phenotypic differences in diverse organisms. However, they have been poorly studied because their specific characteristics make their detection especially challenging and how much they contribute to human diseases is not yet well known. As part of the INVFEST ERC Starting Grant, we have developed a novel high-throughput technique for genotyping multiple human inversions in hundreds of individuals, which opens new opportunities in the characterization of inversion functional effects and their association with diseases. The aim of the IN2DIAG project is to increase the value of this technology as an innovative diagnostic kit for human inversions that could be licensed to an industrial partner for its commercialization. To achieve that, the main goals are: (1) Carry out a proof of principle study of the association of inversions and 10 common diseases and other health-relevant traits to demonstrate the potential applicability of the technology; (2) Extend the current market research of inversion genotyping needs in a clinical setting and strengthen the contacts with potential licensees and end-user companies; and (3) Maintain the current IPR strategy and if necessary expand this protection with additional patents of possible new discoveries. Our project therefore involves a combined approach, strengthening both the scientific and commercial aspects of the technology, to bring to the market a new tool for the analysis of previously unknown genetic variants, helping to fulfill precision medicine promises.

Mots-clés : personal genomics,genetic variants,diagnostics,biomarkers,precision medicine
Projet ERC : MicroParticleControl (Horizon 2020, appel 2015, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Products and processes engineering
Entité participante : KU Leuven — Pays : Belgique — Rôle : PI
Acronyme de l'entité : KUL
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1500000.0 €

Despite the many advantages of microchemical systems and their successful applications in chemical engineering research, one major drawback greatly limiting their use is their susceptibility to channel clogging for flows containing particulate matter. Hence, the aim of the proposed research is to overcome the challenge of clogging in microfluidic devices and to design microfluidic systems that can tolerate particulate matter and synthesize solid materials according to their specifications (e.g. size, purity, morphology). To reach this goal, we apply a combined experimental and theoretical approach, in which the experimental results will lead to model development reflecting the particle formation and interaction kinetics and their coupling to the hydrodynamics. The novel concept of the proposal is to devise engineering strategies to handle the particulate matter inside the reactor depending on if the solid material is i) an unwanted and insoluble by-product of a reaction, or ii) the target compound (e.g. nanoparticle synthesis or crystallization of organic molecules). Depending on the case we will design different ultrasound application strategies and introduce nucleation sites to control the location of particle formation within the microchannel. This project will provide fundamental insight into the physico-chemical phenomena that result in particle formation, growth and agglomeration processes in continuous flow microdevices, and will provide a theoretical tool for the prediction of the dynamics of particle-particle, particle-wall and particle-fluid interactions, leading to innovative microreactor designs.

Mots-clés : microfluidics,clogging,particle formation,crystallization,two phase flow,micro bubbles
Projet ERC : PLATFORM (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Individuals, Markets and Organisations
Entité participante : Centre national de la recherche scientifique — Pays : France — Rôle : PI
Acronyme de l'entité : CNRS
Type d'entité : Recherche
Financement ERC de l'entité : 848750.0 €

Despite the obvious efficiency gains generated by platform intermediation, the last few years have witnessed a renewed concern about its impact on consumer welfare. The pricing practices in platform markets raise a number of challenges to economic theory and competition policy, which I plan to address in this research project. Several components of the project are envisaged: Drip Pricing and Missed Sales Drip pricing is the practice, common among online retailers, of advertising a basic price at the beginning of the purchase process, following which additional fees, only avoidable at a cost to consumers, are then incrementally disclosed or "dripped." I propose a theory to understand the determinants of drip pricing and study optimal regulation in a variety of contexts (card surcharging, shipping and booking fees, airline travel, etc). Intermediation Fees and Price Coherence While reducing search and transaction costs, many intermediaries are blamed for inflating prices through high intermediation fees and price coherence clauses, which prohibit firms from practicing lower prices on transactions not mediated by the platform. This project envisions building a theory of price setting by intermediaries and price-coherence clauses, with applications to the regulation of competing payments methods and online search and booking platforms. Many-to-Many Matching and the Welfare Effects of Customized Pricing Advances in information technology enabled matching intermediaries (e.g., advertising exchanges) to achieve high levels of targeting (making sure advertisers primarily reach the eyeballs of potential customers) and price customization (whereby prices are buyer-specific and are based on the entire consumption basket of a buyer). The aim of this project is to assess how centralized match-making qualitatively affects equilibrium outcomes, and evaluate the welfare effects of policies prohibiting intermediaries from practicing customized pricing.

Mots-clés : platform markets,two sided markets,regulation,pricing,intermediation fees,payment methods,price discrimination,search markets
Projet ERC : PROCEEDS (Horizon 2020, appel 2015, Proof of concept grants)
Entité participante : National Research Council — Pays : Italie — Rôle : PI
Acronyme de l'entité : CNR
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Despite the recent expansion and enormous potential of three dimensional (3D) microscopy and 3D scanning, these technologies currently suffer from two limitations: i) lack of unity: although both technologies aim to unveil the 3D features of a system, they are being developed completely independently, resulting in lower flexibility and higher costs; ii) lack of dynamics: today these technologies can barely be applied to fast moving systems; however, crucial microscopic traits are dynamical, and key industrial features as structural deformation, shear and stress, are induced by motion itself. PROCEEDS will explore the industrial potential of a completely novel software platform that can be applied to both 3D microscopy and 3D scanning under a single dynamical framework. This platform is based upon a very powerful 3D tracking algorithm that we developed within the ERC project SWARM. In this PoC we will turn this algorithm into a market-adjusted software to probe 3D complex dynamical structures in real life applications. We will test two commercialization paths: 1) 3DMICRO where the software is used for the control of multi-camera microscopes, providing the reconstruction of the 3D trajectories of microorganisms and colloidal particles, with impact on the health, processing and food industry. 2) DYSCAN: a new, non-invasive and accurate 3D scanning method of fast moving bodies, which turns swarms of passive tracers into distributed clouds of virtual accelerometers, thus measuring deformation, stress and vibration of structures under heavy dynamic loads, with impact on machine monitoring in energy, automotive and transportation industry.

Mots-clés : three dimensional  3d  tracking software,3d microscopy,3d scanning,machine monitoring,health industry,automated manufacturing
Projet ERC : OCAL (Horizon 2020, appel 2017, Advanced grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Systems and communication engineering
Entité participante : Board of the Swiss Federal Institutes of Technology — Pays : Suisse — Rôle : PI
Acronyme de l'entité : ETH Zurich
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2497058.0 €

Despite wide ranging progress on both the theory and applications of optimal control for more than half a century, considerable challenges remain when it comes to applying the resulting methods to large scale systems. The difficulties become even greater when one moves outside the classical realm of model based optimal control to address problems where models are replaced by data, or macroscopic behaviours emerge out of microscopic interactions of large populations of agents. To address these challenges, we propose here to develop a framework for approximating optimal control problems using randomised optimisation. The starting point will be formulations of optimal control problems as infinite dimensional linear programs. Our recent work suggests that randomised methods on the one hand can serve as a basis for algorithms to approximate such infinite programs and on the other enjoy close connections to statistical learning theory, providing a direct link to data driven approaches. Turning these intuitions into an approximation framework for optimal control that rests on solid theoretical foundations and provides explicit accuracy guarantees will be the methodological contribution of the proposed research. The resulting methods can find a range of applications in engineering and beyond; here we will investigate two such applications. One is motivated by our work on energy management in buildings and districts. The challenge here is the dimensionality of the system, especially if one would like to include weather and other forecast information and the corresponding uncertainty. The second application will be to so-called population systems, that involve the interaction of many agents with local decision-making capabilities coupled through the use of common resources. Here the main challenges are defining suitable "features" to abstract the individual states and the integration of uncertainty due to the presence of non-participating agents.

Mots-clés : approximate dynamic programming,randomised optimisation,distributed,systems,aggregative games,energy demand response,mobility
Projet ERC : VitaminBlock (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Molecules of Life: Biological Mechanisms, Structures and Functions
Entité participante : University of Groningen — Pays : Pays-Bas — Rôle : PI
Acronyme de l'entité : RUG
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Development of new antibiotics is crucial in future since antibiotic resistance is a rapidly growing problem, which severely threatens our ability to combat infectious diseases. Despite the numerous efforts by International Organisations and Governments, Pharmaceutical companies are reluctant to carry out the costly drug development, as the returns are uncertain and evolving drug resistance weakens their business case further. New solutions are thus called for. We have obtained fundamental insight in the mechanisms and proteins, which mediate uptake of multiple B-type vitamins that are indispensable for bacterial growth. The proteins are the only route for vitamin acquisition in many notorious pathogens such as Staphylococcus aureus and Streptococcus pneumoniae, against which novel antibiotics are urgently needed. Based on our breakthrough crystal structures, we have designed and synthesized molecules that allosterically inhibit the uptake of multiple vitamins. This has led to the discovery of several compounds having potential as antibiotic medicines. What is exciting, our approach enables to target specific pathogens, without affecting many beneficial strains, thereby being effective without causing adverse drug events, which is a major advantage compared to the traditional antibiotics. In the Proof of Concept project, we aim to explore the potential of the compounds for drug development and test them thoroughly, for obtaining important proof for potential partners and investors. In addition, we will carry out pre-commercialisation studies aiming at perfecting the commercialisation strategy, protecting the IP ad well as strengthen the network for the best possible commercialisation outcome. Given the technological and pre-commercial proof of concept will be successful, we are expecting our approach to raise a lot of interest in Pharmaceutical industry, racing to find new ways to tackle the antimicrobial resistance.

Mots-clés : antimicrobial compounds,medicinal chemistry,gram positive pathogens
Projet ERC : TheLiRep (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : Max Delbrück Center for Molecular Medicine — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MDC
Type d'entité : Recherche
Financement ERC de l'entité : 150000.0 €

Diabetes is a degenerative disease that affects over 350 million persons worldwide. Type 1 and type 2 diabetes are associated with either destruction or dysfunction of pancreatic insulin-producing β cells. Despite the availability of insulin as treatment to temporarily restore the glucostasis, this remedy is unable to avoid either the acute dangers of hypoglycemia or the long-term complications of hyperglycemia. Eventually, the challenge of treating diabetes centers on the replacement of pancreatic β cells. Due to serious organ shortage for pancreas transplantation, cell-based therapy represents the most promising option and different potential sources for new β cells are currently being explored, including embryonic stem cells and other cell types. A particularly attractive therapeutic strategy is to convert liver adult cells of diabetic patients into functional pancreatic β cells through lineage reprogramming. Fate conversion of liver to pancreas is conceivable for numerous physiological and developmental reasons, and, possibly, suitable for future clinical applications. My ERC-funded project (ERC Starting Grant “HEPATOPANCREATIC”) is focused on the molecular mechanisms underlying cellular plasticity between liver and pancreatic cells. This study has led to the identification of a novel factor, whose ectopic expression converts mouse liver cells into pancreatic cells. Here, we propose a defined and focused set of measures aimed at: 1) extending these findings in human liver cells to assess whether this strategy may be exploited to develop an autologous cell-based therapy of diabetes; and 2) elaborating a solid intellectual property strategy. The “TheLiRep” Proof of Concept (PoC) funding will ensure the full exploitation of the ERC idea and bridge the gap between my research and the earliest stage of a marketable innovation.

Mots-clés : cell therapy,liver,pancreas,lineage reprogramming,diabetes