Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : PIcelles (Horizon 2020, appel 2018, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Universitätsklinikum Aachen — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : UKA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

PIcelles will assess the commercial viability of a novel theranostic nanoformulation for anticancer therapy. Current nanomedicine platforms are not able to boost response rates and survival times due to two main reasons: (1) the high variability in the accumulation of nanomedicines in tumors and metastases; and (2) the poor tissue penetration of nanomedicines in tumors and metastases. Based on results of the ERC project NeoNaNo, we are developing an imageable and penetration-promoting PIcelles platform, which is based on polymeric micelles, that will tackle these challenges by incorporating three key features in one formulation: (1) chelators for radiolabeling, to enable patient pre-selection via non-invasive imaging of target site accumulation; (2) a novel peptide on the micelles’ shell, to allow for active targeting to the microenvironment in tumors and metastases, and also for active pharmacological promotion of nanomedicine penetration; and (3) facile, efficient and stable drug loading, with clinically relevant anticancer agents. In this project, we aim to generate technical and commercial proof-of-concept for our proprietary PIcelles platform technology, enabling us to enter into license deals with large pharmaceutical industries that are in need of novel breakthrough drug delivery technologies for their difficult-to-formulate anticancer agents.

Mots-clés : theranostic,nanomedicine,cancer,platform,tumour
Projet ERC : PROTEGO (Horizon 2020, appel 2015, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : Institutions, Governance and Legal Systems
Entité participante : University of Milan — Pays : Italie — Rôle : Partner
Acronyme de l'entité : UNIMI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 107436.0 €

PROTEGO arises out of a fundamental claim: procedural regulatory instruments have causal effects on the performance of political systems because they trigger accountability towards different stakeholders. The mix of policy instruments may be functional or dysfunctional, depending on how accountability mechanisms are combined. This project provides a theoretical rationale to capture the accountability effects by adopting an extension of delegation theory that considers multiple stakeholders. The theoretical framework will allow us to identify the key social mechanisms that make bureaucracies internalize the preferences of accountees. We will test the observable implications of the framework on outcomes that are crucial to the performance of political systems, such as trust in government, ease of business, control of corruption, sustainability. Empirically, we will collect, validate and analyze original data across the EU and its 28 Member States for the period 2000-2015, distinguishing between instruments that cover central departmental activity and independent regulatory agencies. The new dataset will cover administrative procedure acts, freedom of information, notice and comment, judicial review, impact assessment, environmental appraisal, and non-financial instruments for public spending accountability. These are the procedural instruments that enfranchise accountees. The bivariate relationship between a single instrument and outcomes explains little – because it’s the overall ecology or mix of instruments that produces causal effects. These ecologies combine in different sequences and paths associated with the outcome. Hence we will draw on a suitable methodological approach - Qualitative Comparative Analysis (QCA). Causality and diffusion across time will be also explored via event-history analysis and principal component analysis. PROTEGO will contribute to theories of regulation and accountability, and provide a robust operational model of data and analysis.

Mots-clés : policy instruments,public administration,regulation
Projet ERC : PredictingPain (Horizon 2020, appel 2017, Starting grants)
Domaine scientifique : Life Science
Panel : Neuroscience and Disorders of the Nervous System
Entité participante : Max Planck Society — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : MPG
Type d'entité : Recherche
Financement ERC de l'entité : 1499922.0 €

Pain is a burden for millions of people in terms of suffering, as well as for society in terms of costs. While it is well established that the perception of pain is not necessarily related to the amount of sensory input, a mechanistic framework for this is still lacking at the neurobiological level, although it would be of utmost importance for inspiring new therapeutic approaches. In PredictingPain, I will provide such a framework by applying recent insights from computational neuroscience in the form of ‘predictive coding’ to pain. Predictive coding models assume that perception is an active process in which the brain is not just passively responding to sensory inputs, but is instead constantly generating predictions about its sensory inputs. I will employ three complementary work packages (WP) – all of which use cutting-edge neuroimaging methods in human volunteers – to answer the important question of whether predictive coding can serve as a fundamental mechanism underlying the perception of pain. In WP1, I will elucidate whether the neural architecture of the nociceptive system is capable of implementing a predictive coding scheme. With WP2, I will unravel how the subjective experience of pain is constructed from a rich array of predictive signals. Finally, in WP3 I will employ an experimental model of chronic pain to test how predictions of pain relief exert their beneficial effects when pain is ongoing. A large part of the research in PredictingPain will focus on the human spinal cord, in order to capture predictive signals at this earliest level of central nervous system pain processing, since they will exert a profound effect on processing at higher levels and the resulting pain perception. Together, the outcomes from PredictingPain will provide a novel and mechanistic understanding of pain perception that will provide impetus for the development of new therapeutic approaches in order to reduce the suffering and financial burden that pain imposes.

Mots-clés : brain,neuroimaging,pain,prediction,predictive coding,spinal cord
Projet ERC : Extinction Genomics (Horizon 2020, appel 2015, Consolidator grants)
Domaine scientifique : Life Science
Panel : Integrative Biology: from Genes and Genomes to Systems
Entité participante : University of Copenhagen — Pays : Danemark — Rôle : PI
Acronyme de l'entité : UCPH
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2000000.0 €

Palaeogenomics is the nascent discipline concerned with sequencing and analysis of genome-scale information from historic, ancient, and even extinct samples. While once inconceivable due to the challenges of DNA damage, contamination, and the technical limitations of PCR-based Sanger sequencing, following the dawn of the second-generation sequencing revolution, it has rapidly become a reality. Indeed, so much so, that popular perception has moved away from if extinct species’ genomes can be sequenced, to when it will happen - and even, when will the first extinct animals be regenerated. Unfortunately this view is naïve, and does not account for the financial and technical challenges that face such attempts. I propose an exploration of exactly what the limits on genome reconstruction from extinct or otherwise historic/ancient material are. This will be achieved through new laboratory and bioinformatic developments aimed at decreasing the cost, while concomitantly increasing the quality of genome reconstruction from poor quality materials. In doing so I aim to build a scientifically-grounded framework against which the possibilities and limitations of extinct genome reconstruction can be assessed. Subsequently genomic information will be generated from a range of extinct and near-extinct avian and mammalian species, in order to showcase the potential of reconstructed genomes across research questions spanning at least three different streams of research: De-extinction, Evolutionary Genomics, and Conservation Genomics. Ultimately, achievement of these goals requires formation of a dedicated, closely knit team, focusing on both the methodological challenges as well as their bigger picture application to high-risk high-gain ventures. With ERC funding this can become a reality, and enable palaeogenomics to be pushed to the limits possible under modern technology.

Mots-clés : paleogenomics,extinction,genome reconstruction,conservation genomics,de extinction
Projet ERC : CONNECT-2-CLINIC (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Vrije Universiteit Brussel — Pays : Belgique — Rôle : PI
Acronyme de l'entité : VUB
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 150000.0 €

Pannexin1 (Panx1) channels mediate the exchange of biochemical messengers between the cytosol of a cell and its extracellular environment. This type of cellular communication underlies cell death and inflammation, both which are associated with a plethora of diseases. Closing pannexin channels therefore seems an interesting therapeutic strategy. In this respect, the ERC Starting Grant project CONNECT has demonstrated that peptide-based inhibition of Panx1 channels counteracts the manifestation of acute and chronic liver disease. However, these peptides cope with stability issues thus impeding clinical application. No other types of appropriate Panx1 channel inhibitors are available today despite their promising therapeutic potential. The present CONNECT-2-CLINIC project will meet this urgent need by generating specific and in vivo-applicable Panx1 channel inhibitors. For this purpose, nanobodies targeted towards Panx1 will be produced using unprecedented protocols that combine DNA immunization with new nanodisc technology. Panx1 nanobodies will be tested in vitro for their capacity to inhibit Panx1 channels and to reduce cell death and inflammation. They will be subsequently tested in a human-relevant mouse model of cholestatic liver disease. This technology track will be aligned by a 3-phase business track in order to analyze and create market value. By doing so, the CONNECT-2-CLINIC project will provide solid proof-of-concept for further pharmaceutical development and clinical application.

Mots-clés : connexin,pannexin,peptidomimetic,nanobody,liver disease
Projet ERC : PreciseCellPD (Horizon 2020, appel 2019, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Karolinska Institutet — Pays : Suède — Rôle : PI
Acronyme de l'entité : KI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2500000.0 €

Parkinson’s disease (PD) is a progressive incurable neurodegenerative disorder characterized by the loss of substantia nigra neurons (A9/SNs), a subset of midbrain dopaminergic neurons (mDAs) that are required for functional re-innervation of the striatum. Current treatments for PD are symptomatic and do not prevent disease progression. Proof-of-concept clinical studies using human fetal midbrain tissue for transplantation have shown that replacement of mDAs can change the course of PD. Human pluripotent stem cells (hPSCs) are currently used to generate mDAs for cell replacement therapy in clinical trials. However, our single-cell RNA-sequencing analysis of these preparations revealed that they comprise a complex mixture of cell types, including mDAs but also excessive vascular progenitor-like cells and serotonin neurons, thought to drive dyskinesias. Selective generation of A9/SNs for PD cell replacement therapy remains thus a major challenge. Here I propose to identify how human adult A9/SNs are generated in order to develop a novel cell type-specific precision cell replacement therapy for PD. I hypothesize that a yet undefined network of transcription factors and regulators control A9/SN subtype specification, and that such factors can be used to engineer A9/SNs starting from hPSCs or astrocytes, moving the field beyond the state of the art. This will be achieved by: 1) Using cutting-edge CRISPR and single cell methodologies to identify the factors controlling the specification of human A9/SNs; and 2) developing two novel cell replacement strategies for PD, involving either transplantation of hPSC-derived progenitors forward-programmed into A9/SNs or reprogramming of endogenous striatal glia in situ into A9/SNs, using a method we recently developed. I expect PreciseCellPD will generate groundbreaking knowledge of the mechanisms controlling the generation of human A9/SNs and will set the basis of a novel and transformative precision cell replacement therapy for PD

Mots-clés : human embryonic stem cells,direct in vivo reprogramming,single cell transcriptomics
Projet ERC : LAHACODE (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Ludwig-Maximilians-Universität München — Pays : Allemagne — Rôle : Partner
Acronyme de l'entité : LMU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 0.0 €

Partial differential equations (PDEs) play a central role in mathematics, allowing us to describe physical phenomena ranging from ultra-cold atoms (Bose–Einstein condensation) up to ultra-hot matter (nuclear fusion), from learning algorithms to fluids in the human brain. To understand nature we have to understand their qualitative behavior: existence and long time behavior of solutions, their geometric and dynamical properties – as well as to compute reliably their numerical solution. While linear problems and smooth solutions are nowadays well understood, a reliable description of ‘non-smooth’ phenomena remains one of the most challenging open problems in computational mathematics since the underlying PDEs have very complicated solutions exhibiting high oscillations and loss of regularity. This leads to huge errors, massive computational costs and ultimately provokes the failure of classical schemes. Nevertheless, ‘non-smooth phenomena’ play a fundamental role in modern physical modeling (e.g., blow-up phenomena, turbulences, high frequencies, low dispersion limits, etc.) which makes it an essential task to develop suitable numerical schemes. The overall ambition of LAHACODE is to make a crucial step towards closing this gap – addressing the fundamental question: How and to what extent can we reproduce the qualitative behavior of differential equations in a finite (discretized) world? LAHACODE is situated at the challenging frontiers of analysis and numerics. The main objective is to develop a novel class of numerical schemes for nonlinear PDEs with strong geometric structure at low regularity and high oscillations. The key idea in the construction of the new schemes is to tackle and deeply embed the underlying structure of resonances in the numerical discretizations. As in the continuous case, these terms are central to structure preservation, and provide the new schemes with remarkable properties – allowing reliable approximations where classical schemes fail.

Mots-clés : msc2010  65mxx partial differential equations,initial value and time dependent initial boundary value problems
Projet ERC : LAHACODE (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Mathematics
Entité participante : Sorbonne Université — Pays : France — Rôle : PI
Acronyme de l'entité : Sorbonne U
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1499905.0 €

Partial differential equations (PDEs) play a central role in mathematics, allowing us to describe physical phenomena ranging from ultra-cold atoms (Bose–Einstein condensation) up to ultra-hot matter (nuclear fusion), from learning algorithms to fluids in the human brain. To understand nature we have to understand their qualitative behavior: existence and long time behavior of solutions, their geometric and dynamical properties – as well as to compute reliably their numerical solution. While linear problems and smooth solutions are nowadays well understood, a reliable description of ‘non-smooth’ phenomena remains one of the most challenging open problems in computational mathematics since the underlying PDEs have very complicated solutions exhibiting high oscillations and loss of regularity. This leads to huge errors, massive computational costs and ultimately provokes the failure of classical schemes. Nevertheless, ‘non-smooth phenomena’ play a fundamental role in modern physical modeling (e.g., blow-up phenomena, turbulences, high frequencies, low dispersion limits, etc.) which makes it an essential task to develop suitable numerical schemes. The overall ambition of LAHACODE is to make a crucial step towards closing this gap – addressing the fundamental question: How and to what extent can we reproduce the qualitative behavior of differential equations in a finite (discretized) world? LAHACODE is situated at the challenging frontiers of analysis and numerics. The main objective is to develop a novel class of numerical schemes for nonlinear PDEs with strong geometric structure at low regularity and high oscillations. The key idea in the construction of the new schemes is to tackle and deeply embed the underlying structure of resonances in the numerical discretizations. As in the continuous case, these terms are central to structure preservation, and provide the new schemes with remarkable properties – allowing reliable approximations where classical schemes fail.

Mots-clés : msc2010  65mxx partial differential equations,initial value and time dependent initial boundary value problems
Projet ERC : PLASMA (Horizon 2020, appel 2014, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Fundamental constituents of matter
Entité participante : Chalmers University of Technology — Pays : Suède — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1948750.0 €

Particle acceleration and radiation in plasmas has a wide variety of applications, ranging from cancer therapy and lightning initiation, to the improved design of fusion devices for large scale energy production. The goal of this project is to build a flexible ensemble of theoretical and numerical models that describes the acceleration processes and the resulting fast particle dynamics in two focus areas: magnetic fusion plasmas and laser-produced plasmas. This interdisciplinary approach is a new way of studying charged particle acceleration. It will lead to a deeper understanding of the complex interactions that characterise fast particle behaviour in plasmas. Plasmas are complex systems, with many kinds of interacting electromagnetic (EM) waves and charged particles. For such a system it is infeasible to build one model which captures both the small scale physics and the large scale phenomena. Therefore we aim to develop several complementary models, in one common framework, and make sure they agree in overlapping regions. The common framework will be built layer-by-layer, using models derived from first principles in a systematic way, with theory closely linked to numerics and validated by experimental observations. The key object of study is the evolution of the velocity-space particle distribution in time and space. The main challenge is the strong coupling between the distribution and the EM-field, which requires models with self-consistent coupling of Maxwell’s equations and kinetic equations. For the latter we will use Vlasov-Fokker-Planck solvers extended with advanced collision operators. Interesting aspects include non-Maxwellian distributions, instabilities, shock-wave formation and avalanches. The resulting theoretical framework and the corresponding code-suite will be a novel instrument for advanced studies of charged particle acceleration. Due to the generality of our approach, the applicability will reach far beyond the two focus areas.

Mots-clés : charged particle acceleration,runaway,radiation,magnetic fusion,laser plasma interaction
Projet ERC : MAP-IN-HEART (Horizon 2020, appel 2019, Proof of concept grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Université de Bordeaux — Pays : France — Rôle : PI
Acronyme de l'entité : UBx
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 69500.0 €

Patients at risk of ventricular tachycardia (VT), the primary cause of sudden cardiac death, commonly undergo catheter ablation to cauterize the areas within myocardial scars responsible for arrythmias. However, the initial phase of the intervention devoted to identifying the ablation targets currently involves the intra-cardiac insertion of a mapping catheter characterized for being invasive, often inaccurate, and time-consuming. Pre-operative implementation of 3D cardiac imaging approaches to provide detailed structural information on ablation targets could overcome the shortcomings of standard catheter-based mapping. Still, state-of-the-art techniques have not lived up to their potential so far. During his ERC Starting Grant ECSTATIC (2017-2022), Prof. Hubert Cochet at University of Bordeaux developed a novel 3D image-processing technology (MAP-IN-HEART) which would allow cardiologists to locate VT ablation targets and guide ablation procedures in a non-invasive, highly precise and rapid manner using widely available cardiac CT images, without the need for a mapping catheter. In this ERC PoC project, we will investigate the technical feasibility of the innovative MAP-IN-HEART approach by assessing its efficiency and safety in a limited clinical study, and performing a cost-efficiency analysis. Moreover, we will ensure Freedom-To-Operate and explore all the potential paths for commercialization to finally develop a viable business strategy based on the technological aspects, the market needs and trends. Lastly, during this project we will gain technical and commercial proof-of-concept, providing the necessary information for potential commercialisation routes.

Mots-clés : cardiovacular diseases,ventricular tachycardia,computed tomography,catheter ablation,cardiac 3d image