Data-Gouv-ML/pcri-erc-participations-et-projets-laureats huggingface dataset:
Projet ERC : DIVERGE (Horizon 2020, appel 2020, Starting grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : Lahore institute of research and dedevelopment trust — Pays : Pakistan — Rôle : Partner
Type d'entité : Recherche
Financement ERC de l'entité : 462443.75 €

Depression affects 300 million people and represents one of the biggest challenges to human health to date. Of the burden, 80% pertains to low- and middle-income countries. It is thus imperative to understand the global causes of depression to design effective targeted interventions. DIVERGE will build the first ancestrally diverse data resource for depression, generated from biobanks (N=1.8M) and new studies in Pakistan (N=20K) as well as sub-Saharan Africa (N=13K) with deep phenotyping and genotyping. Differences in depression risk between populations have been shaped by the environment, demography and diverging evolutionary history. Using the novel perspective of evolutionary psychiatry, DIVERGE will comprehensively characterise the genetic architecture of depression and assess how it has been shaped by natural selection. Thereby, I will illuminate how heritability, environmental factors and their interplay affect disease development. I will develop a new method, trans-ethnic colocalization, to address the fundamental question whether genetic risk factors are transferable across populations. This is important to ensure that health benefits of precision medicine can be shared within and across populations. In addition to the big picture approach, I aim to identify specific causes of the disorder. The diversity of the data together with the application of population-matched inheritance models will empower the discovery of novel genetic loci for depression. I will develop and apply cutting-edge methods, including trans-ethnic fine-mapping with functional annotations to uncover biological mechanisms underlying depression loci. Trauma, such as exposure to violence, is a strong risk factor for depression. DIVERGE will investigate the interplay between traumatic life events and genetic susceptibility which could help understand how mental illness differs across groups. These innovations will lead to a step change in our understanding of the aetiology of depression.

Mots-clés : depression,risk factors,diverse populations,transcultural,genome wide association studies,traumatic life events
Projet ERC : FLPower (Horizon 2020, appel 2014, Proof of concept grants)
Entité participante : University of East Anglia — Pays : Royaume-Uni — Rôle : PI
Acronyme de l'entité : UEA
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 149533.75 €

Despite H2 fuel cell technology pre-dating the internal combustion engine the technology has not progressed much in 100 years. All hydrogen fuel cells use precious (rare and expensive) metal catalysts to oxidise H2, and reduce O2, such as Pt. These “precious” metals currently prevent the widespread use of fuel cells. The US Department of Energy has set a target of 0.125g of Pt / kW energy produced from fuel cells, and a total cost of $30 /kW. The current record stands at 0.2 g Pt/kW and a cost of $36/kW. The automotive industry requires the current Pt content of fuel cells to be reduced by 1/3 to become economically viable. Pt is a major cost component and is clearly a problem. This project develops a way to reduce Pt content of fuel cells by half – falling well below DoE targets and those of the automotive industry. We do this by replacing rare and expensive Pt metal used to oxidize H2 on 1 side of the fuel cell with molecular catalysts made of B, C, Cl, and F elements – cheap and abundant materials! The molecular catalysts that we have developed form “frustrated Lewis pairs” (FLP). A suitable Lewis acid and a Lewis base when combined form an FLP which can be used to heterolytically split H2. The resulting Lewis acid hydride is then oxidized at a carbon electrode, and the energetic driving force required to oxidise H2 into 2 H+ and 2e– is greatly reduced by as much as 610 mV (equivalent to catalyzing the reaction by 118 kJ mol-1) without using any Pt. This proposal seeks to build on this pioneering work. We have found that FLP reactions can occur at very electron deficient Lewis acids without needing a Lewis base! Instead we can use a common organic solvent, tetrahydrofuran, as the Lewis base, and form water tolerant Lewis acid catalysts, that cleave hydrogen in seconds on the same timescale as electrooxidation. This fund will allow us to develop aqueous FLP arylborane electrocatalysts and build prototype “frustrated fuel cells” as clean, cheap, energy devices.

Mots-clés : frustrated lewis pairs,electrocatalysis,hydrogen,fuel cells,batteries,electrochemistry,energy
Projet ERC : ScienceGraph (Horizon 2020, appel 2018, Consolidator grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
Entité participante : Leibniz University Hannover — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1381750.0 €

Despite an improved digital access to scientific publications in the last decades, the fundamental principles of scholarly communication remain unchanged and continue to be largely document-based. The document-oriented workflows in science have reached the limits of adequacy as highlighted by recent discussions on the increasing proliferation of scientific literature, the deficiency of peer-review and the reproducibility crisis. In ScienceGRAPH we aim to develop a novel model for representing, analysing, augmenting and exploiting scholarly communication in a knowledge-based way by expressing and linking scientific contributions and related artefacts through semantically rich, interlinked knowledge graphs. The model is based on deep semantic representation of scientific contributions, their manual, crowd-sourced and automatic augmentation and finally the intuitive exploration and interaction employing question answering on the resulting ScienceGRAPH base. Currently, knowledge graphs are still confined to representing encyclopaedic, factual information. ScienceGRAPH advances the state-of-the-art by enabling to represent complex interdisciplinary scientific information including fine-grained provenance preservation, discourse capture, evolution tracing and concept drift. Also, we will demonstrate that we can synergistically combine automated extraction and augmentation techniques, with large-scale collaboration to reach an unprecedented level of knowledge graph breadth and depth. As a result, we expect a paradigm shift in the methods of academic discourse towards knowledge-based information flows, which facilitate completely new ways of search and exploration. The efficiency and effectiveness of scholarly communication will significant increase, since ambiguities are reduced, reproducibility is facilitated, redundancy is avoided, provenance and contributions can be better traced and the interconnections of research contributions are made more explicit and transparent.

Mots-clés : scholarly communication,knowledge graphs,semantic technologies,question answering
Projet ERC : ChAMPioN (Horizon 2020, appel 2016, Advanced grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Glasgow — Pays : Royaume-Uni — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2856679.0 €

Despite decades of research, developing ways to overcome drug resistance in cancer is the most challenging bottleneck for curative therapies. This is because, in some forms of cancer, the cancer stem cells from which the diseases arise are constantly evolving, particularly under the selective pressures of drug therapies, in order to survive. The events leading to drug resistance can occur within one or more individual cancer stem cell(s) – and the features of each of these cells need to be studied in detail in order to develop drugs or drug combinations that can eradicate all of them. The BCR-ABL+ and BCR-ABL- myeloproliferative neoplasms (MPN) are a group of proliferative blood diseases that can be considered both exemplars of precision medicine and of the drug resistance bottleneck. While significant advances in the management of MPN have been made using life-long and expensive tyrosine kinase inhibitors (TKI), patients are rarely cured of their disease. This is because TKI fail to eradicate the leukaemia stem cells (LSC) from which MPN arise and which persist in patients on treatment, often leading to pervasive drug resistance, loss of response to therapy and progression to fatal forms of acute leukaemia. My goal is to change the way we study the LSC that persist in MPN patients as a means of delivering more effective precision medicine in MPN that is a “game-changer” leading to therapy-free remission (TFR) and cure. Here, I will apply an innovative strategy, ChAMPioN, to study the response of the MPN LSC to TKI in innovative pre-clinical laboratory models and directly in patients with MPN - up to the resolution of individual LSC. This work will reveal, for the first time, the molecular and clonal evolution of LSC during TKI therapies, thus enabling the development of more accurate predictions of TKI efficacy and resistance and rational approaches for curative drug therapies.

Mots-clés : bcr abl,jak2,bioinformatics,modelling,nrg xenograft,tyrosine kinase inhibitors,ezh2,c myc,bar coding,single cell,precision medicine,heterogeneity,clonal evolution
Projet ERC : SweetBrain (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Life Science
Panel : Biotechnology and Biosystems Engineering
Entité participante : Tel Aviv University — Pays : Israël — Rôle : PI
Acronyme de l'entité : TAU
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 1487438.0 €

Despite decades of research, the underpinnings of central nervous system (CNS) diseases and clear pathways to effective treatment remain elusive, mainly because of a scarcity of adequate models and methods with the capacity to elucidate human brain physiology. Recent studies suggest that high glucose levels are correlated with neuronal dysfunction and neurodegeneration, yet very little is known about the mechanisms of this relationship. Research in this vein has focused primarily on direct metabolic interactions between neurons and astrocytes, ignoring other cell populations in the neurovascular unit (NVU) that might have a meaningful role. My recent research revealed that the brain vasculature—the ‘gatekeeper’ through which all metabolites must pass to reach the neurons—has direct metabolic coupling with the neurons. Drawing from these observations, I adopt a previously unconsidered perspective and propose that the vasculature drives the neurodegenerative effects of hyperglycemia. Specifically, I hypothesize that high glucose levels change the metabolic function of the brain vasculature, thereby altering the direct endothelium-neuronal crosstalk and triggering neuronal dysfunction. To investigate this hypothesis, I will develop cutting-edge Organ-on-a-Chip (OoC) technology that overcomes the limitations of modeling NVU functionality and cell-cell interactions. Specifically, I will: (1) establish a human-relevant NVU-OoC model for metabolic and functional interactions, in which different cell types grow separately while remaining metabolically and functionally coupled; (2) identify the major metabolic and functional interactions in the human NVU at homeostasis and under diabetic conditions; and subsequently (3) target the vasculature communications to diminish neuronal dysfunction. This research has the potential to revolutionize the study of CNS disease, pointing to an unexplored pathway to a cure, and illuminating fundamental questions regarding brain metabolism.

Mots-clés : brain metabolism,organs on a chip
Projet ERC : GBM-CPP (Horizon 2020, appel 2015, Proof of concept grants)
Entité participante : CERCA Institution — Pays : Espagne — Rôle : PI
Acronyme de l'entité : CERCA;I-CERCA
Type d'entité : Recherche
Financement ERC de l'entité : 147750.0 €

Despite ever-increasing investments in the development of new treatments, many cancers remain incurable. One reason is that most current therapies target redundant functions around which tumour cells can build resistance. We focus instead on a unique and essential cellular function: the Myc oncogene, deregulated in more than 70% of human cancers. Targeting Myc has long been considered unfeasible because of potentially catastrophic side effects. Against this dogma, using a Myc inhibitor called Omomyc, we showed that Myc inhibition displays extraordinary therapeutic benefit in various mouse models of cancer (e.g. lung, brain, pancreas and skin) and causes only mild and reversible side effects. Importantly, no resistance to Omomyc has been observed, and Omomyc constitutes the best Myc inhibitor known to date. Omomyc has so far been used only as a transgene and proof of principle. However, thanks to the ERC-2013-CoG n° 617473, we now have evidence that the Omomyc peptide has cell-penetrating activity, and reaches lung and brain upon nasal administration, where it exerts its anti-tumorigenic activity in cancer cells (data protected by a patent application EP13382167.8). Thus, the Omomyc peptide could become the first clinically viable direct Myc inhibitor to treat lung, brain and other types of cancer. Our overall project encompasses the preclinical development of the Omomyc peptide to reach Phase I/II clinical trials, at which point the technology will be transferred to a pharmaceutical company for further commercialization. Hence, in this ERC Proof of Concept application, we propose to achieve specific, essential early milestones for the pharmaceutical development of the Omomyc product that will de-risk it and noticeably increase its value and the probability of reaching the market.

Mots-clés : omomyc,cancer,therapeutic,peptide production,industrial scale,regulatory activities,derisking,feasibility study,business plan
Projet ERC : SWITCH2MARKET (Horizon 2020, appel 2017, Proof of concept grants)
Entité participante : Leibniz Association — Pays : Allemagne — Rôle : PI
Acronyme de l'entité : LG
Type d'entité : Recherche
Financement ERC de l'entité : 147125.0 €

Despite intense fundamental research, only few biological inspirations have so far made it to real technical solutions. The reason is that the path from an understanding of nature to a successful product has many potential ´show stoppers´. The ERC Advanced Grant SWITCH2STICK addresses the scientific challenges and does not aim at product development and targeted technical optimization towards industrial requirements. Some preliminary industrial contacts, established through bilateral communication, have resulted in extremely promising perspectives for a commercialization of our results. From a technical perspective, our bioinspired concept could revolutionize robotic pick-and-place (handling) operation. The timing appears to be excellent: as new concepts for computerized, virtual fabrication are currently being developed on a worldwide scale, the readiness for implementing new concepts is at an all-time high. When combined with its clear environmental advantages (energy-conserving, noise-free), our invention has overwhelming market potential in the handling of production elements, e.g. electronics, optical components, or in the automotive sector. Preliminary screening suggests that our invention is well IP-protected for future commercialization. The proposed PoC project will tackle the essential issues that remain to be clarified before launching an extensive commercialization activity, including i) competitive analysis, ii) identifying the most promising markets, iii) testing the performance with regard to special requirements lists from industry, iv) developing a well-founded IPR strategy, v) generating a detailed business plan. The results will enable us to enter into targeted bilateral collaborations with leading industrial companies under full protection of our own commercialization potential. The PoC project will be indispensable as a preparatory and accompanying step in establishing a start-up company that markets intelligent micropatterned adhesives.

Mots-clés : materials engineering,mechanical engineering,shaping,biomaterials,robotics,pick and place,handling in vakuum
Projet ERC : CodeSan (Horizon 2020, appel 2019, Starting grants)
Domaine scientifique : Physical Sciences and Engineering
Panel : Computer science and informatics
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 : 1499970.0 €

Despite massive efforts in securing software, about 60 security bugs are publicly reported each month. Systems software is prone to low level bugs caused by undefined behavior (memory corruption, type confusion, or API confusion). Exploits abuse undefined behavior to execute attacker specified code, or to leak information. We propose code sanitization (CodeSan), a comprehensive approach to improve code quality. CodeSan will sanitize software by (i) automating bug discovery during development through software testing and (ii) protecting deployed software through reflective mitigations. CodeSan trades formal completeness for practical scalability in three steps: First, policy-based sanitization makes undefined behavior (through violations of memory safety, type safety, or API flow safety) explicit and detectable given concrete test inputs. Second, automatic test case generation increases testing coverage for large programs without the need for pre-existing test cases, enabling broader and automated use of policy-based sanitization. Third, for deployed software, reflective mitigations place runtime checks precisely where they are needed based on data-flow and control-flow coverage from our testing efforts. CodeSan complements formal approaches by protecting software that is currently out of reach due to its size, complexity, or low level nature. CodeSan is a compelling, comprehensive, and adaptive approach to thoroughly address undefined behavior for complex software. The three proposed thrusts complement each other naturally and will immediately guard large software systems such as Google Chromium, Mozilla Firefox, the Android system, or the Linux kernel, making them resilient against attacks. In line with PI Payer’s track record on open sourcing his group’s research artifacts on cast sanitization, transformative fuzzing, or control-flow hijacking mitigations, all prototypes produced during CodeSan will be released as open-source.

Mots-clés : software security,policy based sanitization,automatic test inference,fuzzing,software mitigation,system security
Projet ERC : OUTSOURCE (Horizon 2020, appel 2019, Consolidator grants)
Domaine scientifique : Life Science
Panel : Prevention, Diagnosis and Treatment of Human Diseases
Entité participante : University of Oslo — Pays : Norvège — Rôle : PI
Acronyme de l'entité : UiO
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 979562.5 €

Despite recent advances in cancer immunotherapy, most patients with metastatic cancer are not cured. Major reasons are lack of homogeneously and highly expressed molecules that can be safely targeted and evoke efficient T-cell responses. I propose that the strong T-cell responses leading to rejection of transplanted organs can be exploited to “reject” cancer by specific recognition of tissue-restricted targets. To this end, I recently demonstrated that healthy donor blood provides a rich source of T cells expressing TCRs that specifically and strongly react to peptides from tissue-restricted self-proteins, when presented on mismatched, foreign Human Leukocyte Antigens (HLA). I propose that patient T cells genetically equipped with such donor TCRs (dTCR T cell therapy) may “reject” cancer-affected organs, including metastases. A high and homogeneous expression of tissue-specific antigens is often maintained on both primary tumor and metastatic cancer cells. Here, I will identify peptides from tissue-restricted proteins as novel candidate TCR targets. Next, I will identify donor T cells that recognize such self-peptides in complex with foreign HLA by use of my patented method, and sequence reactive TCRs. Finally, I will establish a preclinical pipeline to characterize safety and efficacy of TCRs in vitro and in vivo in innovative mouse models. Outsourcing cancer immunity to dTCR T cells may bypass major limitations in current immunotherapies, including checkpoint inhibition and T cells gene-modified with chimeric antigen receptors (CARs). Thus, dTCRs can recognize i) intracellular targets and thus manifold more targets than CARs, ii) tumor-associated self-antigens with high affinity in contrast to patient-derived TCRs, and iii) self-antigens, which are more homogeneously expressed than mutations. dTCR T cell therapy could treat malignancies in organs that are non-essential for survival, such as prostate, or that can be replaced by a transplant, such as bone marrow.

Mots-clés : cancer immunotherapy  adoptive t cell therapy  t cell receptor engineered t cells
Projet ERC : FIRSTSTEPS (Horizon 2020, appel 2020, Advanced grants)
Domaine scientifique : Social Sciences and Humanities
Panel : The study of the human past
Entité participante : University of Tübingen — Pays : Allemagne — Rôle : PI
Type d'entité : Enseignement supérieur ou secondaire
Financement ERC de l'entité : 2583562.0 €

Despite recent discoveries in human evolution, the origin of our species, Homo sapiens, and the process through which it expanded and became established around the globe remain murky. Increasingly, it is viewed as a dynamic process of population expansions and contact among human lineages, occurring in concert with the Pleistocene climatic oscillations, which influence the probability of human survival as well as the availability of land bridges enabling expansions. Dispersals and population contact, therefore, may have been the norm in human evolution and may have played a greater role in shaping our species than previously recognised. In such a model, South-East Europe emerges as a likely area of sustained and / or repeated contact, making this region critical for testing hypotheses about European deep prehistory. Despite this crucial role, however, paleoanthropological research there remains in its infancy, with little existing data and no overarching interpretive framework. FIRSTSTEPS aims to fill this research gap by applying inter-disciplinary cutting edge investigation to recover new and connect existing evidence across sites, periods and regions. Key sites / finds from South-East Europe (Greece, Serbia, Bosnia, Montenegro, Croatia, Romania) and Italy — whose better documented record has yet to be connected to its counterparts to the East and will provide a crucial comparative perspective — will be included. In-depth analysis of important fossil / cultural assemblages from specific chrono-cultural periods ca. 200-30 ka, will be conducted to identify patterns of biological and cultural variation. In parallel, regional and supra-regional perspectives will be constructed beyond individual sites /countries. By addressing this crucial research gap FIRSTSTEPS will take paleoanthropological research in this important region to the next level and squarely place it on the paleolithic map of Europe.

Mots-clés : human evolution,dispersals,adaptation