Agency: Cordis | Branch: FP7 | Program: CP-FP | Phase: HEALTH.2013.2.3.4-2 | Award Amount: 7.61M | Year: 2014
The infectious diseases burden imposed by the parasites of Trypanosomatidae family represents a huge problem on peoples lives in countries where these diseases are endemic. Problems associated with existing drugs include inefficient delivery, insufficient efficacy, excessive toxicity and increasing resistance. New drugs are urgently needed now and in the foreseeable future. The New Medicine for Trypanosomatid Infections (NMTrypI) consortium uses a highly interdisciplinary approach to optimize pteridine, benzothiazole and miltefosine derivatives, as well as natural products against Trypanosomatids. The lead compounds target mechanisms that are associated with protozoa virulence and pathogenicity. The major objectives of this 3-year project are: i) development of drug leads which may be used in combination with a known or an investigational drugs, by using a common drug discovery platform established by experts in their respective fields, ii) development of pharmacodynamic biomarkers enabling the proteomic profiling of compound efficacy and early identification of drug resistance. NMTrypI addresses sleeping sickness, leishmaniasis, and Chagas disease. The partners are SMEs (5) and academics (8) in Europe and in disease-endemic countries (Italy, Greece, Portugal, Sudan, and Brazil). The new platform enables high throughput screening of compound libraries, lead development, testing in relevant animal models, as well as toxicology and safety testing. NMTrypI will translate drug leads into drug candidacy through 6 scientific work packages (WPs1-6) supported by two transversal WPs dedicated to project dissemination and management. The major strength of the consortium lies in the complementary partnersexpertise and the integrated platform that will provide: - at least 1-2 innovative, less toxic and safer drug candidates for Trypanosomatid infections compared to existing ones, - early phase biomarkers for efficacy prediction (overall improved efficacy and safety)
Agency: Cordis | Branch: FP7 | Program: MC-IRSES | Phase: FP7-PEOPLE-2009-IRSES | Award Amount: 172.80K | Year: 2010
Protein-protein interactions are keys to executing important cellular functions. We hypothesize that gain or loss of protein-protein interactions plays important roles in carcinogenesis. We propose a network-based approach to biomarker discovery that uses protein-protein interactions and regulatory transcriptional networks. We will use prostate cancer and gliomas as models. Prostate cancer is the most common form of cancer and the leading cause of cancer death among men in the developed countries. Glioblastoma multiforme (GBM) is the most common and most aggressive type of primary brain tumor and it GBM accounts for 52% of all primary brain tumor cases. Novel markers and therapeutic targets are still needed for these two cancers. We will be focusing on the androgen receptor protein-protein network in prostate cancer and TGF-beta mediated network in gliomas. Protein interactions will be extracted by text mining, from databases, and from structural data on protein complexes. To identify transcription factors and their targets in human, ChIP-Chip and ChIP-Seq experiments will be carried out. The resulting networks serve as a scaffold on which data of deregulated proteins derived from microarray and next-generation sequencing of patient cancer samples will be mapped. The perturbed subnetwork will be visualized with a new method that identifies and highlights network motifs and modules. Promising biomarker candidates will be further examined and validated experimentally. Where possible, candidates will be modelled using protein structural data on protein-protein complexes, providing the basis to design ligands that occupy binding sites in order to disrupt cancer-relevant interactions. Our proposal is highly innovative. We expect to identify key nodal points in the network, to which protein-protein interactions can be disrupted as a way to perturb or interfere with the network. These key nodal points will serve both as biomarkers and therapeutic targets.
Agency: Cordis | Branch: H2020 | Program: ERC-COG | Phase: ERC-CoG-2014 | Award Amount: 2.00M | Year: 2016
Understanding the physics of galaxy formation is arguably among the greatest problems in modern astrophysics. Recent cosmological simulations have demonstrated that feedback by star formation, supernovae and active galactic nuclei appears to be critical in obtaining realistic disk galaxies, to slow down star formation to the small observed rates, to move gas and metals out of galaxies into the intergalactic medium, and to balance radiative cooling of the low-entropy gas at the centers of galaxy clusters. This progress still has the caveat that feedback was modeled empirically and involved tuning to observed global relations, substantially weakening the predictive power of hydrodynamic simulations. More problematic, these simulations neglected cosmic rays and magnetic fields, which provide a comparable pressure support in comparison to turbulence in our Galaxy, and are known to couple dynamically and thermally to the gas. Building on our previous successes in investigating these high-energy processes, we propose a comprehensive research program for studying the impact of cosmic rays on the formation of galaxies and clusters. To this end, we will study cosmic-ray propagation in magneto-hydrodynamic turbulence and improve the modeling of the plasma physics. This will enable us to perform the first consistent magneto-hydrodynamical and cosmic-ray simulations in a cosmological framework, something that has just now become technically feasible. Through the use of an advanced numerical technique that employs a moving mesh for calculating hydrodynamics, we will achieve an unprecedented combination of accuracy, resolution and physical completeness. We complement our theoretical efforts with a focused observational program on the non-thermal emission of galaxies and clusters, taking advantage of new capabilities at radio to gamma-ray wavelengths and neutrinos. This promises important and potentially transformative changes of our understanding of galaxy formation.
Agency: Cordis | Branch: FP7 | Program: MC-IRSES | Phase: FP7-PEOPLE-2010-IRSES | Award Amount: 779.10K | Year: 2011
The focus in cosmology is shifting from the determination of the basic cosmological parameters to developing an understanding of how galaxies formed. Progress in this field has been driven by a combination of computer simulation and observational breakthroughs. Over the next few years, groundbreaking new facilities will come online and will provide data of unprecedented quality with which to test theoretical models. The key objective of our proposal is to allow European scientists to play a leading role in advancing our understanding of galaxy formation, by forging new links and research collaborations with scientists in Latin America and China, which host some of these new experiments. Our research programme covers all aspects of numerical galaxy formation. In addition to building new research capacity, we will organise a series of events to avoid fragmentation of research expertise and to help train a new generation of galaxy formation modellers.
Agency: Cordis | Branch: FP7 | Program: CP-CSA-Infra | Phase: INFRA-2012-2.2.4. | Award Amount: 6.56M | Year: 2012
The Infrastructure for Systems Biology in Europe (ISBE) programme comprises an infrastructure that is designed to meet the needs of European systems biology, in terms of development, applications and training. In order to address this requirement, we are proposing a distributed, interconnected infrastructure which primarily comprises three types of centres: Data Integration Centres (DICs), and systems biology dedicated Data Generation Centres (DGCs), and Data Stewardship Centres (DSCs). DICs are research centres that apply and develop expertise in model-driven data integration and make this expertise available to the community. DGCs are technology-based centres that make available a wide range of high, medium and low throughput technologies that are essential for the acquisition of quantitative datasets under standardised conditions. DSCs are centres that are responsible for data processing, curation and analysis they store data, models and simulations. Each type of centre will be functionally different, but organisationally similar. Within participating universities and other organisations across Europe there will be foci of expertise and facilities which fit the requirements for a DIC, DGC or DSC. Such foci will be evaluated and then designated as local centres of a particular type. Each focus will then form a component of a particular type of DIC, DGC or DSC centre. ISBE centres may be single institutions or can be distributed. Large institutions, such as leading universities, may well contribute facilities and expertise across different types of centres. A particular distributed centre may focus on an area of Systems Biology; for example, a model organism, a disease, or, alternatively an area such as biotechnology, ecology or green biology. Importantly, the ISBE will include technological expertise; for example, stochastic computation, algorithmic modelling, multi-scale modelling integration of diverse high-and low-throughput datasets.