Project acronym 2D-TOPSENSE
Project Tunable optoelectronic devices by strain engineering of 2D semiconductors
Researcher (PI) Andres CASTELLANOS
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary The goal of 2D-TOPSENSE is to exploit the remarkable stretchability of two-dimensional semiconductors to fabricate optoelectronic devices where strain is used as an external knob to tune their properties.
While bulk semiconductors tend to break under strains larger than 1.5%, 2D semiconductors (such as MoS2) can withstand deformations of up to 10-20% before rupture. This large breaking strength promises a great potential of 2D semiconductors as ‘straintronic’ materials, whose properties can be adjusted by applying a deformation to their lattice. In fact, recent theoretical works predicted an interesting physical phenomenon: a tensile strain-induced semiconductor-to-metal transition in 2D semiconductors. By tensioning single-layer MoS2 from 0% up to 10%, its electronic band structure is expected to undergo a continuous transition from a wide direct band-gap of 1.8 eV to a metallic behavior. This unprecedented large strain-tunability will undoubtedly have a strong impact in a wide range of optoelectronic applications such as photodetectors whose cut-off wavelength is tuned by varying the applied strain or atomically thin light modulators.
To date, experimental works on strain engineering have been mostly focused on fundamental studies, demonstrating part of the potential of 2D semiconductors in straintronics, but they have failed to exploit strain engineering to add extra functionalities to optoelectronic devices. In 2D-TOPSENSE I will go beyond the state of the art in straintronics by designing and fabricating optoelectronic devices whose properties and performance can be tuned by means of applying strain. 2D-TOPSENSE will focus on photodetectors with a tunable bandwidth and detectivity, light emitting devices whose emission wavelength can be adjusted, light modulators based on 2D semiconductors such as transition metal dichalcogenides or black phosphorus and solar funnels capable of directing the photogenerated charge carriers towards a specific position.
Summary
The goal of 2D-TOPSENSE is to exploit the remarkable stretchability of two-dimensional semiconductors to fabricate optoelectronic devices where strain is used as an external knob to tune their properties.
While bulk semiconductors tend to break under strains larger than 1.5%, 2D semiconductors (such as MoS2) can withstand deformations of up to 10-20% before rupture. This large breaking strength promises a great potential of 2D semiconductors as ‘straintronic’ materials, whose properties can be adjusted by applying a deformation to their lattice. In fact, recent theoretical works predicted an interesting physical phenomenon: a tensile strain-induced semiconductor-to-metal transition in 2D semiconductors. By tensioning single-layer MoS2 from 0% up to 10%, its electronic band structure is expected to undergo a continuous transition from a wide direct band-gap of 1.8 eV to a metallic behavior. This unprecedented large strain-tunability will undoubtedly have a strong impact in a wide range of optoelectronic applications such as photodetectors whose cut-off wavelength is tuned by varying the applied strain or atomically thin light modulators.
To date, experimental works on strain engineering have been mostly focused on fundamental studies, demonstrating part of the potential of 2D semiconductors in straintronics, but they have failed to exploit strain engineering to add extra functionalities to optoelectronic devices. In 2D-TOPSENSE I will go beyond the state of the art in straintronics by designing and fabricating optoelectronic devices whose properties and performance can be tuned by means of applying strain. 2D-TOPSENSE will focus on photodetectors with a tunable bandwidth and detectivity, light emitting devices whose emission wavelength can be adjusted, light modulators based on 2D semiconductors such as transition metal dichalcogenides or black phosphorus and solar funnels capable of directing the photogenerated charge carriers towards a specific position.
Max ERC Funding
1 930 437 €
Duration
Start date: 2018-03-01, End date: 2023-02-28
Project acronym 4D-PET
Project Innovative PET scanner for dynamic imaging
Researcher (PI) José María BENLLOCH BAVIERA
Host Institution (HI) AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS
Call Details Advanced Grant (AdG), LS7, ERC-2015-AdG
Summary The main objective of 4D-PET is to develop an innovative whole-body PET scanner based in a new detector concept that stores 3D position and time of every single gamma interaction with unprecedented resolution. The combination of scanner geometrical design and high timing resolution will enable developing a full sequence of all gamma-ray interactions inside the scanner, including Compton interactions, like in a 3D movie. 4D-PET fully exploits Time Of Flight (TOF) information to obtain a better image quality and to increase scanner sensitivity, through the inclusion in the image formation of all Compton events occurring inside the detector, which are always rejected in state-of-the-art PET scanners. The new PET design will radically improve state-of-the-art PET performance features, overcoming limitations of current PET technology and opening up new diagnostic venues and very valuable physiological information
Summary
The main objective of 4D-PET is to develop an innovative whole-body PET scanner based in a new detector concept that stores 3D position and time of every single gamma interaction with unprecedented resolution. The combination of scanner geometrical design and high timing resolution will enable developing a full sequence of all gamma-ray interactions inside the scanner, including Compton interactions, like in a 3D movie. 4D-PET fully exploits Time Of Flight (TOF) information to obtain a better image quality and to increase scanner sensitivity, through the inclusion in the image formation of all Compton events occurring inside the detector, which are always rejected in state-of-the-art PET scanners. The new PET design will radically improve state-of-the-art PET performance features, overcoming limitations of current PET technology and opening up new diagnostic venues and very valuable physiological information
Max ERC Funding
2 048 386 €
Duration
Start date: 2017-01-01, End date: 2021-12-31
Project acronym 4SUNS
Project 4-Colours/2-Junctions of III-V semiconductors on Si to use in electronics devices and solar cells
Researcher (PI) María Nair LOPEZ MARTINEZ
Host Institution (HI) UNIVERSIDAD AUTONOMA DE MADRID
Call Details Starting Grant (StG), PE7, ERC-2017-STG
Summary It was early predicted by M. Green and coeval colleagues that dividing the solar spectrum into narrow ranges of colours is the most efficient manner to convert solar energy into electrical power. Multijunction solar cells are the current solution to this challenge, which have reached over 30% conversion efficiencies by stacking 3 junctions together. However, the large fabrication costs and time hinders their use in everyday life. It has been shown that highly mismatched alloy (HMA) materials provide a powerful playground to achieve at least 3 different colour absorption regions that enable optimised energy conversion with just one junction. Combining HMA-based junctions with standard Silicon solar cells will rocket solar conversion efficiency at a reduced price. To turn this ambition into marketable devices, several efforts are still needed and few challenges must be overcome.
4SUNS is a revolutionary approach for the development of HMA materials on Silicon technology, which will bring highly efficient multi-colour solar cells costs below current multijunction devices. The project will develop the technology of HMA materials on Silicon via material synthesis opening a new technology for the future. The understanding and optimization of highly mismatched alloy materials-using GaAsNP alloy- will provide building blocks for the fabrication of laboratory-size 4-colours/2-junctions solar cells.
Using a molecular beam epitaxy system, 4SUNS will grow 4-colours/2-junctions structure as well as it will manufacture the final devices. Structural and optoelectronic characterizations will carry out to determine the quality of the materials and the solar cells characteristic to obtain a competitive product. These new solar cells are competitive products to breakthrough on the solar energy sector solar cells and allowing Europe to take leadership on high efficiency solar cells.
Summary
It was early predicted by M. Green and coeval colleagues that dividing the solar spectrum into narrow ranges of colours is the most efficient manner to convert solar energy into electrical power. Multijunction solar cells are the current solution to this challenge, which have reached over 30% conversion efficiencies by stacking 3 junctions together. However, the large fabrication costs and time hinders their use in everyday life. It has been shown that highly mismatched alloy (HMA) materials provide a powerful playground to achieve at least 3 different colour absorption regions that enable optimised energy conversion with just one junction. Combining HMA-based junctions with standard Silicon solar cells will rocket solar conversion efficiency at a reduced price. To turn this ambition into marketable devices, several efforts are still needed and few challenges must be overcome.
4SUNS is a revolutionary approach for the development of HMA materials on Silicon technology, which will bring highly efficient multi-colour solar cells costs below current multijunction devices. The project will develop the technology of HMA materials on Silicon via material synthesis opening a new technology for the future. The understanding and optimization of highly mismatched alloy materials-using GaAsNP alloy- will provide building blocks for the fabrication of laboratory-size 4-colours/2-junctions solar cells.
Using a molecular beam epitaxy system, 4SUNS will grow 4-colours/2-junctions structure as well as it will manufacture the final devices. Structural and optoelectronic characterizations will carry out to determine the quality of the materials and the solar cells characteristic to obtain a competitive product. These new solar cells are competitive products to breakthrough on the solar energy sector solar cells and allowing Europe to take leadership on high efficiency solar cells.
Max ERC Funding
1 499 719 €
Duration
Start date: 2018-02-01, End date: 2023-01-31
Project acronym AIR-NB
Project Pre-natal exposure to urban AIR pollution and pre- and post-Natal Brain development
Researcher (PI) Jordi Sunyer
Host Institution (HI) FUNDACION PRIVADA INSTITUTO DE SALUD GLOBAL BARCELONA
Call Details Advanced Grant (AdG), LS7, ERC-2017-ADG
Summary Air pollution is the main urban-related environmental hazard. It appears to affect brain development, although current evidence is inadequate given the lack of studies during the most vulnerable stages of brain development and the lack of brain anatomical structure and regional connectivity data underlying these effects. Of particular interest is the prenatal period, when brain structures are forming and growing, and when the effect of in utero exposure to environmental factors may cause permanent brain injury. I and others have conducted studies focused on effects during school age which could be less profound. I postulate that: pre-natal exposure to urban air pollution during pregnancy impairs foetal and postnatal brain development, mainly by affecting myelination; these effects are at least partially mediated by translocation of airborne particulate matter to the placenta and by placental dysfunction; and prenatal exposure to air pollution impairs post-natal brain development independently of urban context and post-natal exposure to air pollution. I aim to evaluate the effect of pre-natal exposure to urban air pollution on pre- and post-natal brain structure and function by following 900 pregnant women and their neonates with contrasting levels of pre-natal exposure to air pollutants by: i) establishing a new pregnancy cohort and evaluating brain imaging (pre-natal and neo-natal brain structure, connectivity and function), and post-natal motor and cognitive development; ii) measuring total personal exposure and inhaled dose of air pollutants during specific time-windows of gestation, noise, paternal stress and other stressors, using personal samplers and sensors; iii) detecting nanoparticles in placenta and its vascular function; iv) modelling mathematical causality and mediation, including a replication study in an external cohort. The expected results will create an impulse to implement policy interventions that genuinely protect the health of urban citizens.
Summary
Air pollution is the main urban-related environmental hazard. It appears to affect brain development, although current evidence is inadequate given the lack of studies during the most vulnerable stages of brain development and the lack of brain anatomical structure and regional connectivity data underlying these effects. Of particular interest is the prenatal period, when brain structures are forming and growing, and when the effect of in utero exposure to environmental factors may cause permanent brain injury. I and others have conducted studies focused on effects during school age which could be less profound. I postulate that: pre-natal exposure to urban air pollution during pregnancy impairs foetal and postnatal brain development, mainly by affecting myelination; these effects are at least partially mediated by translocation of airborne particulate matter to the placenta and by placental dysfunction; and prenatal exposure to air pollution impairs post-natal brain development independently of urban context and post-natal exposure to air pollution. I aim to evaluate the effect of pre-natal exposure to urban air pollution on pre- and post-natal brain structure and function by following 900 pregnant women and their neonates with contrasting levels of pre-natal exposure to air pollutants by: i) establishing a new pregnancy cohort and evaluating brain imaging (pre-natal and neo-natal brain structure, connectivity and function), and post-natal motor and cognitive development; ii) measuring total personal exposure and inhaled dose of air pollutants during specific time-windows of gestation, noise, paternal stress and other stressors, using personal samplers and sensors; iii) detecting nanoparticles in placenta and its vascular function; iv) modelling mathematical causality and mediation, including a replication study in an external cohort. The expected results will create an impulse to implement policy interventions that genuinely protect the health of urban citizens.
Max ERC Funding
2 499 992 €
Duration
Start date: 2018-09-01, End date: 2023-08-31
Project acronym ANIMETRICS
Project Measurement-Based Modeling and Animation of Complex Mechanical Phenomena
Researcher (PI) Miguel Angel Otaduy Tristan
Host Institution (HI) UNIVERSIDAD REY JUAN CARLOS
Call Details Starting Grant (StG), PE6, ERC-2011-StG_20101014
Summary Computer animation has traditionally been associated with applications in virtual-reality-based training, video games or feature films. However, interactive animation is gaining relevance in a more general scope, as a tool for early-stage analysis, design and planning in many applications in science and engineering. The user can get quick and visual feedback of the results, and then proceed by refining the experiments or designs. Potential applications include nanodesign, e-commerce or tactile telecommunication, but they also reach as far as, e.g., the analysis of ecological, climate, biological or physiological processes.
The application of computer animation is extremely limited in comparison to its potential outreach due to a trade-off between accuracy and computational efficiency. Such trade-off is induced by inherent complexity sources such as nonlinear or anisotropic behaviors, heterogeneous properties, or high dynamic ranges of effects.
The Animetrics project proposes a modeling and animation methodology, which consists of a multi-scale decomposition of complex processes, the description of the process at each scale through combination of simple local models, and fitting the parameters of those local models using large amounts of data from example effects. The modeling and animation methodology will be explored on specific problems arising in complex mechanical phenomena, including viscoelasticity of solids and thin shells, multi-body contact, granular and liquid flow, and fracture of solids.
Summary
Computer animation has traditionally been associated with applications in virtual-reality-based training, video games or feature films. However, interactive animation is gaining relevance in a more general scope, as a tool for early-stage analysis, design and planning in many applications in science and engineering. The user can get quick and visual feedback of the results, and then proceed by refining the experiments or designs. Potential applications include nanodesign, e-commerce or tactile telecommunication, but they also reach as far as, e.g., the analysis of ecological, climate, biological or physiological processes.
The application of computer animation is extremely limited in comparison to its potential outreach due to a trade-off between accuracy and computational efficiency. Such trade-off is induced by inherent complexity sources such as nonlinear or anisotropic behaviors, heterogeneous properties, or high dynamic ranges of effects.
The Animetrics project proposes a modeling and animation methodology, which consists of a multi-scale decomposition of complex processes, the description of the process at each scale through combination of simple local models, and fitting the parameters of those local models using large amounts of data from example effects. The modeling and animation methodology will be explored on specific problems arising in complex mechanical phenomena, including viscoelasticity of solids and thin shells, multi-body contact, granular and liquid flow, and fracture of solids.
Max ERC Funding
1 277 969 €
Duration
Start date: 2012-01-01, End date: 2016-12-31
Project acronym APACHE
Project Atmospheric Pressure plAsma meets biomaterials for bone Cancer HEaling
Researcher (PI) Cristina CANAL BARNILS
Host Institution (HI) UNIVERSITAT POLITECNICA DE CATALUNYA
Call Details Starting Grant (StG), PE8, ERC-2016-STG
Summary Cold atmospheric pressure plasmas (APP) have been reported to selectively kill cancer cells without damaging the surrounding tissues. Studies have been conducted on a variety of cancer types but to the best of our knowledge not on any kind of bone cancer. Treatment options for bone cancer include surgery, chemotherapy, etc. and may involve the use of bone grafting biomaterials to replace the surgically removed bone.
APACHE brings a totally different and ground-breaking approach in the design of a novel therapy for bone cancer by taking advantage of the active species generated by APP in combination with biomaterials to deliver the active species locally in the diseased site. The feasibility of this approach is rooted in the evidence that the cellular effects of APP appear to strongly involve the suite of reactive species created by plasmas, which can be derived from a) direct treatment of the malignant cells by APP or b) indirect treatment of the liquid media by APP which is then put in contact with the cancer cells.
In APACHE we aim to investigate the fundamentals involved in the lethal effects of cold plasmas on bone cancer cells, and to develop improved bone cancer therapies. To achieve this we will take advantage of the highly reactive species generated by APP in the liquid media, which we will use in an incremental strategy: i) to investigate the effects of APP treated liquid on bone cancer cells, ii) to evaluate the potential of combining APP treated liquid in a hydrogel vehicle with/wo CaP biomaterials and iii) to ascertain the potential three directional interactions between APP reactive species in liquid medium with biomaterials and with chemotherapeutic drugs.
The methodological approach will involve an interdisciplinary team, dealing with plasma diagnostics in gas and liquid media; with cell biology and the effects of APP treated with bone tumor cells and its combination with biomaterials and/or with anticancer drugs.
Summary
Cold atmospheric pressure plasmas (APP) have been reported to selectively kill cancer cells without damaging the surrounding tissues. Studies have been conducted on a variety of cancer types but to the best of our knowledge not on any kind of bone cancer. Treatment options for bone cancer include surgery, chemotherapy, etc. and may involve the use of bone grafting biomaterials to replace the surgically removed bone.
APACHE brings a totally different and ground-breaking approach in the design of a novel therapy for bone cancer by taking advantage of the active species generated by APP in combination with biomaterials to deliver the active species locally in the diseased site. The feasibility of this approach is rooted in the evidence that the cellular effects of APP appear to strongly involve the suite of reactive species created by plasmas, which can be derived from a) direct treatment of the malignant cells by APP or b) indirect treatment of the liquid media by APP which is then put in contact with the cancer cells.
In APACHE we aim to investigate the fundamentals involved in the lethal effects of cold plasmas on bone cancer cells, and to develop improved bone cancer therapies. To achieve this we will take advantage of the highly reactive species generated by APP in the liquid media, which we will use in an incremental strategy: i) to investigate the effects of APP treated liquid on bone cancer cells, ii) to evaluate the potential of combining APP treated liquid in a hydrogel vehicle with/wo CaP biomaterials and iii) to ascertain the potential three directional interactions between APP reactive species in liquid medium with biomaterials and with chemotherapeutic drugs.
The methodological approach will involve an interdisciplinary team, dealing with plasma diagnostics in gas and liquid media; with cell biology and the effects of APP treated with bone tumor cells and its combination with biomaterials and/or with anticancer drugs.
Max ERC Funding
1 499 887 €
Duration
Start date: 2017-04-01, End date: 2022-03-31
Project acronym ARMOS
Project Advanced multifunctional Reactors for green Mobility and Solar fuels
Researcher (PI) Athanasios Konstandopoulos
Host Institution (HI) ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS
Call Details Advanced Grant (AdG), PE8, ERC-2010-AdG_20100224
Summary Green Mobility requires an integrated approach to the chain fuel/engine/emissions. The present project aims at ground breaking advances in the area of Green Mobility by (a) enabling the production of affordable, carbon-neutral, clean, solar fuels using exclusively renewable/recyclable raw materials, namely solar energy, water and captured Carbon Dioxide from combustion power plants (b) developing a highly compact, multifunctional reactor, able to eliminate gaseous and particulate emissions from the exhaust of engines operated on such clean fuels.
The overall research approach will be based on material science, engineering and simulation technology developed by the PI over the past 20 years in the area of Diesel Emission Control Reactors, which will be further extended and cross-fertilized in the area of Solar Thermochemical Reactors, an emerging discipline of high importance for sustainable development, where the PI’s research group has already made significant contributions, and received the 2006 European Commission’s Descartes Prize for the development of the first ever solar reactor, holding the potential to produce on a large scale, pure renewable Hydrogen from the thermochemical splitting of water, also known as the HYDROSOL technology.
Summary
Green Mobility requires an integrated approach to the chain fuel/engine/emissions. The present project aims at ground breaking advances in the area of Green Mobility by (a) enabling the production of affordable, carbon-neutral, clean, solar fuels using exclusively renewable/recyclable raw materials, namely solar energy, water and captured Carbon Dioxide from combustion power plants (b) developing a highly compact, multifunctional reactor, able to eliminate gaseous and particulate emissions from the exhaust of engines operated on such clean fuels.
The overall research approach will be based on material science, engineering and simulation technology developed by the PI over the past 20 years in the area of Diesel Emission Control Reactors, which will be further extended and cross-fertilized in the area of Solar Thermochemical Reactors, an emerging discipline of high importance for sustainable development, where the PI’s research group has already made significant contributions, and received the 2006 European Commission’s Descartes Prize for the development of the first ever solar reactor, holding the potential to produce on a large scale, pure renewable Hydrogen from the thermochemical splitting of water, also known as the HYDROSOL technology.
Max ERC Funding
1 750 000 €
Duration
Start date: 2011-02-01, End date: 2017-01-31
Project acronym AUTAR
Project A Unified Theory of Algorithmic Relaxations
Researcher (PI) Albert Atserias Peri
Host Institution (HI) UNIVERSITAT POLITECNICA DE CATALUNYA
Call Details Consolidator Grant (CoG), PE6, ERC-2014-CoG
Summary For a large family of computational problems collectively known as constrained optimization and satisfaction problems (CSPs), four decades of research in algorithms and computational complexity have led to a theory that tries to classify them as algorithmically tractable vs. intractable, i.e. polynomial-time solvable vs. NP-hard. However, there remains an important gap in our knowledge in that many CSPs of interest resist classification by this theory. Some such problems of practical relevance include fundamental partition problems in graph theory, isomorphism problems in combinatorics, and strategy-design problems in mathematical game theory. To tackle this gap in our knowledge, the research of the last decade has been driven either by finding hard instances for algorithms that solve tighter and tighter relaxations of the original problem, or by formulating new hardness-hypotheses that are stronger but admittedly less robust than NP-hardness.
The ultimate goal of this project is closing the gap between the partial progress that these approaches represent and the original classification project into tractable vs. intractable problems. Our thesis is that the field has reached a point where, in many cases of interest, the analysis of the current candidate algorithms that appear to solve all instances could suffice to classify the problem one way or the other, without the need for alternative hardness-hypotheses. The novelty in our approach is a program to develop our recent discovery that, in some cases of interest, two methods from different areas match in strength: indistinguishability pebble games from mathematical logic, and hierarchies of convex relaxations from mathematical programming. Thus, we aim at making significant advances in the status of important algorithmic problems by looking for a general theory that unifies and goes beyond the current understanding of its components.
Summary
For a large family of computational problems collectively known as constrained optimization and satisfaction problems (CSPs), four decades of research in algorithms and computational complexity have led to a theory that tries to classify them as algorithmically tractable vs. intractable, i.e. polynomial-time solvable vs. NP-hard. However, there remains an important gap in our knowledge in that many CSPs of interest resist classification by this theory. Some such problems of practical relevance include fundamental partition problems in graph theory, isomorphism problems in combinatorics, and strategy-design problems in mathematical game theory. To tackle this gap in our knowledge, the research of the last decade has been driven either by finding hard instances for algorithms that solve tighter and tighter relaxations of the original problem, or by formulating new hardness-hypotheses that are stronger but admittedly less robust than NP-hardness.
The ultimate goal of this project is closing the gap between the partial progress that these approaches represent and the original classification project into tractable vs. intractable problems. Our thesis is that the field has reached a point where, in many cases of interest, the analysis of the current candidate algorithms that appear to solve all instances could suffice to classify the problem one way or the other, without the need for alternative hardness-hypotheses. The novelty in our approach is a program to develop our recent discovery that, in some cases of interest, two methods from different areas match in strength: indistinguishability pebble games from mathematical logic, and hierarchies of convex relaxations from mathematical programming. Thus, we aim at making significant advances in the status of important algorithmic problems by looking for a general theory that unifies and goes beyond the current understanding of its components.
Max ERC Funding
1 725 656 €
Duration
Start date: 2015-06-01, End date: 2020-05-31
Project acronym AVATAR
Project Integrating Genomics and Avatar Mouse Models to Personalize Pancreatic Cancer Treatment
Researcher (PI) Manuel HIDALGO MEDINA
Host Institution (HI) HOSPITAL UNIVERSITARIO DE FUENLABRADA
Call Details Advanced Grant (AdG), LS7, ERC-2014-ADG
Summary The prognosis of patients with metastatic pancreatic cancer (PDAC) is very poor. Recent studies have started to elucidate the genetic landscape of this disease to show that PDAC is a genetically complex, unstable, and heterogeneous cancer. However, in-depth analysis of individual patient genomes couple with personalize Avatar mouse models is providing highly effective therapeutic opportunities for the individual patient. Thus, metastatic PDAC appears a candidate disease to implement a genomics-base, personalized treatment approach. In this project, we will conduct an open label, multicenter, randomized phase III study in patients with standard of care resistant metastatic pancreatic cancer aiming to test the hypothesis that an integrated personalized treatment approach improves survival compare to a conventional treatment. Patients randomized to the personalize treatment arm will undergo a biopsy of a metastatic lesion to perform a targeted genome analysis using next generation sequencing. In addition, we will generate a personalize Avatar mouse model from the same patient. We will employ sophisticated bioinformatic analysis as well as mining of drug response-genetic databases to select, for each individual patient, candidate therapeutic targets that will be experimentally tested in the patient´s Avatar model to select the most effective regimen that will ultimately applied to the patient. In addition, based on the genomic data, we will design an individualized monitoring plan for each patient using BEAMing technology to monitor circulating levels of mutated genes. Furthermore, with a discovery goal, we will perform in depth genomic analysis of metastatic PDAC lesions in this cohort of clinically well-annotated patients with Avatar mouse models for therapeutic validation. Overall we expect this work will contribute to our understanding of PDAC and will favourably impact the treatment of this dismal cancer.
Summary
The prognosis of patients with metastatic pancreatic cancer (PDAC) is very poor. Recent studies have started to elucidate the genetic landscape of this disease to show that PDAC is a genetically complex, unstable, and heterogeneous cancer. However, in-depth analysis of individual patient genomes couple with personalize Avatar mouse models is providing highly effective therapeutic opportunities for the individual patient. Thus, metastatic PDAC appears a candidate disease to implement a genomics-base, personalized treatment approach. In this project, we will conduct an open label, multicenter, randomized phase III study in patients with standard of care resistant metastatic pancreatic cancer aiming to test the hypothesis that an integrated personalized treatment approach improves survival compare to a conventional treatment. Patients randomized to the personalize treatment arm will undergo a biopsy of a metastatic lesion to perform a targeted genome analysis using next generation sequencing. In addition, we will generate a personalize Avatar mouse model from the same patient. We will employ sophisticated bioinformatic analysis as well as mining of drug response-genetic databases to select, for each individual patient, candidate therapeutic targets that will be experimentally tested in the patient´s Avatar model to select the most effective regimen that will ultimately applied to the patient. In addition, based on the genomic data, we will design an individualized monitoring plan for each patient using BEAMing technology to monitor circulating levels of mutated genes. Furthermore, with a discovery goal, we will perform in depth genomic analysis of metastatic PDAC lesions in this cohort of clinically well-annotated patients with Avatar mouse models for therapeutic validation. Overall we expect this work will contribute to our understanding of PDAC and will favourably impact the treatment of this dismal cancer.
Max ERC Funding
2 498 688 €
Duration
Start date: 2015-10-01, End date: 2020-09-30
Project acronym BETTERSENSE
Project Nanodevice Engineering for a Better Chemical Gas Sensing Technology
Researcher (PI) Juan Daniel Prades Garcia
Host Institution (HI) UNIVERSITAT DE BARCELONA
Call Details Starting Grant (StG), PE7, ERC-2013-StG
Summary BetterSense aims to solve the two main problems in current gas sensor technologies: the high power consumption and the poor selectivity. For the former, we propose a radically new approach: to integrate the sensing components and the energy sources intimately, at the nanoscale, in order to achieve a new kind of sensor concept featuring zero power consumption. For the latter, we will mimic the biological receptors designing a kit of gas-specific molecular organic functionalizations to reach ultra-high gas selectivity figures, comparable to those of biological processes. Both cutting-edge concepts will be developed in parallel an integrated together to render a totally new gas sensing technology that surpasses the state-of-the-art.
As a matter of fact, the project will enable, for the first time, the integration of gas detectors in energetically autonomous sensors networks. Additionally, BetterSense will provide an integral solution to the gas sensing challenge by producing a full set of gas-specific sensors over the same platform to ease their integration in multi-analyte systems. Moreover, the project approach will certainly open opportunities in adjacent fields in which power consumption, specificity and nano/micro integration are a concern, such as liquid chemical and biological sensing.
In spite of the promising evidences that demonstrate the feasibility of this proposal, there are still many scientific and technological issues to solve, most of them in the edge of what is known and what is possible today in nano-fabrication and nano/micro integration. For this reason, BetterSense also aims to contribute to the global challenge of making nanodevices compatible with scalable, cost-effective, microelectronic technologies.
For all this, addressing this challenging proposal in full requires a funding scheme compatible with a high-risk/high-gain vision to finance the full dedication of a highly motivated research team with multidisciplinary skill
Summary
BetterSense aims to solve the two main problems in current gas sensor technologies: the high power consumption and the poor selectivity. For the former, we propose a radically new approach: to integrate the sensing components and the energy sources intimately, at the nanoscale, in order to achieve a new kind of sensor concept featuring zero power consumption. For the latter, we will mimic the biological receptors designing a kit of gas-specific molecular organic functionalizations to reach ultra-high gas selectivity figures, comparable to those of biological processes. Both cutting-edge concepts will be developed in parallel an integrated together to render a totally new gas sensing technology that surpasses the state-of-the-art.
As a matter of fact, the project will enable, for the first time, the integration of gas detectors in energetically autonomous sensors networks. Additionally, BetterSense will provide an integral solution to the gas sensing challenge by producing a full set of gas-specific sensors over the same platform to ease their integration in multi-analyte systems. Moreover, the project approach will certainly open opportunities in adjacent fields in which power consumption, specificity and nano/micro integration are a concern, such as liquid chemical and biological sensing.
In spite of the promising evidences that demonstrate the feasibility of this proposal, there are still many scientific and technological issues to solve, most of them in the edge of what is known and what is possible today in nano-fabrication and nano/micro integration. For this reason, BetterSense also aims to contribute to the global challenge of making nanodevices compatible with scalable, cost-effective, microelectronic technologies.
For all this, addressing this challenging proposal in full requires a funding scheme compatible with a high-risk/high-gain vision to finance the full dedication of a highly motivated research team with multidisciplinary skill
Max ERC Funding
1 498 452 €
Duration
Start date: 2014-02-01, End date: 2019-01-31
