RESEARCH TOPICS FUNDED
Call for projects of the FC3R – Results publication in April 2024
With this call for projects, the FC3R has undertaken to provide financial support for innovative projects that develop or democratise "Digital Approaches" that will enable progress to be made in Replacement (modelling, in silico development of digital twins, etc.), Reduction (exploitation of existing results "Data mining", analysis of large datasets "Big data", etc.) or Refinement (digital "monitoring" sensors, non-contact experimentation, etc.) in the life sciences. Cross-disciplinary and collaborative projects have been encouraged, and particular attention has been paid to managing data and making it available to the community (PGD, FAIR, Open Science, etc.).
Of the 40 projects submitted, 9 were selected by the Scientific Committee for total funding by the FC3R of 399 990 €.
AMI : Animal-Machine Interfaces to refine non-human primates’ welfare monitoring, digital enrichments and social group management.
Abstract:
Concern for the welfare of captive non-human primates (NHP) is a legitimate societal debate and a priority for all facilities working with these animals. Researchers suggest developing animal-machine interfaces (AMI) for NHP to significantly improve their welfare and monitoring. AMI would offer interactive enrichment possibilities, such as ‘on-demands’ digital entertainment, enabling animals to control their environment. These interfaces would also enhance physiological and psychological monitoring of the animals via thermal cameras, sensors and artificial intelligence programs, enabling earlier detection of possible physical or mental health problems. The overall aim of the project is to use innovative modern tools to improve the housing conditions, daily life and well-being of all captive NHP.
The project is carried out by : Sébastien BALLESTA.
Funding allocated:
The project AMI is allocated a funding of € 48 000.
DIOGENES : Digital twIns fOr reducinG animal usE iN rhEumatoid arthritiS.
Abstract:
Digital Twins, namely virtual representations of systems that can be used for monitoring and dynamic predictions, could serve as a key technology for personalised medicine by modelling the behaviour of virtual patients. To build such medical digital twins, we need to develop appropriate modelling and computational methods and find ways to calibrate such models to actual human patients or patient populations. Digital Twins are a promising and emerging concept in medicine and can have a tremendous impact on the reduction or possibly elimination of animal use in biomedicine.
The project is carried out by : Anna NIARAKIS.
Funding allocated:
The project DIOGENES is allocated a funding of € 46 333.
DrugDataMiner : Non Clinical and Clinical Data Extraction to reduce the use of animals in research and testing.
Abstract:
The aim of the project DrugDataMiner is to make both non clinical and clinical data more accessible for the purposes of reuse and reducing the number of animals that need to be tested. Such data does exist but is under-exploited because it is dispersed and requires expertise to extract the relevant information. We will develop an AI method based on natural langage processing to analyze and extract information from marketing authorization dossiers, publications or patents. We are going to be starting from the list of authorised medicines already in the database e-Drug3D. Our aim is to create an automated analysis method that can be queried via a web interface and highlight information of interest for reducing the use of animals, while at the same time advancing scientific knowledge.
The project is carried out by : Dominique DOUGUET.
Funding allocated:
The project DrugDataMiner is allocated a funding of € 29 000.
LEARN (L3Rn) : Development of an innovative platform for teaching experimental physiology in higher education..
Abstract:
Although taking into account the societal context, physiology teaching at university continues to include animals, mainly due to the absence of satisfactory alternative methods. The simulation systems currently available are rare, rudimentary, unsophisticated and restricted to basic conditions. The aim of this project is to acquire non-invasive physiological data on cardio-respiratory function, mobility and vocalizations in rats, in order to build a set of education material including video demonstrations and a digital platform for simulating different conditions related to dayly life; In the long term, these teaching tools will make it possible to replace the use of animals for general training courses, and to significantly reduce their number and refine the procedures for professionnal training courses.
The project is carried out by : Stéphane TANGUY.
Funding allocated:
The project LEARN (L3Rn) is allocated a funding of € 49 437.
MOUSETUBEV2 : Organisation of the sharing and re-use of rodents sound recordings to understand their vocal communication.
Abstract:
Rodents communicate using ultrasounds. Understanding the conditions and types of vocalisations they make remains an important scientific target. To stimulate research, we aim to develop a new version of mouseTube, a database gathering mouse ultrasonic vocalisations. mouseTube V2 will optimally organize curated data and allow external applications to automatically analyse audio recordings. This will boost our knowledge on rodent ultrasonic communication while sparing further animals from experiments. mouseTube V2 will provide the scientific community with a catalogue of existing analysis software and an annotated reference test dataset. mouseTube V2 will be open to the public, and highlight the latest research advances in a simple and accessible way. Altogether, this project favours the exchange and re-use of animal data through open numeric tools.
The project is carried out by : Elodie EY-.
Funding allocated:
The project MOUSETUBEV2 is allocated a funding of € 45 000.
OvoTox : Coupling physiologically-based kinetic models of endocrine axes with structured cell population dynamics models: an integrative approach of reproductive toxicity.
Abstract:
The impact of micropollutants on living organisms is a major concern for health and the environment. Endocrine disruptors (ED) interfere with the physiology of organisms and can alter major biological functions, particularly the reproductive function. Fish are species of interest in toxicology, because their aquatic living environment and their physiology make them particularly sensitive to pollutants. The project partners have developed a mathematical models making it possible to assess the level of exposure of different organs to ED and their influence on thesecretion of hormones allowing the communication between organs. Our objective is to integrate into the model a new module, centered on the production of reproductive cells, which will enable one to predict accurately the qualitative and quantitative effects on fish spawning, both in the short and long term.
The project is carried out by : Frédérique CLEMENT.
Funding allocated:
The project OvoTox is allocated a funding of € 50 000.
sIRMaqc : standardizing anatomical and quantitative MRI for connectomics.
Abstract:
The aim of the sIRMaqc project is to implement a strategy for standardizing MRI data and processing for connectomics studies in animals. These studies will make it possible to answer fundamental neuroscience questions or better understand neuropathologies using non-invasive MRI. More specifically, using a limited number of animals and innovative MRI methods, the project will create digital twins of mice. These can then be used by the entire international community, avoiding the need to acquire their own reference data and greatly limiting the number of animals used.
The project is carried out by : Sylvain MIRAUX.
Funding allocated:
The project sIRMaqc is allocated a funding of € 49 720.
SYNLET : Investigating Synthetic Lethality to Guide Personalization of Glioblastoma Treatment.
Abstract:
Statistical methodologies are urgently needed to personalize cancer therapies. We aim to design such approach focusing on identifying synthetic lethal interactions (SLi) to selectively target cancer cells. Synthetic lethality harnesses the simultaneous loss of two genes leading to cell death, whereas the loss of either gene alone is non-lethal. An existing algorithm has identified SLi from transcriptomics and CRISPR genetic vulnerability data from a cancer cell line public database. It will be refined for glioblastoma, the most frequent and aggressive brain tumors in adults. The clinical relevance of the SLi identified using public data will be investigated in drug screening on patient-derived cell lines. The validated SLi will be further explored in mathematical models representing digital twins of the patients to gain a deep understanding of the cell death mechanisms.
The project is carried out by : Annabelle BALLESTA.
Funding allocated:
The project SYNLET is allocated a funding of € 45 000.
SYNPLASTOOL : Development of the Synapse Plasticity tool for prediction of synapse plasticity outcome in silico.
Abstract:
Synaptic plasticity, crucial for brain functions like learning and memory, involves adaptive changes synapses in response to activity. Current research depends on experiments using rodent brain slices, lacking a digital tool accurately predicting synapse outcomes. Our project aims to create SYNPLASTOOL, a digital alternative for exploring synapse plasticity. We published a reliable mathematical model tested across diverse experimental settings. Using this model, we also generated predictive maps for synapse outcomes and initiated the construction of SYNPLASTOOL. Supported by FC3R funding, our objectives are tool refinement, validation against experiments, and promotion in neuroscience and education. This tool refines experimental settings before rodent use, potentially reducing their necessity by studying synapse plasticity virtually. Our open-science approach seeks widespread tool adoption, offering electrophysiologists a rodent-free approach to study synaptic plasticity.
The project is carried out by : Hélène MARIE.
Funding allocated:
The project SYNPLASTOOL is allocated a funding of € 37 500.
AMI : Animal-Machine Interfaces to refine non-human primates’ welfare monitoring, digital enrichments and social group management.
DIOGENES : Digital twIns fOr reducinG animal usE iN rhEumatoid arthritiS.
DrugDataMiner : Non Clinical and Clinical Data Extraction to reduce the use of animals in research and testing.
Abstract:
Concern for the welfare of captive non-human primates (NHP) is a legitimate societal debate and a priority for all facilities working with these animals. Researchers suggest developing animal-machine interfaces (AMI) for NHP to significantly improve their welfare and monitoring. AMI would offer interactive enrichment possibilities, such as ‘on-demands’ digital entertainment, enabling animals to control their environment. These interfaces would also enhance physiological and psychological monitoring of the animals via thermal cameras, sensors and artificial intelligence programs, enabling earlier detection of possible physical or mental health problems. The overall aim of the project is to use innovative modern tools to improve the housing conditions, daily life and well-being of all captive NHP.
The project is carried out by : Sébastien BALLESTA.
Funding allocated:
The project AMI is allocated a funding of € 48 000.
Abstract:
Digital Twins, namely virtual representations of systems that can be used for monitoring and dynamic predictions, could serve as a key technology for personalised medicine by modelling the behaviour of virtual patients. To build such medical digital twins, we need to develop appropriate modelling and computational methods and find ways to calibrate such models to actual human patients or patient populations. Digital Twins are a promising and emerging concept in medicine and can have a tremendous impact on the reduction or possibly elimination of animal use in biomedicine.
The project is carried out by : Anna NIARAKIS.
Funding allocated:
The project DIOGENES is allocated a funding of € 46 333.
Abstract:
The aim of the project DrugDataMiner is to make both non clinical and clinical data more accessible for the purposes of reuse and reducing the number of animals that need to be tested. Such data does exist but is under-exploited because it is dispersed and requires expertise to extract the relevant information. We will develop an AI method based on natural langage processing to analyze and extract information from marketing authorization dossiers, publications or patents. We are going to be starting from the list of authorised medicines already in the database e-Drug3D. Our aim is to create an automated analysis method that can be queried via a web interface and highlight information of interest for reducing the use of animals, while at the same time advancing scientific knowledge.
The project is carried out by : Dominique DOUGUET.
Funding allocated:
The project DrugDataMiner is allocated a funding of € 29 000.
LEARN (L3Rn) : Development of an innovative platform for teaching experimental physiology in higher education..
MOUSETUBEV2 : Organisation of the sharing and re-use of rodents sound recordings to understand their vocal communication.
OvoTox : Coupling physiologically-based kinetic models of endocrine axes with structured cell population dynamics models: an integrative approach of reproductive toxicity.
Abstract:
Although taking into account the societal context, physiology teaching at university continues to include animals, mainly due to the absence of satisfactory alternative methods. The simulation systems currently available are rare, rudimentary, unsophisticated and restricted to basic conditions. The aim of this project is to acquire non-invasive physiological data on cardio-respiratory function, mobility and vocalizations in rats, in order to build a set of education material including video demonstrations and a digital platform for simulating different conditions related to dayly life; In the long term, these teaching tools will make it possible to replace the use of animals for general training courses, and to significantly reduce their number and refine the procedures for professionnal training courses.
The project is carried out by : Stéphane TANGUY.
Funding allocated:
The project LEARN (L3Rn) is allocated a funding of € 49 437.
Abstract:
Rodents communicate using ultrasounds. Understanding the conditions and types of vocalisations they make remains an important scientific target. To stimulate research, we aim to develop a new version of mouseTube, a database gathering mouse ultrasonic vocalisations. mouseTube V2 will optimally organize curated data and allow external applications to automatically analyse audio recordings. This will boost our knowledge on rodent ultrasonic communication while sparing further animals from experiments. mouseTube V2 will provide the scientific community with a catalogue of existing analysis software and an annotated reference test dataset. mouseTube V2 will be open to the public, and highlight the latest research advances in a simple and accessible way. Altogether, this project favours the exchange and re-use of animal data through open numeric tools.
The project is carried out by : Elodie EY-.
Funding allocated:
The project MOUSETUBEV2 is allocated a funding of € 45 000.
Abstract:
The impact of micropollutants on living organisms is a major concern for health and the environment. Endocrine disruptors (ED) interfere with the physiology of organisms and can alter major biological functions, particularly the reproductive function. Fish are species of interest in toxicology, because their aquatic living environment and their physiology make them particularly sensitive to pollutants. The project partners have developed a mathematical models making it possible to assess the level of exposure of different organs to ED and their influence on thesecretion of hormones allowing the communication between organs. Our objective is to integrate into the model a new module, centered on the production of reproductive cells, which will enable one to predict accurately the qualitative and quantitative effects on fish spawning, both in the short and long term.
The project is carried out by : Frédérique CLEMENT.
Funding allocated:
The project OvoTox is allocated a funding of € 50 000.
sIRMaqc : standardizing anatomical and quantitative MRI for connectomics.
SYNLET : Investigating Synthetic Lethality to Guide Personalization of Glioblastoma Treatment.
SYNPLASTOOL : Development of the Synapse Plasticity tool for prediction of synapse plasticity outcome in silico.
Abstract:
The aim of the sIRMaqc project is to implement a strategy for standardizing MRI data and processing for connectomics studies in animals. These studies will make it possible to answer fundamental neuroscience questions or better understand neuropathologies using non-invasive MRI. More specifically, using a limited number of animals and innovative MRI methods, the project will create digital twins of mice. These can then be used by the entire international community, avoiding the need to acquire their own reference data and greatly limiting the number of animals used.
The project is carried out by : Sylvain MIRAUX.
Funding allocated:
The project sIRMaqc is allocated a funding of € 49 720.
Abstract:
Statistical methodologies are urgently needed to personalize cancer therapies. We aim to design such approach focusing on identifying synthetic lethal interactions (SLi) to selectively target cancer cells. Synthetic lethality harnesses the simultaneous loss of two genes leading to cell death, whereas the loss of either gene alone is non-lethal. An existing algorithm has identified SLi from transcriptomics and CRISPR genetic vulnerability data from a cancer cell line public database. It will be refined for glioblastoma, the most frequent and aggressive brain tumors in adults. The clinical relevance of the SLi identified using public data will be investigated in drug screening on patient-derived cell lines. The validated SLi will be further explored in mathematical models representing digital twins of the patients to gain a deep understanding of the cell death mechanisms.
The project is carried out by : Annabelle BALLESTA.
Funding allocated:
The project SYNLET is allocated a funding of € 45 000.
Abstract:
Synaptic plasticity, crucial for brain functions like learning and memory, involves adaptive changes synapses in response to activity. Current research depends on experiments using rodent brain slices, lacking a digital tool accurately predicting synapse outcomes. Our project aims to create SYNPLASTOOL, a digital alternative for exploring synapse plasticity. We published a reliable mathematical model tested across diverse experimental settings. Using this model, we also generated predictive maps for synapse outcomes and initiated the construction of SYNPLASTOOL. Supported by FC3R funding, our objectives are tool refinement, validation against experiments, and promotion in neuroscience and education. This tool refines experimental settings before rodent use, potentially reducing their necessity by studying synapse plasticity virtually. Our open-science approach seeks widespread tool adoption, offering electrophysiologists a rodent-free approach to study synaptic plasticity.
The project is carried out by : Hélène MARIE.
Funding allocated:
The project SYNPLASTOOL is allocated a funding of € 37 500.
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