Results & outcomes

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The REMEDIA toolbox

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Toolbox Database

A global unified database
gathering phenotype and exposome information.

toolbox-atmoshere

A versatile atmospheric simulation chamber  
targeting specific complex exposomes.

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A sensor device  
combining environmental and biomarker toolkits, flexible in terms of targeted pollutants and biomarkers.

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A machine learning supervised analysis  
using artificial intelligence techniques to predict health outcomes according to risk profiles.

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A Pan-European multi-criteria risk assessment tool  
mapping the overall exposome risk-related pulmonary diseases in Europe.

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Cost-effectiveness models
assessing the costs, performance and cost-effectiveness of a selection of prevention strategies targeting exposome risk factors.

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Econometric models
testing the interactions between economic, environmental and epidemiological variables.

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A causal inference model
allowing the identification of relevant risk factors.

toolbox-guidelines

New guidelines and recommendations
based on REMEDIA findings to better predict disease risks.

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A major breakthrough

Deciphering the impact of environmental components throughout life on COPD and CF could represent a major breakthrough in reducing morbidity and mortality associated with these two non-curable diseases and would lead to the identification of modifiable risk factors on which preventive action could be implemented.

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REMEDIA will try to identify one or several complex association(s) of exposome components linked with specific COPD and CF phenotypes, lung function trajectories and/or maximum lung function reached.

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REMEDIA will provide an integrated personal sensor device that will measure selected air pollutants together with specific biomarkers that reflect the health effects of exposome in COPD and CF patients.

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REMEDIA will deliver a tool allowing to edit risk indicators for the identification of subjects at risk to develop specific phenotype(s) of COPD or CF diseases, and to design the mapping of risk assessment levels for COPD and CF diseases.

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REMEDIA will propose cost-effective prevention strategies and new guidelines and recommendations.

These guidelines will take into account the risk due to certain exposomes for patients with COPD or CF and will then be implemented and disseminated at the end of the REMEDIA project.

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Useful guidance for future public health and environmental policies at European level

Developing a Human Exposome Project would present a fundamental shift in looking at health, by moving research away from ‘one exposure, one disease’ understanding to a more complex picture upon which to build solid, cost-effective preventive actions and policies in the future.

New guidelines, recommendations and cost-effective prevention strategies will be produced in the context of the REMEDIA Project. Thanks to the toolbox developed at the project completion, including new effective risk assessment models based on machine learning and an innovative sensor device, an expected perspective of the project will be to implement these instruments within an evidence-based information system to allow continuous data collection. Information thus gathered would provide useful guidance for future public health and environmental policies at the European level.

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REMEDIA contribution to other substantial impacts

Findings obtained in the REMEDIA project will be relevant to populations that are largely beyond patients with COPD or CF.
The identification of exposome components as essential modifiers of COPD and CF phenotypes could be applicable to other associated diseases (asthma, rheumatoid arthritis, inflammatory bowel diseases…), thus could have a global impact on several diseases of high burden.

 

The 2 atmospheric simulation chambers developed by LISA & FORTH can be further adapted to newly identified exposomes.
Those two fully versatile chambers could represent great tools to develop and use in order to simulate the effects of complex atmospheres in the context of diseases other than COPD and CF. This could be applied for example to preclinical models of cardiac, neurological diseases, etc.