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CORDIS

The RapiD and SecuRe AI enhAnced DiaGnosis, Precision Medicine and Patient EmpOwerment Centered Decision Support System for Coronavirus PaNdemics

Descripción del proyecto

Plataforma innovadora de diagnóstico y pronóstico para pandemias de coronavirus

El proyecto DRAGON, financiado con fondos europeos, apoya el esfuerzo de un consorcio multinacional de institutos de investigación académica, socios biotecnológicos y farmacéuticos, organizaciones de pacientes y asociaciones profesionales para desarrollar una plataforma plurifacética de diagnóstico y pronóstico para prevenir y combatir futuras pandemias de coronavirus. Los datos de la pandemia actual se utilizarán para validar y optimizar las propuestas de diagnóstico y pronóstico. Gracias al uso de técnicas avanzadas de inteligencia artificial, el perfilado molecular se convertirá en un método clínico de precisión para el desarrollo acelerado de terapias nuevas. El estudio propuesto será uno de los primeros en desarrollar técnicas innovadoras de aprendizaje automático e introducir mejoras en los procedimientos clínicos que podrían ser revolucionarios durante futuros brotes de coronavirus.

Objetivo

In this project, a multinational consortium of high-tech SMEs, academic research institutes, biotech and pharma partners, affiliated patient-centred organisations and professional societies will achieve a multi-faceted diagnostic and prognostic platform and a precision medicine approach. This consortium will together realize a patient empowerment centred decision support system that will enable multiple stakeholders to participate in improved and more rapid diagnosis and prognosis, as well as the potential of precision medicine for accelerated development of new therapies. Citizens and patients will be empowered to contribute to the efficient planning and usage of resources. The project will begin by rapidly delivering a nomogram. Data from the pandemic will be used to validate and further optimise a scalable multifactorial diagnosis/prognosis solution. Existing and new data and sample collection efforts will be used to perform molecular profiling, which - using advanced AI techniques will be shaped into a precision medicine approach. These initial outputs will undergo further enhancement and assessment to evaluate the value they add to the development of a decision support system. The entire effort will be supported by the deployment of a federated machine learning system that will allow for the GDPR compliant use of multinational data resources. The various iterations of the decision support system and the federated machine learning system will be made available to other coronavirus initiatives with the intent to develop a stakeholder community that forms the basis for a highly efficient innovation ecosystem. Our proposed study will be one of the first to develop innovative machine learning, and clinical procedure improvement that will potentially make a huge socio-economic impact for the coronavirus outbreak.

Régimen de financiación

RIA - Research and Innovation action

Coordinador

UNIVERSITEIT MAASTRICHT
Aportación neta de la UEn
€ 1 114 670,16
Dirección
MINDERBROEDERSBERG 4
6200 MD Maastricht
Países Bajos

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Región
Zuid-Nederland Limburg (NL) Zuid-Limburg
Tipo de actividad
Higher or Secondary Education Establishments
Enlaces
Coste total
€ 1 114 670,16

Participantes (18)