Health

Andalusian Computational Medicine Platform integrates bioinformatics and…

GRANADA, 7 (EUROPE PRESS)

The Progreso y Salud Foundation, an entity dependent on the Ministry of Health and Consumer Affairs, has integrated two of its work areas into the recently established Computational Medicine Platform of the Andalusian Public Health System (SSPA), aimed at researching diseases from the data science perspective.

The Board has explained through a statement that it is a platform designed to support and promote innovation in the management of biomedical big data within the health system, including work areas such as genomics, medical imaging and clinical data with the idea of ​​favoring a more personalized medicine that improves and optimizes patient care and makes the public health system more sustainable.

The Computational Medicine Platform is led by Joaquín Dopazo, until now director of the Clinical Bioinformatics Area of ​​the Progreso y Salud Foundation. It is structured in four lines of work: development of biomedical applications; intelligent systems and data science; translational bioinformatics; and big data; all of them will work in synergy from different perspectives on the data produced in the health system, mainly genomic, clinical and medical imaging data.

The ultimate goal is to develop new ways to improve diagnosis, prognosis and treatment decisions, thus promoting precision, sustainable and equitable medicine.

“The effective management of the data generated in the health system offers enormous potential in dealing with diseases”, assured Dopazo, explaining that “the population of Andalusia is greater than that of 30 European countries, which allows its Population Health Database, one of the largest and most detailed clinical databases in the world, already stores a cumulative cohort of more than 13 million patients.”

“With the Computational Medicine Platform we will be able to approach the study of clinical data in a comprehensive way, maximizing the knowledge that can be obtained”, he stressed, concluding that “this knowledge directly reverts, increasing the precision of our medicine through new biomarkers, clinical decision support systems, among others; which results in greater personalization of medicine and greater sustainability of the health system”.

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