As response to a recommendation for the integration of genome sequencing in the SARS-CoV-2 surveillance published by the Public Health Commission of the Interterritorial council in 22 January 2021, a joint instruction was carried out, 1/2020 from the General Secretariat for Research, Development and Innovation in Health and the Management Directorate of the Andalusian Health Service, for the Management of samples in the approach to Personalized Medicine in COVID-19.
This computational infrastructure constitutes a crucial element to support the ongoing transformation of the Andalusian Health System from a passive data warehouse to an active entity able of managing, interpreting and generating Real World Evidence (RWE), on new biomedical knowledge from its Real World Data (RWD).
With this project we intend to find biomarkers of evolution and prognosis that can have an immediate impact on clinical management and therapeutic decisions in patients infected by SARS-CoV-2.
CSyF SARS-CoV-2 seguimiento Andalucía
Un consorcio, compuesto por 14 hospitales que cubren todas las provincias de Andalucía, los 5 Institutos de Investigación Sanitaria de Andalucía, la Subdirección Técnica de Gestión de la Información, la Dirección General de Salud Pública (Servicio de Vigilancia Epidemiológica y Salud Laboral) y la Fundación Progreso y Salud, pretende usar la red de centros de diagnóstico de la comunidad Andaluza y los secuenciadores de los Institutos de investigación Sanitaria y centros asociados para secuenciar unas 1.000 muestras del virus SARS-CoV-2 cubriendo toda Andalucía y representado una muestra lo más equilibrada posible de las distintas tipologías de pacientes (edad, sexo, complicaciones previas, tratamientos previos), así como los distintos cuadros clínicos observados y las respuestas a los tratamientos.
Covid-19 drug repurposing
Proponemos el uso de un modelo mecanístico basado en inteligencia artificial que ya ha demostrado su efectividad en enfermedades raras para la reutilización de fármacos para Covid-19.
Mechanistic models for drug repurposing in rare diseases with machine learning methods
ML analysis of genomic Big Data will definitely change the paradigm of research in RD, where diseases are typically addressed one at a time. This proposal constitutes an innovative approach to domains in which no much information exists but genomic Big Data are available, by using ML to expand the current biological knowledge.
Disease Maps Project is an open community effort to comprehensively represent disease mechanisms for various diseases. The consortium comprises computational biology teams working on disease models and clinicians or experimental biologists who would like to contribute as domain experts. The aim is to actively expand the knowledge in molecular mechanisms of diseases.
Machine Learning Frontiers in Precision Medicine
The Marie Curie Innovative Training Network entitled “Machine Learning Frontiers in Precision Medicine” brings together leading European research institutes in machine learning and statistical genetics, both from the private and public sector, to train 14 early stage researchers. These scientists will apply machine learning methods to health data. The goal is to reveal new insights into disease mechanisms and therapy outcomes and to exploit the findings for precision medicine, which hopes to offer personalized preventive care and therapy selection for each patient.
Undiagnosed Rare Diseases Programme (ENoD)
The Program for Undiagnosed Rare diseases, EnoD, is an initiative of CIBERER aimed at improving knowledge about the genetic causes of rare diseases. It entails the discovery of new genes and variants. It is effective through the study of specific clinical cases without molecular diagnostics. To this end, ENoD program places research directly at the service of the National Health System.
ENoD is framed in one of the priority international lines (IRDIRC, H2020) as it is the identification of the genetic causes of rare diseases.
Information Technology Infrastructure for the implementation of a system for Personalized Genomic Medicine in Hereditary Diseases and Cancer
The information technology infrastructure will be dedicated to hosting a centralized bioinformatic system for genomic and precision medicine, aimed at diagnosing, providing treatment recommendations, and preventative medicine.
Proyecto Genoma 1000 Navarra (NAGEN 1000)
NAGEN: Proyecto Genoma 1000 Navarra (NAGEN 1000) is an initiative led by the Navarrabiomed biomedical research centre whose purpose is to transfer the use of the cutting-edge whole human genome analysis technology to Navarra’s public health care system. To this end, 1,000 genomes of patients with rare diseases and certain types of cancer in the Navarrese Health Service-Osasunbidea (SNS-O) and of their relatives are being analysed.
Medical Genome Project
The Medical Genome Project (MGP) was the first regional genomics project carried out in Spain, starting by 2010. MGP was an unprecedented study that has tackled the sequencing of hundreds of human genomes of phenotyped sick individuals and control individuals, to develop the technologies to speed up the laborious process of discovering genes responsible for a given disease. This also means exploring new approaches in the development of diagnostic techniques that allow early detection of these diseases and opens new possibilities for the generation of drugs or therapies that allow their treatment, also at the genetic or cellular level.