Dr. Sanchez-Cabo is a mathematician by training, working for 25 years in bioinformatics. Her focus is the integrative analysis of big biomedical data using mathematical models and advanced statistical techniques, including AI approaches and causal inference methods. After obtaining her PhD in Life Sciences from the University of Manchester and a postdoctoral stay at the Graz University of Technology (Austria) she joined the National Center for Cardiovascular Research, where she currently leads the Computational Systems Biomedicine Lab and the Bioinformatics Unit, which integrate a team of 25 bioinformaticians of different backgrounds. So far she has authorshipped more than 120 scientific articles in peer-reviewed journals and obtained over 7M € in competitive calls at the national and international level. She is also an associate professor at the Universidad Autonoma de Madrid, member of the advisory board of the European Elixir infrastructure and the vicepresident of the Spanish Society for Bioinformatics and Computational Biology (SEBiBC).
Talk title: Towards digital twins for cardiovascular research
Abstract: Digital twins are high-resolution models of individuals built upon their multi-layer and dynamic molecular and phenotypical characteristics, integrating prior knowledge with patient-specific data. Widely used in other fields, they are a young field in biomedicine, since the underlying networks are often unknown. Thanks to the large amount of molecular, clinical and imaging data gathered in different biobanks, and particularly in the PESA study at CNIC (https://pesastudy.org/), we are applying causal inference techniques at the core of explainable AI to infer the personalized paths leading from health to disease. This virtual representations of individuals with similar characteristics, can be used to simulate the effect of different interventions on CV health. Also, the longitudinal nature of our studies makes it possible to test in vivo the proposed models.