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Helping machine learning to help us in personalized medicine

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Sprecher: Dr. Julio Saez-Rodriguez, University Heidelberg, Germany
Veranstaltung: Mittwoch, den 23. September 2020 16:00 - Sonntag, den 13. September 2020 17:30
Ort: Online

This conference is part of the AI4Health Lecture Series organised by the Department of Computer Science and the Department of Life Sciences and Medicine of the University of Luxembourg. 

Abstract

One area where artificial intelligence is expected to have a major impact in the health area is by developing algorithms that help us provide the right drug for each patient, that is, for personalized medicine. In this talk I will discuss our work applying machine learning on large pharmaco-genomic screenings in cell lines to build predictive models. Integration of this data with prior knowledge on signaling pathways and transcription factors provides biomarkers and offer hypotheses for novel combination therapies. Our own analysis as well as the results of a crowdsourcing effort (as part of a DREAM challenge) reveals that prediction of drug efficacy is far from accurate, implying important limitations for personalised medicine. An important aspect that deserves further attention is the dynamics of signaling networks and how they response to perturbations such as drug treatment. I will present how cell-specific logic models, trained with measurements upon perturbations, can provides new biomarkers and treatment opportunities not noticeable by static molecular characterisation. In summary, I will advocate that combining the right data with biological knowledge will be important to build predictive models for personalized medicine.

Speaker

Julio Saez-Rodriguez is Professor of Medical Bioinformatics and Data Analysis at the Faculty of Medicine of the University of Heidelberg, and director of the institute of computational biomedicine. He is also a group leader of the EMBL-Heidelberg University Molecular Medicine Partnership Unit, and a co-director of the DREAM challenges (http://dreamchallenges.org) to crowdsource computational systems biology. He obtained his M.S. in Chemical Engineering in 2001, and a PhD in 2007 at the University of Magdeburg and the Max-Planck-Institute. He was a postdoctoral fellow at Harvard Medical School and M.I.T., and a Scientific Coordinator of the NIH-NIGMS Cell Decision Process Center from 2007 to 2010. From 2010 until 2015 he was a group leader at EMBL-EBI with a joint appointment in the EMBL Genome Biology Unit in Heidelberg, as well as a senior fellow at Wolfson College (Cambridge). From 2015 to 2018 he was professor of Computational Biomedicine at the RWTH University Medical Hospital in Aachen, Germany. He is interested in developing and applying computational methods to acquire a functional understanding of signaling networks and their deregulation in disease, and to apply this knowledge to develop novel therapeutics. Current emphasis in his group is on use of single-cell technologies, multi-omics integration, and understanding multi-cellular communication. More information at www.saezlab.org

Link: AI4Health Lecture Series
Julio