Applying computational modelling to decipher disease-specific molecular networks
Nils Blüthgen
Many diseases are driven by alterations in intra-cellular and inter-cellular signalling pathways, and many treatment concepts exist that block those signalling pathways. Although these pathways have been largely mapped out it still hard to predict how our cells react these drugs. The main reasons are that these signalling pathways work quantitatively, and show strong cross-talks and feedbacks. In this talk I discuss how perturbation approaches combined with mathematical modelling and AI can help to better predict those responses.
Deciphering inter-organ trajectories to understand multimorbidity
Wolfgang Kübler
Multimorbidity, or the presence of two or more chronic health conditions in an individual, poses a growing healthcare problem with increasing prevalence, but one that still lacks mechanistic understanding. Epidemiologic studies and experimental evidence points have fueled the emerging recognition that multimorbidity is not the result of random co-incidence of different chronic diseases, but rather begins as a single-organ disease that proceeds to incite damage in secondary organs through dysregulated inter-organ communication. Signals mediating this inter-organ communication in health and disease comprise hormones, proteins, peptides, lipids as well as metabolites and toxins, but also neuronal or mechanical signals as well as trafficking of cells or extracellular vesicles. Of late, the increasing availability of longitudinal biosamples from well-characterized patient cohorts in combination with advances in multi-omics based sample analyses, multimodal data integration, and AI-based analysis of multidimensional datasets enables for the first time the analysis of such complex signal mechanisms and interactions along the trajectories from health to multimorbidity.
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How is artificial intelligence reshaping health and medicine? Join #AIforGood to explore the future of #AI4health with Eric Topol, Founder and Director of its Scripps Research Translational Institute.
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