Abstract 

Large-scale omics data analyzed by artificial intelligence (AI) technology is finding its way into the clinic to revolutionize our approach to medicine as a whole. Beyond personalized medicine, AI-driven medical data profiling is leaving massive footprints - from drug repurposing to a mechanistic redefinition of diseases. To move away from organ- and symptom-based disease descriptors to clinically actionable mechanistic approaches, computational systems and network medicine emerged. We will introduce the field, discuss current approaches and pitfalls as well as potential future avenues. While we first focus on oncology to illustrate the principles of systems/network medicine - as a running example - along the talk, we will change our focus to arbitrary diseases to demonstrate the potential and scalability of the field and our own work. Specifically we will illustrate how massive distributed medical genomics and microbiome data can be analyzed in a privacy-preserving fashion using federated learning.