TP5 - SyMBoD

Integrative system medicine platform

System medicine platforms require the integration of clinical and research data, mathematical and computational models and user-friendly tools for efficient, personalized diagnoses and identification of therapy options („theranostics“). To make our research data findable, accessible, interoperable and reusable (FAIR) and to meet the needs of platform users, storage, access, manipulation and distribution of the data generated from the consortium will be facilitated by intuitive user interfaces. In particular, we will provide a framework for semantic integration of clinical and multi-omics data from the other subprojects and external knowledge resources by harmonizing metadata across several data sources and developing annotation and integration tools for experimentalists. Furthermore, we will seamlessly plugin exploratory and predictive bioinformatics and machine learning analyses for optimisation of simulations and models as well as for stratification of patients. Here, we build upon existing and newly-developed bioinformatics methods for network-based identification of system biology driven biomarkers and de novo stratification of patients into mechanistic endophenotypes. Phenotypic parameters obtained this way will be directly feedable into CAD/CAE simulations and models developed in SP4, which will in turn be integrated as interactive workflows within the platform. Rich interactive visualizations for hypothesis generation based on integrative data analyses and therapy option suggestion using individually optimized 3D scaffold models will allow platform users to perform end-to-end individualized bone regenerative therapy optimizations. Ultimately, we will advance the research platform into a patient-centric system for personalized bone regenerative therapy that is optimized towards clinicians’ needs and practices. This subproject is augmented by the collaboration between The Baumbach Lab at TUM and Genevention GmbH who have sufficient hardware resources, extensive software development experience and state-of-the-art scientific expertise in the field.