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Central information infrastructure

Central information infrastructure, centralized biomaterial and machine learning analyses

Sonja Ständer, Martin Dugas, Walter Magerl

Research projects and collaborative groups that involve multiple institutes are of great importance to answer key questions of complex diseases. When different basic research approaches meet patient oriented projects and if the latter ones include different perspectives, questionnaires and examinations, it becomes even more complex. Such a comprehensive approach is the fundament of the research unit PRUSEARCH and was successful by close collaboration and thorough coordination. Stand-alone research units are often not able to manage structure and logistics involved in combining multidisciplinary data, interoperability methods and biomaterial processing. Being a platform project, this project (#Z) has supported the other subprojects to overcome these challenges, pool expertise and reducing parallel expenditures.

We will continue to provide and manage a central information infrastructure by building an up-to-date flexible and data protection legislation conform data capture system connected to a consented project space within a centralized database. It includes automatic integration and pseudonymization of multiple clinical data, questionnaire responses and standardized functional characterizations. Furthermore the homepage will be extended both regarding the publicly accessible and the research group internal private section. The internal section provides access to the database for each project. Harmonized standard operation procedures (SOPs) will be enhanced and updated. Central biomaterial analyses for skin biopsies of all-center recruited patients with chronic pruritus and their controls will be continued and enhanced. Material exchange between research unit partners will be coordinated by #Z, including combined use of biopsies from the same patient in different projects. Furthermore, #Z will provide basic material analysis such as dermatohistopathologic and molecular characterization of material and centralized high-throughput mRNA-sequencing and microbiome analysis. Finally #Z will provide the information infrastructure for intelligent data capture and perform centralized bioinformatics analysis of these data. The complexity of the datasets will be addressed applying machine learning analyses.

Coordination, harmonization of protocols and methods, actual handling of biomaterials and bioinformatics within the consortium, including state-of-the-art machine learning methods, requires a central project which will allow achievement of the additional value aimed to in this consortium.