Workflow; Data exchange interface; research data integration ; Software evaluation; Connection to clinical data warehouse; Biobanking mangagment solutions
Huemer Markus, Mairpady Shambat Srikanth, Bergada-Pijuan Judith, Söderholm Sandra, Boumasmoud Mathilde, Vulin Clément, Gómez-Mejia Alejandro, Antelo Varela Minia, Tripathi Vishwachi, Götschi Sandra, Marques Maggio Ewerton, Hasse Barbara, Brugger Silvio D., Bumann Dirk, Schuepbach Reto A., Zinkernagel Annelies S. (2021), Molecular reprogramming and phenotype switching in Staphylococcus aureus lead to high antibiotic persistence and affect therapy success, in Proceedings of the National Academy of Sciences
, 118(7), e201492011-e201492011.
Despite the success of antibiotics, chronic bacterial infections still cause a substantial disease burden. The main reason is antibiotic resistance, which is becoming a more and more deleterious problem. This public health issue together with the ageing population with increased comorbidities and advances in surgical implants in Western societies is likely to be one of the most important health problems while we are approaching the post-antibiotic era. One of the most important goals of today’s medicine and research must be on the one hand to improve the understanding of bacterial infections for tailoring still effective antimicrobial therapies more successfully and on the other hand to reduce resistance development. Our hypothesis is that individual therapeutic strategies (e.g. novel biomarkers, understanding the physiologic relevance of the colonizing microbiome, etc.) will critically improve patient outcomes. The key challenge towards developing such a personalized medicine approach of infectious diseases is the integration of clinical, molecular, and epidemiological data with biological samples stored in a variety of biobanks. The aim of our project is to establish a proof of concept network for the University Hospital Zurich (USZ) by harmonizing sample management processes, implementing a joint biobanking management system (BIMS), and establishing the link and interoperability between the partner biobanks as well as with external sample collections and data repositories. This set-up is expected to significantly improve data quality and will enable efficient access to samples (bacteria, serum, tissue) from different organ sites thus facilitating the investigation of systemic effects of bacterial infection as well as the causative agent. Additionally, interoperable data will help to optimize treatment of bacterial infections and thus clinical outcome. Advances in information technology (IT) allow the collection of large health-related patient data. Big data require algorithmic analysis and a secure IT infrastructure for computing, interoperability, data storage and data sharing. Our scientific collaboration network of already established biobanks from various cohorts including the prospective cohorts for bacterial infections (vascular graft infections, infective endocarditis, multi-resistant bacteria) and the biobanks of surgery (burns and multiple injuries cohorts), with tissue biobanks (pathology) and stool microbiota biobank sets the stage for future interdisciplinary and inter-institutional translational research studies allowing personalized diagnostics and treatment.The implementation of the proposed harmonized IT solution in a university hospital setting for biobanks with different backgrounds and sample types demands a diligent and exhaustive business analysis and requirements engineering. The consortium for this project comprises all relevant stakeholders and national collaboration partners in order to ensure alignment with regulatory and scientific requirements as well as full integration into the hospital IT services. Such a sustainable, fully integrated and joint Biobanking management system will enable research access to complementary samples with the overall goal of optimizing treatment for bacterial infections and thus clinical outcome.