Sharing of biomedical research data facilitates independent validation of findings, the design of future clinical trials and the reuse of data to test new hypothesis. One platform to share data is the Immunology Database and Analysis Portal (ImmPort), a public warehouse providing open access to clinical and mechanistic data from currently 341 immunological and clinical studies. In addition to valuable high-throughput data elements, ImmPort provides access to individual-level data from clinical studies. Many of these clinical studies in ImmPort have an abundance of data associated with them that is not annotated and parsed into the structured ImmPort MySQL database model but made available as separate files in various different formats. In this form the data are not readily available for data mining or secondary analysis. We will prioritize the unstructured data from clinical studies for integration into the structured MySQL ImmPort model to facilitate better access and reuse. We further will harmonize the used vocabularies in the database for which a preferred terminology is not yet established but which is of high interest for secondary analyses. Currently, the mining of available data across studies in ImmPort is a challenge for users who have no experience in informatics and, therefore, rely on the keyword search on ImmPort?s web page. To address this critical need, we will develop an interactive cross-study data exploration and visualization user interface for data in the ImmPort model including the functionality to create cross-study exports. The data newly structure into the ImmPort model as well as the user interface will be integrated into ImmPort and its web page. The treatments of several diseases (e.g. allergies, organ transplantation) rely on the induction of immune tolerance. In ImmPort serval studies focus on different diseases but with the underlying topic of immune tolerance. We will perform a secondary analysis of the shared individual-level clinical and mechanistic data of these studies towards the identification of potential universal drivers of developing clinical immune tolerance. This analysis will be used to develop a step-by-step tutorial for the interactive user interface.
The reuse of publicly available clinical study data is important to validate findings but also to perform additional analyses, especially by combining data from several studies, for example as we will show in order to identify universal characteristics for patients who can develop immune tolerance e.g. during food allergy treatments but also after organ transplantation. This project will extend on the usability of this kind of patient-level clinical data shared through the Immunology Database and Analysis Portal (ImmPort) by structuring currently unstructured data, as well as developing an interactive cross-study data exploration and visualization user interface especially for users who lack expertise in informatics.
