Abstract
The number of clinical studies and associated research has increased significantly in the last few years. Particularly in rare diseases, an increased effort has been made to integrate, analyse, and develop new knowledge to improve patient stratification and wellbeing. Clinical databases, including digital medical records, hold significant amount of information that can help understand the impact and progression of diseases. Combining and integrating this data however, has provided a challenge for data scientists due to the complex structures of digital medical records and the lack of site wide standardization of data entry. To address these challenges we present a python backed tool, Meda, which aims to collect data from different sources and combines these in a unified database structure for near real-time monitoring of clinical data. Together with an R shiny interface we can provide a near complete platform for real-time analysis and visualization.