Medical research is highly data-driven, and projects are made and broken by the quantity and quality of data available. Biostorage Technologies, a company that stores and manages biological samples for the top biopharmaceutical companies and academic research institutions, knew that it could dramatically enhance the way that research is conducted globally, by using the power of a logical data warehouse.
Disparate Data Sources Led to Research Roadblocks
Rick Hart, director of technology solutions at Biostorage, spoke about this new initiative at TDWI Chicago (you can download the presentation used from Slideshare). The company was aware that researchers had been coming up against roadblocks because they lacked basic data about what samples were available, where they were stored, what they could be used for, and most importantly, how they might be re-used, since more often than not, biological samples are stipulated for a single use in a single study. Also, much of the related data, such as clinical information, patient profiles, and genotyping data, was stored on different systems and was owned by different parties, and there was no straightforward way to link the sample data with data from these other systems.
A Logical Data Warehouse Connected the Dots
To unify the data, with an eye toward streamlining the research process, Biostorage established a logical data warehouse, dubbed ISIDOR (for Integrated Sample Intelligence Data Online Repository), which uses data virtualization, furnished by the Denodo Platform, to access the myriad sources. These sources run the gamut from laboratory information management systems (LIMS), to lab hardware data (billions of devices), to clinical trial management systems (CTMS), to office docs and partner databases. Enabled by data virtualization, ISIDOR provides a single window with which to view all of the available sample data, along with related information, including data from other sample management applications.
By using ISIDOR, researchers can:
- Easily visualize sample availability through interactive dashboards
- More easily share samples across the research community
- Check project feasibility in advance, based on sample availability
- Track and count the number of samples received from each source, and run analytics on sample sets that span multiple sources
- Search for samples based on demographic, geographic, and other secondary data
Data virtualization plays a strong role here, you can read more about data virtualization in the life sciences industry here. If you have thoughts on moving to a logical data warehouse architecture, within a research environment, please share your thoughts below.
- Advanced Medical Research, Powered by a Logical Data Warehouse - June 29, 2016