High-Throughput Data Generation Requires High-Tech Data Management
Historically, one of the primary challenges faced by drug development teams was generating enough data to conduct authoritative research. Innovative technologies introduced over the last decade have all but solved this, but R&D teams now face an equally daunting challenge: efficiently managing and analyzing the massive amounts of data produced by high-throughput technologies. These technologies have outpaced the data management systems of many organizations, creating a bottleneck at the point of analysis and slowing R&D productivity.
Team-Based Science Brings Data Sharing Challenges
The shift to team-based approaches in research has also compounded the challenges of handling massive datasets. For maximum productivity, teams must work across disciplines, which often means sharing data with geographically dispersed team members and collaborators. Some of the common challenges that arise in this type of high-volume, collaborative environment include:
- The lack of a central point of access for data generated across team members.
- The lack of visibility into what data has already been generated.
- The lack of a reliable method for handing off data to other team members.
- The lack of automated data integration tools, requiring team members to manually integrate data from multiple sources.
While some of these challenges can be solved through well documented processes and communication standards, LabKey Biologics is specifically designed to enable this type of team-based science. Over the course of the next few months, we will be discussing each of these barriers, the challenges they cause, and how R&D teams can overcome them with the help of LabKey Biologics. Subscribe to the LabKey blog to follow along.