It does not take long to understand why data management can be difficult for life sciences organizations – and why poor data management stymies innovation. The data that enterprises hold can go back many years, predating standardization efforts. They can be simple tabular data or complex imaging data. They can also be sourced from numerous places. Life sciences companies often have cemented processes and organizational silos that have been in place for decades. While these institutional norms cannot be dismantled and rebuilt overnight, de-siloing data is a critical first step to accelerating R&D.
In an era of cost-cutting and increasing demands for efficiency, many pharma research teams are taking steps to realize new...
