Data Management: Transforming Big Data Into Actionable Insights

Unprecedented advances in diagnostic and other scientific technologies are creating an ability to generate high-content and high-throughput molecular and cell-based assays at unprecedented rates—giving translational researchers massive amounts of complex data earlier in the clinical development process. That’s the good news. However, that news is tempered by the challenge of obtaining valuable insights from such complex data through the assimilation of biomarker data (specialty and esoteric lab) and clinical data (efficacy or pharmacokinetics)—a process that historically has been tedious and difficult. Furthermore, in order to unlock the full potential of these data once collected, highly specialized data management resources must be assembled to support informatics and data science.  Delivering on the promise of precision medicine requires new approaches and informatics platforms to address these new challenges. Proper assimilation of collective data by specialized resources will allow for the identification and stratification of  high-responding patient cohorts, improve safety profiles, effectively guide dose selection, and reduce the time and cost of clinical trials. Studies introducing complex and content-rich biomarkers to the realm of decision-making processes now require new technology-enabled services, namely biomarker data management (BDM).