Unlocking the potential of real-world data through emerging data sources

Real-world data (RWD) has rapidly gained importance for regulatory submissions. RWD is also collected to routinely monitor and evaluate the post-market safety of drugs, medical devices, and diagnostics, addressing the shortcomings of traditional controlled trials. Clinical data derived from the real-world use of a treatment provides insights into a more heterogeneous patient population than is typically examined in clinical trials. The emergence of technology-driven data collection via wearables, registries or open-source databases leads to a lot of data to supplement the clinical research pipeline. For collecting RWD, one has to look for data outside of the known infrastructure of clinical trials. However, once collected, it usually presents as unstructured, voluminous and dynamic. Additionally, RWD can be incomplete and lack endpoints and therefore the quality requires careful assessment. In this talk, we will discuss how RWD qualifies as a valid source, practical implementation and abstraction of RWD sources, and the evolving skill set required for data managers.