Clinical trials are becoming more complex and a confluence of forces—including the ongoing COVID-19 pandemic, greater emphasis on patient experience, increasing protocol complexity, and precise value differentiation—is accelerating this complexity. Trials have evolved to include an ever-expanding array of data sources, increased data volume and precision, decentralized clinical trials (DCT), and adaptive designs.
These environmental and industry changes have led to significant data management challenges because clinical data management (CDM) technologies and processes have not progressed at the same breakneck speed. Further, technology ecosystems are often built with a mix of disparate tools that are homegrown or from different vendors, and the individual components lack interoperability. Consequently, trial data is largely managed with tools and processes that are not able to evolve and adapt at the speed required to support the realities of the ever-changing modern clinical trial.