From traditional clinical data to electronically captured patient-reported outcomes and wearables data, today’s clinical trials capture more data from more sources than ever before. This variety gives clinical trial sponsors the tools to conduct more innovative trial designs, but it also requires more data management resources.

While data managers and other individuals tackle more challenging workloads, traditional clinical data management approaches and technology have failed to keep up with the increasing, volume, variety, and velocity of clinical trial data. Systems capable of storing, recording, and managing higher quantities of data are required, as well as the capability to analyze all that data. Because currently, data management teams can only use a fraction of the data that’s stored.

A data lakehouse approach enables data management teams to not only store vast amounts of data, but more easily manage and analyze that data. By realizing the full power of that data, clinical trial sponsors can gain comprehensive and interwoven insights that lead to more efficient clinical trials, as well as more effective programs, trial designs, and products.