The 2017 eClinical Landscape Study from Tufts Center for the Study of Drug Development found that companies take an average 68 days to build and release a clinical study database, a timeline that has a correlation to the downstream process.
“The standard timeline to get a study operational is 60 days, but the industry on average is not hitting that milestone, and this is causing further delays in data entry and database lock,” Richard Young, VP of Veeva Vault EDC told Outsourcing-Pharma.com.
“The biggest surprise is that timelines for data management activities take just as long today as they did when I started in data management almost 25 years ago,” added Young.
According to the report, delays in releasing the study database are associated with an increase of nearly a month downstream for other data management processes.
Several reasons were cited as the causes for clinical database build delays, with protocol changes cited most by 45% of respondents.
Additionally, more than three-quarters (77%) of the survey respondents said they have issues loading data into their electronic data capture (EDC) application and 66% said EDC system or integration issues are the primary reasons they are unable to load study data.
“Clinical trials are growing in complexity, and data management processes will only get more complicated as CROs and sponsors manage an increasing variety of clinical trial data,” said Young. “Data is highly fragmented and managed in siloes as a result of technology limitations. As study designs become even more complex, data management will play a critical role in trial success.”
The study also found that sponsors take approximately 40% longer than contract research organizations (CROs) to build the database (73 vs. 53 days) and to get to database lock (39 vs. 28 days).
“Reducing the time it takes to build and release the clinical database can have a positive impact on subsequent trial timelines and, ultimately, lead to developing treatments more quickly, effectively, and safely,” added Young. “It is clear that a modern approach is needed in clinical data management.”