Characterizing Pain Points in Clinical Data Management and Assessing the Impact of Mid-Study Updates

Harper, Beth; Smith, Zachary; Snowdon, Jane; DiCicco, Robert; Hekmat, Rezzan; Van Willis; Weeraratne, Dilhan; Getz, Ken

BACKGROUND: The causes, degree and disruptive nature of mid-study database updates and other pain points were evaluated to understand if and how the clinical data management function is managing rapid growth in data volume and diversity. METHODS: Tufts Center for the Study of Drug Development (Tufts CSDD)—in collaboration with IBM Watson Health—conducted an online global survey between September and October 2020. RESULTS: One ninty four verified responses were analyzed. Planned and unplanned mid-study updates were the top challenges mentioned and their management was time intensive. Respondents reported an average of 4.1 planned and 3.7 unplanned mid-study updates per clinical trial. CONCLUSION: Mid-study database updates are disruptive and present a major opportunity to accelerate cycle times and improve efficiency, particularly as protocol designs become more flexible and the diversity of data, most notably unstructured data, increases.