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 hundred ninety 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.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8104918 | PMC |
| http://dx.doi.org/10.1007/s43441-021-00301-z | DOI Listing |
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