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European Biopharmaceutical Review

Why is Data Integrity Important?




Data integrity encompasses the completeness, consistency, and accuracy of data. There are various ways in which integrity could be compromised, through deliberate destruction of records or falsification of data, but more commonly, through inadequate training, or improper systems and recording.

It is important to be able to demonstrate that data are compliant on these aspects. If regulators have any doubts about data compliance, it is very likely to have a detrimental impact on the results of any related submission. During the last 10 years, the number of warning letters sent out by the FDA citing data integrity issues has increased significantly (1).

Inability to demonstrate data integrity upon submission for market approval could ultimately result in a failed submission. Nearly 10% of all unsuccessful new drug submissions to the FDA fail due to data deficiency issues (2). Here, we discuss the important role that data integrity and compliance play in the reliable and robust evaluation of clinical trials, how to assess and maintain data integrity, and what can be done when data deficiencies are identified.

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Laura Grey is a Principal Statistician at Quanticate, with an MSc in Medical Statistics and a PhD in Actuarial Mathematics and Statistics. She provides statistical expertise to clients in all aspects of clinical trials. Prior to joining Quanticate, Laura worked in research for 10 years investigating occupational and environmental health.

Santosh Tymms provides high-quality statistical support to clients, contributes to process improvement and knowledge sharing within the department, and researches data quality oversight. Santosh has worked in medical statistics for four years following a Master of Science with Distinction from Lancaster University, UK.
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Laura Grey
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Santosh Tymms
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