Myths and Misconceptions about Data Integrity

Interview with Bob McDowall

Have you taken time to read the regulations and guidance documents about data integrity, or do you believe the myths, rumors, or third-party opinions?

You may use your company’s QA to interpret the rules for you, but they too can be wrong. However, there is no excuse for incompliance. In Q18 of the FDA Guidance, it says that everyone at every management level involved in any incompliance that is discovered should be subject to personal consequences (i.e. “removed from cGMP positions”).

The unfortunate fact is that lot of organizations are stuck with outdated procedures because they believe well-worn data integrity myths. These myths harden into misconceptions that can lead to incompliant record quality and painful and expensive difficulties with regulators.

The Truth about Data Integrity

In a no-nonsense interview with data integrity expert Bob McDowall, we will work to uncover the truth about data integrity and what instrumentation and software can help you achieve it. Statements heard around the industry that will be addressed include:

  • “Paper is easier and cheaper to handle than electronic records.”
  • “I can avoid maintaining computers in the lab easily by connecting my instruments directly.”
  • “If I adopt electronic instruments, I must revalidate my methods.”
  • “I should connect all instruments and brands to the same system to reduce the effort of validation.”
  • “Systems should not be updated too often, as they must be revalidated each time.”
  • “Without regulatory pressure, I will never get the resources I need to go electronic.”
  • “An auditor or inspector is always right, and their instructions must be followed.”
  • “I prefer to buy a system and software that is fully compliant and validated.”


In his own colorful style, McDowall will review each statement in turn and classify whether it is a misconception, myth, or maybe even the truth! Afterwards, you should be better able to review your current setup and decide what actions to pursue to ensure all-important data integrity in the workflows you run daily in your lab.