Why is IT system validation so important?

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As data integrity evolves, regulators are taking a close look at software systems. In particular, auditors look for cases where the configuration and use of the software can create data integrity issues. Confirming that a lab’s software configurations do not create data integrity risks is an essential part of IT system validation.

What is the impact of this new direction on your laboratory?

Previous audits may have looked for evidence of data integrity violations. The current trend is for auditors to look at the “opportunity component” of Cressey’s fraud triangle – specifically, does the setup prevent breaches? If your lab receives a warning letter from the FDA citing one of your computer systems, the remediation requirements will likely be extended to include all of your systems.

For these reasons, computer systems must be validated for their intended use, that is, how the software is configured to meet regulatory requirements. This way, all faults and risks will be documented (and corrected) and your laboratory can avoid the costs associated with regulatory action.

Software validation requirements are based on two main approaches:

  • GAMP 5 — the risk-based approach and the associated V-model
  • Electronic Records and Electronic Signatures (ERES) —21 CFR Part 11 for the United States and equivalent requirements for other regulatory bodies (such as Annex 11 in Europe)

What about computer system validation (CSV)?

Computer System Validation (CSV) ensures that intended workflows, including software usage, are rigorously tested to identify and correct any issues. Although required for the pharmaceutical and other regulated industries, it is often seen as a cost that can delay the implementation of new essential software.

By partnering with Agilent and applying the Agilent CSV Starter Kits, which are based on the GAMP 5 model, your lab can save time and money. In fact, an Agilent CSV Starter Kit can cut setup time by 50% or more, leaving you more time for scientific analysis.

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Gordon K. Morehouse