Columns | Column: Focus on Quality

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United States Pharmacopoeia (USP) general chapter <1058> on Analytical Instrument Qualification (AIQ) now has a new title from a draft update for public comment: Analytical Instrument and System Qualification (AISQ). A new three-phase integrated lifecycle phase approach to qualification and validation is described. But will laboratories and suppliers implement it?

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Data process mapping is an effective way to identify data integrity vulnerabilities and remediate them. A modified example published by the Active Pharmaceutical Ingredients Committee (APIC) is reviewed critically. Can it be simplified?

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The United States Food and Drug Administration (FDA) is using Remote Interactive Evaluations (RIE) to assess regulatory compliance, review submission material, or determine the timing of future inspections. Here, we look at some of the impacts of RIE on GxP laboratories. Although RIE is voluntary, is this an offer that you cannot refuse?

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The publication of a new FDA compliance policy for pre-approval inspections (PAIs) introduces a new objective to inspect research and development in pharmaceutical development. We explore how this could influence the PAI process now.

Two recent warning letters show that the US FDA is substantially increasing the amount of remediation work it requires for companies to correct data integrity noncompliance. That work can be very expensive—far exceeding the cost of ensuring compliance in the first place.

Regulatory definitions can be confusing at all levels. In this article clear definitions of raw data are clarified and compared. A discussion of static and dynamic data is given along with a detailed summary of the impact of these terms on raw data.

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The password paradox states that simple passwords are simple to remember but easy to break, but complex passwords that are difficult to hack are also difficult to remember. Is there a better way?

Does a one size fits all data life cycle meet laboratory requirements for data integrity? No! The reason is that there are many different types of analytical procedures and this requires a flexible analytical data life cycle.

Data governance requires a multi-layered approach that runs throughout a regulated organization from top to bottom.  Although data governance features in the majority of GxP data integrity guidance documents, the approach to the topic should be business-driven rather than regulatory-driven.