Data Integrity In Your Contamination Control Strategy

You will hopefully not be shocked to learn that data integrity is an integral part of a properly running cleanroom. If this does come as a surprise to you, we highly recommend you read on and take notes. But for many cleanroom or particle counter professionals, the term “data integrity” has been drilled into our skulls so much we sometimes forget the true meaning of it. Moreover, we forget the role it can play in our Contamination Control Strategies (CCSs).

The recent updates to GMP Annex 1 is centered around Quality Risk Management (QRM) through a comprehensive CCS. Your CCS should be based on a risk assessment, and address the following to start:

• Complete integration through all stages of the product life cycle.
• Knowledgeable personnel who can recognize when something has put sterility at risk.
• Investigation protocols when equipment fails, including corrective and preventive action (CAPA).
• Strick risk management protocols to avoid contamination.
• Involved senior management in both monitoring and regular reviews.
• Risk-free finishing, storing, and transporting of the product.
• Contamination monitoring methods and tools.
• Points of contamination monitoring.
• Design of and materials used in the construction of the cleanroom.
• The use and management of utilities.
• Regular and in depth training for personnel, especially on gowning.

This is just a brief summary of some of the points included in the Annex 1 update, but one thing is for certain: you need a comprehensive Contamination Control Strategy that dictates your cleanroom’s design and function. This cannot be an afterthought, the cleanroom – and all that comes with it – should be designed around this strategy.

So where does data integrity come into play in this strategy? We’re so glad you asked!

What Is Data Integrity?

First things first, let’s briefly define data integrity so we are all on the same page. If someone in the US is referring to regulations around data integrity, they are probably talking about 21 CFR 11. This refers to the 11th part of the US Food and Drug Administration’s (FDA’s) Title 21 Code of Federal Regulations. The FDA defines data integrity as the “completeness, consistency, and accuracy of data. Complete, consistent, and accurate data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate (ALCOA).”

Data integrity serves a number of purposes in a cleanrom, but to the regulatory authorities, it has one main cause: to certify you are following best practices and producing safe products.

One of those best practices is following ALCOA+. This acronym stands for:

• Attributable: It must be clear who recorded the date, with a signature and date.
• Legible: The data must be clearly able to be understood without unexplained symbols.
• Contemporaneous: Data should be recorded immediately upon its generation.
• Original: The data should be the original or a certified copy.
• Accurate: Data should accurately reflect the situation or observation.

Complete: Records should leave nothing out – include testing and re-testing.

Consistent: Time stamps should come in the expected sequence. Across the board, data generation should be the same.

Enduring: Data should only be recorded using invalidated electronic systems (or, if unavailable, controlled worksheet in laboratory notebooks).

Available: For the lifetime of the record, it needs to be readily available for review and audits.

Following ALCOA+ is made simpler when you integrate complaint technology and tools to aid in this. 21 CFR 11 is specifically designed to ensure you maintain the highest level of data integrity possible while remaining agile.

Data Integrity In Your Contamination Control Strategy

Your data integrity is the lifeblood of your CCS – and your cleanroom in general. It is the information that flows through your systems, ensuring you that everything is functioning properly and there are no abnormalities. It is what keeps the room running smoothly, because it removes doubt of contamination while simultaneously serving as the foundation for audits and classification.

So look at it this way… If you were designing a car, would you get to the end stages of design and only then figure out the power source? What if one component is meant to be electric and another is meant to run on gas, while yet another needs diesel?

Building your CCS is the same: you need to consider how to maintain data integrity from the start. All data handled in your cleanroom needs to have the utmost integrity for the cleanroom to function properly, pass audits, and maintain classification. If you design your CCS without data integrity in mind, the systems will not exist to make this process seamless. You will end up with disorganized paper trails and complex audits, so you’ll have to designate man hours where they shouldn’t need to be.

If you, instead, build your CCS around data integrity, you’ll find yourself with a smooth process and simpler audits, as well as more confidence and security in your cleanroom.