Arm & Hammer Animal and Food Production

WEBINAR: Use data to validate and verify your food safety story.

Posted June 17, 2021 by Dr. Christine Alvarado, Technical Services Manager
Food Safety


The production of safe food is important to not only the health and safety of your customers, but the strength and sustainability of your brand. Safe food, made and delivered on a consistent basis, establishes trust and confidence in your brand, not to mention securing public health.

Customer and consumer trust in your brand is strengthened when the processes used to create safe food are validated and verified using sound science and data. The data harvested each day builds your food safety story and enables science-based decisions that elicit customer trust.

The validation of data tells us if the processes we are using are the right thing to do to accomplish our production objectives. Verification proves truth and accuracy, verifying that we are doing what we said we were going to do.

Validation covers two elements:

  • Element 1: Scientific support and design. Demonstrating that specific process control measures can adequately prevent, reduce or eliminate specific hazards.
  • Element 2: In-plant validation. This validates that you can execute the process as described to get the desired effect.

Scientific support and design.

Before you begin the process of conducting studies internally to validate food safety processes, start by gathering scientific or technical data that closely matches your actual production process. This data can validate that your processes prevent, reduce or eliminate hazards identified in HACCP analyses. The final, and often most overlooked, part of Element 1 is the identification of critical operational parameters important to making the production process successful. The scientific support should identify the following:

  • The product being studied, whether that’s chicken, beef, pork or other protein product. This includes formulation and intrinsic factors—percent fat, for example—that could impact results.
  • The potential hazard, either biological, physical or chemical
  • The expected level of hazard reduction or prevention to be achieved. Are we expecting a one-log reduction or some other measurement?
  • The process that will be implemented that will achieve the desired reduction or prevention. Is this a dip, spray, drench or other system?
  • How these processing steps will be monitored. This could include time, pH, humidity, contact time and other elements.

The required documentation to support the scientific process includes published processing guidelines or peer-reviewed scientific information, including a challenge or pack study. This could also include expert advice from processing authorities, which is also backed up by data that supports the validity of the process and expected results.

Some common errors in the scientific support category include no defined critical parameters in the scientific documentation. Another error is when the validated process is not followed as written in the original validation. An example could include not using the proper temperature as defined in the assigned protocols. One simple error could include using a “vegetable” validation for a “meat” process—while some processes are similar, they are not completely comparable. Also, the technical document should support the effectiveness of the process.

Putting supporting documentation into practice.

Element 2 of the food safety process is really the heart and soul of the program. This is where in-plant data is collected to demonstrate the effectiveness of the implementation of the critical operational parameters, and the analysis of the data to determine if the parameters are being implemented effectively.

Now that we have element 1 paperwork complete and documentation available, we can collect and analyze the data. This can be covered in three critical steps:

  • Step 1: Objective. This determines what to show in the validation. Be very specific with what you want to show and think about what success will look like at the end of the process. Know what questions you want answered and how you will validate a successful outcome. Also understand the minimum number of samples required to meet your process constraints and answer your objective question.
  • Step 2: Define success. What will you measure that will help define a successful process outcome? One important factor to consider is determining if you will measure hazard prevalence or load. Prevalence requires more samples and is associated with cross contamination, and it is also more important for FSIS regulation. Load is more easily changed with interventions and more directly associated with the efficacy of interventions. Finally, understanding your incoming prevalence or load will be important to understanding and defining success.
  • Step 3: Identify variation in the process you are going to measure. This could include shift, day or week variation or, in some instances, variation by season. It’s important to look at variation and not just average.  For example, if you are running 350 ppm of antimicrobial on average, but the variation is from 200 ppm to 600 ppm, the 200 ppm level will cause significant problems even if your average is adequate.

To fully understand what the vast amount of data collected represents, it is important to use a statistician in the process. Involve them early to avoid asking the question, after the data is collected, ‘What do I do now?’.

Validating and verifying your food safety story is integral for the confidence and trust in your products. This builds customer support and solidifies your company and product brands. Implementing the proper validation and verification procedures adds stability to your processes and helps ensure consistent product quality over time. Contact us to get started.

Get additional insights from the rest of our Combating Salmonella series:

Use quantitative data to target Salmonella control.
Prevalence vs. Enumeration: What is best for you?



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