FDA Process Validation Guide Places New Emphasis on Understanding and Controlling Variation

Jul 15, 2011

george-rodriguesThe US FDA has issued revised recommendation for process validation which includes better means for understanding and controlling sources of variation. While this document refers to control of manufacturing processes, the same principles apply to measurement processes in the laboratory. In fact, it is impossible to demonstrate that a manufacturing process is in control unless the associated measurement methods used to monitor that process are also adequately precise and reproducible.

The updated FDA guide “Process Validation: General Principles and Practices” (January 2011) advises pharmaceutical manufacturers to do the following:

• Understand the sources of variation
• Detect the presence and degree of variation
• Understand the impact of variation on the process and ultimately on product attributes
• Control the variation in a manner commensurate with the risk it represents to the process and product

With this language, the FDA is asking manufacturers to establish and defend their decisions regarding control of variation, and to do so within a risk analysis framework.

In my opinion, this approach has great practical utility for laboratories.  We can think of the analytical work flow in process terms and consider the entire sequence of analytical operationsfrom sample collection through sample preparation and instrumental analysissince each phase can contribute to variation. It is also helpful to consider the various sources as arising from category types, such as equipment, personnel, environment, methods, and reference standards.

Within analytical laboratories, liquid handling can be a source of significant variation, and application of these principles will reduce variation and associated risk. For example, handheld pipettes, equipment choice, personnel skill, and environmental conditions are particularly important sources of variation that can be controlled by implementing best practices. With automated liquid handling equipment, the operator impact is lessened, but the particular method programmed into the device becomes more important and should be properly optimized and controlled.

For more information

Minimizing Liquid Delivery Risk: Laboratory Environmental Conditions as Sources of Error  Read article 

Optimizing Automated Liquid Handlers Using Longitudinal Data to Understand Performance  Read article 

About the Author

George Rodrigues, Ph.D.

George Rodrigues, PhD, is Senior Scientific Manager at Artel, the global leader in liquid delivery quality assurance. Rodrigues is responsible for developing and delivering communications and consulting programs designed to maximize laboratory quality and productivity through science-based management of liquid delivery.  Rodrigues is Artel’s chief representative to key commercial clients, government regulatory bodies and industry organizations.  His speaking and teaching engagements, along with his publications, build awareness of the challenges and solutions for laboratories in maintaining data integrity and confidence in their testing protocols.  He plays a key role in developing the manufacturing and quality assurance processes for Artel products and organizes programs to assist pharmaceutical, biotechnology and clinical laboratories in improving their liquid delivery quality assurance and analytical process control. Rodrigues earned his BS in Chemical Engineering at the U.C. Berkeley, and a PhD in Chemical Engineering at the University of Wisconsin. Dr. Rodrigues can be contacted at (207) 854-0860.