Guest blog by Justin O. Neway, PhD., Vice President & Chief Science Officer, Aegis Analytical, firstname.lastname@example.org
More than a year has passed since the FDA issued its guidance, “Process Validation: General Principles and Practices,” which describes process validation in three stages – Process Design, Process Qualification and Continued Process Verification. Companies are making progress with how to incorporate these guidelines cost effectively for science-based decision making that improves quality–the consequences of poor quality are too costly.
The guideline for Stage 3 – Continued Process Verification – states, “An ongoing program to collect and analyze product and process data that relate to product quality must be established (§ 211.180(e))…The data should be statistically trended and reviewed by trained personnel. The information collected should verify that the quality attributes are being appropriately controlled throughout the process.”
In reality, manufacturers have to balance available resources (i.e., “trained personnel”) with tasks such as accessing and aggregating data from multiple sources, including paper records. This can be especially challenging without proper IT systems in place to effectively manage process validation data throughout the tech transfer and manufacturing process. When evaluating technology options, manufacturing teams should look for tools that can help them more easily monitor product and process data as outlined by the FDA.
Companies that adopt QbD and implement best practices for data analysis to achieve a culture of process understanding will reap greater rewards, including:
- Improved batch yields
- Lower final product testing and release costs and reduced operating costs from fewer deviations and investigations
- Reduced raw material and finished product inventory costs
- Faster tech transfer and regulatory approval of new products and process changes
- Fewer and shorter regulatory inspections of manufacturing sites.