Continued process verification: Difference between revisions

Revision as of 13:08, 3 November 2014

Revision as of 13:09, 3 November 2014

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==Data Collection and Analysis==

Crucial in effective CPV implementation is an appropriate data collection procedure. Data must allow for statistical analytics and trend analysis of process consistency and capability.<ref>{{cite web|title=Continued Process Verification (CPV)|url=http://www.atris-systems.com/216.0.html|publisher=Atris Information Systems|accessdate=3 November 2014}}</ref> A correctly implemented procedure will minimize overreactions to individual production outlier events and guarantee genuine process inconsistency are detected. While production variability can sometimes be obvious and even casually identified the FDA recommends using statistical tools to quantitatively detect problems and identify root causes. Initially, continued process verification should be based on quality standards established in the design phase. After a period of time variations can be detected by identifying deviation from historical data using statistical tools. Furthermore these same tools can also be used to identify opportunities to optimize processes that may pre-emptively increase quality reliability.<ref>{{cite web|title=A Case for Stage 3 Continued Process Verification|url=http://www.pharmamanufacturing.com/articles/2014/stage3-continued-process-verification|publisher=PharmaPharmaceutical Manufacturing|accessdate=3 November 2014}}</ref>

==References==