Continued process verification (CPV) is the collection and analysis of end-to-end production components and processes data to ensure product outputs are within predetermined quality limits. In 2011 the Food and Drug Administration published a report outlining best practices regarding business process validation in the pharmaceutical industry. Continued process verification is outlined in this report as the third stage in Process Validation. 
Its central purpose is to ensure that processes are in a constant state of control, thus ensuring final product quality. Central to effective CPV is a method with which to identify unwanted process inconsistencies in order to execute corrective or preventive measures. Once quality standards are set in place they must be monitored with regular frequency to confirm those parameters are being met. Continued process verification not only helps protect consumers from production faults, but business also see benefits in implementing a CPV program. Should product outputs not match target standards it can be very costly to investigate the problem source without existing CPV data.
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. 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.
References.
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