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Using control charts to evaluate pharmaceutical manufacturing process variability

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Abstract

A control chart is a graphical display of a product quality characteristic that has been measured or computed periodically from a process at a defined frequency. Control charts were developed by Walter Shewhart in 1920s and are still widely used in various industries. In this paper, we discuss the use of control charts to evaluate pharmaceutical manufacturing process variability. We first discuss different types of control charts followed by some key considerations for constructing a control chart for pharmaceutical manufacturing processes. We also share several illustrative case studies where both variable (continuous numeric data) control charts and attribute (categorical data or discrete numeric data) control charts are utilized to monitor pharmaceutical manufacturing process variation. Control charts are effective tools to detect the presence of special cause variation in the manufacturing process and to ascertain if the process has reached a state of statistical control. Control charts are also useful tools to monitor the routine commercial production and to continually confirm the state of statistical control. When the control chart detects the presence of special cause variation, continual improvements can be initiated to correct and/or prevent potential failures so that the process remains in a state of statistical control and ensure the product consistently complies with the regulatory standards. In turn, this can greatly facilitate transforming the pharmaceutical manufacture from the reactive troubleshooting paradigm to a proactive failure reduction or prevention paradigm.

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