PQRI Case Study (6): Packaging Line GMP Optimization - Pharmaceutical Technology

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PQRI Case Study (6): Packaging Line GMP Optimization
The sixth in a series of eight case studies from the Product Quality Research Institute focuses on packaging line GMP optimization.


Pharmaceutical Technology
pp. 46-48

The risk analysis


Table I: Sample severity categories.
The assessment effort required that potential product defects from any given packaging operation be defined and graded for severity, frequency, and on the ability of the operation and/or an operator to detect the defect. Tables I and II summarize the definitions and categories applied for severity and frequency. Defect detection was categorized and graded on a 0-to-4 scale to reflect a detection capability of "none" (unable to detect) to "always" detect.

A team of packaging subject-matter experts, and local site packaging engineers familiar with the subject packaging lines under assessment, worked to collect relevant data about the packaging line. All operations involved with the line function (e.g., equipment, procedures) were listed and all corresponding potential failures were then listed. For each potential failure, the team worked to understand its potential impact on packaging operations and then worked to assign a severity category. Following severity classification, the team reviewed the dominant causes relevant to the defined potential failure and assigned each a frequency category.


Table II: Sample frequency categories.
For each potential failure, all safeguards (e.g., detection capabilities) were reviewed and a detection capability was assigned. For determinations of severity, frequency, and detection, all relevant data was taken into consideration, to include maintenance and operation logs, batch records, deviation investigations, customer complaint records, and so forth.

In the FFEA model, the calculated frequency (F) is combined with the ability to detect (D) and then plotted against severity (S) as follows:





Table III: Resulting work product (sample).
The resulting work output from this assessment was recorded in tabular form. Table III shows an excerpt of the resulting work product.


Figure 1: Risk matrix.
Using the collected tabular information, a risk matrix was assembled (see Figure 1). In Figure 1, items A through D from Table III are noted to reflect their calculated frequency. The risk matrix helps to visually prioritize the results from the risk analysis. In this case study, item "A" would get immediate action to eliminate or reduce the risk. Items "B" and "D" would be evaluated and actions would be taken if practical and appropriate to reduce or eliminate risk. No actions would be required for item "C".


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