Evaluation of Validation Content Uniformity Test Results Using Lower Probability Bound Distribution Charts

By Pramote Cholayudth
 
 
One of the widely recognized references on process validation with regard to sampling and testing plans is the US Food and Drug Administration’s Draft Guidance for Industry: Powder Blends and Finished Dosage Units—Stratified In-Process Dosage Unit Sampling and Assessment (1) that is based on the Product Quality Research Institute (PQRI)’s Recommendation Report (2). However, it is a non-binding document (i.e., the industry may use any alternative approaches even after it becomes the official guidance). Another well-known relevant reference is the PDA Technical Report No. 25: Blend Uniformity Analysis: Validation and In-Process Testing (3). The sampling, testing, and corresponding acceptance criteria limits in validation study will follow these two statistics-based documents. The validation test results with respect to critical quality attributes (CQAs) require to be statistically evaluated (e.g., estimating confidence limits as appropriate, demonstrating the high probability of passing the tests, etc.).
   
According to Torbeck (4), “… If statistical procedures were given in the USP, companies would have little incentive to develop better procedures.” His comment is now reconfirmed. The industry may not have a good approach like J.S. Bergum’s method if the United States Pharmacopeia (USP) provided some kind of statistical procedures. Bergum is one of the leading professionals who suggested the use of the new statistical procedures. His methods (5, 6) introduced both how to establish the validation acceptance criteria and how to evaluate the validation test results. In protocol development, all the validation practitioners may follow some recognized documents including Bergum’s in establishing the acceptance criteria limits. However some of them may not be confident in using statistical tools for evaluation of the test results, especially for the multiple stage tests (e.g., content uniformity and dissolution).
   
To provide an alternative to such a statistical evaluation, this article introduces an approach to using lower probability bound distribution charts, constructed according to Bergum’s methods, for evaluation of content uniformity test results.

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