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MANUFACTURING
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Qualifi cation? We should fi rst take into consideration what types of variability exist in a process. These types of variability are:
The examination of variability within the cleaning run often reveals those parts of the equipment train or individual parts of equipment that perhaps are harder to clean or sample, thus possibly causing variable or aberrant results.
• Variability within each individual cleaning run (also called “inter-run” variability)
• Variability between the cleaning runs (also known as “intra-runs” variability)
products, information did not reveal any signifi cant diff erences, the results of the study and subsequent investigation showed that chemical interactions of ingredients in the formulation of Product A signifi cantly contributed to a longer time to remove residuals. This was important to learn because just a theoretical evaluation wouldn’t have revealed this complexity. Therefore, it is recommended to perform studies and plot data normalizing them when appropriate so that they could be presented on the same plane so that previously unknown sources of variability could be found.
Stage 2: ECP Performance Qualifi cation
The second stage of validation is called Performance Verifi cation. This stage is customarily referred to as Cleaning Validation. Usually, 3 consecutive successful runs are performed to qualify the process using a well-characterized, well-documented, and consistent cleaning procedure. During these studies, one cleans the equipment, collects appropriate samples, and evaluates the data using pre-defi ned statistical tools. We should mention here that for years, it was not habitual to use statistics to evaluate ECP, and it might be a new concept for many readers.
28 | | January/February 2015
The author of this article strongly encourages the usage of such methods as they will provide meaningful insights into sources of ECP variability. Remember that a result that you did not expect or is hard to explain still tells you something, and thus becomes part of the “story.” And we believe that each process tells a “story.” So what statistical methods should we employ during Stage 2: Process
The examination of variability within the cleaning run often reveals those parts of the equipment train or individual parts of equipment that perhaps are harder to clean or sample, thus possibly causing variable or aberrant results. However, if the cleaning process is consistent, the results of the validation studies should illustrate this consistency. The fi rst step in the review of the data would be checking their normality. Don’t be discouraged, though, if your data set is non-normal. Non-normal is a very typical outcome of a cleaning validation study since the point of ECP is to remove manufacturing and cleaning process residuals completely. Therefore, the results of many sampling and tests yield either “0” or close to “0.” Upon fi nding out how normal your data is, one should calculate confi dence intervals around sample results population data set.
Figure 3. Comparison of total organic carbon for 7 products.
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