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perspective.  I think, from development to validation runs, you bring variability as an additional measure of your process capability.  It sort of opens that door for that analysis, and if you really look at it, as you go through the validation runs, when you start determining whether your samples collected are normally distributed or not, that I think tremendously helps to make sure the samples we collect later on during validation are more representative and actually could be focused on where the high risk might be.  And you can take this back and connect it to, for example, the PQRI blend uniformity proposal that went for stratified sampling. So I think that's the part I wanted to make sure we understand.

DR. KIBBE:  This individual test has to then have additional requirements on when the samples are collected during the run and what happens if there are blanks.

DR. HUSSAIN:  That's the point I want to emphasize, is process validation is planned to address that.  I think we have not discussed that or presented that part of the work to this committee.  It was simply focused on the statistical criteria, but there are layers

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