Uniformity of Dosage Units Using Large Sample Sizes - Pharmaceutical Technology

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Uniformity of Dosage Units Using Large Sample Sizes
New European Pharmacopoeia chapter aims to resolve problems with applying the harmonized UDU test to large sample sizes.


Pharmaceutical Technology
Volume 36, Issue 10, pp. 118-122

In practice, current technology typically returns sample sizes of a few hundred, so that if the first largely deviating unit is allowed at n = 500, it was argued by several stakeholders that such acceptance criteria would not fully resolve the main concern—the 2.9.40 zero-tolerance criteria for a largely deviating unit.


Table II: Adopted test (Ph.Eur. supplement 7.7): Number of largely deviating units allowed for a selection of sample sizes.
On the other hand, a batch that complies with the adopted acceptance criteria for LDU when evaluated on a large sample would have a 75% probability to pass the zero-tolerance criterion for LDU when evaluated on a small sample n = 30 (9). An extract of the revised acceptance criteria that are now integrated in the adopted chapter 2.9.47 is presented in Table II :

"Editorial issues." In the adopted Ph. Eur. text, the introduction to the general chapter has been rewritten to further clarify the relationship between the two alternative tests of 2.9.47 and the existing 2.9.40 (as discussed above). The tables of acceptance criteria (k, c1, c2 versus sample size n) have been expanded, and there has been no rounding of the sample sizes performed where a certain set of acceptance criteria apply.

The criteria for a "medium-sized" batch sizes (30 < n < 100) have been removed, as these were found to be less relevant for the problem statement (demonstration of UDU using large sample sizes).

Demonstration of the performance of the adopted 2.9.47 test. In the following, a series of operations characteristic (OC) curves are presented to demonstrate the performance of the new test, compared with the performance of the harmonised UDU test (Note: in the figures, Alternative 1 and 2 are denoted as "Option 1 and 2"; reference is also made to Figure 2 ).


Figure 3: OC curves for normal distributed batches with an off-target mean.
Figure 3 represents the same situation as shown in Figure 2, except that the simulated batches has an off-target mean at 96 %. The batches are normal distributed around the off-target mean.


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