A Proposed Content-Uniformity Test for Large Sample Sizes - Pharmaceutical Technology

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A Proposed Content-Uniformity Test for Large Sample Sizes
The authors describe a modified version of the Large-N test used to determine content uniformity.


Pharmaceutical Technology
pp. 72-79

Modified Large-N test

This paper proposes a modification to the Large-N test by increasing the QL from 0.048 to 0.030. This change is demonstrated by OC curves for sample sizes from n = 100 to n = 500. This modification results in a more conservative test than the Large-N test because the number of tablets allowed outside of 85–115% LC is reduced. The value of 0.030 for the QL was chosen because of its performance against the ICH UDU test's OC curve (discussed below) and because the former ICH content-uniformity test allowed 1 tablet (1/30 = 0.033) outside of the 85–115% range. Using the same QL for all sample sizes simplifies the calculation for the acceptable number of tablets.

The modified Large-N test is as follows:

  • Define the acceptance limit (c) by calculating 3.0% of n and round it down to the nearest integer. For example, for n = 250, 3.0% of the 250 tablets is 7.5, which will be rounded down to c = 7.
  • The batch complies if the number of tablets outside the range of 85.0–115.0% of LC is no more than c.


Table II: Acceptance values for the Large-N and Modified Large-N tests.
For sample sizes of 100 to 500 tablets, the proposed alternative test is similar to or more conservative than the harmonized compendia test for UDU. A comparison of the acceptance values using the Large-N and modified Large-N test is provided in Table II.


Figure 3: Large-N and modified Large-N operating characteristic curves for n = 100 with International Conference on Harmonizations (ICH) uniformity of dosage units (UDU) test (batch mean = 96% and 100% label claim [LC]). StDev is standard deviation.
Figures 3–4 show the OC curves for batch means of 96% and 100% LC and sample sizes of 100 and 500 units for the ICH UDU test, as well as the Large-N and modified Large-N tests. Sample sizes of 100 and 500 units were chosen because they cover the current typical range of sample sizes.


Figure 4: Large-N and modified Large-N operating characteristic curves for n = 500 with International Conference on Harmonizations (ICH) uniformity of dosage units (UDU) test (batch mean = 96% and 100% label claim [LC]). StDev is standard deviation.
The OC curves provide the probability of passing each test at various values of the batch standard deviation (SD). For example, if 100 tablets are tested from a batch with a batch mean of 96% LC (see Figure 3), then for an SD of about 6.4% LC, the probability of passing either the ICH UDU or Large-N test is about 54%, and the probability of passing the modified Large-N test is about 30%. For the same set of curves at a standard deviation of about 4.0% LC, the probability of passing either Large-N test or the ICH UDU test is more than 99.8%. Also, as can be seen in these figures, the test is sensitive to how far the batch mean is from its target (i.e., 100%).

Coverage, or the percentage outside 85–115% LC, is a function of the average and the standard deviation of the batch. As the batch mean moves away from target, the standard deviation required to achieve the same probability of passing the test is reduced. Therefore, if a batch is produced off-target, the standard deviation needs to decrease to attain constant coverage. The figures also show that the curves become steeper as the sample size increases; this change is expected because the test becomes more discriminating as the sample size increases. For sample sizes of 100 to 500 units, these curves show that the modified Large-N test is similar to or more stringent than the ICH UDU test.


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