Modified LargeN test
This paper proposes a modification to the LargeN 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 LargeN 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 contentuniformity 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 LargeN 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 LargeN and Modified LargeN 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 LargeN and modified LargeN test is provided in Table
II.
Figure 3: LargeN and modified LargeN 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 LargeN and modified LargeN tests. Sample sizes of 100 and 500 units were chosen because they cover the current
typical range of sample sizes.
Figure 4: LargeN and modified LargeN 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 LargeN test is about 54%, and the probability of passing the modified LargeN test is about
30%. For the same set of curves at a standard deviation of about 4.0% LC, the probability of passing either LargeN 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 offtarget, 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 LargeN test is similar to or more stringent than the ICH UDU test.
