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A Proposed Content-Uniformity Test for Large Sample Sizes
Applications of process analytical technology (PAT) for in-process and/or end-product release testing are attracting wide interest from both regulators and the pharmaceutical industry. Nondestructive measurement techniques such as near-infrared spectroscopy, together with statistical modeling of the obtained spectrum, facilitate fast and precise measures supporting the vision of improved manufacturing process understanding. Such techniques can generate a significant amount of data in real time and thereby open the possibility of improved process control and capability. In such scenarios, the added value of traditional lot-release testing based on a random sample from the batch is questioned.
One of the potential applications of PAT is real-time evaluation of tablet content uniformity. A related issue is the choice of acceptance criteria in light of the increased sample size because the International Conference on Harmonization's (ICH) uniformity of dosage units (UDU) test is based on either 10 or 30 dosage units (1). To address this issue, the Pharmaceutical Research and Manufacturers of America (PhRMA) Chemistry, Manufacturing, and Controls (CMC) Statistics Expert Team (SET) published an alternative to the ICH test in 2006 that could be used as a batch-release specification when testing a large number of dosage units (2). This proposed test was intended as an alternative, not as a replacement, to the ICH UDU test as the official regulatory method. Through interactions with European and American regulators during the second half of 2009, questions about the PhRMA approach were raised; this feedback highlighted the need to modify the test to achieve quality equivalent to or better than the ICH UDU test across the entire test range.
This paper provides a modified version of the test described in the PhRMA CMC SET paper. This modified test is proposed as an alternative test and not as a replacement; it is intended perform similar to or better than the ICH test with the increased sample size. In both the original and modified tests, the proportion of dosage units within 85–115% of label claim (LC) (the "coverage of 85–115% LC") is proposed as the measure of the uniformity of the batch. The acceptance criteria for these tests are based on counting the number of dosage units in the sample outside 85–115% LC and rejecting the batch if that count is too high. The acceptance criteria for these tests are meant to support effective regulatory application of PAT to processing. The tests are nonparametric; simple to implement, use, and regulate; and are applicable to large sample sizes. The modified version of the PhRMA CMC SET alternate test provides the same or better assurance as the harmonized UDU test with respect to the batch's uniformity.
An alternative uniformity of dosage units test
The European Pharmacopoeia, Japanese Pharmacopoeia, and United States Pharmacopeia (USP) contributed to the ICH-harmonized pharmacopeial specification (e.g., USP <905> and Ph. Eur. 2.9.40) for the content UDU, which is based on either 10 or 30 dosage units. The PhRMA CMC SET proposed an alternative to the ICH test to address the issue of developing acceptance criteria for increased sample size due to PAT. The tablet-sampling procedure (e.g., one tablet every three minutes) is established before batch manufacture. The resulting sample size is determined by the sampling procedure, and is larger than 30 dosage units, more likely 100 to 500 units. The PhRMA CMC SET test, called the "Large-N" test in this paper, is a one-tiered counting test for uniformity of dosage units. The nonparametric test is based on counting the number of dosage units outside the 85–115% range of label claim and rejects the batch if that count is outside the set limit.
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:
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.
Discussion of results outside 75–125%
The acceptance criteria for the Large-N and modified Large-N tests do not include a requirement for zero tolerance of tablets outside 75–125% LC, which is a requirement of the 30-sample ICH UDU test. Passing a batch using the Large-N or modified Large-N test with a zero-tolerance criterion depends on the sample size and the true proportion of tablets falling outside 75–125% LC. If the content-uniformity results follow a normal distribution, the following provides justification against a zero-tolerance rule because there is inherent control of the number of tablets outside 75–125% LC through counting the number of tablets outside 85–115%. Adding a zero-tolerance rule would act as a disincentive to collecting the larger sample size, which could result in a deterrent to process understanding.
The modified Large-N counting test controls the percent of tablets outside 85–115% LC to no more than 3%. As the sample size increases (e.g., from 100 to 500 units), the OC curve becomes steeper, the test's discriminating ability increases, and the level of quality assurance is raised.
The modified test maintains the beneficial properties of the original test. This test has the advantage of being mathematically simple and simple to implement, requiring only a look-up table or a simple mathematical calculation. There is a priori flexibility in selecting the sample size. Similar to the original Large-N test, this test is nonparametric, having the benefit that the test behaves well when the underlying distribution is not normal and testing for normality is not required.
Because this proposed test inherently controls the number of tablets outside 75–125% LC and zero tolerance on this population of tablets could create a disincentive to process understanding and future technology development, the authors recommend careful thought about additional test requirements.
The authors wish to thank Fasheng Li, associate director of statistics–Groton at Pfizer (New York) for creating the plots used in the paper. Thank you to Tom Garcia, a research fellow for global regulatory CMC–Groton at Pfizer and Ambarish Singh, associate director of global regulatory sciences–CMC at Bristol-Myers Squibb (New York) for reviewing the paper.
James Bergum* is an associate director of nonclinical biostatistics at Bristol-Myers Squibb, 1 Squibb Drive, New Brunswick, NJ 08903,
tel. 732.227.5981, fax 732.227.3005, firstname.lastname@example.org
*To whom all correspondence should be addressed.
Submitted: Mar. 15, 2010. Accepted: Apr. 12, 2010.
1. USP 33–NF 28 Reissue, General Chapter <905>, "Uniformity of Dosage Units," (US Pharmacopeial Convention, Rockville, MD, Oct. 2010, pp. R–86).
2. D. Sandell, et al., Drug Info. J., 40, 337–344 (2006).