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

Latest Issue
PharmTech

Latest Issue
PharmTech Europe

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

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.


Table I: Large-N test acceptance limit for various n.
The number of units (Y) outside the target interval (85–115% LC) is binomially distributed with parameters n (sample size) and p (true proportion outside). When p = 0.048, the quality level (QL) calculated corresponds to 95.2% coverage, associated with a 50% probability of complying with the ICH UDU test. The test translates to finding the largest integer t, called c, such that: c = max{t ; Prob(Yt || p = 0.048) ≤ 0.5}. Table I provides c for various sample sizes. For example, if 500 units are tested and 23 or fewer results are outside 85–115% LC, the batch passes the test.


Figure 1: Large-N (various percent label claim [LC]) operating characteristic curves for n = 100 with International Conference on Harmonizations (ICH) uniformity of dosage units (UDU) test (100% LC). StDev is standard deviation. (ALL FIGURES ARE COURTESY OF THE AUTHORS)
The test is designed to be more conservative than the ICH UDU test for all levels of batch quality where the probability of accepting a batch is less than 0.5. The acceptance limit, c, depends on the sample size, n.


Figure 2: Large-N (various percent label claim [LC]) operating characteristic curves for n = 500 with International Conference on Harmonizations (ICH) uniformity of dosage units (UDU) test (100% LC). StDev is standard deviation.
Figures 1 and 2 show operating characteristic (OC) curves for the Large-N test for sample sizes of 100 and 500, respectively, compared to the OC curve for the ICH UDU test when the batch mean is 100% LC. Here, the probability to accept the batch is plotted against batch standard deviation with curves varying by batch mean. If the mean is off target, the standard deviation must decrease to maintain constant coverage; this change results in the shift to the left in the curves. Also, the test is symmetric; a mean of 98% produces the same OC curve as a mean of 102%. Note that for the sample size of 500, the probability of accepting the lot under the Large-N test is slightly higher than passing the ICH UDU test for small standard deviations; this higher probability is expected because increasing the sample size results in a more discriminating test.


ADVERTISEMENT

blog comments powered by Disqus
LCGC E-mail Newsletters

Subscribe: Click to learn more about the newsletter
| Weekly
| Monthly
|Monthly
| Weekly

Survey
What role should the US government play in the current Ebola outbreak?
Finance development of drugs to treat/prevent disease.
Oversee medical treatment of patients in the US.
Provide treatment for patients globally.
All of the above.
No government involvement in patient treatment or drug development.
Finance development of drugs to treat/prevent disease.
23%
Oversee medical treatment of patients in the US.
14%
Provide treatment for patients globally.
7%
All of the above.
47%
No government involvement in patient treatment or drug development.
9%
Jim Miller Outsourcing Outlook Jim MillerOutside Looking In
Cynthia Challener, PhD Ingredients Insider Cynthia ChallenerAdvances in Large-Scale Heterocyclic Synthesis
Jill Wechsler Regulatory Watch Jill Wechsler New Era for Generic Drugs
Sean Milmo European Regulatory WatchSean MilmoTackling Drug Shortages
New Congress to Tackle Health Reform, Biomedical Innovation, Tax Policy
Combination Products Challenge Biopharma Manufacturers
Seven Steps to Solving Tabletting and Tooling ProblemsStep 1: Clean
Legislators Urge Added Incentives for Ebola Drug Development
FDA Reorganization to Promote Drug Quality
Source: Pharmaceutical Technology,
Click here