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Statistical Properties of Large Sample Tests for Dose Content Uniformity

  • Shen, Meiyu1
  • Tsong, Yi1
  • Dong, Xiaoyu1
  • 1 Food and Drug Administration, 10903, New Hampshire Ave, Silver Spring, MD, 20993, USA , Silver Spring (United States)
Published Article
Therapeutic Innovation & Regulatory Science
Springer International Publishing
Publication Date
Sep 01, 2014
DOI: 10.1177/2168479014524961
Springer Nature


The European Union (EU) test for uniformity of dosage units using large sample sizes was published in European Pharmacopoeia 7.7 in 2012. There are 2 alternative tests. Option 1 is a parametric two-sided tolerance interval-based method modified with an indifference zone and counting units outside of (0.75 M, 1.25 M) (here, M is defined by sample mean, X̄, as M = 98.5% if X̄ < 98.5%, M = 101.5% if X̄ > 101.5%, and M = X̄ otherwise). Option 2 is a nonparametric counting method with an additional indifference-zone concept. The authors extended the parametric two one-sided tolerance interval-based method that was proposed for dose content uniformity testing based on 30 tablets to large sample sizes with the restriction that all operating characteristic curves of the two one-sided tolerance intervals for any given sample size intersect with the operating characteristic curve of the US Pharmacopoeia harmonized method for a sample size of 30 at the acceptance probability of 90% when the individual tablets with on-target mean are assumed to be normally distributed. This paper studies the acceptance probabilities in relation to the batch mean and batch standard deviation among the 2 EU options and the authors’ proposed method. The acceptance probabilities of EU options 1 and 2 and the proposed method were compared using simulation; results revealed that both EU options 1 and 2 produce larger acceptance probabilities when the batch mean is off-target. Furthermore, for a given standard deviation, the acceptance probability of EU option 2 at a mean 102% of the label claim is larger than that at a mean of 100% of the label claim under the normality assumption.

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