Acceptance Limits for the New ICH USP 29 Content-Uniformity Test - Pharmaceutical Technology

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Acceptance Limits for the New ICH USP 29 Content-Uniformity Test
Revisions to the United States Pharmacopeia's (USP) uniformity test require manufacturers to establish new acceptance limits. The authors present their method for calculating acceptance limits consistent with USP's revised content-uniformity test requirements.

Pharmaceutical Technology

n = number of observations at each location

Then the upper confidence limit for the sum of the between-location and within-location variance components (i.e., σ) is:

Given the sample within-location standard deviation (SE) and the sample between-location standard deviation (SM), one computes a confidence interval for σ using the Graybill–Wang method. Since the sample mean and mean squares for the between-location and within-location standard deviations are independent, the overall confidence level (1– α) is the product of the two individual confidence levels for μ and σ. Each individual confidence level is the square root of the overall confidence level (μ is two-sided and σ is upper one-sided). One can generate an acceptance limit table by finding the largest combinations of within- and between-location standard deviations for a fixed sample mean, such that the resulting confidence region remains below the prespecified LBOUND.

Sample content uniformity acceptance limit tables

Tables assume that the target (i.e., the average of potency specification) is 100% and that the sampling plan is to test one dosage unit from each of n separate locations throughout the batch. Passing the tabled limit ensures, with the chosen level of confidence, that there is at least a 95% chance of passing the USP uniformity of dosage units test ‹905› for samples taken from that batch.

Click here to view sample tables

James S. Bergum, PhD,* is an associate director in the nonclinical biostatistics department of Bristol-Myers Squibb, One Squibb Dr., New Brunswick, NJ 08903, tel. 732.227.5981,
Hua Li, PhD, is a vice-president of management science at Merrill Lynch & Co.

*To whom all correspondence should be addressed.

Submitted: Feb. 16, 2007. Accepted: Aug. 20, 2007.


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