Figure 4: 2.9.47 Alternative 1: OC curves (sample size n = 1,000) for long-tailed and bimodal distributions, as compared
to normal distributions with the same standard deviation. The results are compared with the UDU test (dotted curves). An illustration
of the batch distributions is presented in Figure 5 below.
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In
Figure 4
, the probability to pass the criteria of Alternative 1 for long-tailed and bimodal batches, respectively, is compared with
the OC curve for normal distributed batches (n = 1000). The long-tailed distribution could typically appear in a batch where
there is an inadequate blending process, or where demixing occurs. The bimodal distribution could typically appear where several
independent pieces of equipment are involved in a crucial stage of the process, and one of the pieces is faulty. Examples
include a rotary tablet press and single-dose preparations (e.g., powders) that are filled by several independent filling
stations. Obviously, the long-tailed and the bimodal batches always have a smaller probability to pass the test than the normal
distributed batches, provided that overall standard deviation is the same. The UDU test is also sensitive to the distribution
of the batch, but there is a wide range of standard deviations where the UDU test is indecisive or in some cases even less
discriminating for non-uniformly distributed batches. The new alternative tests are more precise as they evaluate a larger
sample.
Figure 5: OC curves (sample size n = 1,000) for long-tailed and bimodal distributions, as compared to normal distributions
with the same standard deviation. 2.9.47 Alternative 2.
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In
Figure 5
, the same simulated batches have been evaluated by the nonparametric test criteria of Alternative 2. Comparing Figures 4
and 5, it is evident that the two alternatives are very similar in their evaluation of the tested batches, in particular for
the long-tailed and the bimodal batches. When looking at
Figure 6
, it is evident that any differences in evaluation based on the general L1 criteria would be compensated for by the L2 criterion,
which is identical in the two alternatives.
Figure 6: Illustration of the relative importance of the L1 and the L2 criteria in the evaluation of acceptable dose uniformity
according to 2.9.47 (n =500). Green + red area: Probability to pass the L1 criteria. Red area: Probability that a batch that
passes the L1 criteria, fails the L2 criteria. Green area: the probability to pass the 2.9.47 test.
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Figure 6
illustrates whether the different simulated batches are rejected based on the general L1 criteria (AV/ c1), or based on the
additional L2 criteria for largely deviating units (c2). The green + red area represents the probability that the batch passes
the L1 criteria, and the red area alone represents the probability that a batch that passes the L1 criteria but fails the
L2 criteria. Consequently, the green area alone is equivalent to the area under the curve in
Figure 4
, which represents the probability to pass the 2.9.47 test. It is apparent that the L2 criterion is important to disclose
bimodal- and long-tailed distributions, as well as other deviations from normality. For the normal distributed batches, the
L2 criterion hardly contributes to the evaluation at all. However, when evaluating the dose uniformity of a batch, and in
particular by a third party, it is not practical, nor necessary to make any assumption as to the distribution of the batch
or the sample.
Conclusion
The recently adopted Ph.Eur. General Chapter 2.9.47 should resolve the problems that have been addressed regarding the applicability of the harmonized
UDU test (Chapter 2.9.40) when applied to large sample sizes. With the new test criteria, more information from the large
sample is taken into account in the evaluation of dose uniformity than is available in a subset of the sample (n = 30). Thus,
manufacturing processes where a large sample size is available are more precisely evaluated.
The new test does not represent new regulatory expectations. Chapter 2.9.40 represents the requirements for acceptable dose
uniformity, and 2.9.47 is just an alternative means to demonstrate compliance with the 2.9.40 criteria.
The proposed test criteria are at least equally stringent as the requirements of Ph.Eur. 2.9.40, and more discriminating due to the larger sample size. Although the new test originally has been motivated by PAT
applications, it is applicable also to traditional sampling and analysis.
Acknowledgments
The initial draft and adopted chapter were elaborated by the members of the Ph.Eur. PAT Working Party (Chair: Prof. G. Ragnarsson, Medical Products Agency, Sweden). We also acknowledge many helpful proposals
and comments from experts from industry, industry associations, and regulatory authorities that participated in an expert
hearing on Sept. 29, 2010, and contributed through the public comment process.
Ø. Holte is a scientific officer with the Norwegian Medicines Agency.
M. Horvat is a leading scientist with Lek Pharmaceuticals. Both authors are representing the European Pharmacopoeia (Ph.Eur.) PAT Working
Party.
References
1. Ph.Eur., General Chapter 2.9.40 Uniformity of Dosage Units (European Pharmacopeia, Council of Europe, France).
2. USP, General Chapter <905> Uniformity of Dosage Units (US Pharmacopeial Convention, Rockville, Maryland).
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4. J. Limberg and M. Savsek, Pharmeuropa Scientific Notes
2, 45–48 (2006).
5. D. Sandell et al., Drug Information Jrnl.
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