Uniformity of Dosage Units Using Large Sample Sizes - Pharmaceutical Technology

Latest Issue
PharmTech

Latest Issue
PharmTech Europe

Uniformity of Dosage Units Using Large Sample Sizes
New European Pharmacopoeia chapter aims to resolve problems with applying the harmonized UDU test to large sample sizes.


Pharmaceutical Technology
Volume 36, Issue 10, pp. 118-122


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.
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.
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.
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.

. 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).

3. See Ph.Eur. Dosage Form Monographs (e.g., <Tablets>).

4. J. Limberg and M. Savsek, Pharmeuropa Scientific Notes 2, 45–48 (2006).

5. D. Sandell et al., Drug Information Jrnl. 40 337–344 (2006).

6. M. Diener et al., Drug Information Jrnl. 43 287–298 (2009).

7. L. Foust et al., Pharm. Technol. 31 (9) 108–115 (2007).

8. J.R. Murphy and K.L. Griffiths,Pharm. Technol. 30 (1) 52–60 92006).

9. J. Bergum and K.E. Vukovinsky, Pharm. Technol. 34 (11) 72–79 (2010).

10. . Holte and M. Horvat, Pharmeuropa 23.2, 286–293 (2011).


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.
26%
Oversee medical treatment of patients in the US.
13%
Provide treatment for patients globally.
11%
All of the above.
39%
No government involvement in patient treatment or drug development.
11%
Jim Miller Outsourcing Outlook Jim MillerCMO Industry Thins Out
Cynthia Challener, PhD Ingredients Insider Cynthia ChallenerFluorination Remains Key Challenge in API Synthesis
Marilyn E. Morris Guest EditorialMarilyn E. MorrisBolstering Graduate Education and Research Programs
Jill Wechsler Regulatory Watch Jill Wechsler Biopharma Manufacturers Respond to Ebola Crisis
Sean Milmo European Regulatory WatchSean MilmoHarmonizing Marketing Approval of Generic Drugs in Europe
FDA Reorganization to Promote Drug Quality
FDA Readies Quality Metrics Measures
New FDA Team to Spur Modern Drug Manufacturing
From Generics to Supergenerics
CMOs and the Track-and-Trace Race: Are You Engaged Yet?
Source: Pharmaceutical Technology,
Click here