Demonstrating Comparability of Stability Profiles Using Statistical Equivalence Testing - The authors present an approach for testing statistical equivalence of two stability profiles. - BioPharm

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Demonstrating Comparability of Stability Profiles Using Statistical Equivalence Testing
The authors present an approach for testing statistical equivalence of two stability profiles.


BioPharm International
Volume 24, Issue 3, pp. 36-42

CONCLUSION

Assessing product and process comparability culminates in the understanding of the consequence of a change as it relates to ensuring the safety and efficacy of products. The information that feeds the understanding includes historical product/process variability, the science of the molecules, and objective comparability acceptance criteria that provide the path forward in the decision making. At the end of the study, the goal is to make the desired change and state with confidence that the historical and new process/product are comparable with no adverse impact on product quality, safety, or efficacy.

The most appropriate methodology when assessing comparability is the use of an equivalence test. The steps for conducting an equivalence test are the same when comparing means or stability slopes. Specifically, one defines the EAC using scientific knowledge and historical process variability, determines an appropriate experimental design to minimize type 1 and type 2 errors, collects the data, and interprets the results. If the EACs are appropriately established, passing an equivalence test provides the strongest statistical evidence of comparability.

Leslie Sidor* is director of quality engineering and Rick Burdick is principal quality engineer, both at Amgen Global Quality Engineering; Darrin Cowley is director of product quality and Brent Kendrick is scientific director, both at Amgen Analytical Sciences,
.

REFERENCES

1. ICH, Q5E Comparability of Biotechnological/Biological Products Subject to Change in Their Manufacturing Process (Geneva, June 2005).

2. D. Chambers et al., Pharm. Technol. 29 (9), 64–80 (2005).

3. C. Chen et al., BioPharm Int. 23 (2), 40–45 (2010).

4. M.J. Chatfield and P.J. Borman, Anal. Chem. 81 (24), 9841–9848 (2009).

5. S. Welleck, Testing Statistical Hypotheses of Equivalence (Chapman and Hall/CRC, Boca Raton, FL, 2003).


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