Determination of Shelf-Life from Stability Data: From Replicates or from Averages?

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Stability data of samples of pharmaceuticals are often generated as replicate test results, typically as duplicates. A statistical analysis for determination of an expiration date can then be applied on either the replicates or their corresponding averages in line with the methodology suggested in International Council for Harmonisation (ICH) Q1A(R2) and Q1E guides. This paper aims at clarifying when a shelf-life derived from all replicates or averages is justified and correct. When replicate stability data represent preparations of the same sample, this is a case of pseudoreplication, and, therefore, the statistically derived shelf-life should be based on the averages of the replicates. However, when these replicate data represent independently and randomly selected and tested samples at each time point, a statistically derived shelf-life based on all replicate data is justifiable.

ICH Q1A (R2) and Q1E are often followed in the pharma industry for the evaluation of stability data of drug substances and products and for a statistical extrapolation of a shelf-life of a drug product or a retest period for a drug substance. The length of derived shelf-life or retest period is based heavily on whether data exhibit a change-over-time and/or variability. The outcome of the statistical evaluation depends on the number of the stability data points analyzed. Usually, a new product submission file is expected to include stability data collected during at least the first year (0, 3, 6, 9, and 12-month time intervals) along with a projected shelf-life (or retest period) statistically derived from these five time points. This shelf-life is subsequently updated as more data are generated. Stability samples are usually each tested in several replicates (duplicates or triplicates) while an average result is recorded as a representative test result. For instance, in the case of a solid dosage form such as tablets, not fewer than 20 tablets are randomly selected from the original stability sampling units (e.g., bottle), weighed to determine a tablet average weight, and ground to make a uniform composite from which several portions (typically two) are tested to yield assay results of the mean content of the active ingredient in an average tablet. Thus, the final test results to be subsequently employed for a statistical analysis consist of either these individual replicates or of a single average result of these replicates.

Often, the drug characteristic that is being tested changes linearly over time, and, therefore, a simple linear regression analysis is first performed on the stability data. The shelf-life/retest period is then determined as the time at which the 95% one-sided confidence limit for the mean curve intersects either the lower (e.g., assay of the pharmaceutical active ingredient) or the upper (e.g., impurity content) specification. While the suitability of the linear model is also expected to be evaluated and justified, this paper concentrates solely on how the stability data are used to derive a shelf-life/retest period from a fitted linear model. Should the shelf-life be derived from a linear model fitted to either all individual replicates (duplicates or triplicates) results or to their arithmetic average results?

Peer-reviewed research

Submitted: Jan. 1, 2024
Accepted: Feb. 20, 2024

About the author

Raphael Bar, PhD, rbar@netvision.net.il, is a pharmaceutical consultant at BR Consulting.

Article details

Pharmaceutical Technology®
Vol. 48, No. 6
June 2024
Pages: 24–29

Citation

When referring to this article, please cite it has Bar, R. Determination of Shelf-Life from Stability Data: From Replicates or from Averages? Pharmaceutical Technology 2024, 48 (6) 24–29.