Retest periods

The purpose of stability testing is to assess the effects of temperature, humidity, light, and other environmental factors on the quality of a drug substance or product. The data produced are used to establish storage conditions, retest periods, shelf loss, and to justify overages included in products for stability reasons. The most useful equation relating temperature and reaction rate is the Arrhenius equation. This equation (27) may be integrated and rewritten as Eqs. (31) and (32). 

Standard. The degree of variability of individual batches affects the confidence that a future production batch will remain within the acceptance criteria throughout its retest period or shelf life. 

Long-term testing Stability studies under the recommended storage condition for the retest period or shelf life proposed (or approved) are performed with several drug substance batches in the stipulate packaging. In the general case, the storage condition is at a temperature of 25°C and 60% relative humidity. 

A storage statement for the finished API should be prepared in compliance with the national and regional requirements. The established retest period, which is supported by the stability data, should be displayed on the certificate of analysis (COA) and as appropriate on the container label also. 

In a scenario where significant change occurs at the intermediate condition, the retest period or shelf life shorter than the period covered by long-term data is appropriate but should not exceed the period covered by long-term data. 

Long-Term and Accelerated Stability Data Show Little Change over Time and/or Variability Under this scenario, the proposed retest period or shelf life can be up to one and a half times as long as but not more than six months beyond the period covered by long-term data without the support of statistical analysis. 

In this scenario, the retest period or shelf life should be based on long-term data. 

Q1E Evaluation of Stability Data Explains possible situations where extrapolation of retest periods/shelf lives beyond real-time data may be appropriate provides examples of statistical approaches to stability data analysis... 

If significant change occurs between 3 and 6 months testing at the accelerated storage condition, the proposed retest period should be based on the real-time data available at the long-term storage condition (Table 2.2). If... 

Drug substances intended for storage below -20°C should be treated on a case-by-case basis. When available longterm stability data on primary batches do not cover the proposed retest period granted at the time of approval, a commitment should be made to continue the stability studies postapproval to firmly establish the retest period. 

Where the submission includes long-term stability data on three production batches covering the proposed retest period, a postapproval commitment is considered unnecessary. Otherwise, one of the following commitments should be made ... 

If the submission includes data from stability studies on at least three production batches, a commitment should be made to continue these studies through the proposed retest period. 

An approach for analyzing the data on a quantitative attribute that is expected to change with time is to determine the time at which the 95%, one-sided confidence limit for the mean curve intersects the acceptance criterion. If analysis shows that the batch-to-batch variability is small, it is advantageous to combine the data into one overall estimate. This can be done by first applying appropriate statistical tests (e.g., P >. 25 for level of significance of rejection) to the slopes of the regression lines and the zero-time intercepts for the individual batches. If it is inappropriate to combine data from several batches, the overall retest period should be based on the minimum time a batch can be expected to remain within acceptance criteria. 

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