Methods for Identifying Out-of-Trend Results in Ongoing Stability Data - Pharmaceutical Technology

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Methods for Identifying Out-of-Trend Results in Ongoing Stability Data
The authors discuss three methods for identification of out-of-trend (OOT) results and further compare the z-score method and the tolerance interval in OOT analysis for stability studies.


Pharmaceutical Technology
Volume 37, Issue 6, pp. 46-51,59

Results and discussion

The simulation gave the same results as the experiment. Therefore, this study was focused only on elaborating the experiment on its own. It must be noted that the obtained limits in this experiment will only apply to this final product in the given dosage form, strength, and primary and secondary packaging.

With the use of the regression-control-chart method, three OOT results were detected in the time points of 9, 18, and 36 months (see Table I). The result in the 9-month time point deviates approximately 0.19%. The result in the 18-month time point deviated by 2%, and the result in the 36-month time point deviated by 3% from the expected value according to the regression line. Taking into consideration that in the time point of 9 months, the regression line was constructed of only three points; the result was falsely identified as an OOT result, and it was not investigated further. In terms of the control limits, the z-score test provides a constant limit of 3σ standard deviations throughout the whole regression line unlike the TI that limits the results within 15σ for the time point of 6 months to 5σ for the time interval of 24 months.

The by-time-point method identified two OOT results in the time points of 18 and 24 months (see Table III). Compared with the results from the historical data for the appropriate time points, the results of the tested batch deviated approximately by 2%. According to the z-value the results deviated 5σ from the average value of the historical data at those time points. In this method, the z-score test provided limits of 3σ, and the TI constant limit of 5.4σ (see Table IV).

The slope-control-chart method analysis resulted in identifying two OOT results (see Table V). The present OOT result for the time point of 18 months deviated 2.05σ and for 24 months deviated 5.97σ from the average value for the slope, according to the z-value. The TI, on the other hand, provided limits of 3.6σ, which were wider than the limits comprised from the z-score test. Ultimately, each manufacturer is responsible for choosing its own control limits, suitable to the analysis of the corresponding final product with its own strength and primary and secondary packaging.

This study provided a thorough explanation of the proposed methods for identification of OOT results. The methods were redesigned and improved to achieve proper evaluation of the tested stability data. The experiment revealed the positive and negative features of the proposed methods, thereby defining their appropriate use.

The regression-control-chart method allowed analysis of the results within a batch, which was achieved by comparing the absolute values of the results and the predicted values that were obtained by extrapolation of the regression line. The main disadvantage of this method was the necessity of having results for each time point due to the fact that the construction of the regression line was based on gradually adding the values in each subsequent time point. For the time period of 0–9 months, the regression line was constructed only from three points; therefore, the calculations for the predicted values were prone to an error. This method, however, is suitable for identification of present OOT results in cases where there is no historical stability data.

The by-time-point method provides analysis of the results in each time point individually, and no assumptions about the shape of the degradation curve are needed. The main advantage of the method was that the absence of having a result in any time point did not affect the analysis of the previous or next time point result. In conclusion, this method is more appropriate for analysis of the results of the first four time points. The main disadvantage is that a large history of data is preferred for proper use of this method. This method, therefore, is not suitable for analysis of ongoing stability data at the beginning of the production of the final product.

By measuring the slope of the regression line, the slope-control-chart method provided analysis of each time point individually by analyzing the influence of each time-point result on the regression line. Any small change in the value of the tested attribute from point to point was precisely recorded in the slope value of each time point. It is advised, therefore, to establish slightly narrower limits in this method in comparison to the first two methods. The main disadvantage of this method is that if the test of the attribute were omitted in any time point for various reasons, the limits of that time point may not be appropriate.

In terms of the limits, the z-score method produced limits that remain constant around all of the time points in all of the methods for OOT results identification. The dependence of the TI on the number of samples included in the calculation was a major drawback for its use in the methods for OOT results identification. The TI requires a large number of results, which is difficult to meet in everyday practice within the pharmaceutical industry. The freedom of choosing the z-score limits remains a decision of each manufacturer, and it is determined according to its own requirements.


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