Purport:
Conducting and managing a stability program is very expensive. To reduce the cost of the stability program, many companies employ options such as bracketing & matrixing (B&M).
Regulatory overview:
In February 2002, Q1D was published by ICH (Step 4) with recommendation for specific principles provided for situations in which B&M can be applied without minimal regulatory consultation. Regulatory agencies also encourage the use of these matrixes to reduce testing and minimize redundant testing.
Statistical methodology:
- ICH Q1D discusses the use of bracketing and matrixing. A full design is a configuration in which samples of all combinations are tested at every time point.
- A reduced design is one in which samples for every factor combination are not all tested at all time points.
- Therefore, assumptions play a critical role in determining whether bracketing or matrixing is appropriate. These assumptions must be assessed and justified prior to the application of any reduced testing.
Pain-points:
ICH Q1D indicates that during the course of a reduced design, a change to full testing or to a less-reduced design can be considered if samples are available to accommodate the change; however, the new design must then be carried out though the remaining time points.
Bracketing:
Bracketing is the design of a stability schedule such that at any time point only the samples on the extremes of certain design factors, for example, strength, container size and/or fill, are tested at all time points as in a full design. The design assumes that the stability of the intermediate levels is represented by the extreme levels tested; therefore, there is no need to generate another similar data set. Thus the use of a bracketing design would not be appropriate if the samples selected for testing are indeed not the extreme configuration.
Matrixing:
Matrixing is a more conservative approach than bracketing, and favored by regulators.
As defined in Q1D, matrixing is a statistical design of a stability schedule. At a specified time point, a selected subset of the total number of possible samples is tested for all factor combinations. At a subsequent time point, another subset of samples for all factor combinations is tested. The design assumes that the stability of each subset of samples tested represents the stability of all samples at
a given time point.
The need:
Pharmaceutical industry does a lot of Product Line Extensions and changing the packing configuration across geographies and the choice of container – closure systems is quite common place. Hence a out of the box solution as a part of the Stability studies toolbox would be highly warranted and this feature is found missing in competitor products.
