If stability studies consist of batches understood to be a random sample from the population of batches, as described above, then the resulting data can be used to estimate the true shelf lives of the batches in the studies. Increasing the number of batches to include in a stability trial only exacerbates the problem.
In this process, the Working Group has considered existing guidelines but sometimes taken the liberty to question elements of these for the purpose of potentially developing an improvement. Because of the limitations associated with using the minimum or central quantile of the distribution of true batch shelf lives to define the true product shelf life, the Working Group proposes that the true product shelf life should be defined in terms of a suitably small quantile of this distribution. A specific batch may have stability characteristics that are slightly better or slightly worse than those of other batches from the production process. If the ICH Q1E methodology is extended so that the batches used in stability studies are treated as a random sample of batches taken from the entire production of the pharmaceutical product, there is still a problem with estimating the true product shelf life as the minimum of the estimated batch shelf lives. For a simple linear regression model, the analysis follows in a stepwise fashion to determine which of the following alternative regression models is most appropriate for characterizing the response of the batches over storage time and estimating the shelf life: Gaining information about both the product and shelf life distributions and the relationship between the two distributions, through replicate or historical batch response, then allows determining the proportion of the shelf life distribution to be considered for defining the estimated product shelf life.