stab for R - A Data Analysis Tool for
Drug Stability with   (demo)

Created by Hsin-ya Lee (hsinyalee@gmail.com), and
Yung-jin Lee (pkpd.taiwan@gmail.com)
College of Pharmacy, Kaohsiung Medical University
Kaohsiung, Taiwan 807

Introduction
This package is used to analyze stability data.  We follow the ICH guideline 'Q1E Evaluation for Stability Data' (from USA FDA site) to design this tool (Here's its .pdf.). This guideline describes when extrapolation should be considered as proposing a retest period for a drug substance or a shelf life of a drug product that extends beyond the period covered by available data from the stability study under the long-term storage condition.

Methods
This package includes two steps.  In the first step, Decision Tree for Data Evaluation follows "Appendix A" of ICH guideline "Q1E Evaluation for Stability Data" that assists users evaluating stability data and guiding users to consider doing an extrapolation for a proposed retest period or shelf life. 
In the second step, Statistical Approaches to Stability Data Analysis is conducted for two different situations.  First one is for a single batch.  This approach estimates the retest period or shelf life for a single batch of drug product.  The relationship between residuals and time is assumed to be linear.  Two-sided 95 % confidence intervals of the regression line for residuals (% relative to the original amount) of a drug product intersect with upper and lower acceptance criteria of label claimed.  Then, the shortest one is the shelf life.  When there are multiple batches (e.g. 3 batched) available,  analysis of covariance (ANCOVA) is first employed to test the difference in slopes and intercepts of the regression lines with different factors (packages, dosage forms, etc.).  Then, based on the statistical results, there can be three possibilities. (1).  slope (P>=0.25) and intercept (P>=0.25): the tests for equality of slopes and equality of intercepts are all no differences.  The data from all batches then should be combined.  Then, a single retest period or shelf life is estimated from the combined data. (2).  slope (P>=0.25) and intercept (P<0.25): the test rejects the hypothesis of equality of intercepts but fails to reject the hypothesis with that all slopes are equal.  The data should be combined to estimate the common slope.  The retest periods or shelf lives for individual batches can be estimated.  Then, the shortest estimate among batches should be chosen as the shelf life for all batches. (3).  [slope (P<0.25) and intercept (P>=0.25)] or [slope (P<0.25) and intercept (P<0.25)]: the result in this scenario shows that the test rejects the hypothesis of equality of all slopes.  It is not appropriate to combine the data from all batches in this situation.  The retest periods or shelf lives for individual batches is estimated.  Then, the shortest estimate among batches should be chosen as the shelf life for all batches.