Estimating shelf-life using L1 regression methods.
The shelf-life of a drug is usually determined by fitting the assayed values of drug potency versus time to a linear least-squares model. In least-squares models, the parameters are estimated by minimizing the sum of squares of the residuals. Shelf-life is estimated as the time corresponding to the intersection point of the fitted line and the minimum acceptable per cent or proportion of the initial drug potency. The least-squares method can be seriously affected by outliers, leading to erroneous shelf-life estimates. In this paper, an alternative method, based on minimizing the sum of absolute deviations, was applied to the shelf-life determination problem. The resistance of these L1 based estimates to outliers was demonstrated using a typical stability dataset.
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Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT 06877.
D004355:Drug Stability; D015233:Models, Statistical; D012044:Regression Analysis; D013997:Time Factors