Predicting the stability of biological standards and products

Abstract

A high level of stability is essential for any biological standard and is desirable in most other biological products. It is in general impossible to observe directly the rate of degradation of a biological standard since no independent scale of measurement is available. An indirect method is therefore required. The most common approach is the accelerated degradation test in which samples are stored for a time at elevated temperatures and then compared with samples stored continuously at low temperature. The relative degradation rates are used to fit the Arrhenius equation (relating degradation rate to temperature) and hence to predict stability under normal storage conditions. Previous statistical work on this problem is reviewed and a maximum likelihood ML approach is suggested which overcomes some of the limitations of the existing methodology. The accelerated degradation test also finds wide application in the shelf-life prediction of biological products where the same statistical methods are appropriate.