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Two‐phase shelf‐life estimation
Author(s) -
Shao Jun,
Chow SheinChung
Publication year - 2001
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.783
Subject(s) - shelf life , guideline , phase (matter) , computer science , off the shelf , linear regression , drug , regression , econometrics , statistics , data mining , mathematics , medicine , machine learning , chemistry , food science , pharmacology , software engineering , organic chemistry , pathology
Abstract Unlike most drug products, some drug products must be stored at several temperatures, such as −20°C, 5°C and 25°C, in order to maintain the stability of the drug products. Drug products of this kind are usually referred to as frozen drug products. The determination of shelf‐life for frozen drug products involves the estimation of drug shelf‐lives at different temperatures, which requires multiple phase linear regression. Mellon suggested obtaining a combined shelf‐life by determining shelf‐lives based on data available at different temperatures. This method, however, does not account for the fact that the shelf‐life at the second‐phase would depend on the shelf‐life at the first phase. As an alternative, we propose a method for determination of drug shelf‐lives for the two phases using a two‐phase regression analysis based on the statistical principle described in the FDA guideline and the ICH guideline. A numerical example is presented to illustrate the proposed method. Copyright © 2001 John Wiley & Sons, Ltd.