共线性
理论(学习稳定性)
阿累尼乌斯方程
湿度
统计模型
统计
期限(时间)
数学
热力学
应用数学
化学
计算机科学
活化能
物理
机器学习
量子力学
有机化学
作者
Klemen Naveršnik,Rok Jurečič
标识
DOI:10.1016/j.ijpharm.2016.01.047
摘要
Accelerated and stress stability data is often used to predict shelf life of pharmaceuticals. Temperature, combined with humidity accelerates chemical decomposition and the Arrhenius equation is used to extrapolate accelerated stability results to long-term stability. Statistical estimation of the humidity-corrected Arrhenius equation is not straightforward due to its non-linearity. A two stage nonlinear fitting approach is used in practice, followed by a prediction stage. We developed a single-stage statistical procedure, called the reference condition approach, which has better statistical properties (less collinearity, direct estimation of uncertainty, narrower prediction interval) and is significantly easier to use, compared to the existing approaches. Our statistical model was populated with data from a 35-day stress stability study on a laboratory batch of vitamin tablets and required mere 30 laboratory assay determinations. The stability prediction agreed well with the actual 24-month long term stability of the product. The approach has high potential to assist product formulation, specification setting and stability statements.
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