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Precision from drug stability studies

重复性 化学 分析物 准确度和精密度 色谱法 标准差 变异系数 残余物 药品 理论(学习稳定性) 再现性 分析化学(期刊) 生物系统 统计 数学 算法 计算机科学 药理学 生物 机器学习 医学
作者
Joachim Ermer,Christoph Arth,Phillippe De Raeve,Donald Dill,Horst-Dieter Friedel,Heidi Höwer-Fritzen,Gerd Kleinschmidt,Gerhard Köller,Heidi Köppel,Mathias Krämer,Markus Maegerlein,U. Schepers,Hermann Wätzig
出处
期刊:Journal of Pharmaceutical and Biomedical Analysis [Elsevier BV]
卷期号:38 (4): 653-663 被引量:32
标识
DOI:10.1016/j.jpba.2005.02.009
摘要

A multi-company investigation is presented to obtain and compare precision results for LC assay procedures. Forty-four drug substances and drug products of various types subjected to 156 stability studies, with 2915 assay values in total, were included. This provides an excellent source of real long-term precision estimates, as the same analytical procedure was applied during the whole stability study, extending from 12 to 60 months. Intermediate precision was calculated either using the residual standard deviation of the regression line or applying an analysis of variances, depending on whether there was a significant degradation of the analyte or not. The results show impressively the large intervals where the individually calculated parameters scatter. Distribution ranges and averages for repeatability, intermediate precision, and the ratio between the two precision levels are mainly dependent on the type of drug product. Repeatabilities were found up to 0.8% for solutions, 1.6% for drug substances, 1.9% for tablets, 2.3% for creams, and 3.4% for a bath. For intermediate precision, which includes additional variability factors due to the reference standard, operator, equipment, reagents, etc., a similar dependency was obtained with a slightly changed order: up to 1.1% for drug substances, 2.2% for solutions, 2.3% for tablets, 3.1% for creams, and 3.2% for a bath. The ratio between the precision levels is up to 2.5 and similar for all investigated drug product types, apart from solutions with up to 5.3. These differences for the types of drug product may be explained by the influence of the sample and/or the sample preparation: the more complex, the higher the variability contribution. For the investigated examples, the impact of the analyte and of the concentration (dosage) seems to be of less importance. Therefore, a classification of drug product types for orientation on acceptable precision (ranges) for LC assay seems to be possible.

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