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基于相关验证数据的测量不确定度评估:采用电感耦合等离子体质谱法测定药品中的元素杂质

Measurement uncertainty evaluation from correlated validation data: Determination of elemental impurities in pharmaceutical products by ICP-MS.

作者信息

Milde David, Pluháček Tomáš, Kuba Martin, Součková Jitka, Bettencourt da Silva Ricardo J N

机构信息

Department of Analytical Chemistry, Faculty of Science, Palacký University Olomouc, 17. listopadu 12, 771 46, Olomouc, Czech Republic.

Department of Analytical Chemistry, Faculty of Science, Palacký University Olomouc, 17. listopadu 12, 771 46, Olomouc, Czech Republic; Department of Contaminants, State Veterinary Institute in Olomouc, Hulínská 2286, 767 60, Kroměříž, Czech Republic.

出版信息

Talanta. 2020 Dec 1;220:121386. doi: 10.1016/j.talanta.2020.121386. Epub 2020 Jul 10.

Abstract

Pharmaceutical products as well as active pharmaceutical ingredients (APIs) are checked for levels of elemental contaminants to guarantee medicines administration will not involve the consumption of level of contaminants greater than their maximum admissible intake. However, the conformity decision is affected by the measurement uncertainty function of analytical steps performance, used standards quality and how measurement performance is assessed during method validation. When an ingredient is considered conform, since the measured concentration is lower than the maximum limit, the risk of a false acceptance depends on how close the measured concentration is from the limit and on the measurement uncertainty. The analytical methods used for pharmaceutical analysis should be validated by ICH and USP recommendations, in order to prove measurements are fit for purpose. The validation must also be economically feasible and have an acceptable duration. This work discusses how to evaluate the uncertainty of elemental analysis in pharmaceutical ingredients from data collected during the validation of the analytical method by following ICH guidelines and USP chapters. A top-down uncertainty evaluation based on results from the analysis of a model API intermediate, with the native analyte after spiking at three concentration levels, where analyses are performed by two analysts in two different days, is presented. The impact of the correlation of some uncertainty components of collected results on the uncertainty evaluation is discussed and considered in the calculations. The developed measurement model was checked by a cross-validation procedure where some validation data was randomly removed and used for an independent model control. The developed uncertainty evaluation methodology was successfully applied to the analysis of Pd in a model API intermediate by ICP-MS after a micro-wave assisted acid digestion, where the risk of a false acceptance of the pharmaceuticals is determined. The measurement performance data and used spreadsheet are made available as Supplementary Material.

摘要

药品以及活性药物成分(API)需检查其元素污染物水平,以确保药物给药过程中所摄入的污染物水平不会超过其最大允许摄入量。然而,合格判定会受到分析步骤性能的测量不确定度函数、所用标准品的质量以及方法验证期间测量性能评估方式的影响。当一种成分被判定为合格时,由于测量浓度低于最大限值,错误接受的风险取决于测量浓度与限值的接近程度以及测量不确定度。用于药物分析的分析方法应按照国际协调会议(ICH)和美国药典(USP)的建议进行验证,以证明测量结果符合目的。验证还必须在经济上可行且持续时间可接受。本文讨论了如何根据在分析方法验证过程中按照ICH指南和USP章节收集的数据来评估药物成分中元素分析的不确定度。本文提出了一种自上而下的不确定度评估方法,该方法基于对一种模型API中间体的分析结果,在加入三种浓度水平的天然分析物后,由两名分析人员在两天内进行分析。讨论了收集结果中一些不确定度分量的相关性对不确定度评估的影响,并在计算中予以考虑。通过交叉验证程序对所建立的测量模型进行了检验,在该程序中随机去除一些验证数据并用于独立的模型控制。所建立的不确定度评估方法成功应用于微波辅助酸消解后通过电感耦合等离子体质谱(ICP-MS)对一种模型API中间体中钯的分析,确定了药物被错误接受的风险。测量性能数据和所用电子表格作为补充材料提供。

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