验收试验
公差间隔
置信区间
计算机科学
可靠性工程
区间(图论)
百分位
集合(抽象数据类型)
质量(理念)
产品(数学)
极限(数学)
统计
数据挖掘
风险分析(工程)
数学
医学
工程类
组合数学
软件工程
几何学
数学分析
哲学
程序设计语言
认识论
作者
Xiaoyu Dong,Yi Tsong,Meiyu Shen
标识
DOI:10.1080/10543406.2014.972511
摘要
According to ICH Q6A (1999), a specification is defined as a list of tests, references to analytical procedures, and appropriate acceptance criteria, which are numerical limits, ranges, or other criteria for the tests described. For drug products, specifications usually consist of test methods and acceptance criteria for assay, impurities, pH, dissolution, moisture, and microbial limits, depending on the dosage forms. They are usually proposed by the manufacturers and subject to the regulatory approval for use. When the acceptance criteria in product specifications cannot be pre-defined based on prior knowledge, the conventional approach is to use data from a limited number of clinical batches during the clinical development phases. Often in time, such acceptance criterion is set as an interval bounded by the sample mean plus and minus two to four standard deviations. This interval may be revised with the accumulated data collected from released batches after drug approval. In this article, we describe and discuss the statistical issues of commonly used approaches in setting or revising specifications (usually tighten the limits), including reference interval, (Min, Max) method, tolerance interval, and confidence limit of percentiles. We also compare their performance in terms of the interval width and the intended coverage. Based on our study results and review experiences, we make some recommendations on how to select the appropriate statistical methods in setting product specifications to better ensure the product quality.
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