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Acceptance Probability (Pa) Analysis for Process Validation Lifecycle Stages

机译:过程验证生命周期阶段的验收概率(Pa)分析

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摘要

This paper introduces an innovative statistical approach towards understanding how variation impacts the acceptance criteria of quality attributes. Because of more complex stage-wise acceptance criteria, traditional process capability measures are inadequate for general application in the pharmaceutical industry. The probability of acceptance concept provides a clear measure, derived from specific acceptance criteria for each quality attribute. In line with the 2011 FDA Guidance, this approach systematically evaluates data and scientifically establishes evidence that a process is capable of consistently delivering quality product. The probability of acceptance provides a direct and readily understandable indication of product risk. As with traditional capability indices, the acceptance probability approach assumes that underlying data distributions are normal. The computational solutions for dosage uniformity and dissolution acceptance criteria are readily applicable. For dosage uniformity, the expected AV range may be determined using the s lo and s hi values along with the worst case estimates of the mean. This approach permits a risk-based assessment of future batch performance of the critical quality attributes. The concept is also readily applicable to sterileon sterile liquid dose products. Quality attributes such as deliverable volume and assay per spray have stage-wise acceptance that can be converted into an acceptance probability. Accepted statistical guidelines indicate processes with C pk > 1.33 as performing well within statistical control and those with C pk < 1.0 as “incapable” (1). A C pk > 1.33 is associated with a centered process that will statistically produce less than 63 defective units per million. This is equivalent to an acceptance probability of >99.99%.
机译:本文介绍了一种创新的统计方法,以了解变化如何影响质量属性的接受标准。由于更复杂的分阶段验收标准,传统的工艺能力措施不足以在制药行业中普遍应用。接受概率的概念提供了一个清晰的度量,该度量是从每个质量属性的特定接受标准得出的。与2011年FDA指南相一致,该方法系统地评估数据并科学地建立证据,表明流程能够始终如一地交付优质产品。接受的可能性提供了产品风险的直接且易于理解的指示。与传统的能力指标一样,接受概率方法假定基础数据分布是正态的。剂量均匀性和溶出度接受标准的计算解决方案很容易应用。对于剂量均匀性,可以使用s lo和s hi值以及最坏情况下的平均值估算值确定预期的AV范围。这种方法允许对关键质量属性的未来批处理性能进行基于风险的评估。该概念也容易适用于无菌/非无菌液体剂量产品。质量属性(例如可交付量和每次喷雾测定)具有阶段性验收,可以将其转换为验收概率。公认的统计准则表明,C pk> 1.33的过程在统计控制范围内表现良好,而C pk <1.0的过程被认为“无能力”(1)。 C pk> 1.33的过程与居中过程相关,根据统计,每百万个缺陷单元将产生少于63个缺陷单元。这等效于> 99.99%的接受概率。

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