首页 > 资讯 > 持续工艺确证中评估关键工艺参数的统计学方法

出自识林

2016-03-28 Lachman CONSULTANTS

在药品制造中，确保工艺处于受控状态并被确证是对公众健康和监管机构都是非常重要的因素。为此，持续工艺确证（CPV）被定义为常规商业化制造工艺的不断监测以确保在性能确认后持续在受控状态运行。这是2011年FDA指南中描述的工艺验证的生命周期方法的组成部分。此外，在2015年，许多其它监管机构（EMA、PICS和WHO）都已经包括了工艺验证的3个阶段的要求：工艺设计、工艺确认和持续工艺确证。

开发一种对所有阶段实用方法的关键在于建立药品关键质量属性（CQA），分配和监测对关于CQA的工艺性能有直接影响关键工艺参数（CPP）。许多企业在建立CPP方面很挣扎。在大多数情况下，这种关系是凭经验分配的，并可能导致在产品生命中监测大量CPP的繁重任务。然而，这些CPP中的很多对产品整体性能具有很少或没有影响，而且可能没有统计学意义。统计学意义应当是CPP识别的起点。

在上周举行的PDA年会上，辉瑞公司质量保证验证高级经理Scott Bazzone介绍了对于CQA建立CPP的风险意义或Z分数（Z Score，统计学中一种无因次值，又称为标准分数）的方法。第一步是计算Z分数，测量CPP关系到质量标准（CQA）的风险程度。

Bazzone博士建议，在最初评估CPP的强度时，Z分数可能是一个非常有价值的工具。Z分数的漂移可指示整个产品生命周期中的工艺漂移。

辉瑞的团队（包括Bazzone博士）最近公布了这一方法（Ke Wang et al., Statistical Tools to Aid in the Assessment of Critical Process Parameters, Pharmaceutical Technology Volume 40, March 20016, Issue 3, Page 36-44 url）。文章包括决策树流程图和计算示例以帮助读者使用该工具。此外，PDA工艺验证兴趣小组已经开始着手关于持续工艺确证的技术报告。有关技术报告以及如何参与请见PDA网站。无论何种剂型，持续工艺确证是商业规模制造的重要组成部分。企业开发工具测量和评估工艺的复现性是极其重要的，对于全球范围的监管机构也非常重要。

Lachman CONSULTANTS - Don Elinski
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Developments in Continuing Process Verification
By Don Elinski | March 28, 2016

In pharmaceutical manufacturing, assuring that processes are in a state of control and verified is a very important element for both public health and regulatory authorities. To this end, Continuing Process Verification (CPV) is defined as the ongoing monitoring of a routine commercial manufacturing process to assure that it continues to operate in a state of control post-performance qualification. It is a component of the Lifecycle approach for Process Validation as described in the 2011 FDA Guidance (here). In addition, in 2015, many other regulatory authorities (EMA, PICS, and WHO) all have included a requirement for 3 stages of Process Validation: Process Design, Process Qualification, and Ongoing/Continuing Process Verification.

The key to developing a practical approach to all phases lies in the establishment of Critical Quality Attributes (CQA) for the drug product and assignment and monitoring of Critical Process Parameters (CPP) that have a direct effect on the performance of the process with regard to the CQA. Many firms struggle with the establishment of CPP. In most cases, the relationship is assigned empirically and can result in an onerous task of monitoring a significant number of CPP over the life of the product. However, many of these CPPs have little or no impact on product performance as a whole, and may not be statistically significant. Statistical significance should be a starting point for CPP identification.

At the PDA Annual Meeting last week, Scott Bazzone, Senior Manager of Quality Assurance Validation at Pfizer presented the approach that is used there with regards to establishing the risk significance or Z Score of a CPP to the CQA. The first step is the calculation of a Z score, which measures degree of risk that a CPP has in relationship to the specification (CQA).

Dr. Bazzone suggested that the Z score could be an extremely valuable tool when initially assessing the strength of CPP. Shifts in Z Score could indicate process shifts throughout the Product Lifecycle.

The team at Pfizer (including Dr. Bazzone) has recently published this approach (Ke Wang et al., Statistical Tools to Aid the Assessment of Critical Process Parameters, Pharmaceutical Technology Volume 40, March 20016, Issue 3, Page 36-44 url). The paper includes a flowchart to aid the reader in use of the tools, as well as examples of calculations. In addition, the Process Validation Interest Group of the Parenteral Drug Association has started work on a Technical Report on Continuing/Ongoing Process Verification. More information on the Technical Report and how to participate in the process can be found on the PDA website. Regardless of the dosage form, continuing process verification is an important component to commercial scale manufacturing. It is essential for the industry to develop tools to measure and assess the reproducibility of processes, as it is clearly critical to regulators worldwide.