It is the objective of a systematic and holistic Quality-by-Design approach to demonstrate and ensure that an analytical procedure is fit for its intended purpose over its entire lifecycle. Such a lifecycle approach, as proposed for a new USP General Information Chapter includes the three stages Procedure Design and Development, Procedure Performance Qualification, and Continued Procedure Performance Verification, in alignment to manufacturing process validation. A decisive component of this approach is the Analytical Target Profile, which defines the performance requirements for the measurement of a Quality Attribute as the target for selection, development and optimization of the respective analytical procedures. Although the most benefit can be gained by a comprehensive Quality-by-Design approach establishing the Analytical Target Profile in the very beginning of a drug development project, it may also be established retrospectively for analytical procedures long in routine use, in order to facilitate future lifecycle activities such as continual improvements, transfers, monitoring and periodic performance evaluations. In contrast to the first two stages of the analytical lifecycle with usually limited amount of data, the Continued Procedure Performance Verification stage offers the possibility to utilize a much more reliable data base to collect, analyze, and evaluate data that relate to analytical procedure performance. This monitoring program should be aligned as far as possible with other quality systems already in place and may include performance indicators such as Conformity (i.e. out-of specification test results with analytical root-cause), Validity (i.e. failure to meet method acceptance criteria, e.g. system suitability tests), and (numerical) analytical performance parameters (e.g. ranges for replicate determinations, control sample results, etc). In addition to the monitoring of analytical control parameters by means of control charts, average (pooled) performance parameters can be calculated. Over time, a large number of data can be included and thus the reliability of these estimates is increased tremendously. Such reliable estimates for the true performance parameters, e.g. repeatability or intermediate precision are essential to identify systematic effects (also called special cause variation) with good confidence. The intent of the analytical procedure performance evaluation is to identify substandard performance, identify root cause through investigations, and determine when additional activities are required to improve it. Examples are provided for the monitoring and evaluation of performance parameters for the compendial drug substance Furosemide and for biopharmaceutical applications.

中文翻译：

---

药物分析的生命周期管理：如何建立有效且相关的持续性能监控程序。

一种系统的，整体的“按设计质量”方法的目的是证明并确保分析程序在其整个生命周期中都适合其预期目的。针对新的USP一般信息一章提出的这种生命周期方法包括三个阶段，即过程设计和开发，过程性能鉴定和持续过程性能验证，以与制造过程验证保持一致。这种方法的决定性组成部分是分析目标配置文件，它定义了测量质量属性的性能要求，作为选择，开发和优化相应分析程序的目标。尽管通过在药物开发项目的一开始就建立分析目标配置文件的全面设计质量方法可以获得最大的收益，但也可以追溯性地建立长期使用常规分析程序的方法，以利于将来的发展。生命周期活动，例如持续改进，转移，监控和定期绩效评估。与通常只有少量数据的分析生命周期的前两个阶段相比，“连续过程性能验证”阶段提供了利用更可靠的数据库来收集，分析和评估与分析过程性能相关的数据的可能性。该监控程序应尽可能与已经存在的其他质量体系保持一致，并可能包括性能指标，例如合格性（即，具有分析性根本原因的不合格测试结果），有效性（即，不符合方法接受标准，例如系统适用性测试）和（数值）分析性能参数（例如重复测定的范围，对照样品结果等）。除了通过控制图监视分析控制参数外，还可以计算平均（池）性能参数。随着时间的流逝，可以包含大量数据，因此这些估计的可靠性得到了极大的提高。对真实性能参数的这种可靠估计，例如 重复性或中间精度对于确定系统效果（也称为特殊原因变异）具有良好的信心至关重要。分析程序性能评估的目的是识别不合格的性能，通过调查确定根本原因，并确定何时需要进行其他活动来改进它。提供了用于监测和评估药物原料速尿和生物制药应用的性能参数的示例。