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ALCOA+ is the acronym for the key concepts that can help to support record and data integrity [8]. See Table 1.1. | ALCOA + 是关键概念的首字母缩写,有助于支持记录和数据完整性。参见表1.1。 | |
Attributable • Attributable to the person or system generating the data • Identify the person or system performing an activity that creates or modifies data • Linked to the source of the data | 可归属的 •可归属到生成数据的人员或系统 •识别执行创建或修改数据的活动的人员或系统 •链接到数据源 | |
Legible • Readable and permanent • Accessible throughout the data life cycle • Original data and any subsequent modifications are not obscured | 清晰可读 •易读且永久 •在整个数据生命周期内可访问 •原始数据和任何后续修改不会被掩盖 | |
Contemporaneous • Recorded or observed at the time the activity is performed | 同步的 •在活动进行的当时来记录或观察 | |
Original • Original data is the first recording of data, or a “true copy” which preserves content or meaning | 原始的 •原始数据是数据的首次记录,或保留内容或意义的“真实副本” | |
Accurate • Free from error • No editing performed without documented amendments • Conforming to truth or standard | 准确的 •无错误 •只在有文件修订记录的情况下进行编辑 •符合事实或标准 | |
Complete • All data, and relevant metadata, including any repeat or re-analysis performed | 完整的 •所有数据和相关元数据,包括进行的任何重复或再分析 | |
Consistent • Application of good documentation practices throughout any process • The application of date and time stamps in the expected sequence | 一致的 •在整个过程中遵循良好文件管理规范 •日期和时间戳都按预期顺序呈现 | |
Enduring • Recorded in a permanent, maintainable form for the retention period | 持久的 •在保存期内以永久、可维护的形式记录 | |
Available • Available and accessible for review, audit, or inspection throughout the retention period | 可用的 •在整个保存期内可用于审查、稽查或检查 | |
Audit Trail In this document the term audit trail refers to a data audit trail of operator entries and actions that create, modify, or delete regulated records, as required by 21 CFR Part 11 [10] and EU Annex 11 [11], as distinguished from other system and technical logs. | 审计跟踪 在本文件中,术语审计跟踪是指根据21 CFR第11部分和欧盟附件11的要求,创建、修改或删除受监管记录的操作员条目和操作的数据审计跟踪,与其他系统和技术日志不同。 | |
GxP The term “GxP” is used within this Guide to represent the encompassing regulations (Good Practices) to which different aspects of regulated companies must adhere. It is not intended to imply that all regulatory requirements are the same across Good Manufacturing Practice (GMP), Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Distribution Practice (GDP), and Good Pharmacovigilance Practice (GVP, also known as GPvP), etc. | GxP 本指南中使用的术语“GxP”代表受监管公司的不同方面必须遵守的法规(良好实践)。这并不意味着药品生产质量管理规范(GMP)、药物临床试验质量管理规范(GCP)、药物非临床研究质量管理规范(GLP)、药品分销质量管理规范(GDP)和药物警戒质量管理规范(GVP,也称为GPvP)等的所有监管要求均相同。 | |
Data Integrity and Quality Data integrity and data quality are sometimes used interchangeably, but there is actually a difference between these two terms. It is the awareness of the similarities and differentiation between data integrity and data quality that is less prevalent and therefore a number of examples are provided in Appendix M2 Table 9.1 to aid in this clarification. | 数据完整性和质量 数据完整性和数据质量有时可以互换使用,但这两个术语之间实际上存在差异。 意识到数据完整性和数据质量之间的相似性和差异不太普遍,因此在附录M2表9.1中提供了许多示例,以帮助澄清。 | |
Understanding Data Integrity | | |
The need for data integrity is well established through predicate rules, through data integrity guidance, and through industry acceptance of data integrity as an essential component to protecting patient safety and ensuring product quality | 通过既定规则、数据完整性指南以及行业认可数据完整性作为保护患者安全和确保产品质量的重要组成部分,充分确定了数据完整性的需求 | |
Data integrity is the assurance that the data is original and trustworthy, and that this assurance has been maintained throughout the data lifecycle. | 数据完整性是指保证数据具有原始性和可信度,并且在整个数据生命周期内都如此。 | |
The requirements for data integrity are discussed comprehensively in the ISPE GAMP® Guide: Records and Data Integrity [8]. | 在ISPE GAMP指南:记录和数据完整性中全面讨论了数据完整性的要求。 | |
Understanding Data Quality | | |
The ISPE GAMP® Guide: Records and Data Integrity [8] states that: | | |
“Data quality relates to the data’s fitness to serve its intended purpose in a given context within a specified business or regulatory process. | “数据质量与数据在特定业务或监管流程中在给定背景下满足其预期目的的适合性相关。 | |
Data quality management activities address aspects including accuracy, completeness, relevance, consistency, reliability, and accessibility.” | 数据质量管理活动涉及的方面包括准确性、完整性、相关性、一致性、可靠性和可访问性。” | 数据完整性范围更广?更加覆盖了整个生命周期? 数据质量只是特指某一部分活动? |
MHRA [12] defines data quality as: “The assurance that data produced is exactly what was intended to be produced and fit for its intended purpose. This incorporates ALCOA.” | MHRA将数据质量定义为:“确保生成的数据与预期生成的数据完全一致,并适用于其预期目的。这包括ALCOA。” | 说实话没看出来数据完整性和数据质量的区别。 或者说为了这一点区别,把问题搞得这么复杂 意义在哪? |
The Organisation for Economic Co-operation and Development (OECD) [13] defines data quality as: “Data quality is the assurance that the data produced are generated according to applicable standards and fit for intended purpose in regard to the meaning of the data and the context that supports it. Data quality affects the value and overall acceptability of the data in regard to decision-making or onward use.” | 经合组织(OECD)将数据质量定义为: “数据质量是指确保生成的数据符合适用标准,并且在数据含义和支持数据的背景方面符合预期目的。数据质量影响数据在决策或后续使用方面的价值和总体可接受性。” | 本来我还期望说数据质量会在数据采集的设计方面有什么亮眼的定义。 或者说有一些统计学方面的内容 说实话又让我失望了 |
Data quality requires that the data is organized and able to be accessed, sorted, and searched to enable the business to effectively use the data, and is reflected in the list below: | 数据质量要求对数据是有条理的并能够访问、排序和搜索,使业务能够有效使用数据,并反映在以下列表中: | 这句话还有点我期待的意思 我的理解应该是: 数据质量在数据完整性可用性的基础上,提出了易用性的更高要求 就算是如此,有必要搞得这么复杂晦涩吗? |
Data Accuracy: The extent to which the data is free of identifiable errors | | |
Data Accessibility: The level of ease and efficiency at which data is legally obtainable, within a well-protected and controlled environment | 数据可访问性: 在受到良好保护和控制的环境中合法获取数据的容易程度和效率 | |
Data Comprehensiveness: The extent to which all required data within the entire scope are collected, documenting intended exclusions | 数据全面性: 收集整个范围内所有必要数据,记录刻意排除的情况 | |
Data Consistency: The extent to which the data is reliable, identical, and reproducible by different users across applications | 数据一致性: 不同用户在不同应用中数据可靠、相同和可重现 | |
Data Currency: The extent to which data is up-to-date; a datum value is up-to-date if it is current for a specific point in time, and it is outdated if it was current at a preceding time but incorrect at a later time | 数据实时性: 数据实时的程度;如果某个特定时间点的数据值为当前数据,则该数据值为最新数据;如果之前时间点的数据值为当前数据,但之后时间点的数据值不正确,则该数据为过时数据 | |
Data Nomenclature: A consistent approach to metadata entry that facilitates identification of data relating to the same product or process for use in trending and/or data analytics, for example, a data lake. Discussed more fully in Section 4.7 | 数据命名法: 元数据录入的一致方法,有助于识别与相同产品或过程相关的数据,用于趋势分析和/或数据分析,例如数据湖。在第4.7节中更全面地讨论 | 看晕了吧 说白了就是数据的分门别类 跟上面的易用性是一回事 |
Data Granularity: The level of detail at which the attributes and characteristics of data quality are defined | | |
Data Precision: The degree to which measures support their purpose, and/or the closeness of two or more measures to each other | 数据精确度: 测量支持其目的的程度,和/或两个或多个测量彼此的接近程度 | 说实话我有点无语了 数据精确度 你说一个数据,在可接受的这个维度上,它要么是对的 要么是错的 它有什么精确度? |
Data Relevancy: The extent to which data is useful for the purposes for which it was collected | | |
Data Timeliness: The availability of up-to-date data within the useful, operative, or indicated time | | 跟数据完整性的要求没区别,说白了就是在检察官要求的,合理的时间内提供正确的数据 |
Note: Items in bold underline are reasonably addressed in ALCOA+ as part of data integrity attributes. | | |
Data quality is defined by the Data Management Body of Knowledge (DMBOK) [14] as: “…the planning, implementation, and control of activities that apply quality management techniques to data, in order to assure it is fit for consumption and meet the needs of data consumers.” | 数据管理知识体系(DMBOK)将数据质量定义为: “……将质量管理技术应用于数据的活动的规划、实施和控制,以确保其适合消费并满足数据消费者的需求。” | |
See Figure 8.2 in Appendix M1 for the concept of data producers and consumers within knowledge and data management. | 关于知识和数据管理中数据生产者和消费者的概念,请参见附录M1中的图8.2。 | |
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In this Guide, data is classified as regulated, operational, or unnecessary, as originally defined in ISPE GAMP® RDI Good Practice Guide: Data Integrity – Manufacturing Records [15]: | 在本指南中,按照ISPE GAMP RDI良好实践指南:数据完整性-生产记录中的最初定义,将数据分为需监管、操作类或不必要: | 生产中数据做这样的分类是很有必要的 对基于风险的决策是很有帮助的 |
“Regulated: used for a regulated decision or to support a regulated process, that is, data as required by, or in support of, the predicate rules – what we have to keep | “受监管的:用于受监管的决策或支持受监管的流程,既定规则要求或支持的数据-我们必须保留的内容 | |
Operational: non-regulated data used for business process decisions such as performance analysis and management of maintenance schedules – what we want to keep | 操作类:用于业务流程决策(如性能分析和维护保养计划管理)的非监管数据-我们想要保留的内容 | |
Unnecessary: data not needed due to either the circumstances of its creation (e.g., during a non-regulated activity or process) or because that data does not provide additional context, metadata, or meaning for the activity or process – what we do not need” | 不必要:由于其创建环境(例如,在非监管活动或过程期间)或由于该数据未为活动或过程提供额外的上下文、元数据或意义而不需要数据-我们不需要” | |
Note that some data may needs to be retained for financial, health and safety, or other non-life science regulations. | 请注意,可能需要保留一些数据用于财务、健康和安全或其他非生命科学法规。 | |