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Data integrity (NEW August2016) 数据完整性(2016年8月新增) Data integrity enables good decision-making by pharmaceuticalmanufacturers and regulatory authorities. It is a fundamental requirement ofthe pharmaceutical quality system described in EU GMP chapter 1, applyingequally to manual (paper) and electronic systems. 数据完整性使得药品生产商和法规当局能做出正确决策。它是EU GMP第1章中所述的药品质量体系的基本要求,等同适用于手动(纸质)和电子系统。 Promotion of a quality culture together with implementation oforganisational and technical measures which ensure data integrity is theresponsibility of senior management. It requires participation and commitmentby staff at all levels within the company, by the company’s suppliers and byits distributors. 质量文化的促进与公司实施和保证数据完整性的技术措施,都是高级管理层的职责。它要求公司内所有层次员工、公司供应商及其分销商的参与和承诺。 Senior management should ensure that data integrity risk is assessed,mitigated and communicated in accordance with the principles of quality riskmanagement. The effort and resource assigned to data integrity measures shouldbe commensurate with the risk to product quality, and balanced with otherquality assurance resource demands. Where long term measures are identified inorder to achieve the desired state of control, interim measures should beimplemented to mitigate risk, and should be monitored for effectiveness. 高级管理层应保证对数据完整性风险进行评估、降低,并根据质量风险管理原则进行沟通。为数据完整性措施所配置的资源和付出的努力应该与其对药品质量的风险水平相称,并与其它质量保证资源需求相平衡。如果为了达到所需的控制状态而需要长期措施,则应实施临时措施以减少风险,并监测其有效性。 以下问答描述了基本原则,它有助于成功实施法规当局参与的PIC/S组织公布的现有指南。它应该与国家指南、药品法律和欧盟药事法第4卷中公布的GMP标准结合解读。 The importance of data integrity to quality assurance and public healthprotection should be included in personnel training programmes. 数据完整性对于质量保证和公众安全保护的重要性应包括在个人培训计划中。 · WHO附录5:数据和记录管理规范指南 Data risk assessment should consider the vulnerability of data toinvoluntary or deliberate amendment, deletion or recreation. Control measureswhich prevent unauthorised activity and increase visibility / detectability canbe used as risk mitigating actions. 数据风险评估应考虑数据无意或有意修订、删除或重新创建的弱点。防止未经授权的活动以及增加可视度/检出性的控制措施可以用作降低风险的措施。 Examples of factors which can increase risk of data integrity failureinclude complex, inconsistent processes with open-ended and subjectiveoutcomes. Simple tasks which are consistent, well-defined and objective lead toreduced risk. 可能会增加数据完整性失败风险的因素例子包括不一致的复杂流程,会导致开放式主观结果。简单一致,界定清楚且客观就能降低风险。 Risk assessment should include a business process focus (e.g. production,QC) and not just consider IT system functionality or complexity. Factors toconsider include: 风险评估应包括业务流程关注(例如,生产、QC),而不是仅仅考虑IT系统功能性或复杂性。要考虑的因素包括: · Process complexity · 工艺复杂性 · Process consistency, degree of automation /human interface · 工艺一致性、自动化/人工干预程度 · Subjectivity of outcome / result · 结果的主观性 · Is the process open-ended or well defined · 流程结束是否开放式,是否界定清楚 This ensures that manual interfaces with IT systems are considered in therisk assessment process. Computerised system validation in isolation may notresult in low data integrity risk, in particular when the user is able toinfluence the reporting of data from the validated system. 这会保证在风险评估过程中考虑对IT系统的人工干预。计算机化系统验证单独并不会导致较低的数据完整性风险,尤其是当用户可以对经过验证的系统的数据报告产生影响的时候。
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