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所在平台: Udemy |
课程主页: https://www.udemy.com/course/good-data-integrity-compliant-practices/
课程评论：没有评论
课程名称：良好的数据完整性实践 概述： 数据完整性是数据在整个生命周期中保持完整、一致、准确、可靠和可信的程度。数据的收集与维护必须以安全的方式进行，确保数据可追溯、清晰、及时记录，并且准确无误。确保数据完整性需要适当的质量和风险管理系统，包括遵循科学原则和良好的文档管理实践。 本课程通过两段简短的视频讲座提供关于数据完整性和审计轨迹评审的实用见解。此外，还包括一些详细的录制研讨会，涵盖以下主题： 1. 数据完整性的实践方法 2. 数据完整性与良好文档实践的差异 3. 分析实验室（化学部分）及微生物实验室的数据完整性 4. 基于风险的方法的审计轨迹评审深入讲座 课程最后一讲讨论了制药4.0的重要性，这是未来制药行业的必需品，它是制药质量体系的基本组成部分，具有以下重要性： - 确保药品质量：数据完整性对于确保药物安全、有效且符合质量标准至关重要。 - 保护公众健康：数据完整性是监管机构保护公众健康的工具。 - 促进信息决策：数据完整性提高了数据的价值，帮助做出明智的商业决策。 - 遵循法规：数据完整性确保遵循生命科学和制药行业的各项法规。 数据完整性在生产和访问的每个阶段都至关重要，从初始记录到验证和存档。未能遵守数据完整性要求可能导致未验证的结果、上市后问题、频繁的产品召回、罚款、产品审批延误以及刑事指控等严重后果。
Data integrity is the degree to which data are complete, consistent, accurate, trustworthy, reliable and that these characteristics of the data are maintained throughout the data life cycle. The data should be collected and maintained in a secure manner, so that they are attributable, legible, contemporaneously recorded, original (or a true copy) and accurate. Assuring data integrity requires appropriate quality and risk management systems, including adherence to sound scientific principles and good documentation practices.This course is detailed course which includes first two short video lectures which will give practical and simple insight about Data Integrity and Audit Trail Review.Furthermore, there are recorded webinars which explains in details about;Data Integrity with practical approach, A separate dimension and that is , Data integrity Vs. Good Documentation PracticesThere are separate lectures for data integrity in analytical laboratories (chemical section) and data integrity in microbiology laboratories.Further, there is one detailed lecture on Audit Trail review based on risk based approach. Because, still many companies not implemented audit trail review based on risk based approach.The last lecture is on Pharma 4.0 Which is a need for future pharmaceuticals.It's a fundamental part of a pharmaceutical quality system and is important for a number of reasons, including;Ensuring drug qualityData integrity is essential for ensuring that medicines are safe, effective, and meet quality standardsProtecting public healthData integrity is a tool for regulatory authorities to protect public healthEnabling informed decision-makingData integrity makes data valuable and enables informed business decisionsAdhering to regulationsData integrity ensures adherence to life sciences and pharmaceutical regulationsData integrity is important at every stage of production and access, from initial recording through validation and archiving. Failure to comply with data integrity requirements can lead to:Un-validated resultsPost-marketing issuesFrequent product recallsFinesDelays in product approvalCriminal charges
