Covance, the Drug Development Division of LabCorp, 210 Carnegie Center, Princeton, NJ, USA.
Database (Oxford). 2019 Jan 1;2019. doi: 10.1093/database/baz017.
Assembly of complete and error-free clinical trial data sets for statistical analysis and regulatory submission requires extensive effort and communication among investigational sites, central laboratories, pharmaceutical sponsors, contract research organizations and other entities. Traditionally, this data is captured, cleaned and reconciled through multiple disjointed systems and processes, which is resource intensive and error prone. Here, we introduce a new system for clinical data review that helps data managers identify missing, erroneous and inconsistent data and manage queries in a unified, system-agnostic and efficient way. Our solution enables timely and integrated access to all study data regardless of source, facilitates the review of validation and discrepancy checks and the management of the resulting queries, tracks the status of page review, verification and locking activities, monitors subject data cleanliness and readiness for database lock and provides extensive configuration options to meet any study's needs, automation for regular updates and fit-for-purpose user interfaces for global oversight and problem detection.
组装完整且无错误的临床试验数据集,以进行统计分析和法规提交,需要在研究地点、中心实验室、制药赞助商、合同研究组织和其他实体之间进行大量的工作和沟通。传统上,这些数据是通过多个不相关的系统和流程来捕获、清理和核对的,这既耗费资源又容易出错。在这里,我们引入了一个新的临床数据审查系统,帮助数据管理人员以统一、与系统无关和高效的方式识别缺失、错误和不一致的数据,并管理查询。我们的解决方案能够及时、集成地访问所有研究数据,无论数据来源如何,还可以方便地审查验证和差异检查,并管理由此产生的查询,跟踪页面审查、验证和锁定活动的状态,监控主题数据的清洁度和准备情况,以进行数据库锁定,并提供广泛的配置选项,以满足任何研究的需求,实现定期更新的自动化,并为全球监督和问题检测提供适合用途的用户界面。