检验记录审核：出力不讨好的工作！

ANALYTICAL DATA REVIEW:  THE THANKLESS JOB

分析数据审查：出力不讨好的工作

By Tim Rhines, Ph.D FDA Laboratories Regulatory Affairs Science& Technology

作者： FDA实验室法规事务科学与技术办公室TimRhines博士 

In any analytical laboratory that performscGMP testing, data review is required. However, to an analytical chemist that prefers benchwork, reviewing thedata of a fellow analyst is often deemed an undesirable chore.  The data reviewer rarely gets a “Thank you”for pointing out irregularities in documentation.  The role of the data reviewer is to ensurethat the laboratory analyst’s work adheres to written test methods and  established SOPs and that the conclusions arescientifically correct.  This is a heavyresponsibility that is crucial in protecting a company from significant errorsor fraudulent practices in the laboratory.

在执行cGMP测试的任何分析实验室中，都需要进行数据审查。但是，对于喜欢机械性工作的化学分析师而言，审查其他检验员的数据通常是不受欢迎的苦差事。数据审查人员很少因为指出文件记录中的不规范之处而获得“感谢”。数据审查人员的作用是确保实验室分析人员的工作符合书面的测试方法和既定的SOP，并确保结论科学正确。这是一项沉重的责任，对于保护公司免受实验室重大错误或欺骗行为的侵害至关重要。

The review of laboratory data is requiredby 21 CFR § 211.194(A)(8): “The initials or signature of a second personshowing the original records have been reviewed for accuracy, completeness, andcompliance with established standards.” This statement does not indicate how data is to be reviewed or the skillset that is required to be capable of reviewing data properly.  Common sense dictates that a data reviewershould be a person with the knowledge and experience to fully understand thedata that they are reviewing.  This“common sense” is supported by 21 CFR § 211.25(a): “Each person engaged in themanufacture, processing, packing, or holding of a drug product shall have theeducation, training, and experience, or any combination thereof, to enable thatperson to perform the assigned functions.” When GMP regulations were initially written in the 1970s, the vastmajority of laboratory raw data was recorded on paper and it was the paper thatrepresented the evidence of the work performed in laboratory.  Data review was then performed by a peer orsupervisor.

21 CFR§211.194（A）（8）要求对实验室数据进行审查：“使用第二人姓名缩写或签名表示对原始记录的准确性，完整性并符合既定标准进行审查。”该声明并未指出如何审查数据，也没有指出用以正确审查数据的技能。常识表明，数据审查人员应具有知识和经验，以充分理解他们正在审查的数据。 21 CFR§211.25（a）支持这种“常识”：“从事药品的生产，加工，包装或保存的人员应接受适当足以执行所分配职能的教育，培训和经验或其组合。”在1970年代最初编写GMP法规时，绝大多数实验室原始数据都记录在纸上，纸质记录代表了实验室工作的证据。然后由同行或主管进行数据审查。

With the evolution of computerized dataacquisition systems and electronic laboratory notebooks over the past fewdecades, in conjunction with the focus on data integrity, the skill set of datareviewers has had to evolve and become more specialized.  For example, data reviewers must have a firmgrasp on how to review time/date stamps and audit trails in electroniclaboratory notebooks in order to ensure that laboratory documentation wasperformed in real time.  Additionally,data reviewers must be adept in auditing computerized laboratory instrumentsystems to ensure there is no “extra data” within the system.  As the tools to test samples has become moresophisticated, so has the skill set of the effective data reviewer.

在过去的几十年中，随着计算机化数据采集系统和电子实验室笔记本的发展，以及对数据完整性的关注，数据审查人员的技能已经必须提高并变得更加专业。例如，数据审查人员必须牢牢掌握如何审查电子实验室笔记本中的时间/日期戳和审计追踪，以确保实验室记录是实时执行的。此外，数据审查人员必须熟练执行计算机化实验室仪器系统的审计，以确保系统内没有“遗漏数据”。随着检验样品的工具变得越来越复杂，数据审查人员的技能要求也随之提高。

Today’s laboratory data reviewer must havethe keen instincts of a detective and should not be willing to accept data atface value since, in any instance, there may be trouble looming below thesurface of what appears to be acceptable laboratory data.  The job of a data reviewer may be viewed as“Thankless” by those assigned the task and considered to be an afterthought byothers.  However, data reviewers serve avital role as the safety net of both the analytical laboratory chemists and thecompany that employs them.  To those whoreview analytical data in a GMP laboratory, I want to extend a big THANK YOUfor doing this “Thankless” job.

当今的实验室数据审查人员必须具有敏锐的触觉，并且不会仅从表面上接受数据，因为在任何情况下，看起来似乎可以接受的实验室数据都可能隐藏错误。数据审查人员的工作可能被分配任务的人员视为“不讨好”，并被其他人认为“秋后算账/马后炮”。但是，数据审查人员不管在分析实验室还是在雇用他们的公司，都起着至关重要的作用。对于那些在GMP实验室中审查分析数据的人，我要表示衷心的感谢，感谢你们做这项“不讨好”的工作。