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1、2016年8月EMA发布数据完整性问答1 How can data risk be assessed?Data risk assessment should conside r the vulneability of data to involunta ry or delibe rate amendment, deletion or recr eation. Cont rol meas ures which pr event unautho rised activity and inc rease visibility / detectability can be used as risk m
2、itigating actions.Examples of factors which can increase risk of data integrity failure include complex, inconsistent pr ocesses with open-ended and subjective outcomes. Simple tasks which are consistent, well-defined and objective lead to r educed risk.Risk assessment should include a business pr o
3、cess focus (e.g. pr oduction, QC) and not just conside r IT system functionality or complexity. Fact ors to conside r include: Pr ocess complexity Pr ocess consistency, deg ree of automation /human inte rface Subjectivity of outcome / r esult Is the pr ocess open-ended or well definedThis ens ures t
4、hat manual inte rfaces with IT systems are conside red in the risk assessment pr ocess. Compute rised system validation in isolation may not r esult in low data integ rity risk, in par ticula r when the use r is able to influence the repor ting of data from the validated system.2 How can data critic
5、ality be assessed?The decision which data influences may diffe r in imp or tance, and the impact of the data to a decision may also vary. Points to conside r r ega rding data cr iticality include: What decision does the data influence?For example: when making a batch r elease decision, data which de
6、te rmines compliance with cr itical quality att ributes is of gr eate r imp or tance than war ehouse cleaning recor ds. What is the impact of the data to pr oduct quality or safety?For example: for an oral tablet, active substance assay data is of gr eate r impact to product quality and safety than
7、tablet dimensions data.3. What does Data Lifecycle refer to?Data lifecycle refers to how data is gene rated, pr ocessed, repor ted, checked, used for decision-making, sto red and finally disca rded at the end of the r etention per iod.Data r elating to a pr oduct or pr ocess may cr oss va rious boun
8、da ries within the lifecycle, for example: IT systemsoQuality system applicationsoPr oductionoAnalyticaloStock management systemsoData stor age (back-up and ar chival) Or ganisationaloInte rnal (e.g. between pr oduction, QCandQA)oExte rnal (e.g. between cont ract give rsandaccept ors)oCloud-based ap
9、plications and stor age4 Why is Data lifecycle management important to ensure effective data integrity measures?Data integ rity can be affected at any stage in the lifecycle. It is the refore imp or tant to unde rstand the lifecycle elements for each type of data or record, and ens ure cont rols whi
10、ch are propor tionate to data cr iticality and risk at all stages.5 What should be considered when reviewing the Data lifecycle?The Data lifecycle refers to the: Gene ration and recor ding of data Pr ocessing into usable infor mation Checking the completeness and acc ur acy of repor ted data and pr
11、ocessed inf or mation Data (or r esults) are used to make a decision Retaining and retr ieval of data which pr otects it from loss or unautho rised amendment Reti ring or disposal of data in a cont rolled manne r at the end of its lifeData Lifecycle r eviews are applicable to both pape r and elect r
12、o nic recor ds, although cont rol meas ures may be applied diffe rently. In the case of compute rised systems, the data lifecycle r eview should be perfor med by business pr ocess owne rs (e.g. pr oduction, QC) in collab or ation with IT per sonnel who unde rstand the system ar chitect ure. The desc
13、 ription of compute rised systems r equi red by EU GMP Annex 11 paragr aph 4.3 can assist this r eview. The application of cr itical thinking skills isimp or tant to not only identify gaps in data gove rnance, but to also challenge the effectiveness of the pr oced ural and systematic cont rols in pl
14、ace.Seg regation of duties between data lifecycle stages pr ovides safegua rds against data integ rity failu re by r educing the opportunity for an individual to alte r, mis-repr esent or falsify data without detection.Data r isk should be conside red at each stage of the data lifecycle r eview.6. D
15、ata lifecycle: What risks should be considered when assessing the generating and recording of data?The following aspects should be conside red when dete rmining risk and cont rol meas ur es: How and where is original data created (i.e. paper or electronic) What metadata is associated with the data,
16、to ens ure a complete, acc ur ate andtr aceable record, taking into account ALCOA pr inciples. Does the record per mit the r econst ruction of the activity Whe re is the data and metadata located Does the system require that data is saved to per manent memory at the time of recor ding, or is it held in a temp orary buffe rIn the case of some
