Sampling Errors in Validation.
Recognition of sampling errors and their impact on data variation is an important consideration in pharmaceutical and medical device validation. The evaluation of suspect data may be enhanced by consideration of sampling errors. Validation and compliance professionals must always be aware of the pot...
| Publicado en: | Journal of Validation Technology (JVT) Vol. 17; no. 1; pp. 81 - 89 |
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| Autor principal: | |
| Formato: | tables/charts Journal Article |
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Institute of Validation Technology
Winter2011
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=59215136&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 59215136 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10796630 38NF jtl: Journal of Validation Technology (JVT) issn: 10796630 maglogo: N pubinfo: dt: Winter2011 vid: 17 iid: 1 pid: 34717 pub: Institute of Validation Technology place: Duluth, Minnesota artinfo: ui: 59215136 59215136 104839364 59215136 ppf: 81 ppct: 8 formats: tig: atl: Sampling Errors in Validation. aug: au: Smith, Patricia L. sug: subj: Sampling Error Quality Assurance Technology, Pharmaceutical Analytic Sample Preparation Methods Laboratories Software Data Management ab: Recognition of sampling errors and their impact on data variation is an important consideration in pharmaceutical and medical device validation. The evaluation of suspect data may be enhanced by consideration of sampling errors. Validation and compliance professionals must always be aware of the potential for sampling errors and their impact. Sampling errors may greatly influence validation data, cause incorrect judgments, influence trending, add variation, and otherwise significantly affect data accuracy and precision. Sampling errors may be generally categorized as Material Errors, Process Errors, Sample Errors, and Laboratory Errors. Ten specific individual sampling errors have been identified. Material errors include Fundamental Error, Grouping and Segregation Error, and Nugget Effect. Material variation is due to its composition, its distribution, and inherent material non-uniformity. Material variation is often not fully appreciated and may impact all other sources of variation. Process errors include Non-periodic Process Errors and Periodic Process Errors. Process variation is fairly well understood and contributes to data variation in generally predictable ways. Sample errors include Sample Definition, Sample Collection, and Sample Handling. Sample selection (i.e., sample definition and collection) is often not defined to a sufficient extent to prevent errors and excessive data variation. Laboratory errors include Analytical Error and Data Error. Laboratory error contributions to sampling errors are frequently overlooked. Data errors may occur in processing, sampling, and in the laboratory. Example actual occurrences of sampling errors directly impacting validation are described. pubtype: Academic Journal doctype: tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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