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dc.contributor.authorSchniepp, Susan J-
dc.date.accessioned2020-02-11T07:18:24Z-
dc.date.available2020-02-11T07:18:24Z-
dc.date.issued2019-
dc.identifier.issn1543-2521-
dc.identifier.issn2150-7376 (e)-
dc.identifier.otherBBKH687-
dc.identifier.urihttp://thuvienso.vanlanguni.edu.vn/handle/Vanlang_TV/15132-
dc.descriptionPharmaceutical Technology. Vol 43 (Octorber 2019)vi
dc.description.abstractThe following are definitions, paraphrased from the Pharmaceutical Inspection Co-operation Scheme (PIC/S) (1): * Attributable: The data generated or collected must be traceable back to the individual who generated the information. * Legible: The data recorded must be readable and permanent. * Contemporaneous: The results, measurements, etc. must be recorded at the time the work is performed. * Original: Original or source data are the record, report, notebook etc. where the data point was initially recorded. * Accurate: The data recorded must be complete, consistent, truthful, and representative of facts. * Complete: Information that is critical to recreating and understanding an event. Coupled with the emergence of biosimilars, virtual companies, contract manufacturing organizations, rapid advances in automation and information technology, and the globalization of the industry have resulted in reinterpretation of the attributes associated with maintaining the integrity of data throughout the product lifecycle, whether those data are generated from electronic, paper-based, or hybrid systems. Language in 21 CFR 58.130 (e) addresses the elements of contemporaneous and legible by stating, "All data generated during the conduct of a nonclinical laboratory study, except those that are generated by automated data collection systems, shall be recorded directly, promptly, and legibly in ink.vi
dc.language.isoenvi
dc.publisherMultiMedia Healthcare Inc.vi
dc.subjectLaboratoriesvi
dc.subjectGood Manufacturing Practicevi
dc.subjectData integrityvi
dc.subjectManufacturingvi
dc.subjectCitationsvi
dc.subjectAutomationvi
dc.subjectCFRvi
dc.subjectQualityvi
dc.titleALCOA+ and Data Integrityvi
dc.typeWorking Papervi
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