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ZENODO
Dataset . 2015
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2015
License: CC 0
Data sources: Datacite
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Data from: Quality expectations and tolerance limits of trial master files (TMF) - Developing a risk-based approach for quality assessments of TMFs

Authors: Hecht, Arthur; Busch-Heidger, Barbara; Gertzen, Heiner; Pfister, Heike; Ruhfus, Birgit; Sanden, Per-Holger; Schmidt, Gabriele B.;

Data from: Quality expectations and tolerance limits of trial master files (TMF) - Developing a risk-based approach for quality assessments of TMFs

Abstract

This article addresses the question of when a trial master file (TMF) can be considered sufficiently accurate and complete: What attributes does the TMF need to have so that a clinical trial can be adequately reconstructed from documented data and procedures? Clinical trial sponsors face significant challenges in assembling the TMF, especially when dealing with large, international, multicenter studies; despite all newly introduced archiving techniques it is becoming more and more difficult to ensure that the TMF is complete. This is directly reflected in the number of inspection findings reported and published by the EMA in 2014. Based on quality risk management principles in clinical trials the authors defined the quality expectations for the different document types in a TMF and furthermore defined tolerance limits for missing documents. This publication provides guidance on what type of documents and processes are most important, and in consequence, indicates on which documents and processes trial team staff should focus in order to achieve a high-quality TMF. The members of this working group belong to the CQAG Group (Clinical Quality Assurance Germany) and are QA (quality assurance) experts (auditors or compliance functions) with long-term experience in the practical handling of TMFs.

Risk_analysis_TMF_publication_20150803Risk_analysis_TMF_publication.odt

Keywords

Quality Risk Management, clinical trial, Trial Master File

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
downloads
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1
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Top 10%
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142
51
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