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利用分析方法在新冠疫情期间确保质量——以COVACTA临床研究为例。

Leveraging analytics to assure quality during the Covid-19 pandemic - The COVACTA clinical study example.

作者信息

Ménard Timothé, Bowling Rich, Mehta Pooja, Koneswarakantha Björn, Magruder Eileen

机构信息

F.Hoffmann-La Roche AG, Basel, Switzerland.

Genentech Inc, A Member of the Roche Group, South San Francisco, USA.

出版信息

Contemp Clin Trials Commun. 2020 Dec;20:100662. doi: 10.1016/j.conctc.2020.100662. Epub 2020 Oct 9.

DOI:10.1016/j.conctc.2020.100662
PMID:33073053
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7546713/
Abstract

The world has seen a shift in the ways of working during the Covid-19 pandemic. Routine activities performed at the clinical investigator sites (e.g. on-site audits) that are a part of Quality Assurance (QA) have not been feasible at this time. Analytics has played a huge role in contributing to our continued efforts of ensuring quality during the conduct of a clinical trial. Decisions driven through data, now more than ever, heavily contribute to the efficiency of QA activities. In this report, we share the approach we took to conduct QA activities for the COVACTA study (to treat Covid-19 pneumonia) by leveraging analytics.

摘要

在新冠疫情期间，全球的工作方式发生了转变。作为质量保证（QA）一部分的临床研究机构所开展的常规活动（如现场稽查），目前已无法实施。分析在我们持续努力确保临床试验实施质量方面发挥了巨大作用。如今，基于数据的决策比以往任何时候都更有力地推动了质量保证活动的效率。在本报告中，我们分享了通过利用分析为COVACTA研究（治疗新冠肺炎）开展质量保证活动所采用的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/7562228/00b57e979c8c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/7562228/00b57e979c8c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4723/7562228/00b57e979c8c/gr1.jpg

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本文引用的文献

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Harnessing the Power of Quality Assurance Data: Can We Use Statistical Modeling for Quality Risk Assessment of Clinical Trials?利用质量保证数据的力量：我们能否使用统计建模对临床试验的质量风险进行评估？
Ther Innov Regul Sci. 2020 Sep;54(5):1227-1235. doi: 10.1007/s43441-020-00147-x. Epub 2020 Mar 30.
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