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GMP偏差調(diào)查中常見8大錯誤

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Do You Make These 8 Big Mistakes In Your Deviation Investigations?

偏差調(diào)查中常見8大錯誤

 

By James Blackwell, Ph.D., The Windshire Group, LLC

Deviation investigations are one of the most important quality activities in any GMP(good manufacturing practice) organization. They are also perennially near the top of the list of most frequently cited issues in observations, warning letters, and consent decrees from the U.S. Food and Drug Administration (FDA)and other regulatory authorities. (“There is a failure to thoroughly review [any unexplained discrepancy][the failure of a batch or any of its components to meet any of its specifications] whether or not the batch has been already distributed.”)

偏差調(diào)查是任何GMP組織中最重要的質(zhì)量活動之一。在FDA和其他監(jiān)管機(jī)構(gòu)發(fā)布的缺陷、警告信和同意令中,它們也一直處于最常被引用的問題列表的首要位置。(“未能*審核[任何無法解釋的差異][批次或其任何組分不符合質(zhì)量,無論批次是否已經(jīng)銷售]。”)

Clearly,many organizations have room to improve in the writing and managing of deviation investigations. The following sections identify common missteps companies make when conducting deviation investigations — and how you can avoid them.

顯然,許多組織在偏差調(diào)查的編寫和管理方面仍有改進(jìn)的余地。以下幾節(jié)列出了公司在進(jìn)行偏差調(diào)查時所犯的常見錯誤以及如何避免這些錯誤。

1.Not leveraging historical data for continuous improvement

1.未利用歷史數(shù)據(jù)進(jìn)行持續(xù)改進(jìn)

The information gathered over time through investigations contains a wealth of data that can be used for continuous improvement, increasing productivity, and reducing the recurrence of investigations. Unfortunately, many organizations only review this data once a year and in a somewhat perfunctory manner. A good trending process is an important element in monitoring and proactively responding to developing issues. Tracking investigation data (root cause, functional group, unit operation) will aid in continuous monitoring of the types of events and root causes occurring in your facility by product, process area, and functional group, among others. Develop a list of standard event categories and actionable root causes in order to trend deviation and investigation data. This list can be upwards of 200 or more and can aid investigators in writing their root cause in actionable terms.

 

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