What is the difference between OOS / OOE / OOT?
OOS/OOE/OOT有什么不同？
The terms OOS, OOE and OOT always emerge in connection with the handling of deviating analysis results. But what are their definitions?
術(shù)語(yǔ)OOS、OOE和OOT都是處理分析結果偏差中的概念，那他們的定義是什么呢？
For some time, ECA's Quality Control Working Group has published a SOP on the handling of OOS results and is currently planning the elaboration of a SOP on OOE and OOT. The OOS SOP respectively the draft of the OOT SOP contains the following definitions for the three terms:
ECA的質(zhì)量控制工作組曾經(jīng)公布過(guò)一份關(guān)于處理OOS結果的SOP，目前他們正在計劃起草一份關(guān)于OOE和OOT的SOP。OOT的SOP草案中包括了對三個(gè)術(shù)語(yǔ)的以下定義：
Out-of-Specification (OOS) Results 超標結果（OOS）
A result that falls outside established acceptance criteria which have been established in official compendia and/or by company documentation.
結果超出了由官方藥典和/或公司文件既定的可接受標準。
Out-of-Expectation (OOE) Results 超期望結果（OOE）
An atypical, aberrant or anomalous result within a series of results obtained over a short period of time is an OOE result. An OOE result is a result that meets specifications, but is outside the expected variability of the analytical procedure.
在一個(gè)短時(shí)期內得到的一系列結果中的一個(gè)非典型、異常結果。一個(gè)OOE結果符合質(zhì)量標準，但超出檢驗方法所期望的變動(dòng)范圍。
Out of Trend (OOT) Results 超趨勢結果（OOT）
A time dependent result which falls outside a prediction interval or fails a statistical process control criterion.
與時(shí)間相關(guān)的結果，它超出預期的間隔或未能符合統計學(xué)控制標準。
A trend is a sequence of temporal procedures, e.g. for the manufacture of different batches of a product. There are two types of trends:
趨勢是一個(gè)隨時(shí)間而變化的序列，例如，不同批次產(chǎn)品的生產(chǎn)。趨勢有兩種類(lèi)型：
In one case, no trend is expected, e.g. in production or when analysing process data where everyone expects that they are under statistical control.
一種情況，不期望產(chǎn)生一種趨勢，例如，在生產(chǎn)過(guò)程中或分析過(guò)程中，每個(gè)人都期望這些數據在統計學(xué)控制范圍內。
In the other case, a trend is expected. One typical example for that is stability testing where one expects that the content of the API reduces over the storage period, or that the quantity of impurities increases over time.
另一種情況，預期有一種趨勢。一個(gè)典型的例子是穩定性研究中，會(huì )預期原料藥的含量隨著(zhù)存貯時(shí)間延長(cháng)而降低，或雜質(zhì)會(huì )隨時(shí)間延長(cháng)而增加。
There is a fundamental difference between these two types of OOT results: indeed, in the second situation the dispersion increases over time.
這兩類(lèi)OOT結果之間有根本的差異，事實(shí)上，第二種情形下數據的離散度隨時(shí)間而增加。
The new Chapter 5 of the EU GMP Guide - coming into force on 1st October 2014 - requires that in future certain data have to be recorded so that trends can be recognized and assessed.
在EU GMP指南的第5章中（將于2014年10月1日生效），要求將來(lái)對特定的數據進(jìn)行記錄，這樣可以發(fā)現其趨勢并進(jìn)行評估。
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