这个应该是针对于125%ARL,100%ARL，50%ARL这类前三个浓度的RSD有规定不超过一定的限度值（比如15%）吧！针对于更小浓度比如10%ARL，5%ARL浓度的RSD应该没有规定吧！比如很小浓度的擦拭取样，很可能会存在精确度很差，RSD会很大的问题。至于该RSD指的另一个作用在于选择相关的不同浓度下的取样回收率以用于确定最终取样回收率？？是不是这个意思呢？
这个RSD是针对于每一个浓度内的相对标准偏差，还是针对于几个系列浓度的相对标准偏差，还是针对于这两个的相对标准偏差呢？？？如图中
http://www.pharmtech.com/best-practices-cleaning-validation-swab-recovery-studies?pageID=1
The recommended strategy is to perform triplicate recoveries at the four levels noted above. An example of a recovery data set is shown in Table I. The recoveries at the three higher levels should be at least 70% and should agree within a %RSD of 15%. If the average recoveries are <70% or >105%, an investigation should attempt to optimize the recoveries. If the recovery at the LOQ agrees with the other three, then the range is extended. If the recovery at the LOQ does not agree with the other three, then the limitations of the accuracy at low levels is known, the risk of which decreases the further the ARL is from the LOQ of the test method. Recovery factor determinationThe recovery factor is determined from the recovery data generated from the spiked
coupons. There should be at least nine data points from three different spike levels. The data for the three levels can be averaged to determine the recovery factor. Recovery data can be somewhat variable; therefore, a variability limit is also used. Typically, a %RSD of <15% is considered acceptable variability, although experienced personnel can perform recoveries at <10% RSD. If data for additional spike levels are generated, all data in the recovery average should be included. If the variability of the data exceeds the 15% variability parameter at lower levels, they should not be included in the average for the recovery factor. This approach will not impact the resulting cleaning data. For example, a swab result of 0.1 µg/swab will not change for recovery factors between 50-100%. The importance of the accuracy of the data near the LOQ of the method is inversely proportional to the importance as the accuracy of the data near the ARL based on the difference between the two levels. A seemingly conservative approach is to use the single lowest recovery as the recovery factor. Scientifically and statistically, this approach does not make sense. Scientifically, using this approach would cause samples near the ARL to fail cleaning when in fact they pass. Statistically, the single lowest recovery is not representative because it ignores the majority of the recovery data. Qualification of personnel is also compromised when tested by? a lower recovery factor. The potential damage caused by this approach increases the further the lowest value is from the average. The recommended approach is to use the average of the recovery data set as the recovery factor for all cleaning samples. | 
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发表于 2016-12-16 09:38:37
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