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Mithu
Junior

India,
2018-08-08 10:09

Posting: # 19160
Views: 681
 

 Repeat based on ISR data investigation [Bioanalytics]

Dear Members,

kindly share your thoughts on Repeat analysis based on the ISR data. During ISR sometimes we found that all the selected samples from any specific subject get failed to meet the acceptance criteria and failing with the huge margin with some specific trend i.e. positive or negative.

In such cases, scientists use to go for the investigation and run same samples of ISR again to find out the reason for the failure. During investigation they get the same values which they had got at the time of ISR analysis and not matching with the initial analysis.

Based on this they conclude error in the first/ initial analysis and they reject the original batch which was otherwise technically passing the batch acceptance criteria.

After going for repeat analysis of whole batch sometimes may change the outcome of the study when study passes or fails on border.

If the study gets failed then it would be a problem for a filer and if we ignore result of the ISR from which the investigation is triggered then expecting that some day agency may ask for root cause for the failure in ISR and doubt on the initial analysis.

please share with us your experience or any suggestion to handle such situations.

Regards,

Mithu
Ohlbe
Hero

France,
2018-08-20 18:42

@ Mithu
Posting: # 19188
Views: 426
 

 Repeat based on ISR data investigation

Dear Mithu,

» During ISR sometimes we found that all the selected samples from any specific subject get failed to meet the acceptance criteria and failing with the huge margin with some specific trend i.e. positive or negative.

Excellent: you are looking at individual data, not just "67 % of my samples are within 20 % so ISR pass, so why bother".

» In such cases, scientists use to go for the investigation and run same samples of ISR again to find out the reason for the failure.

OK so far.

» During investigation they get the same values which they had got at the time of ISR analysis and not matching with the initial analysis.

Yes, it can happen.

» Based on this they conclude error in the first/ initial analysis and they reject the original batch which was otherwise technically passing the batch acceptance criteria.

That's where I disagree. If your initial run was passing (CC and QC were fine) but the results are not reproducible, then you have a serious problem, and you can't just say there was an "error". Actually, you may precisely have the type of problems that the ISR experiment was implemented to detect.

You have identified a problem that seems to affect all samples from one or several subjects. You can re-analyse the samples of those subjects. But if you don't know what happened, you can't prove that individual samples of other subjects, not re-analysed for ISR, were not affected too. Actually you may have to re-analyse all samples in your study, possibly after modifying and re-validating your method !

» If the study gets failed then it would be a problem for a filer and if we ignore result of the ISR from which the investigation is triggered then expecting that some day agency may ask for root cause for the failure in ISR and doubt on the initial analysis.

Oh yes, they would not hesitate to challenge the whole study.

» please share with us your experience or any suggestion to handle such situations.

Bioanalysis published a special issue on ISR back in 2011. Some of the papers could help you. Have a look for instance at the review from Manish Yadav and Pranav Shrivastav and at the paper by Aimin Tan et al. They are providing some examples that may give you some ideas.

Regards
Ohlbe
ElMaestro
Hero

Denmark,
2018-08-21 11:32
(edited by ElMaestro on 2018-08-21 14:17)

@ Mithu
Posting: # 19190
Views: 381
 

 Repeat based on ISR data investigation

Hello Mithu,

» kindly share your thoughts on Repeat analysis based on the ISR data. During ISR sometimes we found that all the selected samples from any specific subject get failed to meet the acceptance criteria and failing with the huge margin with some specific trend i.e. positive or negative.

"All samples" means what?
Usually for ISR you only have a few from a subject period.

Come to BioBridges in Prague next month and someone may mention something having a wee bit of remote resemblance to your situation.

» In such cases, scientists use to go for the investigation and run same samples of ISR again to find out the reason for the failure. During investigation they get the same values which they had got at the time of ISR analysis and not matching with the initial analysis.

Be careful. If you are submitting to FDA then be aware that some of their regulators take the guidance very literally. The guidance says no repeats without a root cause, meaning that you do not repeat a sample as part of an investigation. You only repeat a sample if the investigation has given you a root cause (I am not in favour of the literal interpretation of the FDA guidance, but that aspect is entirely is in the hands of powerful people. I am aware of a few EU regulators who are or were enforcing the same policy).

» Based on this they conclude error in the first/ initial analysis and they reject the original batch which was otherwise technically passing the batch acceptance criteria.

If there is a root cause, sounds fair. But if they reject original the batch on basis of the outcome of the repeat only, then it may get tricky.
Some CROs or labs have some very elaborate SOPs with all sorts of funky decision trees allowing e.g. N repeats and if the median or mean or something is more than X % from the original then the reported value is so-and-so and blahblah. This gets regularly questioned by inspectors. Much safer is to report the original unless you have a root cause which in turn isn't founded in the set of repeat values.
Someone hammering your API5000 with a baseball bat and your detector going bat shit crazy, that's a root cause justifying a repeat with reporting of the repeat. A deviation of whatever%
from the original value isn't in itself guaranteed to be a root cause that merits reporting of the repeat, even if the deviation is 250% and verified with a tripple repeat.

if (3) 4

Best regards,
ElMaestro

"(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures." New York Times (ed.), June 9, 2018.
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