Sample handling between despatch and injection Writing it up because I had to work it out twice and would rather nobody else did.
Trying to work out what would count as evidence on sample handling between despatch, before collecting any. This is the part I usually skip and it is the part that makes the rest useful.
If two explanations predict the same observation, observing it does not help. So: what observation would separate them?
Why two laboratories may disagree: after validating the same method, they may still report different purity on the same sample due to integration differences, column age differences, subtle differences in mobile phase pH or temperature. This is normal and not a sign that one is wrong.
Sample stability during analysis is part of validation and is routinely ignored. A preparation that degrades in the autosampler over eight hours produces a sequence-dependent result.
If it helps: the failure mode here is usually boring rather than dramatic.
Seconded. It reads as careful rather than confident, which is the right register.
Clear enough that I do not think I have a follow-up, which is unusual.
I read post #6 twice before replying, because I had assumed the opposite.
A note on how sample handling between despatch gets discussed rather than on sample handling between despatch itself: the confident posts get the replies and the careful ones get ignored, and the careful ones have been right more often.
This follows post #6 rather than contradicting it.
System suitability is the ongoing evidence that a validated method is still performing. Validation is done once; suitability is done every run, and it is the one that appears on a certificate.
Same conclusion as the reply above, reached differently, which is mildly reassuring.
Something worth flagging about sample handling between despatch: the strongest-sounding claims in this thread are the ones with no source attached, which is the usual pattern and not a coincidence.
The most useful single question about a method: what would it fail to detect? Every method has an answer and few documents state it.
Reporting the observation and leaving the explanation open deliberately.
Post #10 is right about the mechanism and I think understates the practical bit.
Sample handling between despatch is well covered in the tag pages, and the older discussions are better than the recent ones because they were argued out properly. Worth twenty minutes before adding to this one.
The reason sample handling between despatch keeps being re-asked is that the answer is conditional and people quote it without the condition. It is not that the answer is unknown.
The limit of quantitation determines what the impurity table can honestly contain. Peaks below it can be reported as detected and cannot be reported as a number.
Post #13 answers the question as asked. The question underneath it is different.
Linearity across the working range is a routine demonstration and it constrains how far a result can be extrapolated. A method linear from 80 to 120 per cent of nominal says nothing about a sample at ten per cent.
On reflection I would soften that slightly.
On post #12 — agreed on the reasoning, with one qualification.
My experience of sample handling between despatch contradicts the reply above. I am posting it as a data point rather than as a refutation, because one person's experience is exactly that.
Sensible. I would want the same detail before I acted on it either.
Where a pharmacopoeial monograph exists, a method that follows it inherits a great deal of assurance. Almost nothing discussed here has one.
System suitability is the ongoing evidence that a validated method is still performing. Validation is done once; suitability is done every run, and it is the one that appears on a certificate.
Worth separating two things that post #16 runs together.
Transfer between laboratories: a method can be transferred from one lab to another, but the receiving lab needs to demonstrate that they can achieve the same performance. This requires comparative testing and sometimes small method refinements.
Small correction to my own earlier position on sample handling between despatch. I had the units the wrong way round, which changes the conclusion by an order of magnitude and therefore changes it entirely.
Noted, and thank you for writing it out rather than summarising it.
Coming back to post #21, because the follow-up matters more than the original answer.
I would put moderate confidence on the mainstream reading of sample handling between despatch and no more. That is not scepticism for its own sake; it is where the sourcing actually stops.
The most useful single question about a method: what would it fail to detect? Every method has an answer and few documents state it.
The answer changed when I changed how I was measuring, which was informative.
Worth separating two things that post #21 runs together.
Adding the boring version of sample handling between despatch, because the interesting version keeps getting posted and the boring one is usually right.
Check the ordinary explanations, in order, and stop when one of them accounts for what you are seeing. Most of the time the second one does.
Post #25 is right about the mechanism and I think understates the practical bit.
Before the thread moves on from sample handling between despatch — what is the sample size behind the claim? I am not being difficult; I have seen the same figure quoted from an n of four and from an n of four hundred.
Adding a note of thanks rather than an opinion. I did not know most of that.
The limit of quantitation determines what the impurity table can honestly contain. Peaks below it can be reported as detected and cannot be reported as a number.
I would be glad to be shown a cleaner way of putting this.
Reading back through the sample handling between despatch threads from last year, the same three questions come up every time and only one of them has ever been answered properly. That seems like a documentation gap rather than a knowledge gap.