An example of IS response. Need your helps. [Bioanalytics]

posted by Ohlbe – France, 2020-05-26 19:46 (1421 d 22:03 ago) – Posting: # 21480
Views: 8,171

Dear Sukalpa,

❝ There might be many reasons behind the enhancement of the response of IS,

❝ 1. System may not stabilized while submitting the batch.

❝ 2. May be column is not saturated enough.

❝ 3. May be the category of the molecule require more stability runs to stabilize. etc.

Could be, though not very likely if this is the only affected run amongst many others, and as the gradual increase is only seen after 100 injections (I would have agreed with you if after 20-30 injections, and stabilising afterwards at a new level).

❝ But there is always a possibility to investigate the reason of the enhancement of the response of IS.

Absolutely, and like Shuanghe, I would have liked to see it done here.

❝ But possibilities of the change in concentrations are less, because we determine concentrations based on the area ratio.

Yes. And this triggers several questions: are the analyte and the IS affected in the same proportion, at all levels of concentration (in which case the accuracy will be maintained), or not ? Is there a risk of detector saturation, due to the increased response ? What about ion suppression of the analyte by the IS and vice-versa ? What about the linearity of the response and of the calibration curve ?

❝ Looking at the data, I think the response of IS and analyte increased proportionally as the QC samples are passed resulting a successful analytical run.

Well, Shuanghe had not provided this information yet when you posted this message. All we knew was that the run passed, meaning that at least 67% of the QCs passed, including 50% at each level of concentration. Looking at the number of QCs and how they are spread over the run, all QCs in the affected region could have failed and the run would have remained acceptable. What made you say that the analyte increased proportionally ?

Such variations in IS can be perfectly fine, without any influence on the reliability of the data. In other cases, they can ruin your results, even with a stable isotope labelled IS. You don't know until you understand what's going on, or until you demonstrate there is no impact.


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