compromise [Bioanalytics]

posted by Helmut Homepage – Vienna, Austria, 2014-06-19 03:13 (3994 d 03:45 ago) – Posting: # 13089
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Dear Ohlbe,

❝ The reason is usually something like […]



I’m afraid you are very right!

❝ The 50 % in the EMA guideline is probably too high, but with a log placement the MQC gets rather low, and leaves a huge gap between MQC and HQC. With a log placement of calibrators, there is also a huge gap between the HLOQ sample and the one before.


The gap disappears if you start thinking in log-scale (which makes sense, IMHO). Let’s explore the example from above (x = 2–200, n = 10). I would place the LQC at St2 (5.57 = 2.78 × LLOQ) and the HQC maybe between St9 & 10 (170 = 85% of ULOQ). How do two MQCs behave? MQC1 based on the arithmetic mean (101, placed between St8 & 9) and MQC2 based on the geometric mean (20, between St5 & 6). Whereas MQC2 splits the curve in halves (five calibrators below/above), MQC1 is extremely asymmetric (eight below, two above).

❝ It may not be a problem with a linear response, but with a quadratic equation this gap between calibration samples does not help to fit the curve…


There is no gap in calibrators.

❝ (where does it become non-linear ?)


Nowhere; it’s nonlinear in the entire range. Commonly the coefficient of the quadratic term is negative – with increasing concentrations the local slope decreases.

❝ and the QCs may not help to see inaccuracies.


Have to think about it.

❝ Personally I would set the MQC around 1/3 of the ULOQ,…


In my example that would still be a 7/3-split of the curve.

❝ …but I have strictly no data or rationale to defend it.


:-D

❝ In any case there may be a need to adjust the concentration of the QC samples based on the concentrations found in the subject samples after the first few runs, if the calibration range is not optimal.


Good point!

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