manojbob
☆    

India,
2020-07-03 16:31
(1363 d 18:50 ago)

Posting: # 21643
Views: 2,727
 

 Exclusion of anchor points in LBA [Bioanalytics]

Guidelines do not provide any criterion for acceptance of anchor points and it is understood because these point are not part of valid calibration range. I wish to seek your suggestion on exclusion of anchors. This query is for method validation as well as routine analysis.
SDT-01 is anchor and STD-02 is LLOQ of the curve - given a situation
1) when the OD of STD-01 is equal to or greater than that of STD-02 and all standards of the curve meet acceptance criteria, can we choose to mask the lower anchor since we know that the OD is higher.
2) The STD-02 of the curve does not meet criteria and when the lower anchor is masked the same would fall within criteria. in such case can the lower anchor be masked and can this be termed as improvement in curve fit.
3) The method is validated and established with anchors and during routine analysis If the lower anchor is masked for any reason, then since anchor point is included in regression formula for 4 or 5 PL, would the next point i.e. STD-02 (LLOQ) be considered as new anchor and in such case would the curve be accepted.
ElMaestro
★★★

Denmark,
2020-07-04 13:28
(1362 d 21:52 ago)

@ manojbob
Posting: # 21650
Views: 1,993
 

 Exclusion of anchor points in LBA

Hi Manojbob,


❝ Guidelines do not provide any criterion for acceptance of anchor points and it is understood because these point are not part of valid calibration range. I wish to seek your suggestion on exclusion of anchors. This query is for method validation as well as routine analysis.


I like this question :-) There are plenty of reviews in this area and funnily enough none of them deal well with these aspects.

❝ SDT-01 is anchor and STD-02 is LLOQ of the curve - given a situation

❝ 1) when the OD of STD-01 is equal to or greater than that of STD-02 and all standards of the curve meet acceptance criteria, can we choose to mask the lower anchor since we know that the OD is higher.

❝ 2) The STD-02 of the curve does not meet criteria and when the lower anchor is masked the same would fall within criteria. in such case can the lower anchor be masked and can this be termed as improvement in curve fit.


Excluding an anchor in order to make a calibrator pass. It sounds so wrong, by the principle of it. The assay or method development may not be very good if the need for this solution is present.

❝ 3) The method is validated and established with anchors and during routine analysis If the lower anchor is masked for any reason, then since anchor point is included in regression formula for 4 or 5 PL, would the next point i.e. STD-02 (LLOQ) be considered as new anchor and in such case would the curve be accepted.


In all cases I think it has to be done as per SOP. You can have decision trees that mandate an achor, or mandate none.
Also, think about defining the role of the anchor. Most companies simply use the anchor on the regression curve, this is what you are doing also. However, the alternative is to use the anchors ODs to define the ODmin and ODmax guesses for the optimiser. And this, I think, is a what I would often prefer in the cases I have dealt with. Nevertheless, not all software offers this opportunity, i.e. I don't recall if Watson LIMS (which is what most CROs use for the regression of ligand binding assays, 4PL and 5PL curves) allows the users to set the initial guess of the optimiser as the anchor's reading. Even when an optimiser fails to converge, I assure you, there is a minimum somewhere and if you have very good anchors then ODmin and ODmax are often well reflected there.
Yet, in real life, I am seeing sometimes just a low anchor but no high anchor because the highest calibrator is not anywhere near the ODmax (meaning: EC50/ED50 etc is somewhere close to the highest calibrator); as a result you will have curve fits between runs where the ODmax varies by a factor 20 or something due to variance. Such ODmax's have nothing to do with real life, but the fits anmd backcalculations may still fit the actual points well. It all traces back to the affinities associate with the antibodies, and these affinities can very a lot between batches (notably polyclonal).

All in all, I think you can mask the anchor if your SOPs specifically allows. If you want to mask because it is convenient and gives nicer data then quite possibly it is better to just call the plate off and re-analyse (also SOP driven). Policies for deactivating points on the curve should be defined at the time of method dev. (or SOP dev), not during sample analysis. Real life, however, will very often throw you a curve ball with these LBAs. :crying:

Pass or fail!
ElMaestro
manojbob
☆    

India,
2020-07-06 08:37
(1361 d 02:44 ago)

@ ElMaestro
Posting: # 21652
Views: 1,930
 

 Exclusion of anchor points in LBA

Hi...Thanks for your insight, it was helpful


Edit: Full quote removed. Please delete everything from the text of the original poster which is not necessary in understanding your answer; see also this post #5[Helmut]
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