Bioequivalence and Bioavailability Forum

Dear DLabes!

❝ … thats the question (Hamlet).

❝ But I have seen almost always constant decimal places (mostly 2-3) in the result from analysts.

Yes, it’s a pity.

❝ May be this is because they all use M$-EXCEL .

Agree, but even for them help is on the way.
In cell A1: original value (to 15 significant figures, if they like)
In cell B1: =IF(A1>1000,ROUND(A1/10,0)*10, IF(A1>100,ROUND(A1,0), IF(A1>10,ROUND(A1,1), IF(A1>1,ROUND(A1,2),ROUND(A1,3)))))
Custom format of column B: 0.???
… will handle values between 0.1 and 10000.

❝ Have you convinced your analysts in using significant digits?

Since I’ve worked as an analyst myself for quite a long time, mainly I succeeded, because I speak the same language.

❝ Or is the discrepancy to the analytical report not an issue?

Yes it is. As a precaution I describe the procedure in the SAP – which is submitted to the EC and the competent authority beforehand. I never experienced any problems. But still I try to avoid such situations and talk to the analysts…

❝ ❝ For many analytical methods even rounding to two significant

❝ ❝ digits would be sufficient – but I would guess everybody would

❝ ❝ start screaming then …

❝ Thats a pity, but "The customer is king".

Yes, but I would say it’s also part of our job to do some education. Otherwise

Rubbish in, rubbish out!

applies.

❝ ❝ I do rounding of analytical data to three significant figures …

❝ Am I right in assuming that you use the rounded values for further processing (PK analysis)?

Exactly.

❝ What about 3 significant digits if LLOQ is given by the analyst with 2 decimals but only 2 significant digits (f.i. 0.88 nano/whatever)?

I can only use the data I get. Three significant figures actually are too high for many analytical methods anyway. If the LLOQ is given with 0.88 I keep it as it is.
As said in my previous post 0.88 implies everything between 0.875 and 0.884, or ~±0.5%, which is just ridiculous. I would prefer 0.9 (1 significant figure = ~±5%)

❝ ❝ C_max… three significant figures; AUC as an integrated

❝ ❝ parameter to four significant figures …

❝ AUC (roughly spoken summed conc. multiplied by time ...) gains precision in comparision to Cmax? I had expected the contrary.

If I look at AUC as an integrated function, most (if actual rather than scheduled sampling times are used – all) the error is contributed by the concentrations. I expected some kind of dampening effect – but to be honest I never checked it before. According to the propagation of errors the muliplication of two erroneous values leads to an addition of errors.
If we assume no error in sampling times, AUC should be given to the same degree of precision as concentrations.
I will modify my SOP, thanks!

❝ Again the question: Rounded values for further processing (statistical analysis of bioequivalence) ?

Yes.