Hello to all,
We are validating an HPLC method for related substances of an Active Pharmaceutical Ingredient (API) and we have found that there isn´t a linear relationship between response and the concentration of the analyte at impurity levels. It has been evaluated by visual inspection and using the most common statistycal parameters to do it. Main results of this statistycal analysis are: when we plot signals as a function of the analyte concentration we find that the curve has the potencial tendency and, because that, we don’t have good precision for response factors and the residual graph obtained is a parabolic curve.
I have never found that before, which means that low concentrations have more response than higher concentrations (Note that the lowest concentrations are higher than the Quantitation Limit using the signal-to-noise method to determine it).
In that case, and according to ICH Q2B, test data may need to be subjected to a mathematical transformation prior to the regression analysis. But, what mathematical transformation is needed? Is it normal for a HPLC method for related substances of an API? Does it mean that for the routine analysis the calibration curve must always be carried out prior to the analysis of samples?
I am looking forward to your kind responses. Thank you.