VALIDATION OF INTERNAL NORMALIZATION FOR IMPURITY ASSAYS

Abstract

The simplicity of the internal normalization made it a very attractive method. Yet, because of its restrictive applicability requirements, internal normalization is not widely implemented in HPLC quantitative analysis. Basically, applicability requirements are that all the solutes must not only be eluted and detected but must also present similar behavior toward the detection system. Ideally, response factors should be identical for all the solutes or, in practice, of the same order of magnitude. The methodology developed to validate, in a rigorous way, internal normalization was based on the use of a statistical tool called analysis of covariance (ANACOVA). ANACOVA is more or less similar to ANOVA but can manage a continuous variable, like for example, concentration. So, it is possible to use it to compare calibration curves of all the different solutes present in a sample, for example, the main product and its impurity. After having checked that for the main product the response factor was the same around the target concentration of the HPLC method, and at low concentration, it was then possible to make comparison with impurity behavior, and to determine whether the use of the response factor was necessary or not. Eventually, ANACOVA enabled the validation of internal normalization by assessing that all the solutes presented required behavior. This methodology was successfully applied to an actual example of liquid chromatography quantitative analysis, taken from the pharmaceutical industry. In this case, internal normalization for impurity assays of an anticytomegalovirus drug substance was validated after response factor correction.

Acknowledgments