Validation of Analytical Procedures: Graphic and Calculated Criteria for Assessment of Methods Linearity in Practice
Introduction. «Linearity» is one of the required characteristics when validating analytical procedures. The issues of the validation of linearity procedures are still relevant.Aim. To consider the main graphical and calculated criteria for confirmation of the linearity of analytical procedures and t...
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Format: | Article |
Language: | Russian |
Published: |
LLC Center of Pharmaceutical Analytics (LLC «CPHA»)
2019-05-01
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Series: | Разработка и регистрация лекарственных средств |
Subjects: | |
Online Access: | https://www.pharmjournal.ru/jour/article/view/692 |
Summary: | Introduction. «Linearity» is one of the required characteristics when validating analytical procedures. The issues of the validation of linearity procedures are still relevant.Aim. To consider the main graphical and calculated criteria for confirmation of the linearity of analytical procedures and their restrictions, as well as to give recommendations.Materials and methods. Statistical calculations were performed using MS Excel. Experimental data were obtained by HPLC.Results and discussion. The main criteria for proving/confirming the linearity of analytical procedures and their restrictions are considered in detail. It is shown that these criteria cannot always give a reliable assessment of the linearity of the procedure, the possible reasons for this are indicated and recommendations are given.Conclusion. When validating the procedures, it is necessary to prove/confirm their linearity by using two, and, more reliably, three criteria, one of which must be the linearity of the plot of measured response (Y) vs concentration of the tested substance (C). On the other hand, we demonstrate here that a formal approach should not be used for the estimation of non-linearity of the procedure when using graphical and calculation criteria based on mathematical statistics, since they do not take into account the possibility of practical insignificance of small deviations from the linear dependence of Y on C. |
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ISSN: | 2305-2066 2658-5049 |