Analytical chemistry, specifically electroanalytical chemistry, plays an important role in many branches of chemistry, biochemistry, pharmacy, food productions, life science, environment, etc. Many decisions are based on the results of quantitative analyses, and it is important to be aware of the quality of the results whenever analytical or electroanalytical methods are used. Analytical properties are quality indicators for a variety of systems, objects, tools, and outputs involved in chemical or biochemical measurements that allow one to compare and validate both analytical processes and the results that they provide. The objective of any analytical measurements is to obtain consistent, reliable, and accurate data. Validated analytical methods play a major role in achieving this goal. Analytical method validation is a major issue in the pharmaceutical industry for controlling drug quality, development, and registration. Simply, it is used to justify the analytical method used, in other words, to show that the method accomplishes what is claimed or intended. Validation is required for the development of new analytical methods, methods submitted as a part of a new drug application, bioequivalence and bioavailability studies, and for the analysis of drugs as raw material or in their dosage forms. Likewise, all laboratory tests must be validated before being introduced for patient testing to insure that the values reported will meet clinical expectations with a desired degree of reliability. Revalidation should be required, to a less or greater degree, following any change in reagents, supporting electrolytes, instruments, or experimental conditions. Evaluation and validation of an electroanalytical method performance is required to assess the degree of error expected due to inaccuracy and imprecision and to confirm that the degree of error meets the anticipated laboratory or clinical requirements. The procedures recommended for method validation differ with the type of test and the anticipated use. Experiments must be designed so that the correct data are obtained. The appropriate statistical methodologies should be used to correctly estimate errors with sufficient precision and to make the right decision about method’s validity.
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