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The different European and American (FDA) regulations related to Good Laboratory Practices (GLP) and to Good Clinical Practices (GCP) recommend that analytical data from studies intended to be included in NDAs have to meet some acceptance criteria. As a consequence, assay methods have to be validated and routinely performed analysis must be checked according to a quality control system.

Available documents defining validation criteria that must be checked during an analytical procedure development are not precise enough (1-4).(Very ?) and they are usually restricted to general concepts and they do not provide any experimental approach. In order to help Drug Industry professionals to validate their analytical procedures a specialized commission from SFSTP established a validation guide in 1992 (5).

With only few exceptions (6, 7), the situation is rather similar in the field of bioanalysis. Available documents whichhave contributed to significant progress occurred in the validation of analytical methods in biological matrices (8, 15, 20). However, these are too general and do not provide any validation strategy. Indeed, the validation work performed in bioanalysis depends mainly on the analyst's experience, on his personal point of view and on the laboratory strategy (16). Consequently, another SFSTP commission was created to design a validation guide for bioanalysis.

The following document is an industrial consensus on both experimental and statistical points of view and the recommended strategy allows the analyst to make experimental work as profitable as possible. This is achieved by obtaining maximum information from the results and then in routine use by reducing the reanalysis risk due to a lack of agreement to the validation criteria.

The following strategy is mainly designed for chromatographic methods, but it can validly be applied to other bioanalytical techniques (capillary electrophoresis, colorimetry, atomic absorption, ...). Moreover, even though it was originally designed for pharmaceutical applications, it can reasonably be applied to other fields with similar specifications (environment, food-products, etc.).


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