Principles of Analytical Validation

Analytical validation can be defined as the collection and evaluation of data generated from the process/method used in making a product whether it is commercial, experimental or a scientific study. Analytical validation establishes experimental evidence that a process/method/study consistently delivers reproducible, precise and accurate results using established and accepted methodology. Analytical validation consists of multiple steps and starts with a validation master plan. A validation master plan has broad scope and will contain more elements with higher stringency for validation of a commercial product than one for validation of results of an experiment that is aimed at publication. A validation master plan, although not absolutely necessary in a laboratory experimental setting, is very helpful for downstream discovery data presentation and should clarify general objectives, procedures and protocols and prioritize validation steps. It should include a description of the equipment to be used with specific parameters such as dynamic range of signal measurement, volumes of samples to be measured, etc. Although not every laboratory validation procedure requires all these principles, all should be considered while planning the validation process. They are specificity, linearity robustness, range, detection limit, quantitation limit, ruggedness, selectivity and sustainability. Here we discuss those that are important in validation of liquid chromatography, a technique that is an integral part of every proteomics study.