In building a research career, especially in the hard sciences and engineering-related fields, before actual research can be conducted, a strategy is needed for data collection, and this strategy forms the research methods. This is important to ensure that the results obtained are repeatable, reproducible, and can be validated using standard methods. Since most research involves some form of analytical method, most of it ultimately relies on collecting usable and valid analytical data.
Analytical Method Validation
Analytical method validation （AMV） is the process of coming up with a final, optimized method that meets the standard requirements of a universally accepted organization. AMV considers many criteria like repeatability, reproducibility, robustness, ruggedness, system suitability, limits of detection, and limits of quantitation, and can vary across industries and research fields.
Several organizations exist that provide criteria to determine what is a validated method, and numerous books, journals, review papers, magazines, and websites are devoted to discussions on AMV. Typically, the resources that guide AMV tend to focus on pharmaceutical fields. However, AMV can guide research in every field unofficially. Indeed, researchers should be aware of these basic, fundamental guidelines in order to conduct an AMV of their own methods before submitting a manuscript to a journal, even if scientific journals don’t strictly require them for manuscript submissions.
Here are a few of the basic guidelines for conducting AMV by The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use （ICH）.
1. Repeatability and reproducibility