An experimental design can be considered as a series of experiments that, in general, are defined a priori and allow the influence of a predefined number of factors in a predefined number of experiments to be evaluated.

Screening for important factors during method optimization or in robustness testing involves two-level screening designs, such as fractional factorial and Plackett–Burman designs, as described in Part 1. This second part on screening designs discusses the experimental protocol for executing these designs and the data analysis of their results.

Screening designs are used to screen for important factors during method optimization or in robustness testing. Usually, two-level screening designs, such as fractional factorial and Plackett–Burman designs, are applied. This column discusses the properties of these designs.

Calibration refers to the process of determining the relation between the output (or response or signal) of a measuring instrument and the value of the input quantity or property. Depending on the univariate or multivariate character of the response (signal) used; either a univariate or a multivariate calibration is performed. The different calibration approaches are summarized in this article.

In a good laboratory practice (GLP) environment, data-handling software cannot be used until it is validated. This even applies to the most simple program that performs calculations or stores data. A detailed documentation of the set-up and the performance of the software — called software validation — is required. The development and validation requirements are described in this article and illustrated with a software for robustness testing (SRT), which guides the user step-by-step through the experimental set-up and interpretation of robustness tests. This software was developed in an Excel (Windows XP) environment and is used as part of method validation in laboratories that require compliance with GLP and 21 CFR Part 11. The software was subjected to software validation regulations and is compliant with electronic records and signature rules (21 CFR Part 11) as it creates, delivers and stores electronic data. The validation tests are based on the computerized system validation (CSV) —..

The robustness/ruggedness of an analytical procedure is a measure of its capacity to remain unaffected by small but deliberate variations in method parameters.

It would help to have a restricted set of chromatographic systems (CS) that together serve as potential starting points in method development.

Analytical chemists are concerned with the quality of their methods and results. An important question in this context is whether the precision of a newly developed and validated method is up to standard. In other words: is the precision of the newly developed method comparable to what could be expected? This article looks at how the Horwitz equation can answer this. It also describes the results of an extensive study involving 10000 laboratories which indicates that the relative reproducibility approximately doubles for every 100-fold decrease in concentration and that, surprisingly, it does not depend on the type of material or method.

The sample size is determined by three factors: the size of the difference between the means that should be detected, the precision of the methods being compared and the significance levels at which the test is performed.