Robustness/ruggedness

The requirements of the analysis determine the best method. In choosing a method, consideration is given to some or all the following design criteria accuracy, precision, sensitivity, selectivity, robustness, ruggedness, scale of operation, analysis time, availability of equipment, and cost. Each of these criteria is considered in more detail in the following sections. 

Analytical methods, particularly those used by accredited laboratories, have to be validated according to official rules and regulations to characterize objectively their reliability in any special field of application (Wegscheider [1996] EURACHEM/WELAC [1993]). Validation has to control the performance characteristics of analytical procedures (see Chap. 7) such as accuracy, precision, sensitivity, selectivity, specificity, robustness, ruggedness, and limit values (e.g., limit of detection, limit of quantitation). 

Methods can only usefully applied in analytical practice when they are sufficiently robust and therefore insensitive to small variations in method conditions and equipment (replacement of a part), operator skill, environment (temperature, humidity), aging processes (GC- or LC columns, reagents), and sample composition. This demand makes robustness (ruggedness) to an important validation criterion that has to be proved by experimental studies. The concepts of robustness and ruggedness mostly have been described verbally where it must be stated that their use is frequently interchangeably and synonymously (e.g., Hendricks et al. [1996] Kellner et al. [1998] EURACHEM [1998] ICH [1994, 1996] Wunsch [1994] Wildner and Wunsch [1997] Valcarcel [2000] Kateman and Buydens [1993]). 

A qualitative term that covers precision and accuracy as well as robustness (ruggedness). 

Typical performance characteristics that should be considered in the validation are precision, accuracy, limit of detection, limit of quantitation, selectivity, range, linearity, robustness, ruggedness... 

Once the appropriate dissolution conditions have been established, the method should be validated for linearity, accuracy, precision, specificity, and robustness/ruggedness. This section will discuss these parameters only in relation to issues unique to dissolution testing. All dissolution testing must be performed on a calibrated dissolution apparatus meeting the mechanical and system suitability standards specified in the appropriate compendia. 

Before an optimized method can be used in routine analysis, it has to be shown that the method is capable of doing what it is claimed to method validation). Before starting with method validation often a robustness or ruggedness test is performed. In a robustness/ruggedness test (Section 6.6) one evaluates the influence of small variations in the procedure on the performance of the method. These small variations are deliberately introduced and represent variations that could occur when a method... 

Y.V. Heyden, A. Nijhuis, J. Smeyers-Verbeke, B.G.M. Vandeginste, D.L. Massart, Guidance for robustness/ruggedness tests in method validation, J. Pharm. Biomed. Anal. 24 (2001) 723. 

Robustness and ruggedness are two analytical performance characteristics that are related closely, and often not easy to distinguish. The main focus of any robustness/ ruggedness investigation is to address the question of whether the assay will be able to withstand changes in the standard laboratory conditions. The robustness of an... 

For obtaining reliable analysis results, the (high-performance) thin-layer chromatographic (TLC) method should he validated before using it as a quality control tool. The validation parameters that should he evaluated are stability of the analyte, specificity/selectivity, linearity, accuracy, precision, range, detection limit, quantification limit, and robustness/ruggedness. 

The last step ofa method development project should be a check of the ruggedness, if the method imder consideration is not to be used for a single application. This means the capability of a method for routine work. The effort and the tests required depend of course on the actual question. Although robustness/ruggedness are very important issues, they are not topics of this book, and therefore the possible tests are only mentioned in brief... 

Method validation Analytical methods must be shown to give reliable data, free from bias and suitable for the intended use. Most methods are multi-step procedures, and the process of validation generally involves a stepwise approach in which optimized experimental parameters are tested for robustness (ruggedness), that is sensitivity to variations in the conditions, and sources of errors investigated. 

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