Analytical methods ruggedness/robustness

An analytical method is selected on the basis of criteria such as accuracy, precision, sensitivity, selectivity, robustness, ruggedness, the amount of available sample, the amount of analyte in the sam-... 

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). 

The robustness of an analytical method can be defined as a measure of the capability of the method to remain unaffected by small, but deliberate, variations in method parameters. The parameter therefore provides an indication of the method reliability during normal usage. The ruggedness of a method is the degree of reproducibility of test results obtained by the analysis of the same samples under a variety of conditions, such as different laboratories, different analysts, different instruments, different lot of reagents, different days, etc. 

Test methods used in the laboratory are generally derived from pharmacopoeias such as the US Pharmacopoeia, British Pharmacopoeia, or European Pharmacopoeia. For test methods that are not from recognized pharmacopoeias, validation of the analytical methods is required. The validation includes testing for accuracy, specificity, ruggedness, robustness, precision, detection limit, quantitation hmit, and range. A discussion of analytical methods vahda-tion is presented in Section 9.6.5. 

Mulholland, M. (1996). Ruggedness tests for analytical chemistry. In Robustness of Analytical Chemical Methods and Pharmaceutical Technological Products (M. W. B. Hendriks, J. H. de Boer, and A. K. Smilde, Eds), pp. 191-232, Elsevier, Amsterdam. 

The purpose of an analytical method is the deliverance of a qualitative and/or quantitative result with an acceptable uncertainty level. Therefore, theoretically, validation boils down to measuring uncertainty . In practice, method validation is done by evaluating a series of method performance characteristics, such as precision, trueness, selectivity/specificity, linearity, operating range, recovery, LOD, limit of quantification (LOQ), sensitivity, ruggedness/robustness, and applicability. Calibration and traceability have been mentioned also as performance characteristics of a method [2, 4]. To these performance parameters, MU can be added, although MU is a key indicator for both fitness for purpose of a method and constant reliability of analytical results achieved in a laboratory (IQC). MU is a comprehensive parameter covering all sources of error and thus more than method validation alone. 

As is indicated in Figure 8, this process is likely to be an iterative one. However, it is essential that good written records are kept during this phase so that, in the event of problems at subsequent levels, investigations may be more readily carried out. Alas, far too often the excuse of analytical creativity is cited for lack of such records. The most important outcome from this initial evaluation should be an assessment of robustness (or ruggedness) of the developed procedure. The AO AC Guide,Use of statistics to develop and evaluate analytical methods is an excellent source for a discussion of statistical procedures for both inter- and intra-laboratory studies. 

The robustness of an analytical method can be described as the ability to reproduce the method in different laboratories or under different circumstances without the occurrence of unexpected differences in the obtained results. The term ruggedness is considered here as a synonym for robustness. The robustness of a method is tested in a robustness test. The most frequently u.sed definition for robustness in this area is due to the International Conference on Harmonisation of Technical Requirements for the Registration of Pharmaceuticals for Human Use (ICH) [79,80. It defines robustness as follows. The robustness of an analytical procedure is a measure of its capacity to remain unaffected by small, but deliberate variations in method parameters and provides an indication of its reliability during normal usage."... 

The United States Pharmacopoeia (U.S.P.) [5] in a chapter on validation of compendial methods, defines analytical performance parameters (accuracy, precision, specificity, limit of detection, limit of quantitation, linearity and range, ruggedness, and robustness) that are to be used for validating analytical methods. A proposed United States Pharmacopeia (U.S.P.) general chapter on near-infrared spectrophotometry [6] addresses the suitability of instrumentation for use in a particular method through a discussion of operational qualifications and performance verifications. 

Elements in an immunoassay that could impact its robustness include incubation temperatures, light exposure (enzyme-linked immunosorbent assay, ELISA), and different lots of matrix (plasma, serum CSF). The ruggedness of the analytical method can be tested by implementing changes to the analysts, different instruments, batch size, and the day, time, or other environment factors otherwise should not greatly impact the consistency of the assay. 

Ruggedness or robustness of the analytical methods identifies critical assay parameters. Stability of the analyte in samples prior to and after sample preparation, temperature conditions, different lots of reagents, etc. must be investigated to define frame conditions for reliable results. 

Principles and Characteristics Whereas parameters most relevant to method development are considered to be accuracy, system precision, linearity, range, LOD, LOQ, sensitivity and robustness, method validation parameters are mainly bias, specificity, recovery (and stability of the analyte), repeatability, intermediate precision, reproducibility and ruggedness. However, method development and validation are highly related. Also, validation characteristics are not independent they influence each other. Acceptance criteria for validation parameters should be based on the specification limits of the test procedure. Quantitation and detection limits need a statement of the precision at their concentration levels. Procedures used for validation of qualitative methods are generally less involved than those for quantitative analytical methods. According to Riley [82], who has discussed the various parameters for validation of quantitative analytical methods, the primary statistical parameters that validate an analytical method are accuracy and precision. 

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. 

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]). 

Consequently, it was proposed to define (Burns et al. [2005]) Robustness of an analytical procedure is the property that indicates insensitivity against changes of known operational parameters on the results of the method and hence its suitability for its defined purpose and Ruggedness of an analytical procedure is the property that indicates insensitivity against changes of known operational variables and in addition any variations (not discovered in intra-laboratory experiments) which may be revealed by inter-laboratory studies (Burns et al. [2005]). 

For non-compendial procedures, the performance parameters that should be determined in validation studies include specificity/selectivity, linearity, accuracy, precision (repeatability and intermediate precision), detection limit (DL), quantitation limit (QL), range, ruggedness, and robustness [6]. Other method validation information, such as the stability of analytical sample preparations, degradation/ stress studies, legible reproductions of representative instrumental output, identification and characterization of possible impurities, should be included [7], The parameters that are required to be validated depend on the type of analyses, so therefore different test methods require different validation schemes. 

A review of ruggedness testing methods is presented in Chapter 3 and in Chapter 5 examples are given. In these chapters procedures are described that test the robustness or ruggedness of existing methods. Hence, incorporating robustness explicitly in analytical techniques (see Section 1.1) is not discussed. 

This review describes the determination of robustness and ruggedness in analytical chemistry. The terms ruggedness and robustness as used in method validation are sometimes considered to be equivalent [1,2], In other publications a difference is made between the two terms [3]. In the following only the term ruggedness will be used. 

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