Robustness of an analytical method

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. 

The robustness of an analytical method is a measure of the method s capacity to remain unaffected by small, but deliberate, variations in method parameters, and it provides an indication of the method s reliability during normal use. 

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."... 

Investigation of factors on an analytical signal for judging the robustness of an analytical method or to test for interferences. 

The relative method standard deviation is a suitable evaluation criterion for the robustness of an analytical method that requires calibration. If it stays constant, the method is robust for the evaluated period of time. 

Verification implies that the laboratory investigates trueness and precision in particular. Elements which should be included in a full validation of an analytical method are specificity, calibration curve, precision between laboratories and/or precision within laboratories, trueness, measuring range, LOD, LOQ, robustness and sensitivity. The numbers of analyses required by the NMKL standard and the criteria for the adoption of quantitative methods are summarized in Table 10. 

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]). 

Relative robustness will have values between 0 (no robustness) and 1 (ideal robustness). Burns et al. [2005] defines the relative robustness of an analytical procedure as the ratio of the ideal signal for an uninfluenced method compared to the signal for a method subject to known operational parameters determined in an intra-laboratory experiment (Burns et al. [2005]). 

In biomedical and pharmaceutical analysis, and particularly in the pharmaceutical industry, much attention is paid to the quality of the obtained analytical results because of the strict regulations set by regulatory bodies. Proper method validation demonstrates the fit of an analytical method for a given purpose. In this context, robustness testing has become increasingly important. 

Titrimetric methods are still widely used in pharmaceutical analysis because of their robustness, cheapness and capability for high precision. The only requirement of an analytical method that they lack is specificity. This chapter covers the theoretical basis of most of the commonly used methods the practical aspects of titrations have been covered thoroughly by other textbooks. 

Robustness of an analytical procedure is a measure of the analytical method to remain unaffected by small but deliberate variations in method parameters and provides an indication of its reliability during normal usage. 

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. 

Method validation covers a number of aspects of an analytical method that have already been evaluated in the course of development and use. The values of the calibration parameters must be known to use the method to analyze a particular sample, and any serious deviations from the measurement model should have been discovered. In addition, however, every method should undergo a robustness study as the practicality of the method may ultimately depend on how rugged it is. 

The robustness of an analytical procedure is a measure of its capacity to remain unaffected by small but deliberate variations in the analytical procedure parameters. The robustness of the analytical procedure provides an indication of its reliability during normal use. The evaluation of robustness should be considered during development of the analytical procedure. If measurements are susceptible to variations in analytical conditions, the analytical conditions should be suitably controlled or a precautionary statement should be included in the procedure. For example, if the resolution of a critical pair of peaks was very sensitive to the percentage of organic composition in the mobile phase, that observation would have been observed during method development and should be stressed in the procedure. Common variations that are investigated for robustness include filter effect, stability of analytical solutions, extraction time during sample preparation, pH variations in the mobile-phase composition, variations in mobile-phase composition, columns, temperature effect, and flow rate. 

The precision of an analytical method is obtained from multiple analyses of a homogeneous sample. You can determine overall precision of the method, including sample preparation. Such precision data are obtained by one laboratory on one day, using aliquots of the homogeneous sample that have been independently prepared. Such interlaboratory precision is called repeatability. Interlaboratory precision, if appropriate, is also determined as part of a measurement of reproducibility or robustness of the method (see below). 

Assay validation characterizes the assay performance so that the significance of the measured assay values obtained is readily understood [75]. Test methods should be validated when important decisions are to be based on the data generated [30]. Thus, the extent of method validation depends on the stage of clinical supply manufacture. The key elements of assay validation for a method are to establish reliability, the intra- and interlaboratory test variation, and relevance, the meaning of the results for a specific purpose [19]. The robustness of an analytical procedure (according to the ICH-Validation of Analytical Methods, 1993) is its measured capacity to be unaffected by small variations in controlled parameters and reliability under normal usage [35]. 

Validation of an analytical method is often done under the best of conditions such as use of a new column on dedicated equipment by an analyst experienced with the method. But what about routine analysis of commercial samples by many analysts in a busy Quality Control laboratory Robustness establishes the reliability of the method with respect to deliberate variations in the operating parameters, evaluates use of different column lots from the vendor, and also determines the stability of sample and standard solutions. Quality by Design (QbD) principles have begun to impact method development and validation activities to a wider extent and application of QbD concepts should result in higher quality and more robust analytical... 

The final goal of an analytical method is to determine quantitatively each compound of interest. Furthermore, the method must be robust, accurate and reproducible. To achieve these goals, the analytes should ideally appear at the end of the column (detector) as individual peaks to be easily identified and quantified. 

The robustness of an analytical RP HPLC method can be determined through the following six steps [5] ... 

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-... 

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