Analytical performance parameters Robustness

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. 

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. 

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. 

The validation of an analytical procedure produces performance parameters of a well-behaved and well-conditioned system/instrument (including defined variations) which are more or less snapshots of the combination procedure/system. In order to routinely confirm the suitability of the integrated measurement instrumentation used with a given procedure, system suitability test parameters should be defined on the basis of the validation results and robustness studies. Larger variations under routine conditions or multiple laboratories should also be taken into consideration. 

A more comprehensive model-based design method. Internal Model Control IMC), was developed by Morari and coworkers (Garcia and Morari, 1982 Rivera et al., 1986). The IMC method, like the DS method, is based on an assumed process model and leads to analytical expressions for the controller settings. These two design methods are closely related and produce identical controllers if the design parameters are specified in a consistent manner. However, the IMC approach has the advantage that it allows model uncertainty and tradeoffs between performance and robustness to be considered in a more systematic fashion. 

The evaluation of robustness is normally considered during the development phase and depends on the type of procedure under study. Experimental design (e.g., fractional factorial design or Plackett-Burman design) is common and useful to investigate multiple parameters simultaneously. The result will help to identify critical parameters that will affect the performance of the method. Common method parameters that can affect the analytical procedure should be considered based on the analytical technique and properties of the samples ... 

The performance characteristics of any analytical method involve the evaluation of the following parameters calibration range, limit of detection, precision, trueness, specificity, recovery, and robustness [40]. 

If analytical measurements are susceptible to variations in the analysis parameters or sample preparation conditions, the method must be suitably controlled or a precautionary statement must be included in the written procedure that alerts the chemist to the susceptibility. The method s system suitability parameters should be defined in such a way that meeting all system suitability criteria would ensure that the method is currently being performed within the acceptance window provided by validation robustness testing. 

In figure 1 a) we address the comparison between the analytical adsorption isotherm in one dimension and Monte Carlo simulation. The simulations have been performed for monomers, dimers and 10>mers adsorbed on chains of M/k =1000 sites with periodic boundary conditions. Different values of the parameter c have been considered. In all cases, the computational data fully agree with the theoretical predictions, which reinforce the robustness of the two methodologies employed here. 

At this stage, any co-elution of the key analytes is corrected by fine-tuning the separation parameters, mostly by adjusting selectivity (a) (see Figure 2.17). This process may be quite challenging and iterative for multi-component assays of complex samples. Afterwards, efforts are focused on improving other method performance measurements such as sensitivity, peak shape, robust-... 

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]. 

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. 

In some cases it is observed that, under the experimental conditions used (mobile phase composition, ionization and API interface parameters), more than one ionized form of the intact analyte molecule is observed, i.e. adduct ions of various kinds (see Section 5.3.3 and Table 5.2). An example is shown in Figure 9.6, in which a well known anticancer drug (paclitaxel, Figure 9.6(a)) was analyzed by positive ion ESI-MS (infusion of a clean solution). The first spectrum (Figure 9.6(b)) shows four different adducts (with H+, NH, Na+ and K+). Adjustment of the cone (skimmer) potential (Section 5.3.3a), to lower values in this case, enabled production of the ammonium ion adduct to dominate the MS spectrum (Figure 9.6(c)) in a robust fashion, and this ion yielded a useful product ion spectrum (that appeared to proceed via a first loss of ammonia to give the protonated molecule) which was exploited to develop an MRM method that was successfully validated and used. It is advisable to avoid use of analyte adducts with alkali metal ions (commonly Na+ and to some extent K+) since, when subjected to colli-sional activation, these adducts frequently yield the metal ion as the dominant product ion with only a few low abundance product ions derived from the analyte molecule. However, when feasible, both the ammonium adduct and protonated molecule should be investigated as potential precursor ions at least until it becomes clear that one will provide superior performance (sensitivity/selectivity compromise) than the other. 

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