Analytical performance parameters Selectivity

Analytical procedures are classified as being compendial or non-compendial in character. Compendial methods are considered to be valid, but their suitability should be verified under actual conditions of use. To do so, one verifies several analytical performance parameters, such as the selectivity/specificity of the method, the stability of the sample solutions, and evaluations of intermediate precision. 

Guidelines for the selection of analytical performance parameters required for method validation are given in Table 11. 

The steps to be included into the analytical process Selection of analytical performance parameters Model solution (sample) to be used for validation experiments Degree of instrumentation Stability problems... 

The aim of the analysis should be kept in mind when analytical performance parameters are selected for the validation experiments. Table 5 lists the most important analytical performance parameters used for validation of TLC and HPLC methods. As is apparent from the data presented in Table 5, the parameters used for the two chromatographic techniques are not very different. The importance of each individual parameter used in the experiments to validate TLC or HPLC methods is, however, different, especially if the purpose of the analysis is considered. This is demonstrated in Table 5, where the primary analytical parameters are indicated as a function of the analytical aims. 

The analytical performance parameters (precision, / /value, Rs, etc.) considered to be sensitive to changes in the experimental variables should be selected. 

The following analytical performance parameters were included into the validation process selectivity stability during chromatograidiic development and in solution spot stability prior to the run and after development linearity and range precision reproducibility limit of quantitation limit of detection accuracy. The definitions used for the performance parameters the methods applied to determine them and the acceptance criteria were also described. Therefore, these papers can be recommended to be used by practicising chromatographers. 

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. 

Fit the purpose calibration. It is common sense to check instrument performance each day, and GLP requirements simply formalize the performance and documentation of these checks. On the other hand, it is also important to use the right test (full calibration, verification, system suitability test, or instrument and method validation) to verify the performance and to avoid needlessly lengthy procedures. As already discussed (see Sections 13.2.3 and 13.3.1), it is not always necessary to perform a MS full calibration every day. For example, if a particular MS is used only to record complete full-scan mass spectra, a daily calibration or verification of the calibration of the m/z ratio scale is required. However, in the case where a MS is coupled with an LC and utilized primarily for the analysis of one or more analytes in the selected ion monitoring (SIM) mode, it does not always require a daily verification of the calibration. In this specific case it is quite common in LC-MS and LC-MS/MS applications to test only the following performance parameters (a) sensitivity, (b) system precision,... 

The frequency of OQ/performance verification depends not only on the type of instrument and the stability of the performance parameters, but also on the acceptance criteria specified. In general, the time intervals should be selected such that the probability is high that all parameters are still within the operational specifications. Otherwise, analytical results obtained with that particular instrument are questionable. The OQ/performance verification history of the type of instrument can be used to set reasonable test intervals. Here the importance of proper selection of the procedures and acceptance limits becomes very apparent. 

Several key parameters must be considered to achieve selectivity and optimal analytical performance. At a minimum, spectral range, signal-to-noise ratio, and sample thickness or optical path length must be considered. In practice, these parameters are interdependent and their optimization can be difficult to realize. A detailed analysis of these parameters has been published.31... 

Ensuring high-quality analytical performance in trace analysis, if separation of sample components by extraction is indispensable, requires implementation of the appropriate extraction method and establishment of suitable operational parameters to ensure a high efficiency of extraction. Selection of extraction conditions is crucial for quantitative recovery of analyte, or at least for sufficient effectiveness. If an aqueous solution is one of the extraction phases, problems such as complex-ation, hydrolysis, and solvation can play an important role. Extraction of elements from aqueous to organic phase often requires selection of appropriate ligands and control of pH. 

Ion-selective electrodes (ISEs) represent the current primary methodology in the quantification of S-Li [11-13], Moreover, ISE modules are parts of large and fully automated clinical chemistry analysers. In practice, the validation parameters are most often chosen in terms of judging the acceptability of the new measurement system for daily use. For this reason, the first approach was to study whether the detected imprecision fulfilled the desired analytical quality specifications. Secondly, proficiency testing (PT) results from past samples were of great value in predicting future bias. The identity of the three ISE methods was evaluated using patient samples. The analytical performance was checked after 6 months routine use. Without any exception, method validations always mean an extra economical burden. Therefore, the validation parameters chosen and processed have to be considered carefully. 

Knowing the most influential parameters of a specific biosensor architecture is the basis to understand and fine tune the performance of these devices in a rational manner. Figure 1.8 summarizes the key features of typical biosensors and lists several that are of additional importance for commercial devices. Among these, selectivity, sensitivity, accuracy, response, and recovery time as well as operating lifetime are some of the most important key factors. Keeping in mind the needs of the specific analytical task of interest, it seems to be necessary to characterize at least the key parameters mentioned in Figure 1.8 in order to specify the analytical performance of a biosensor design. 

After the introduction of a selected sample volume into a flow system, it is transported through the analytical path, and subjected to several physical and chemical processes such as reagent addition, chemical reaction and dispersion. Understanding how these processes affect the flowing sample and the formation of the chemical species to be monitored is essential for optimising manifold design and, hence, analytical performance. To this end, it is important to consider the flow pattern and how to modify it by varying experimental parameters. 

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. 

The most economic way of using CRMs for calibration purposes is to validate a procedure for routine analysis. The analytical procedure is carried out with the CRMs analysed as samples. "IMth the results achieved, all relevant analytical parameters can be determined, e.g. uncertainty, recovery, reproducibility, selectivity, linearity, etc. The procedure is then well known for the specific sample type and the specific analytes for which it is validated and can be applied routinely for this analytical problem, with a few regular reviews of the analytical performance. CRMs in this case are not used for calibration but rather for validation of the procedure and regular review of the method performance. 

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