Analytical performance parameters Specificity

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. 

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. 

When a suitable immobilization protocol is identified for the application of interest, the sensor is studied and optimized in its analytical performances. The specificity is tested by using a negative control, which is a non-complementary sequence and does not hybridize the probe and, if the immobilization is properly performed, no recordable signal should be found. The reproducibility, expressed as coefficient of variation (CV, equal to (standard deviation)/A/av), is another important parameter to be considered. 

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. 

Traceability and MU both form parts of the purpose of an analytical method. Validation plays an important role here, in the sense that it confirms the fitness-for-purpose of a particular analytical method [4]. The ISO definition of validation is confirmation by examination and provision of objective evidence that the particular requirements of a specified intended use are fulfilled [7]. Validation is the tool used to demonstrate that a specific analytical method actually measures what it is intended to measure and thus is suitable for its intended purpose [2,11]. In Section 8.2.3, the classical method validation approach is described based on the evaluation of a number of method performance parameters. Summarized, the cri-teria-based validation process consists of precision and bias studies, a check for... 

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 traditional criteria approach is to identify specific performance parameters and to assign numeric values to these. These numeric values represent cutoff or threshold values the method parameters must meet in order for the method to be acceptable. The alternative approach is focused on fitness for purpose and MU. In this fitness-for-purpose approach, the overall MU is estimated as a function of the analyte concentration (see Section 8.2.2). 

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. 

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. 

It therefore depends on each specific case, which performance parameters are to be confirmed before starting the analysis. The scope of validation thus might depend to a certain extent on the customers needs. If they are very diverse (e.g. the laboratory has a customer, who is interested in lower concentrations of a particular analyte as well as a customer who brings a sample with a higher concentration of the same analyte, but this customer requires very low measurement uncertainty), it is worth broadening the scope of validation or confirmation, otherwise it would be sufficient to evaluate/confirm key parameters for the intended use. The general rule should be that only those parameters that are needed to be fulfilled due to the customers requirements must be confirmed. However, a lot of additional measurements are usually done to evaluate the procedure s performance parameters (Table 3) and the result s properties (traceability, measurement uncertainty). 

In evaluation of the performance characteristics of a candidate method, precision, accuracy (trueness), analytical range, detection limit, and analytical specificity are of prime importance. The sections in this chapter on method evaluation and comparison contain a detailed outline of these concepts and their assessment. The estimated performance parameters for a method can then be related to quality goals that ensure acceptable medical use of the test results (see section on Analytical Goals), From a practical point of view, the ruggedness of the method in routine use is of importance. Reliable performance when used by different operators and with different batches of reagents over longer time periods is essential. 

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. 

ELISA tests are used widely for the detection of contaminants both in analytical laboratories and in the food industry. Commercial kits are generally used, as they have the advantage of containing all the materials necessary to run the tests (in some cases the preparation of solutions is required). They meet performance specifications set by the manufacturer, which are evaluated by the end user to see if the method is suitable for his or her application (processed food, type of matrix, etc.). Quantitative tests require the use of a microplate or strip reader. Some commercial ELISA kits are available on the market for the detection of soy allergens [12,13] (see Table 17.1 for performance parameters). The column raw and processed food relates to information provided by the manufacturer about the applicability to raw and processed food. 

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. 

The analytic theory outlined above provides valuable insight into the factors that determine the efficiency of OI.EDs. However, there is no completely analytical solution that includes diffusive transport of carriers, field-dependent mobilities, and specific injection mechanisms. Therefore, numerical simulations have been undertaken in order to provide quantitative solutions to the general case of the bipolar current problem for typical parameters of OLED materials [144—1481. Emphasis was given to the influence of charge injection and transport on OLED performance. 1. Campbell et at. [I47 found that, for Richardson-Dushman thermionic emission from a barrier height lower than 0.4 eV, the contact is able to supply... 

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