Analytical performance parameters Precision

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

Drying 5°C temperature Running distance The same experiments are performed, but the running distance differs with 10% (rel). Analytical performance parameters precision... 

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. 

A number of experimental considerations must be addressed in order to use XRF as a quantitative tool, and these have been discussed at length [75,76]. The effects on the usual analytical performance parameters (accuracy, precision, linearity, limits of detection and quantitation, and ruggedness) associated with instrument are usually minimal. 

NIR spectroscopy became much more useful when the principle of multiple-wavelength spectroscopy was combined with the deconvolution methods of factor and principal component analysis. In typical applications, partial least squares regression is used to model the relation between composition and the NIR spectra of an appropriately chosen series of calibration samples, and an optimal model is ultimately chosen by a procedure of cross-testing. The performance of the optimal model is then evaluated using the normal analytical performance parameters of accuracy, precision, and linearity. Since its inception, NIR spectroscopy has been viewed primarily as a technique of quantitative analysis and has found major use in the determination of water in many pharmaceutical materials. 

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. 

Plates from the same sources The same experiments are performed on three plates supplied by the same manufacturer. Analytical performance parameters Rf, R precision, lowest detectable quantity Sample Model A, and B or C. 

UM-chamber The same experiments are performed on plates with same particle size and dimension as in conventional chamber. Analytical performance parameters Rf, precision, lowest detectable quantity Sample Model A and B or C. Temperature 5°C Eluent 10% (rel) amount prior to run Forced flow chamber Instrumental conditions are changed. Analytical performance parameters R, Rf, precision, lowest detectable quantity Sample Model A and B or C. 

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 ability of a tPLC system to produce the same values of retention time and peak areas for analytes of interest is determined by evaluating the precision obtained under standardized conditions and analytical methods. The precision (reproducibility) values obtained are functions of the autosampler, cartridge, and detectors employed. Due to the parallel design of the tPLC system described in this chapter, reproducibility evaluations of retention time and peak area involved comparisons of results obtained for these parameters for consecutive runs performed in the same column and across different columns. 

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. 

Extent of Validation Depends on Type of Method On the one hand, the extent of validation and the choice of performance parameters to be evaluated depend on the status and experience of the analytical method. On the other hand, the validation plan is determined by the analytical requirement(s) as defined on the basis of customer needs or as laid down in regulations. When the method has been fully validated according to an international protocol [63,68] before, the laboratory does not need to conduct extensive in-house validation studies. It must only verify that it can achieve the same performance characteristics as outlined in the collaborative study. As a minimum, precision, bias, linearity, and ruggedness studies should be undertaken. Similar limited vahdation is required in cases where it concerns a fully validated method which is apphed to a new matrix, a well-established but noncol-laboratively studied method, and a scientifically pubhshed method with characteristics given. More profound validation is needed for methods pubhshed as such in the literature, without any characteristic given, and for methods developed in-house [84]. 

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,... 

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. 

The dynamic range of a mass spectrometer is defined as the range over which a linear response is observed for an analyte as a function of analyte concentration. It is a critical instrument performance parameter, particularly for quantitative applications, because it defines the concentration range over which analytes can be determined without sample dilution or preconcentration, which effects the accuracy and precision of an analytical method. Dynamic range is limited by physiochemical processes, such as sample preparation and ionization, and instrumental design, such as the type of mass analyzer used and the ion detection scheme. 

The determination of silicon is complex, and a number of factors may interfere with its measurement. The element s concentration is mostly assessed in serum or urine, but to what extent these parameters are reliable indices of the total body burden is not yet clear. Moreover, until now no certified reference material is available. Hence, the availability of standardized techniques and methods that attain a sufficiently good analytical performance to allow accurate and precise analysis of biological fluids is mandatory. 

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