Quantitation validation parameters

Validation Parameter Identification Impurities (Quantitation) Impurities (Limit) Assay... 

Validation parameter Identification Testing for impurities Quantitative Limit test Assay... 

Validation parameter Confirmation of the identity of pure substances Determination of identity of unknown substances Amount single pure substance Amount active substance Limit test (semi- quantitiative) Amount impurities/ degradation products (quantitative) Dissolution speed of substances Bioequivalence studies... 

LC-MS(MS) quantitative methods for antidepressant determination should fulfill special requirements regarding linearity range, LLOQ or the need for high throughput, depending on the specific application for which they were developed. Conditions and studied validation parameters for selected LC-MS(MS) methodologies for antidepressant determination are shown in Table 1. 

There is a general agreement that at least the following validation parameters should be evaluated for quantitative procedures selectivity, calibration model (linearity), stability, accuracy (bias, precision) and limit of quantification. Additional parameters which might have to be evaluated include limit of detection, recovery, reproducibility and ruggedness (robustness) [2,4-10,12],... 

Analytical method validation has developed within the pharmaceutical industry over the years in order to produce an assurance of the capabilities of an analytical method. A recent text on validation of analytical techniques has been published by the international Conference on Harmonisation (ICH) [19]. This discusses the four most common analytical procedures (1) identification test, (2) quantitative measurements for content of impurities, (3) limit test for the control of impurities and (4) quantitative measurement of the active moiety in samples of drug substance or drug product or other selected components of the drug product. As in any analytical method, the characteristics of the assay are determined and used to provide quantitative data which demonstrate the analytical validation. The reported validation data for CE are identical to those produced by an LC or GC method [11] and are derived from the same parameters, i.e. peak time and response. Those validation parameters featured by the ICH (Table 1) are derived from the peak data generated by the method. Table 1 also indicates those aspects of a CE method (instrumentation and chemistry), peculiar to the technique, which can affect the peak data and highlights factors which can assist the user in demonstrating the validation parameters. 

Before the performance of method transfer activities involving protocols and acceptance criteria, it was customary for a receiving laboratory to repeat some or all of the validation experiments. This laboratory was thereby deemed to be qualified as described above. The choice of validation parameter(s) depends highly on the type of method being transferred. For example, content uniformity assays to determine consistency of product potency depend heavily on the method and system precision. As a second example, a determination of trace impurities in an API could not be reproduced between two sites if their instruments did not yield similar limits of detection and limits of quantitation. A detailed discussion on the rational choice of validation parameters that would need to be repeated by the receiving laboratory is beyond the scope of this chapter. The reader is referred to the method validation chapter by Crowther et al. for additional information on this subject. 

Validation parameter Assay Category I Assay Category II Quantitative Assay Category II Limit Test Assay Category III Identification... 

To facilitate the understanding of the specific applications and interpretation of validation parameters for LBAs, it is useful to consider first some important differences between low molecular weight compounds and macromolecules, especially differences in the in vivo disposition of these two classes of molecules and between the chromatographic assays and LBAs used for their respective quantitation. 

Given the foregoing discussion of some of the unique characteristics of macromolecules that lead to clear differences in their pharmacokinetics compared to those typical of small-molecule drugs, there is a subset of the entire group of bioanalytical assay validation parameters that are of key importance in support of pharmacokinetics of candidate macromolecular therapeutics. Assuming demonstration of accuracy and precision of sufficient quality for the intended application of the assay (e.g., non-GLP discovery support or GLP toxicokinetic support, as discussed above), the most important characteristics of a given assay in support of pharmacokinetic studies are likely to be selectivity, specificity, and reproducibility for analysis of incurred samples. These are all related to the ability of the LBA to detect and quantitate solely, or as closely as possible to solely, the analyte of interest. 

The discrimination factor has also been used in error analysis in quantitative HPLC (22). Since resolution is not sensitive to relative p height and the error in quantitation depends strongly on the location of the valley between the peaks, do is a valid parameter for duuacterizing errors in quantitative analysis. The error can be expressed using the fractional area F, and fractional height for the smallest pe i (the one for which the error is the higliest) ... 

As a benchmark set for the quantitative validation of dispersion corrections, Hobza and coworkers suggested the S22 set (Jurecka et al. 2006), which contains 22 weakly bonded dimers. This S22 benchmark set provides interaction energies of hydrogen-bonded, dispersion-bonded and mixed complexes, which are the calculated results of the CCSD(T) method at the complete basis set (CBS) limit (Riley et al. 2010). Due to its convenience, this benchmark set has been used not only in testing the accuracies of dispersion corrections but also in determining the adjustable parameters of semiempirical dispersion-corrected functionals. Table 6.1 displays the mean absolute deviations (MAD) of various dispersion-corrected DPT calculations for the S22 benchmark set in ascending order. This table shows clearly that, independent of the dispersion corrections combined, the LC-tvdW methods... 

Prior to its use a method has to be validated. Validation is the formal proof that the method is suitable for the intended purpose. This requires that all steps and parameters of the method have been clearly specified in a written method description, any necessary equipment was qualified, and acceptance criteria for each validation point have been agreed upon. For quantitative methods the International Conference on Harmonization (ICH) has issued specific guidelines for setting up a validation protocol and for parameters that have to be validated for different applications. These include specificity, accuracy, precision, LOD, LOQ, linearity, and range as well as robustness. The only required validation parameter for qualitative methods is specificity. 

The validation parameters as per guidelines of the Committee for Proprietary Medicinal Products (CPMP-European Community) are selectivity, linearity range, limit of detection and quantitation, accuracy and precision. The majority of investigators working on the quantitative TLC have reported only relative standard deviation (RSD) data (99,143.145,164,176,182) many important parameters... 

Principles and Characteristics Whereas parameters most relevant to method development are considered to be accuracy, system precision, linearity, range, LOD, LOQ, sensitivity and robustness, method validation parameters are mainly bias, specificity, recovery (and stability of the analyte), repeatability, intermediate precision, reproducibility and ruggedness. However, method development and validation are highly related. Also, validation characteristics are not independent they influence each other. Acceptance criteria for validation parameters should be based on the specification limits of the test procedure. Quantitation and detection limits need a statement of the precision at their concentration levels. Procedures used for validation of qualitative methods are generally less involved than those for quantitative analytical methods. According to Riley [82], who has discussed the various parameters for validation of quantitative analytical methods, the primary statistical parameters that validate an analytical method are accuracy and precision. 

IPC method validation is similar to the drug substance and product method validation however, special consideration should be given to the sample reactivity and stability. IPC method validation requires coordination with the process chem-ist/engineers to provide fresh reaction and process samples for the analysis. Table 1 has a list of in-process validation parameters that should be evaluated for chromatographic IPC limit and quantitative tests. These parameters are based on the ICH guidelines.The IPC analyses are categorized into RAP (COR and impurity determination) and solution concentration assays (%, w/v % v/v and mg/mL). 

Several alternative attempts have been made to quantify Lewis-acid Lewis-base interaction. In view of the HSAB theory, the applicability of a scale which describes Lewis acidity with only one parameter will be unavoidably restricted to a narrow range of struchirally related Lewis bases. The use of more than one parameter results in relationships with a more general validity ". However, a quantitative prediction of the gas-phase stabilities of Lewis-acid Lewis-base complexes is still difficult. Hence the interpretation, not to mention the prediction, of solvent effects on Lewis-add Lewis-base interactions remains largely speculative. 

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