Validation quantitative aspect

Although screening tests are evaluated qualitatively, as a rule, quantitative aspects of test statistics and probability theory have to be considered. In this respect, validation of qualitative analytical procedures has been included in international programs and concepts, see Trullols et al. [2004]. 

In reference 88, response surfaces from optimization were used to obtain an initial idea about the method robustness and about the interval of the factors to be examined in a later robustness test. In the latter, regression analysis was applied and a full quadratic model was fitted to the data for each response. The method was considered robust concerning its quantitative aspect, since no statistically significant coefficients occurred. However, for qualitative responses, e.g., resolution, significant factors were found and the results were further used to calculate system suitability values. In reference 89, first a second-order polynomial model was fitted to the data and validated. Then response surfaces were drawn for... 

Finally, the use of a u-polarity field instead of different and more empirical electrostatic, hydrophobic, and hydrogen-bonding fields should lead to considerable advantages in molecular field analysis (MFA) techniques such as ComFA. On the one hand, a includes all three aspects of interactions in a single field, and on the other hand, this interaction picture meanwhile is much better validated quantitatively than the empirical fields presently used in MFA. The only problem here is that a is a surface property and thus less a field in space. With some effort it should be possible to develop reasonable functions for the extension of a perpendicular to the molecular surface and thus to generate a kind of 3D a-filed as required for MFA. 

Validation can be a method of quantifying the performance of a process in this case measuring the performance of a quantitative method. In 1985, E. M. Fry wrote Validation has a quantitative aspect—it s not just that you demonstrate that a process does what it purports to do you actually have to measure how well its does that... then, the processes that cause variability. .. must be identified. Experiments are conducted (that is, validation runs) to ensure that factors that would cause variability, are under control (1). ... 

The responses of main interest also are different in method development and robustness testing. In development, the considered responses are related to the quality of the separation (l),such as, for electrophoretic methods, migration times, peak shapes, and the resolutions between neighboring peaks. When the separation is optimized and the method is validated, thus also in robustness testing, the responses of main interest are related to the quantitative aspects of the method, such as contents, concentrations, or recoveries. The responses considered during development occasionally are considered in a second instance, for example, as system suitability test (SST) parameters. 

It is evident that the coefficient of cBAA (a) is higher at copolymer compositions characterized by larger amounts of styrene whereas the opposite is valid for the coefficient of eBAB (b). Solvent effects on the hypochromism of styrene-methyl methacrylate random copolymers seem to be correlated, at least qualitatively, to the variation in a and b as functions of styrene content in the copolymer. Specific solvent effects on the extinction coefficients eAAA, baa> and bab account for the quantitative aspects of hypochromism. Full details will be given (II). 

Consider Monod s model of growth. It is often possible to arrange experimental conditions so that a single substrate does in fact limit growth. One can then proceed to test the more quantitative aspects of the model. Monod s model has been applied to two cases batch growth and continuous propagation. To fulfill the first requirement for a valid model, it should predict the results of (say) continuous propagation from batch data, if the model is to be accepted. 

Method validation has traditionally focused on quantitative aspects, and with the exception of the last few years, less attention has been paid to reliable identification. Confirmation of potential positives is a matter of concern due to the imdesirable effects associated with erroneous... 

Process validation should be extended to those steps determined to be critical to the quality and purity of the enantiopure drug. Establishing impurity profiles is an important aspect of process validation. One should consider chemical purity, enantiomeric excess by quantitative assays for impurity profiles, physical characteristics such as particle size, polymorphic forms, moisture and solvent content, and homogeneity. In principle, the SMB process validation should provide conclusive evidence that the levels of contaminants (chemical impurities, enantioenrichment of unwanted enantiomer) is reduced as processing proceeds during the purification process. 

Barber PA, Demchuk AM, Zhang J, Buchan AM. Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score. Lancet 2000 355 1670-1674. 

An important aspect of all methods to be discussed concerns the choice of the model complexity, i.e., choosing the right number of factors. This is especially relevant if the relations are developed for predictive purposes. Building validated predictive models for quantitative relations based on multiple predictors is known as multivariate calibration. The latter subject is of such importance in chemo-metrics that it will be treated separately in the next chapter (Chapter 36). The techniques considered in this chapter comprise Procrustes analysis (Section 35.2), canonical correlation analysis (Section 35.3), multivariate linear regression... 

In summary, the CSL guidelines can be simply applied in each laboratory and contain very clear instructions. The validated procedures do not focus on the central analytical part only. Important secondary aspects of the whole procedure (sample processing, analyte stability, extraction efficiency) are also considered. For each parameter which is determined, different criteria for the evaluation of quantitative, semi-quantitative and screening methods are given. Here, it should be noted that compared with other guidelines the requirement for the precision of quantitative methods is very stringent (RSD < 10%). 

Part—I has three chapters that exclusively deal with General Aspects of pharmaceutical analysis. Chapter 1 focuses on the pharmaceutical chemicals and their respective purity and management. Critical information with regard to description of the finished product, sampling procedures, bioavailability, identification tests, physical constants and miscellaneous characteristics, such as ash values, loss on drying, clarity and color of solution, specific tests, limit tests of metallic and non-metallic impurities, limits of moisture content, volatile and non-volatile matter and lastly residue on ignition have also been dealt with. Each section provides adequate procedural details supported by ample typical examples from the Official Compendia. Chapter 2 embraces the theory and technique of quantitative analysis with specific emphasis on volumetric analysis, volumetric apparatus, their specifications, standardization and utility. It also includes biomedical analytical chemistry, colorimetric assays, theory and assay of biochemicals, such as urea, bilirubin, cholesterol and enzymatic assays, such as alkaline phosphatase, lactate dehydrogenase, salient features of radioimmunoassay and automated methods of chemical analysis. Chapter 3 provides special emphasis on errors in pharmaceutical analysis and their statistical validation. The first aspect is related to errors in pharmaceutical analysis and embodies classification of errors, accuracy, precision and makes... 

This chapter deals with the validation of capillary electrophoresis (CE) methods. It describes the various validation characteristics, namely accuracy, precision, specificity, detection limit, quantitation limit, linearity, and range in accordance with the official guidelines. Practical aspects related to the calculation of these parameters and factors affecting them in CE analysis have also been described. Validation requirements have been described according to the goal of the method. The chapter contains numerous tables and diagrams to illustrate these ideas. It also covers other related aspects such as instrument qualification, revalidation, and method transfer. 

Chapter 4.4 addressed various aspects of qualitative identification of pollutants with common analytical techniques, such as chromatography and elemental analysis. Another integral component of environmental analysis is pollutant quantitation. For the data to be valid and usable, the analytes must be not only correctly identified but also properly quantified. 

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