Assay parameters definitions

Parameter Definitive Quantitative Assay Relative Quantitative Assay Quasi- Quantitative Assay Qualitative Assay... 

Usually, a mathematical model simulates a process behavior, in what can be termed a forward problem. The inverse problem is, given the experimental measurements of behavior, what is the structure A difficult problem, but an important one for the sciences. The inverse problem may be partitioned into the following stages hypothesis formulation, i.e., model specification, definition of the experiments, identifiability, parameter estimation, experiment, and analysis and model checking. Typically, from measured data, nonparametric indices are evaluated in order to reveal the basic features and mechanisms of the underlying processes. Then, based on this information, several structures are assayed for candidate parametric models. Nevertheless, in this book we look only into various aspects of the forward problem given the structure and the parameter values, how does the system behave ... 

These tests are performed by collecting data from replicate injections of standard or other solutions as specified in the individual monograph. The specification of definitive parameters in a monograph does not preclude the use of other suitable operating conditions (see Procedures under Tests and Assays in General Provisions). Adjustments of operating conditions to meet system suitability requirements may be necessary. 

Definition Limit of quantitation is a parameter of quantitative assays for low levels of compounds in sample matrices, such as impurities and degradation products in food additives and processing aids. It is the lowest concentration of analyte in a sample that can be determined with acceptable precision and accuracy under the stated experimental conditions. The limit of quantitation is expressed as the concentration of analyte (e.g., percentage, milligram per kilogram, parts per billion) in the sample. 

The validation process begins in method development in that the documentation reporting the validation data must include a record of the method development process, giving details of the conditions explored and the rationale of the progression of the process. The validation proper consists of a series of tests for which there are acceptance criteria which vary depending on the type of assay being carried out. Literal definitions of the parameters for which tests must be carried out are discussed elsewhere in this book but are repeated here as a reminder. 

The definitions, methods, and parameters used to validate analytical and bioana-lytical methods are not universal they vary with the type of assay and the regulatory agency. Here, we introduce the more broadly used figures of merit with their generally accepted definitions. Basic statistical procedures are also presented. More technical sources of further information are offered in the Suggested Reading section. 

This guideline refers to terms and definitions of parameters included in validation experiments, whereas Q2B describes the way in which validation can be performed. Attributes covered in Q2A include specificity (for identification tests) accuracy, precision, specificity, detection limit, quantitation limit, linearity, and range (for impurity tests) and accuracy, precision, specificity, linearity, and range for assay measurements (e.g., content, potency, and dissolution testing). 

Some of the most definitive studies of Mg(II)-activated enzymes have been performed by mangetic resonance (NMR, ESR) methods with the Mn(ll)-substituted species. An integrated picture of the role of the metal ion in catalysis in almost all cases also includes data from kinetics (steady state and pre-steady state), equilibrium binding, and optical spectroscopic methods. As stated above, there are but a few examples of true Mn-containing enzymes, especially in mammalian sytems. Table 1 provides a non-exhaustive list of examples of both Mn-specific and Mn/Mg-activated enzymes. Within the latter category are enzymes that show a preference for but not absolute specificity for one ion or the other. The distinction between these categories is not simple, often being dependent upon the source or form of the enzyme and various parameters as the type of assay used, temperature, pH, and others. 

Screen validation phase tests the screening assay in a more production-like environment. For example, the lab bench results are replicated on the HTS robotic system. Critical quality control experiments are performed at this stage in the process. This involves screen rehearsal with a small number of compounds (i.e., a few thousand), thus validating the screening process. Process precision is measured by repeating the mini-screen on a different day. This procedure allows definition of all the quality control parameters. Typical values include the following ... 

As the laboratory works through the use cases and the above questions to define selection requirement, it should get a good idea of which systems may best meet the requirements. It is recommended at this point to perform some proof-of-concept testing to determine whether the automated assay will produce acceptable results. There is no way to prove this definitively until the system is purchased and installed, but it is possible to test specific parameters such as ... 

The recovery of an analyte in an assay is defined by the FDA in a strictly operational way as the detector response obtained Ifom an amount of the analyte added to and extracted from the biological matrix, compared to the detector response obtained for the true concentration of the pure authentic standard. Recovery pertains to the extraction efficiency of an analytical method within the limits of variability. Recovery of the analyte need not be 100 %, but the extent of recovery of an analyte and of the internal standard should be consistent, precise, and reproducible. Recovery experiments should be performed by comparing the analytical results for extracted samples at three concentrations (low, medium, and high) with unextracted standards that represent 100 % recovery (FDA 2001). In terms of the symbols used in Section 8.4, the recovery is thus defined as the ratio (R /R"), and is equivalent to determination of F provided diat no suppression or enhancement effects give rise to differences between R and R" and that the proportional systematic errors and 1 are negligible. The FDA definition of recovery also corresponds to that of the PE ( process efficiency ) parameter (Matuszewski 2003) discussed in Section 5.3.6a, since the former (FDA 2001) measures a combination of extraction efficiency and matrix effects (if any). 

The assays described so far utilize UCNPs simply as labels but they can also be used for sensing chemical and biological parameters or analytes. According to [44], chemical sensors are miniaturized analytical devices that can deliver real-time and on-line information on the presence of specific compounds or ions in complex samples. Similar definitions do exist for biosensors [45]. There are additional definitions for sensors that also include more specific details like handiness, small size, operational and storage stability. One common criterion is the option of performing continuous and reversible measurements. However, this requirement is not always fulfilled, particular in the case of biosensors where binding constants are very high [46, 47]. 

Each chapter is subdivided into sections beginning with a short introduction or general description, which gives a brief overview of the subject. Then functional, structural, and genetic aspects of each enzyme are described, with examples of typical applications. Functional aspects include (1) reaction conditions (optimal or recommended reaction conditions, kinetic parameters, cofactor requirements, and inhibitors/inactivators) (2) activity assay and unit definition (3) substrate specificity and (4) catalytic mechanism. The section on enzyme functions should enable the reader to predict the possible outcome of a reaction under a given condition and provide the basis for which the activity of an enzyme can be optimized or fine tuned to obtain the desired results. 

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