Qualitative data guidelines

While most BEIs are quantitative, data sometimes support only a screening-type guideline that is non-quantitative or semiquantitative. Such guidelines typically are used for substances on which there are good qualitative data on human exposure and the biological determinant concentration, but poor quantitative data relating exposure to the determinant. They most commonly are used for substances that cause chronic, systemic health effects when absorbed through the skin. Nonquantitative determinants are useful especially for substances, like 4,4 -methylene bis(2-chloroaniline) (MBOCA), that meet these criteria and... 

Good practice guidelines illustrate how these parameters are typically examined for both normal and postulated abnormal conditions, such as variations in reactant quantity, concentration, agitation, sequence, time, failure of utilities, and instrumentation. Qualitative hazard evaluation protocols are not well suited for such complex chemical phenomena (e.g., the severity of an uncontrolled reaction under a loss of electrical power may not be apparent without sufficient test data). 

This chapter will look at the use of CE for pharmaceutical analysis and will include descriptions of the various modes of CE and their suitability for quantitative and qualitative analysis of pharmaceutical compounds. Practical applications of CE for the analysis of pharmaceuticals will be covered, these applications include drug assay, impurity determination, physicochemical measurements, chiral separations, and the analysis of small molecules. A section covering the approach to CE method development for pharmaeeutical analysis will include guidelines to selecting the best mode of CE for an intended separation. Extensive data will be provided on successful pharmaceutical separations with references to extra source material for the interested reader. This chapter will provide a comprehensive and up to date view of the role and importance of CE for the analysis of pharmaceuticals and will provide the reader with practical information and real data that will help them to decide if CE is suitable for an intended separation. 

In essence, the DAL Objectives provide a way for the certification authority to evaluate the applicant s product lifecycle data and processes to establish if the data supports the assertion that the system is assured. It provides a measureable way to deal with evidence that may have qualitative properties (e.g., human review evidence) and/or quantitative properties (e.g., test results of an algorithm). By using an objective-based approach, these guidelines/standards provide the developer with some flexibility in choosing methods and techniques that best suit their needs, provided that the evidence (i.e., output or deliverables or data items) satisfies these objectives. 

We employ the guidelines of [18] to conduct the case study. A case study is the most appropriate research methodology for this setting, as its primary objective is exploratory, with a flexible design, and collecting qualitative (instead of quantitative) data. Concretely, the case study encompasses the following steps ... 

When reporting the results of qualitative and quantitative phase analyses, a minimal amount of information should be presented regarding the data analysis procedure to enable verification, reproduction and comparison of the results. As a guideline. Table 4.3 supplies a list of properties and settings that characterise a QPA routine some parameters are specific to Rietveld analysis, but most are applicable to other XRD analysis methods as well. 

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