Journal article Open Access

T.Sudha*, G.Divya, J.Sujaritha, P. Duraimurugan

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<identifier identifierType="DOI">10.5281/zenodo.1036496</identifier>
<creators>
<creator>
<creatorName>T.Sudha*, G.Divya, J.Sujaritha, P. Duraimurugan</creatorName>
<affiliation>Department of Pharmaceutical Analysis, Adhiparasakthi College of Pharmacy, Melmaruvathur-603 319.</affiliation>
</creator>
</creators>
<titles>
</titles>
<publisher>Zenodo</publisher>
<publicationYear>2017</publicationYear>
<subjects>
<subject>Experimental Design, Response Surface Methodology, Factorial Design, Optimization, Fractional Factorial Design.</subject>
</subjects>
<dates>
<date dateType="Issued">2017-08-30</date>
</dates>
<resourceType resourceTypeGeneral="Text">Journal article</resourceType>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/1036496</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.1036495</relatedIdentifier>
<relatedIdentifier relatedIdentifierType="URL" relationType="IsPartOf">https://zenodo.org/communities/iajpr</relatedIdentifier>
</relatedIdentifiers>
<rightsList>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">&lt;p&gt;The ability of a chromatographic method to successfully separate, identify and quantitative species is determined by many factors, many of which are in the control of the experimenter. When attempting to discover the important factors and then optimize a response by turning these factors by using multivariate statistical techniques for the optimization of chromatographic system. The surface response methodologies and experimental design give a powerful suite of statistical methodology. Advantage includes modeling by empherical function, a defined number of experiments to be performed and available software to accomplish the task of two uses of experimental design in chromatography for showing lack of significant factors and then optimizing a response within their method development. Plackett - Burman design (Screening) widely used in validation studies and fraction factorial designs and their extensions such as (response surface) central composite designs are most popular optimizers. Box-Behnken and Doehlert designs are becoming more used as efficient alternatives. The use of mixture designs for optimization of mobile phase is also related. A discussion about model validation is presented. Then simultaneously the multiple responses are optimized, the desirability function is used and discussed the criteria for judging the quality of a chromatogram by using multi criteria decision making studies. Some applications of multivariate techniques for optimization of chromatographic methods are also summarized.&lt;/p&gt;</description>
</descriptions>
</resource>

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