Title: Expanding Horizons in the Validation of GMO Analytical Methods: Fuzzy-Based Expert Systems
Authors: BELLOCCHI GIANNIACUTIS MarcoPAOLETTI ClaudiaCONFALONIERI ROBERTOTREVISIOL PatriziaGRAZIOLI EMANUELECHARLES DELOBEL CHRYSTELESAVINI CRISTIANMAZZARA MARCOVAN DEN EEDE GUY
Citation: FOOD ANALYTICAL METHODS vol. 1 no. 2 p. 126-135
Publisher: SPRINGER
Publication Year: 2008
JRC N°: JRC40118
ISSN: 1936-9751
URI: http://www.springerlink.com/content/d31134312016k24x/fulltext.pdf
http://publications.jrc.ec.europa.eu/repository/handle/JRC40118
DOI: 10.1007/s12161-008-9021-8
Type: Articles in Journals
Abstract: Validation is the process establishing the suitability of an analytical method for a particular purpose. Various guidelines defining statistical procedures for validation of chemical, bio-chemical, pharmaceutical and genetic methods have been developed and ad hoc validation metrics (indices and test statistics) are available and routinely used, for in-house and across laboratories testing, and decision-making. However, there is no universally accepted practice for assay validation and, often, subjectivity plays an important role in the interpretation of validation studies¿ results. Instead, the key to rational validation studies relies upon the formalisation and harmonisation of procedures for their design and interpretation of results. Fuzzy-based techniques can be helpful in such respect. Fuzzy logic allows summarising the information obtained by classic independent validation statistics into one synthetic index of overall method performance. The possibility of having a comprehensive indicator of method performance has the advantage of permitting direct method comparison, facilitating the evaluation of many individual, possibly contradictory, metrics. Objective of this paper is to illustrate the advantages that a fuzzy-based aggregation method could bring into the validation of analytical methods and to propose its application for the evaluation of methods¿ performance. Validation metrics are compared for practical examples of method performance in collaborative studies. Fuzzy-logic based rules are shown to be applicable to improve insights into model quality and interpretation of results.
JRC Institute:Institute for Health and Consumer Protection

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