Introducing Chemical Engineering Processes into Optimal Design of Measuring Systems Equipped with Biosensors

摘要

Biosensors as 'dip in and register' devices, generically offer simplified reagentless analyses for a range of biomedical and industrial applications and for this reason this area has continued to develop into an ever-expanding and multidisciplinary field during the last decades. Just moving from the proof-of-concept stage to field testing and commercialization, they require the establishment of chemical engineering processes for their advancement to measuring equipments. This work presents a decision support system for the selection of sample treatment to precede biosensing, in order to minimize interference. The proposed system is comprised of (a) a Knowledge Base developed through rules based reasoning from four separate databases relating to biosensors, treatment processes, samples and application environment, used to provide the alternatives that are re-evaluated through case-based reasoning by a separate whole cases database and (b) an integrated fuzzy multicriteria analysis method (FMCA) to provide the optimal solutions, tailor-made by the authors to help researchers engaged in biosensor development to select the best biosensor-pretreatment method suited for a specific application while fulfilling a set of technoeconomic criteria. The algorithmic procedure developed by the authors for the realization of the selection procedure has been implemented in the case of reduced glutathione measurement in serum.