Optimal design of amperometric biosensors applying multi-objective optimization and decision visualization

This paper presents a method combining mathematical modeling, multi-objective optimization and multi-dimensional visualization intended for the design and optimization of amperometric biosensors. An approach for optimizing the biosensor parameters is based on the availability of mathematical model of a catalytic biosensor (bioelectrode). A multi-objective visualization of trade-off solutions and Pareto optimal decisions is applied for the selection of the most favorable decision by a human expert when designing the biosensor. The proposed method is applied to the industrially relevant optimization of a glucose dehydrogenase-based amperometric biosensor utilizing the synergistic substrates conversion. The following three objectives were optimized: the apparent Michaelis constant, the output current and the enzyme amount.