Mathematical and Computational Modelling for Biosensors: A Modular Approach

Abstract

Biosensors are analytic devices which detect biochemical and physiological changes and represent an emerging technology for low-cost, rapid and simple-to-operate biomedical diagnostic tools. Biosensor design and functionality are based on well understood physical and chemical processes which can be easily translated into mathematical models involving ordinary and partial differential equations. Using mathematical and computational modelling techniques to characterize the biosensor response as a function of its input parameters in a wide range of physical contexts can guide the experimental work, thus reducing development time and costs. This thesis is based on a close collaboration with Biochemistry researchers at the National Centre for Sensor Research (NCSR) and Biomedical Diagnostics Institute (BDI) at Dublin City University and the mathematical models we develop are relevant to ongoing experimental work in these centres relating to design optimization of biocatalytic and bioaffinity devices. Our approach is to use numerical solutions as a first step towards determining the accuracy of these models, since the simulations successfully reproduce the experimental outcomes; future work can then concentrate on a more detailed theoretical analysis.