A numerical platform for predicting the performance of paper-based analytical devices

Abstract

This article presents a numerical platform for predicting the performance of paper-based analytical devices. The capillary flow, reaction, dissolution, and other physicochemical phenomena associated with device operation are accounted for using Darcy's law, Richard's equation and other transport equations. The platform can be used for different paper substrates, biorecognition methods, detection systems (such as optical and electrochemical detection), device patterns and dimensions, and ways in which the device is operated such as the input method of the body fluid. The device performance is quantified using indicators such as assay time, signal strength and product cost. The predictive capability of this numerical tool is verified with devices reported in the literature. It is shown that the platform can be used to identify possible improvements to these existing devices. More importantly, it can also serve as a numerical tool for synthesizing new paper-based analytical devices with minimum experimental effort.