51: Optimizing sensitivity in lateral flow assays: Effects of reaction kinetics and nanoparticle valency

Abstract: Lateral flow assays (LFAs) are widely used for rapid and point-of-care diagnostics; however, their sensitivity remains a key limitation, particularly at low analyte concentrations. In this study, we developed a mathematical framework based on the convection–diffusion–reaction (CDR) model to investigate how flow velocity, binding kinetics, and nanoparticle valency influence assay sensitivity. Model parameters, including association rate constants (kon), dissociation rates (koff), and nanoparticle valency, were systematically varied while maintaining constant equilibrium occupancy. Simulation results were normalized using dimensionless time to enable direct comparison with published models. Our results show strong agreement with literature data (see Figure 1), validating the modeling approach. Sensitivity was significantly enhanced by decreasing flow velocity, which increased analyte residence time at the test line and improved binding efficiency. Additionally, higher nanoparticle valency and faster effective reaction kinetics increased analyte capture rates, leading to improved signal intensity (T/C ratio). However, results indicate that optimization requires a balance between transport and reaction processes rather than maximizing a single parameter. This work provides quantitative insights into the interplay between transport dynamics and binding interactions in LFAs and offers practical design guidelines for improving sensitivity. The developed framework can be extended to more complex assay formats, including competitive binding systems and spatially resolved models, to support the design of next-generation diagnostic devices.