The effect of report particle properties on lateral flow assays: A mathematical model

Abstract Lateral flow assays (LFAs) have found widespread applications in biomedical fields, but improving their sensitivity remains challenging mainly due to the unclear convection-diffusion-reaction process. Therefore, we developed a 1D mathematical model to solve this process in LFAs. The model depicts the actual situation that one report particle may combine more than one target, which overcomes the deficiency of existing models where one report particle combines only one target. With this model, we studied the effect of report particle characteristics on LFAs, including binding site density, target analyte and report particle concentration. The model was qualitatively validated by reported experimental data and our designed experiments where the report particle with different accessible binding site (HIV-DP) densities is obtained by changing the ratio of HIV-DP and Dengue-DP in preparing AuNP-DP aggregates. The results indicate that a strong signal intensity can be obtained without consuming excess detector probe with the optimum binding site (N = 30). A maximum normalized target concentration of 120 is obtained to prevent the false-negative result, while a minimum normalized report particle concentration of 0.015 is recommended to produce a strong signal. The developed model would serve as a powerful tool for designing highly effective LFAs.