4.6 Article

An improved detection limit and working range of lateral flow assays based on a mathematical model

Journal

ANALYST
Volume 143, Issue 12, Pages 2775-2783

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c8an00179k

Keywords

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Funding

  1. National Natural Science Foundation of China [51322604]
  2. National Program for Support of Top-Notch Young Professionals
  3. Foundation for Innovative Research Groups of the National Natural Science Foundation of China [51322604]
  4. National Instrumentation Program of China [2013YQ190467]
  5. Key Program for Science and Technology Innovative Research Team in Shaanxi Province of China [2017KCT-22]
  6. Program for Innovative Research Team in Yulin Shaanxi Province of China [2017KJJH-02]
  7. China Postdoctoral Science Foundation [2017M623167]
  8. Initiative Postdocs Supporting Program [BX201700186]

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Lateral flow assays (LFAs) have attracted considerable attention in biomedical diagnostics. However, it's still challenging to achieve a high detection sensitivity and extensive working range, mainly because the underlying mechanism of complex reaction processes in LFAs remains unclear. Many mathematical models have been developed to analyze the complex reaction processes, which are only qualitative with limited guidance for LFA design. Now, a semi-quantitative convection-diffusion-reaction model is developed by considering the kinetics of renaturation of nucleic acids and the model is validated by our experiments. We established a method to convert the LFA design parameters between the simulation and experiment (i.e., inlet reporter particle concentration, initial capture probe concentration, and association rate constant), with which we achieved a semi-quantitative comparison of the detection limit and working range between simulations and experiments. Based on our model, we have improved the detection sensitivity and working range by using high concentrations of the inlet reporter particles and initial capture probe. Besides, we also found that target nucleic acid sequences with a high association rate constant are beneficial to improve the LFA performance. The developed model can predict the detection limit and working range and would be helpful to optimize the design of LFAs.

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