Increasingly medical diagnostic platforms rely upon the use of colloidal nanoparticles for the detection of biomolecules. Colloids offer greatly increased surface area to volume ratios and lack diffusion limitations that typically reduce reaction rates in assays employing planar surfaces. These characteristics are anticipated to improve the speed to answer as well as the total number of analytes that are captured in colloidal assay systems. This paper details a reaction-diffusion modeling approach to optimize colloidal affinity-based bioassays, with emphasis on the key figures of merit of projected sensitivities and time to answer over a broad range of conditions. The computational results illustrate the intuitive sense that colloidal sensing surfaces have improved kinetics as compared to solid supports, that the curvature of the spherical sensing surface probes a larger volume than a planar surface of the same area resulting in a larger diffusional driving force for reaction to the surface and equilibrium of bound analyte. The governing regime of particle systems skewed toward kinetically limited regimes and multiple configurations of particle diameter and concentration achieved equivalent analyte capture. Surface based sensor platforms have benefited from miniaturization of the capture area and particle capture systems provide a route to further surface miniaturization, as well as unique opportunities for the rapid analysis of dilute samples of particular interest for point-of-care (POC) diagnostics. (C) 2018 Elsevier Ltd. All rights reserved.