A computer-implemented method for data analysis and inference of particle diffusion in mucus barriers and generic permeable biomaterials, the method comprising: a) collecting experimental data of observed particle movement through samples of a target material; b) analyzing the collected data to determine at least one stochastic diffusive process that is being observed for particular particles in the particular material sample; c) using one or more of the at least one observed stochastic diffusive process to simulate the diffusion of particles through the target material, wherein the simulating the diffusion of particles through the target material of step c) comprises performing a plurality of simulations, wherein each simulation simulates the movement of particles through a target material of a particular thickness, and includes, for each particle simulated: c1) using the Gaussian parameters of a cluster to which the particle is assigned to determine standard deviations from the Gaussian distribution; c2) converting the standard deviations into Hurst parameters; c3) using the Hurst parameters to simulate, using a best-fit fractional Brownian motion model, fractional Brownian motion for the particle, which results in a simulated path of the particle through the target material; and c4) using the plurality of simulated paths to calculate passage time distributions through the target material of the particular thickness, wherein data from the plurality of simulations is used to calculate passage time distributions for each of a plurality of thicknesses of the target material; d) using the passage time distributions for the thicknesses of the target material to determine how passage time scales according to thickness of the target material; and e) verifying the simulation results. a) collecting experimental data of observed particle movement through samples of a target material; b) analyzing the collected data to determine at least one stochastic diffusive process that is being observed for particular particles in the particular material sample; c) using one or more of the at least one observed stochastic diffusive process to simulate the diffusion of particles through the target material, wherein the simulating the diffusion of particles through the target material of step c) comprises performing a plurality of simulations, wherein each simulation simulates the movement of particles through a target material of a particular thickness, and includes, for each particle simulated: c1) using the Gaussian parameters of a cluster to which the particle is assigned to determine standard deviations from the Gaussian distribution; c2) converting the standard deviations into Hurst parameters; c3) using the Hurst parameters to simulate, using a best-fit fractional Brownian motion model, fractional Brownian motion for the particle, which results in a simulated path of the particle through the target material; and c4) using the plurality of simulated paths to calculate passage time distributions through the target material of the particular thickness, wherein data from the plurality of simulations is used to calculate passage time distributions for each of a plurality of thicknesses of the target material; c1) using the Gaussian parameters of a cluster to which the particle is assigned to determine standard deviations from the Gaussian distribution; c2) converting the standard deviations into Hurst parameters; c3) using the Hurst parameters to simulate, using a best-fit fractional Brownian motion model, fractional Brownian motion for the particle, which results in a simulated path of the particle through the target material; and c4) using the plurality of simulated paths to calculate passage time distributions through the target material of the particular thickness, d) using the passage time distributions for the thicknesses of the target material to determine how passage time scales according to thickness of the target material; and e) verifying the simulation results.