Randomized approaches for identifiability analysis and model reduction in fibrin polymerization kinetics

Abstract

In the early stages of wound healing, fibrin polymerization plays an essential role in clot formation and subsequent healing. Sialic acid is known to impact fibrin polymerization kinetics, but the exact mechanisms are not well understood. We build upon existing studies using a reaction system-based mathematical model for fibrin matrix formation by introducing randomization to local sensitivity-based parameter identifiability analysis, with biochemical reaction rates serving as the model parameters. The application of randomization to initial parameter values facilitates greater exploration throughout parameter space. Our approach generates several model realizations that are screened for the quality of curve fits to data for fibrin matrix concentration and then used to determine consistently unidentifiable parameters as candidates for removal. Among these candidate reduced models, the most accurate one is selected and then used to estimate and compare influential parameter values from data corresponding to three experimental designs with different levels of sialic acid. Using statistical significance tests on the estimated values of influential parameters, results are interpreted to inform the potential mechanisms that may be altered by sialic acid concentration on fibrinogen.