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Mathematical models of thrombosis are currently used to study clinicalscenarios of pathological thrombus formation. Most of these models involveinherent uncertainties that must be assessed to increase the confidence inmodel predictions and identify avenues of improvement for both thrombosismodeling and anti-platelet therapies. In this work, an uncertaintyquantification analysis of a multi-constituent thrombosis model is performedconsidering a common assay for platelet function (PFA-100). The analysis isperformed using a polynomial chaos expansion as a parametric surrogate for thethrombosis model. The polynomial approximation is validated and used to performa global sensitivity analysis via computation of Sobol' coefficients. Six outof fifteen parameters were found to be influential in the simulationvariability considering only individual effects. Nonetheless, parameterinteractions are highlighted when considering the total Sobol' indices. Inaddition to the sensitivity analysis, the surrogate model was used to computethe PFA-100 closure times of 300,000 virtual cases that align well withclinical data. The current methodology could be used including commonanti-platelet therapies to identify scenarios that preserve the hematologicalbalance.

Uncertainty quantification of a thrombosis model considering the clotting assay PFA-100