Structural changes in the cytoskeleton during metastatic transformation make cancer cells more deformable, and recent experimental studies confirm a direct correlation between cell invasiveness and cell deformability. Several microfluidic approaches have recently developed to exploit this cellular property for high-throughput assessment of metastatic risk from small samples of patient’s blood. While demonstrating feasibility in the lab, these technologies often lack a solid theoretical foundation or do not show adequate sensitivity to cellular mechanical properties (“mechanotype”). The long-term goal of this project is to optimize microfluidic tests for metastatic risk assessment, including circulating tumor cell (CTC) isolation and mechanotype analysis, through predictive computational modeling. Specific aims of the presented study are 1) to expand the capability of our custom computational algorithm for viscoelastic cell deformation and migration to simulate cell sorting and CTC isolation in channels with complex geometry, including channels with pillars and bifurcations, and 2) to demonstrate the capability of our algorithm to optimize microfluidic methods for cancer cell mechanotype measurement.