Optimization of the Flow Parameters for a Liver Organ-on-a-Chip Computational Model

Abstract The organ-on-a-Chip (OOC) concept appeared intending to increase the efficiency and effectiveness of R&D activities, and open doors to precision and personalized medicine. However, for such devices to provide adequate results, they must mimic a specific human microenvironment with great accuracy. In the present work, a computational model of an organ-on-a-chip model was developed and optimized by evaluating the effectiveness and characteristics of some optimization methods. To perform the optimization and simulation, a geometry appropriate to the needs was first designed, having in base the current literature. After that, a mesh set capable of maintaining a balance between the accuracy of the results and computational performance was generated and a mesh study was conducted. Then, the simulation and optimization were performed. The latter was conducted by applying two different methods, the Multi-Objective Genetic Algorithm (MOGA) and Nonlinear Programming by Quadratic Lagrangian (NLPQL), for later comparison of results. Bearing in mind the hemodynamics in the liver, the goal of this optimization was to minimize the organ model blood flow mean velocity, in order to allow the adequate transfer of substances between the blood and liver cells.