In this study a mathematical model was used to simulate the breakthrough curves of the recombinant 503 antigen of Leishmania infantum chagasi using immobilized metal affinity expanded bed adsorption chromatography. Initially, experimental curves were carried out in different conditions such as superficial liquid velocity, settled bed height as well as the initial 503 antigen concentration. The particle swarm optimization (PSO) algorithm was used for global parameter estimation by a general rate model, which proved to be an efficient tool for parameter estimation in chromatographic processes. Modeling and simulation of the 503 antigen breakthrough curves displayed a good performance during the estimation and validation stages. The highest global process efficiencies obtained was 88.8%. Finally, the validated model was used in the optimization stage, showing the process and column efficiencies of 89.2% and 75.9%, respectively. The results showed the applicability of this approach for modeling and optimization of chromatographic processes. (C) 2016 Elsevier B.V. All rights reserved.