In reactive multiphase systems, the reactive phase can be manipulated not only by temperature and pressure, but also via coexisting "service" phases. For the exploitation of the full potential of such systems, a model-based reactor design that includes an accurate calculation of the equilibrium composition using advanced thermodynamic models is mandatory. This is of special importance when innovative solvent systems with complex phase behavior are considered. In this work, an equation based model containing reaction kinetics and an advanced equation of state, namely the perturbed-chain statistical associating fluid theory (PC-SAFT), was implemented for large-scale optimization. Exemplified on the hydroformylation of 1-octene it is demonstrated how such a model framework can be used as basis for optimal reactor design. After fitting the PC-SAFT parameters to pure component data the model was used to study the influence of product formation on the solubilities of H-2 and CO. Finally, the reaction conditions were optimized in order to maximize the differential selectivity to the desired product n-nonanal. It is shown that the performance of the hydroformylation reaction system can be significantly increased by optimally controlling temperature, total pressure, and the amount of H-2 and CO in the gas phase. (C) 2013 Elsevier Ltd. All rights reserved.