This project has two major objectives. First, to develop a MIMO model-based predictive closed-loop system to guide patient-individualized ICU sedation (using the previous knowledge of SISO control during anesthesia). Simulations will be applied to virtually optimize the control system. Then, the controller will be implemented in the existing software platform RUGLOOP, capable of managing vital signs monitoring and controlling drug infusioon technology. Second, we will validate the robustness of this system both in simulations and clinical conditions in the ICU. Finally, we will investigate if automation in guidancce of ICU sedation will optimize patient stability and outcome.