This work proposes a method to construct a state-shared model for multiple_input multiple_output (MIMO) systems. A state_shared model is defined as a linear time invariant state_space structure that is driven by measurement signals _the plant outputs and the manipulated variables, but shared by different multiple input/output models. The genesis of the state_shared model is based on a particular reduced non_minimal realization. Any such realization necessarily fulfills the requirement that the output of the state_shared model is an asymptotically correct estimate of the output of the plant, if the process model is selected appropriately. The approach is demonstrated on a nonlinear MIMO system - a physiological model of calcium fluxes that controls muscle contraction and relaxation in human cardiac myocytes. This work proposes a construct to a state-shared model for multiple_input multiple_output (MIMO) systems. A state_shared model is defined as a linear time invariant state_space structure that is driven by measurement signals _ the plant outputs and the manipulated variables, but shared by different multiple input / output models. The genesis of the state_shared model is based on a particular reduced non_minimal realization. The genesis of the state_shared model is based on a particular reduced non_minimal realization. model is selected appropriately. The approach is demonstrated on a nonlinear MIMO system - a physiological model of calcium fluxes that controls muscle contraction and relaxation in human cardiac myocytes.