| Abstract: |
| Finding the optimal balance between over-suppression and under-suppression of the immune response is difficult to achieve in renal transplant patients, all of whom require lifelong immunosuppression. We use a mathematical model of the immune response to kidney transplant and BKV to enhance personalized treatment by application of control theory, and determine an optimal individualized treatment strategy. We design a feedback optimal control using the Receding Horizon Control (RHC) methodology. To address the non-linearity and lack of observations for all model states associated with the dynamical system we use non-linear Kalman Filtering state estimation techniques. |
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