Patient-Specific Modeling and Model Predictive Control Approach to Personalized Optimal Anemia Management.

Abstract

In the condition of anemia, kidneys produce less erythropoietin hormone to stimulate the bone marrow to make red blood cells (RBC) leading to a reduced hemoglobin (Hgb) level, also known as chronic kidney disease (CKD). External recombinant human erythropoietin (EPO) is administrated to maintain a healthy level of Hgb, i.e., 10 - 12 g/dl. The semi-blind robust model identification method is used to obtain a personalized patient model using minimum dose-response data points. The identified patient models are used as predictive models in the model predictive control (MPC) framework. The simulation results of MPC for different CKD patients are compared with those obtained from the existing clinical method, known as anemia management protocol (AMP), used in hospitals. The in-silico results show that MPC outperforms AMP to maintain healthy levels of Hgb without over-or-under- shoots. This offers a considerable performance improvement compared to AMP which is unable to stabilize EPO dosage and shows oscillations in Hgb levels throughout the treatment.Clinical Relevance-This research work provides a framework to help clinicians in decision-making for personalized EPO dose guidance using MPC with semi-blind robust model identification using minimum clinical patient dose-response data.