The derangements of mineral metabolism that accompany chronic kidney disease (CKD) greatly increase the risk of cardiovascular mortality. Veterans suffer from CKD and the cardiovascular consequences disproportionately compared to the general population. Amelioration of the biochemical abnormalities, specifically phosphate (Pi), calcium (Ca), and parathyroid hormone (PTH) is associated with superior survival in dialysis patients; however, only a minority of patients can achieve and sustain the levels proposed by Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. The major barriers are the complexity and individual diversity of CKD-MBD and the heterogeneity in individual response to therapy. We have developed and validated a systems biology model encompassing both measurable (serum Ca, Pi, and PTH) as well as non-measurable, clinically relevant parameters of mineral metabolism such as loss of bone mineral and vascular calcification. Applying artificial intelligence techniques of reinforcement learning in combination with our model, we have determined that standard therapeutic approaches targeting Pi, Ca, and PTH may not result in optimal control of the pathophysiologic processes that result in morbidity and mortality. These results suggested two hypotheses to be tested in this proposal. Hypothesis 1: Based on individual biochemical and mineral flux responses to therapy, we can identify phenotypic subsets of CKD-MBD whose courses of disease are distinct, and which mandate different therapeutic approaches. Hypothesis 2: Targeting the abnormal fluxes of mineral, out of bone and into the vascular smooth muscle, will lead to significant refinements in the therapy of CKD-MBD for the individual by incorporating the degree of bone turnover into the recommendations for achieving KDIGO guidelines for biochemical parameters. We will address these hypotheses through the following aims: Aim 1. Obtain human data on non-routinely measured markers of mineral metabolism and cardiovascular health within CKD-MBD. Aim 2. Enhance the Systems Biology Model of CKD-MBD with additional markers of mineral metabolism. Aim 3. Develop Systems Biology guided treatment regimen to CKD-MBD based on clinical end points. Aim 4. Validate treatment regimen for physician’s acceptance using Physician-in-the-Loop approach. This innovative and highly translational approach will advance the over-arching goal of this project to improve clinical outcomes for Veterans with CKD-MBD through the application of personalized therapeutics. The use of large Veteran databases to develop personalized medical therapy for complex disease, exemplified in this application, is a priority for the Department of Veterans Affairs.