Leveraging Quantitative Systems Pharmacology and Artificial Intelligence to advance treatment of Chronic Kidney Disease Mineral Bone Disorder

Artificial intelligence is a powerful tool for exploration of complex processes but application to clinical syndromes is challenging. Using a mathematical model describing the movement of calcium and phosphate between body compartments combined with machine learning, we show the feasibility of testing alternative goals of therapy for Chronic Kidney Disease Mineral Bone Disorder while maintaining acceptable biochemical outcomes. These simulations demonstrate the potential for using this platform to generate and test hypotheses in silico rapidly, inexpensively, and safely.