A Network-Based Precision Medicine Platform for Personalized Treatment of Multiple Myeloma.
Multiple Myeloma (MM) is an incurable malignancy of bone marrow plasma cells affecting more than 20,000 patients each year, with a median survival after diagnosis of approximately 6 years. Despite recent advancements in therapy, the disease remains fatal in most patients. Genetic mutations have been characterized for MM, but the causes of MM pathogenesis are still unclear. Due to the nature of this disease, a personalized therapeutic approach would likely improve patient outcomes for MM. We propose to develop a complete “bench-to-bedside” intelligent learning precision medicine platform for personalized cancer therapy based on a novel comprehensive integrative network approach. Importantly, the system will employ reinforcement learning techniques to improve drug recommendations based on physician feedback and treatment outcomes.