Depicting Radium223 therapy efficacy for prostate cancer bone metastasis: a mathematical modeling approach

Radium223 (Rad223) has lately improved survival in prostate cancer bone metastatic patients. However, clinical response is often followed by relapse and disease progression, and associated mechanisms of efficacy and resistance are poorly understood. Research efforts to overcome this gap require substantial time and resource investment. Computational models, integrated with experimental data, can overcome this limitation and drive research in a more effective fashion. Accordingly, we developed an agent-based model of prostate cancer bone metastasis progression and response to Rad223 as an agile platform to maximize its efficacy. The driving coefficients were calibrated on ad hoc experimental observations retrieved from intravital microscopy and the outcome further validated, in vivo. The in silico tumor growth matched in vivo trend with 98.3% confidence. Tumor size determined efficacy of Rad223, with larger lesions insensitive to therapy, while medium- and micro-sized tumors displayed up to 5.02 and 152.28-fold size decrease compared to control-treated tumors, respectively. Eradication events occurred in 65 ± 2% of cases in micro-tumors only. In addition, Rad223 lost any therapeutic effect, also on micro-tumors, for distances bigger than 400 μm from the bone interface. This model has the potential to be further developed to test additional bone targeting agents such as other radiopharmaceuticals or bisphosphonates.