Multidisciplinary analysis of evolution based Abiraterone treatment for metastatic castrate resistant prostate cancer

Background We present a multidisciplinary approach to clinical trial design and analysis in a pilot study (NCT02415621) in which evolution-based mathematical models guide patient-specific dosing for Abiraterone treatment in men with castrate resistant metastatic prostate cancer. Methods Abiraterone plus prednisone were administered intermittently based on an evolutionary mathematical model. Outcomes are compared to historical controls and a matched contemporaneous cohort who met trial eligibility but received SOC dosing. Longitudinal cohort data allowed modification of pre-trial model parameter estimates. Model simulations of each patient using updated parameters critically evaluated trial design. Results Trial patients, on average, received no abiraterone during 59% of time on treatment. Median Time to Radiographic Progression (TTP) was 30.4 months compared to 14.3 months in the contemporaneous SOC group (p<0.001). All patients in the SOC group have progressed but 4 in the adaptive cohort remain on treatment at >1800 days. Longitudinal trial data found the competition coefficient ratio (αRS/αSR) of sensitive and resistant populations, a critical factor in intratumoral evolution, was 2 to 3-fold higher than pre-trial estimates. Computer simulations using the corrected parameter unexpectedly demonstrated optimal cycling can reduce the resistant cells. Longitudinal data from 4 trial patients who remain on treatment are consistent with model predictions. Modeling results predict protocol changes that will allow similar outcomes in most patients. Conclusions Administration of abiraterone using evolution-based mathematical models decreased drug dosing and increased radiographic TTP. Integration of mathematical models into trial design identifies novel insights into key treatment parameters and provides optimization strategies for follow-up investigations.