Morken, Jason D.

353 Background: One mechanism leading to castrate-resistant prostate cancer (CRPC) is upregulation of CYP17. Abiraterone acetate (AA) inhibits CYP17 and continuous AA administration (CAAA) is one the most common and effective CRPC treatments. Mathematical models can be potentially powerful clinical tools for optimizing treatment strategies and eliminating guess work. Here, we introduce a new model which builds on our previous work (Morken JD, Packer A, Everett RA, Nagy JD, Kuang Y. Mechanisms of resistance to intermittent androgen deprivation therapy identified in prostate cancer patients by novel computational method. Cancer Res 2014;74:2673-83.) and may be capable of predicting how patients will respond to CAAA and intermittent AA administration (IAAA). We are currently proposing a personalized IAAA protocol on the basis of these results. Methods: In this ongoing retrospective study, we use PSA data from patients whom underwent CAAA to validate the accuracy of our model of tumor growth and evolution. The PSA output is driven by dynamics of three cell populations—castration-sensitive (CS), castration-resistant abiraterone-sensitive (CSAS), and castration-sensitive abiraterone-resistant (CSAR) cells. We fit the model output to PSA data to find parameter values which minimize normalized mean squared error (NMSE). Once parameters are obtained, we ran simulations employing various IAAA protocols. Results: The model’s PSA dynamics are highly accurate. NMSE is very low across patients ranging from 0.0001-0.0085. Conclusions: Our results suggest that there exists an IAAA protocol for each patient that, at worst, yields the same time to tumor progression as CAAA, yet improves quality of life and reduces cost. In nearly 20% of patients, IAAA appears to delay tumor progression over CAAA. The model is accurate at predicting how patients will respond to CAAA and IAAA for patients whose PSA is regularly monitored. Near-future work aims to personalize IAAA protocol based on patient pre CRPC PSA dynamics and to identify a protocol which delays progression for most patients.