Andrew J. Armstrong

This paper develops a memory-driven model to predict enzalutamide resistance in prostate cancer by integrating reinforcement learning and clinical data, outperforming traditional models in capturing treatment dynamics and patient responses.

The paper shows that AR inhibition in prostate cancer causes DNA replication stress, which can be exploited by combining with a TLS inhibitor to enhance treatment efficacy.