Preventing Evolutionary Rescue in Cancer

Cancer therapies can fail due to the ability of cancer cells to adapt and gain resistance against anti-cancer drugs. Standard therapies wait until evidence of rebound prior to starting a new drug regimen. Working with Srishti Patil, Dr. Noble, and Dr. Viossat, we investigate the theoretical merits of a strategy to switch anti-cancer drug regimens when the cancer population is still below the detectable threshold. In this state, the cancer cell population is vulnerable to stochastic extinction. Cancer cell populations are modeled via stochastic equations (with exponentially distributed individual birth, death, and mutation rates). We perform computational and mathematical analysis to validate this strategy on this model.