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Cancers are complex evolving systems that adapt to therapeutic intervention through a suite of resistance mechanisms, therefore whilst fixed maximum tolerated dose therapies generally achieve impressive short-term responses, they unfortunately give way to treatment resistance and tumor relapse. Here we discuss evolutionary therapy, a reactive therapeutic approach that changes and evolves with the tumor being treated. Due to the dynamic feedback between changing treatments and the evolving tumor, mathematical models are essential to drive treatment switch points and predict appropriate dosing and drug combinations. Through the integrated application of mathematical and experimental models as well as clinical data we will illustrate that, evolutionary therapy can drive either tumor control or extinction. Our results strongly indicate that the future of precision medicine shouldn't only be in the development of new drugs but rather in the smarter evolutionary, and model informed, application of preexisting ones.

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