275

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Issue 275: Cancer research has traditionally focused on developing new agents, but an underexplored question is that of the dose and frequency of existing drugs. Most drugs are administered according to predetermined schedules that seek to deliver the maximum tolerated dose and are only adjusted for toxicity. However, over the past decade it has become clear that cancers are complex and evolving systems, which in our opinion require for a more dynamic and personalized approach. In this perspective, we bring together key concepts and research on treatment scheduling from across different fields and advocate for a synthesis in which each patient is mapped to the strategy that best matches their current disease characteristics and treatment objectives (their 'tumorscape', depicted here). Furthermore, we discuss how to achieve this level of personalization, we need mathematical modeling, and we conclude with promising examples of model-guided schedule personalization, and a call to action to address key outstanding challenges.