Whether the nom de guerre is Mathematical Oncology, Computational or Systems Biology, Theoretical Biology, Evolutionary Oncology, Bioinformatics, or simply Basic Science, there is no denying that mathematics continues to play an increasingly prominent role in cancer research. Mathematical Oncology-defined here simply as the use of mathematics in cancer research-complements and overlaps with a number of other fields that rely on mathematics as a core methodology. As a result, Mathematical Oncology has a broad scope, ranging from theoretical studies to clinical trials designed with mathematical models. This Roadmap differentiates Mathematical Oncology from related fields and demonstrates specific areas of focus within this unique field of research. The dominant theme of this Roadmap is the personalization of medicine through mathematics, modelling, and simulation. This is achieved through the use of patient-specific clinical data to: develop individualized screening strategies to detect cancer earlier; make predictions of response to therapy; design adaptive, patient-specific treatment plans to overcome therapy resistance; and establish domain-specific standards to share model predictions and to make models and simulations reproducible. The cover art for this Roadmap was chosen as an apt metaphor for the beautiful, strange, and evolving relationship between mathematics and cancer.

中文翻译：

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2019 年数学肿瘤学路线图。

无论其名义是数学肿瘤学、计算或系统生物学、理论生物学、进化肿瘤学、生物信息学，还是简单的基础科学，不可否认的是，数学在癌症研究中继续发挥着越来越重要的作用。数学肿瘤学——这里简单地定义为数学在癌症研究中的应用——与许多其他依赖数学作为核心方法论的领域相互补充和重叠。因此，数学肿瘤学的范围很广，从理论研究到用数学模型设计的临床试验。该路线图将数学肿瘤学与相关领域区分开来，并展示了这一独特研究领域的特定重点领域。该路线图的主题是通过数学、建模和模拟实现医学的个性化。这是通过使用患者特定的临床数据来实现的：制定个体化筛查策略以早期发现癌症；预测治疗反应；设计适应性的、针对患者的治疗计划以克服治疗阻力；并建立特定领域的标准来共享模型预测并使模型和模拟可重复。本路线图的封面艺术被选为数学与癌症之间美丽、奇怪和不断发展的关系的恰当隐喻。