Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran.
National Research Council Canada, Montreal, QC H4P 2R2, Canada; Center for Bioinformatics, McGill University, Montreal, QC H3G 0B1, Canada.
Semin Cancer Biol. 2015 Feb;30:1-3. doi: 10.1016/j.semcancer.2014.06.005. Epub 2014 Jun 24.
The complexity of cancer progression can manifests itself on at least three scales that can be described using mathematical models, namely microscopic, mesoscopic and macroscopic scales. Multiscale cancer models have proven to be advantageous in this context because they can simultaneously incorporate the many different characteristics and scales of complex diseases such as cancer. This has driven the expansion of more predictive data-driven models, coupled to experimental and clinical data. These models are defining the foundations that facilitate the forthcoming design of patient specific cancer therapy. This should be considered as a great leap toward the era of personalized medicine. Consequently, further improvements in mathematical modeling of cancer will lead to the design of more sophisticated cancer therapy approaches.
癌症进展的复杂性至少可以在三个尺度上表现出来，可以使用数学模型来描述，即微观、介观和宏观尺度。多尺度癌症模型已被证明在这方面具有优势，因为它们可以同时纳入癌症等复杂疾病的许多不同特征和尺度。这推动了更多基于数据的预测模型的扩展，这些模型与实验和临床数据相结合。这些模型正在为即将到来的患者特异性癌症治疗设计奠定基础。这可以被视为迈向个性化医疗时代的一大步。因此，癌症数学建模的进一步改进将导致更复杂的癌症治疗方法的设计。
