Conseil national de recherches du Canada. Thérapeutique en santé humaine
Texte, Chapitre de livre
artificial neural network; cancer modeling; cancer therapy; mathematical model; network biology; personalized medicine; prediction; rating scale; systems biology
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.
Date de publication
Seminars in Cancer Biology30 (février 2015) : 1–3.