Understanding and effectively modeling the dynamics of cancer and treatment affected normal tissues at all biocomplexity levels by using any efficient combination of mathematical and computer modeling approaches (discrete, continuous, deterministic, stochastic, analytical, numerical etc.) is a fundamental research challenge in oncology. Obviously this target presupposes success in understanding and modeling numerous critical mechanisms involved in cancer and affected normal tissue development and treatment response, as well as the subsequent integration of all those modeling modules. As the demands of such an endeavour are especially high, a parallelism with the history of Newtonian physics might serve as a source of guidance and inspiration. It has been suggested that cancer epitomizes the entire biology. In this context a title like: "Philosophiae Naturalis Principia Mathematica: Pars II, Materia Vivens" (Mathematical Principles of Natural Philosophy: Part II, Living Matter) might to some extent describe the collaborative and heavily multidisciplinary efforts on a worldwide scale to apply the analytical way of thinking on the description of natural phenomena (mechanisms) involving living matter and especially on those related to cancer. Obviously stochasticity is one of the key players in such an approach. A thorough, quantitative, rigorously clinically validated and exploitable understanding of such multi-scale phenomena is expected to dramatically accelerate the achievement of cancer cure on a patient individualized basis through treatment optimization in silico (on the computer). Such an expectation seems also to be compatible with the US National Cancer Program's goal of eliminating the suffering and death due to cancer by 2015. In this context the term In Silico Oncology has been proposed to denote a new scientific, technological and clinical discipline aiming at both understanding the multiscale cancer and related biological phenomena and optimize treatment in the patient individualized context.
References
G. Stamatakos, based on " Spotlight on Cancer Informatics," Cancer Informatics No 2, pp.99-102, 2006.
What is in silico oncology?
In Silico Oncology is a complex and multiscale combination of sciences and technologies in order to simulate malignant tumour growth and tumour and normal tissue response to therapeutic modalities at all levels of biocomplexity. The aim is to better understand cancer and related phenomena and to optimize therapeutic interventions by performing in silico (on the computer) experiments based on the individual data (clinical, imaging, histopathologic, molecular) of the patient.
