  The aim of this chapter is to provide a brief introduction into the basics of
a top-down multilevel tumor dynamics modeling method primarily based on
discrete entity consideration and manipulation. The method is clinically
oriented, one of its major goals being to support patient individualized
treatment optimization through experimentation in silico (=on the computer).
Therefore, modeling of the treatment response of clinical tumors lies at the
epicenter of the approach. Macroscopic data, including i.a. anatomic and
metabolic tomographic images of the tumor, provide the framework for the
integration of data and mechanisms pertaining to lower and lower biocomplexity
levels such as clinically approved cellular and molecular biomarkers. The
method also provides a powerful framework for the investigation of multilevel
(multiscale) tumor biology in the generic investigational context. The
Oncosimulator, a multiscale physics and biomedical engineering concept and
construct tightly associated with the method and currently undergoing clinical
adaptation, optimization and validation, is also sketched. A brief outline of
the approach is provided in natural language. Two specific models of tumor
response to chemotherapeutic and radiotherapeutic schemes are briefly outlined
and indicative results are presented in order to exemplify the application
potential of the method. The chapter concludes with a discussion of several
important aspects of the method including i.a. numerical analysis aspects,
technological issues, model extensions and validation within the framework of
actual running clinico-genomic trials. Future perspectives and challenges are
also addressed.
