Computer Simulations And Modeling In
Oncology: Methods And Applications
Author(s)
C. Guiot, P. Paolo Delsanto & A. S. Gliozzi
Abstract
Computational models and simulations can be powerful tools for gaining an
insight into the extremely complex mechanisms governing tumoral growth. In
order to be relied upon, however, they must be validated by comparison with
sufficiently long strings of experimental or observational data. For obvious
ethical reasons it is virtually impossible to obtain such data \“in vivo”. It may be,
therefore, expedient to study the growth of tumoral lines \“in vitro” or \“ex vivo”,
i.e. by transplanting them into lab animals (e.g., mice). In fact, experiments with
as many as 900 successive transplants into new healthy mice have been
performed. Using a recently proposed technique for the analysis of experimental
datasets (the Phenomenological Universalities Approach), we have succeeded to
reproduce, to an excellent level of reliability, the results of such \“multipassage”
growth and to explain quantitatively why the growth curves become
progressively steeper at each new transplant. We believe that our method could
also be applied to study metastatic diffusion and suggest new experiments to
further validate our approach and results.
Keywords: tumor models, growth models, data analysis.
Keywords
tumor models, growth models, data analysis.
Related Book
Other papers in this volume
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