Optimisation of Cancer Drug Treatments Using Cell Population Dynamics - Mathematical Methods and Models in Biomedicine - page 293

Focusing on cell population models, for cancer is never the problem of a single
cell, we thus advocate in this chapter the interest of using structured cell population
dynamics, to be further integrated in a multiscale setting, in the optimisation of drug
delivery in oncology. From intracellular molecular dynamics to human populations,
aiming at getting closer to actual clinical applications, we clearly have still hard
work ahead, both in modelling and model analysis and in experimental identification
and validation. Various therapeutic optimisation methods have been reviewed in
their principles, and we have shown, focusing even more on linear population
growth for cancer and for healthy cells, how it is possible to choose one, adapted to
the model under consideration. The question of therapeutic optimisation in cancer
is vast, and it may be treated in quite different manners, which have to be adapted
to the particular clinical problem at stake. Nevertheless, modelling the target, the
means of control, and taking account of the known clinical issues, there is still room
for mathematical developments to pave the way for optimisation methods that will
be able to face always more clinical challenges, all the more so as more links will
be developed between mathematicians and clinicians.
Acknowledgments Access to data mentioned in Subsection 7.4 has been provided to us by G. van
der Horst's lab in Erasmus Medical Centre (Rotterdam, The Netherlands); it was supported by a
grant from the European Research Area in Systems Biology (ERASysBio+) and FP7 to the French
National Research Agency (ANR) #ANR-09-SYSB-002-004 for the research network Circadian
and Cell Cycle Clock Systems in Cancer (C5Sys) coordinated by Francis Levi (Villejuif, France).
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