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Modelling targets for anticancer drug control optimisation in physiologically structured cell population models

Frédérique Billy 1 Jean Clairambault 1, 2 Olivier Fercoq 3 Tommaso Lorenzi 4 Alexander Lorz 1, 2 Benoît Perthame 1, 2
2 BANG - Nonlinear Analysis for Biology and Geophysical flows
LJLL - Laboratoire Jacques-Louis Lions, Inria Paris-Rocquencourt
3 MAXPLUS - Max-plus algebras and mathematics of decision
CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique, Inria Saclay - Ile de France
Abstract : The main two pitfalls of therapeutics in clinical oncology, that limit increasing drug doses, are unwanted toxic side effects on healthy cell populations and occurrence of resistance to drugs in cancer cell populations. Depending on the constraint considered in the control problem at stake, toxicity or drug resistance, we present two different ways to model the evolution of proliferating cell populations, healthy and cancer, under the control of anti-cancer drugs. In the first case, we use a McKendrick age-structured model of the cell cycle, whereas in the second case, we use a model of evolutionary dynamics, physiologically structured according to a continuous phenotype standing for drug resistance. In both cases, we mention how drug targets may be chosen so as to accurately represent the effects of cytotoxic and of cytostatic drugs, separately, and how one may consider the problem of optimisation of combined therapies.
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Frédérique Billy, Jean Clairambault, Olivier Fercoq, Tommaso Lorenzi, Alexander Lorz, et al.. Modelling targets for anticancer drug control optimisation in physiologically structured cell population models. ICNAAM 2012 - 10th international conference of numerical analysis and applied mathematics, Simos, Thodoros, Sep 2012, Kos, Greece. pp.1323-1326, ⟨10.1063/1.4756399⟩. ⟨hal-00780721⟩

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