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Modeling the Impact of Anticancer Agents on Metastatic Spreading

A collaboration between MGHI, the CMI-LATP and the Laboratoire de Toxicocinétique et Pharmacocinétique both from Marseille has lead to a publication entitled : Modeling the Impact of Anticancer Agents on Metastatic Spreading S. Benzekry, N. André, A. Benabdallah, J. Ciccolini, C. Faivre, F. Hubert and D. Barbolosi published in Mathematical Modelling of Natural Phenomena.

Among others, we have studied here the modelization of metronomic chemotherapy and its combination with anti-VEGF treatments.

Research Article

Modeling the Impact of Anticancer Agents on Metastatic Spreading S. Benzekry, N. André, A. Benabdallah, J. Ciccolini, C. Faivre, F. Hubert and D. Barbolosi

- CMI-LATP, UMR 6632, Université de Provence, Technopôle Château-Gombert 39, rue F. Joliot-Curie, 13453 Marseille cedex 13, France
- Laboratoire de Toxicocinétique et Pharmacocinétique UMR INSERM 911, CRO2 27, boulevard Jean Moulin, 13005 Marseille, France
- Service d’Hématologie et Oncologie Pédiatrique, Hôpital pour enfants de La Timone Marseille, France
- Metronomics Global Health Initiative

Abstract Treating cancer patients with metastatic disease remains an ultimate challenge in clinical oncology. Because invasive cancer precludes or limits the use of surgery, metastatic setting is often associated with (poor) survival, rather than sustained remission, in patients with common cancers like lung, digestive or breast carcinomas. Mathematical modeling may help us better identify non detectable metastatic status to in turn optimize treatment for patients with metastatic disease. In this paper we present a family of models for the metastatic growth. They are based on four principles : to be as simple as possible, involving the least possible number of parameters, the main informations are obtained from the primary tumor and being able to recover the variety of phenomena observed by the clinicians. Several simulations of therapeutic strategies are presented illustrating possible applications of modeling to the clinic.

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