title: Mixed immunotherapy and chemotherapy of tumors: feedback design and model updating schemes.
abstract: In this paper, a recently developed model governing the cancer growth on a cell population level with combination of immune and chemotherapy is used to develop a reactive (feedback) mixed treatment strategy. The feedback design proposed here is based on nonlinear constrained model predictive control together with an adaptation scheme that enables the effects of unavoidable modeling uncertainties to be compensated. The effectiveness of the proposed strategy is shown under realistic human data showing the advantage of treatment in feedback form as well as the relevance of the adaptation strategy in handling uncertainties and modeling errors. A new treatment strategy defined by an original optimal control problem formulation is also proposed. This new formulation shows particularly interesting possibilities since it may lead to tumor regression under better health indicator profile.
authors.affiliation: CNRS/GIPSA-Lab/University of Grenoble, BP 46, Domaine Universitaire, rue de la Houille Blanche, 38400 Saint Martin d'Hères, France. sophie.chareyron@inpg.fr
authors.forename: S
authors.initials: S
authors.lastname: Chareyron
authors.forename: M
authors.initials: M
authors.lastname: Alamir
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use*; D003131:Combined Modality Therapy; D003198:Computer Simulation; D005246:Feedback; D006801:Humans; D007167:Immunotherapy; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000188:drug therapy / Q000276:immunology / Q000628:therapy*; D016896:Treatment Outcome
chemical_list: D000970:Antineoplastic Agents