Dynamical models of biomarkers and clinical progression for personalized medicine: The HIV context

R Thiébaut 1 Mélanie Prague 2 D Commenges 2
2 SISTM - Statistics In System biology and Translational Medicine
Epidémiologie et Biostatistique [Bordeaux], Inria Bordeaux - Sud-Ouest
Abstract : Mechanistic models, based on ordinary differential equation systems, can exhibit very good predictive abilities that will be useful to build treatment monitoring strategies. In this review, we present the potential and the limitations of such models for guiding treatment (monitoring and optimizing) in HIV-infected patients. In the context of antiretroviral therapy, several biological processes should be considered in addition to the interaction between viruses and the host immune system: the mechanisms of action of the drugs, their phar-macokinetics and pharmacodynamics, as well as the viral and host characteristics. Another important aspect to take into account is clinical progression, although its implementation in such modelling approaches is not easy. Finally, the control theory and the use of intrinsic properties of mechanistic models make them very relevant for dynamic treatment adaptation. Their implementation would nevertheless require their evaluation through clinical trials.
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Soumis le : jeudi 31 août 2017 - 13:42:58
Dernière modification le : mardi 18 septembre 2018 - 16:24:02
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R Thiébaut, Mélanie Prague, D Commenges. Dynamical models of biomarkers and clinical progression for personalized medicine: The HIV context. Advanced Drug Delivery Reviews, Elsevier, 2013, 65, pp.954 - 965. 〈10.1016/j.addr.2013.04.004〉. 〈hal-00933761v2〉



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