Modeling of Optimal Targeted Therapies Using Drug-Loaded Magnetic Nanoparticles for Liver Cancer

@article{mellal2016,
  author = {Mellal, Lyès and Folio, David and Belharet, Karim and
    Ferreira, Antoine},
  publisher = {IEEE},
  title = {Modeling of {Optimal} {Targeted} {Therapies} {Using}
    {Drug-Loaded} {Magnetic} {Nanoparticles} for {Liver} {Cancer}},
  journal = {IEEE Transactions on NanoBioscience},
  volume = {15},
  number = {3},
  pages = {265-274},
  date = {2016-05-01},
  url = {https://dfolio.fr/publications/articles/2016mellalTNB.html},
  doi = {10.1109/tnb.2016.2535380},
  issn = {1536-1241},
  langid = {en},
  abstract = {To enhance locoregional therapies for liver cancer
    treatment, we propose in this study a mathematical model to optimize
    the transcatheter arterial delivery of therapeutical agents. To
    maximize the effect of the treatment and minimize adverse effects on
    the patient, different mathematical models of the tumor growth are
    considered in this study to find the optimal number of the
    therapeutic drug-loaded magnetic nanoparticles to be administered.
    Three types of therapy models are considered, e.g. angiogenesis
    inhibition therapy, chemotherapy and radiotherapy. We use
    state-dependent Riccati equations (SDRE) as an optimal control
    methodology framework to the Hahnfeldt’s tumor growth formulation.
    Based on this, design optimal rules are derived for each therapy to
    reduce the growth of a tumor through the administration of
    appropriate dose of anti-angiogenic, radio- and chemo-therapeutic
    agents. Simulation results demonstrate the validity of the proposed
    optimal delivery approach, leading to reduced intervention time, low
    drug administration rates and optimal targeted delivery.}
}