[Mathematical dynamical models for personalized medicine]

Med Sci (Paris). 2014 Nov:30 Spec No 2:23-6. doi: 10.1051/medsci/201430s205. Epub 2014 Nov 17.
[Article in French]

Abstract

One of the necessary conditions to perform any personalized medicine is to obtain good individual predictions. In addition to the numerous markers available (omics data), the methods used to analyze the data are very important too. We are presenting an example of mathematical dynamical mechanistic model that could be used for adapting the antiretroviral treatment in patients infected by the human immunodeficiency virus. The interest of this type of approach is to build a model based on biological knowledge about the interaction between markers and therefore to allow for a better predictive power.

Publication types

  • English Abstract

MeSH terms

  • Anti-HIV Agents / pharmacokinetics
  • Anti-HIV Agents / therapeutic use
  • Azacitidine / pharmacokinetics
  • Azacitidine / therapeutic use
  • CD4 Lymphocyte Count
  • CD4-Positive T-Lymphocytes / virology
  • Dideoxynucleosides / pharmacokinetics
  • Dideoxynucleosides / therapeutic use
  • HIV Infections / drug therapy
  • HIV Infections / immunology
  • HIV Infections / virology
  • HIV-1 / drug effects
  • HIV-1 / enzymology
  • HIV-1 / physiology
  • HLA-B Antigens / genetics
  • Humans
  • Lamivudine / pharmacokinetics
  • Lamivudine / therapeutic use
  • Models, Theoretical*
  • Precision Medicine*
  • Receptors, CCR5 / genetics
  • Reverse Transcriptase Inhibitors / pharmacokinetics
  • Reverse Transcriptase Inhibitors / therapeutic use
  • Virus Attachment

Substances

  • Anti-HIV Agents
  • CCR5 protein, human
  • Dideoxynucleosides
  • HLA-B Antigens
  • HLA-B*57:01 antigen
  • Receptors, CCR5
  • Reverse Transcriptase Inhibitors
  • Lamivudine
  • Azacitidine
  • abacavir