• DocumentCode
    3171986
  • Title

    Scheduling of optimal medication strategies for early HIV infection

  • Author

    Khalili, Samira ; Armaou, Antonios

  • Author_Institution
    Pennsylvania State Univ., University Park
  • fYear
    2007
  • fDate
    9-13 July 2007
  • Firstpage
    4112
  • Lastpage
    4117
  • Abstract
    This work focuses on scheduling the optimal treatment strategy for patients at the early stage of HIV infection. Unlike patients with an established HIV infection, complete eradication of the infection is still possible at this stage. Treatment has the ability to further increase the probability of eradication. However, high dosages of drugs should be avoided, if possible, because of toxicity effects and high cost of the current drugs. Stochastic simulation is capable of determining the infection probability at early infection stage. Consequently, to obtain acceptable treatment strategies, an optimization problem was formulated, employing a stochastic model to predict the response of an average patient to treatment. Treatment strategies for prompt and also a few days latency in treatment initiation were obtained. Results were compared with constant treatment strategy and were shown to be more successful.
  • Keywords
    diseases; patient treatment; HIV infection; infection probability; optimal medication strategy scheduling; optimal patient treatment strategy; stochastic model; stochastic simulation; Biological system modeling; Costs; Diseases; Drugs; Human immunodeficiency virus; Mathematical model; Medical treatment; Predictive models; Stochastic processes; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2007. ACC '07
  • Conference_Location
    New York, NY
  • ISSN
    0743-1619
  • Print_ISBN
    1-4244-0988-8
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2007.4282889
  • Filename
    4282889