Title :
Scheduling of optimal medication strategies for early HIV infection
Author :
Khalili, Samira ; Armaou, Antonios
Author_Institution :
Pennsylvania State Univ., University Park
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;
Conference_Titel :
American Control Conference, 2007. ACC '07
Conference_Location :
New York, NY
Print_ISBN :
1-4244-0988-8
Electronic_ISBN :
0743-1619
DOI :
10.1109/ACC.2007.4282889