Title :
Taking Side Effects into Account for HIV Medication
Author :
Costanza, Vicente ; Rivadeneira, Pablo S. ; Biafore, Federico L. ; D´Attellis, C.E.
Author_Institution :
Grupo de Sist. No Lineales, Univ. Nac. del Litoral, Santa Fe, Argentina
Abstract :
A control-theoretic approach to the problem of designing “low-side-effects” therapies for HIV patients based on highly active drugs is substantiated here. The evolution of side effects during treatment is modeled by an extra differential equation coupled to the dynamics of virions, healthy T-cells, and infected ones. The new equation reflects the dependence of collateral damages on the amount of each dose administered to the patient and on the evolution of the viral load detected by periodical blood analysis. The cost objective accounts for recommended bounds on healthy cells and virions, and also penalizes the appearance of collateral morbidities caused by the medication. The optimization problem is solved by a hybrid dynamic programming scheme that adhere to discrete-time observation and control actions, but by maintaining the continuous-time setup for predicting states and side effects. The resulting optimal strategies employ less drugs than those prescribed by previous optimization studies, but maintaining high doses at the beginning and the end of each period of six months. If an inverse discount rate is applied to favor early actions, and under a mild penalization of the final viral load, then the optimal doses are found to be high at the beginning and decrease afterward, thus causing an apparent stabilization of the main variables. But in this case, the final viral load turns higher than acceptable.
Keywords :
cellular biophysics; diseases; drugs; dynamic programming; medical computing; microorganisms; nonlinear dynamical systems; patient treatment; HIV medication side effects; HIV patients; collateral morbidities; control theoretic approach; extra differential equation; healthy T-cell dynamics; highly active drugs; hybrid dynamic programming scheme; infected cell dynamics; low side effect therapies; optimization problem; periodical blood analysis; viral load evolution; virion dynamics; Antiretroviral drugs; HIV; nonlinear dynamics; optimal control; side effects; Algorithms; Anti-HIV Agents; Antiretroviral Therapy, Highly Active; CD4-Positive T-Lymphocytes; Computer Simulation; Dose-Response Relationship, Drug; Drug Toxicity; HIV Infections; HIV-1; Humans; Models, Biological; Nonlinear Dynamics; Viral Load;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2010.2049845