Taking side effects into account for HIV medication.
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.
Costanza
Vicente
V
"Grupo de Sistemas No Lineales", Institutode Desarrollo Tecnológico para la Industria Química, Facultad de Ingeniería Qímica (Universidad Nacional del Litoral, Consejo Nacional de Investigaciones Científicas y Técnicas), 3000 Santa Fe, Argentina. tsinoli@santafe-conicet.gov.ar
Rivadeneira
Pablo S
PS
Biafore
Federico L
FL
D'Attellis
Carlos E
CE
D000465:Algorithms; D019380:Anti-HIV Agents / Q000008:administration & dosage / Q000009:adverse effects*; D023241:Antiretroviral Therapy, Highly Active / Q000009:adverse effects / Q000379:methods; D015496:CD4-Positive T-Lymphocytes; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control; D015658:HIV Infections / Q000188:drug therapy*; D015497:HIV-1; D006801:Humans; D008954:Models, Biological; D017711:Nonlinear Dynamics; D019562:Viral Load
D019380:Anti-HIV Agents