Taking side effects into account for HIV medication. 2010

Vicente Costanza, and Pablo S Rivadeneira, and Federico L Biafore, and Carlos E D'Attellis
"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

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.

UI MeSH Term Description Entries
D008954 Models, Biological Theoretical representations that simulate the behavior or activity of biological processes or diseases. For disease models in living animals, DISEASE MODELS, ANIMAL is available. Biological models include the use of mathematical equations, computers, and other electronic equipment. Biological Model,Biological Models,Model, Biological,Models, Biologic,Biologic Model,Biologic Models,Model, Biologic
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D004305 Dose-Response Relationship, Drug The relationship between the dose of an administered drug and the response of the organism to the drug. Dose Response Relationship, Drug,Dose-Response Relationships, Drug,Drug Dose-Response Relationship,Drug Dose-Response Relationships,Relationship, Drug Dose-Response,Relationships, Drug Dose-Response
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D015496 CD4-Positive T-Lymphocytes A critical subpopulation of T-lymphocytes involved in the induction of most immunological functions. The HIV virus has selective tropism for the T4 cell which expresses the CD4 phenotypic marker, a receptor for HIV. In fact, the key element in the profound immunosuppression seen in HIV infection is the depletion of this subset of T-lymphocytes. T4 Cells,T4 Lymphocytes,CD4-Positive Lymphocytes,CD4 Positive T Lymphocytes,CD4-Positive Lymphocyte,CD4-Positive T-Lymphocyte,Lymphocyte, CD4-Positive,Lymphocytes, CD4-Positive,T-Lymphocyte, CD4-Positive,T-Lymphocytes, CD4-Positive,T4 Cell,T4 Lymphocyte
D015497 HIV-1 The type species of LENTIVIRUS and the etiologic agent of AIDS. It is characterized by its cytopathic effect and affinity for the T4-lymphocyte. Human immunodeficiency virus 1,HIV-I,Human Immunodeficiency Virus Type 1,Immunodeficiency Virus Type 1, Human
D015658 HIV Infections Includes the spectrum of human immunodeficiency virus infections that range from asymptomatic seropositivity, thru AIDS-related complex (ARC), to acquired immunodeficiency syndrome (AIDS). HTLV-III Infections,HTLV-III-LAV Infections,T-Lymphotropic Virus Type III Infections, Human,HIV Coinfection,Coinfection, HIV,Coinfections, HIV,HIV Coinfections,HIV Infection,HTLV III Infections,HTLV III LAV Infections,HTLV-III Infection,HTLV-III-LAV Infection,Infection, HIV,Infection, HTLV-III,Infection, HTLV-III-LAV,Infections, HIV,Infections, HTLV-III,Infections, HTLV-III-LAV,T Lymphotropic Virus Type III Infections, Human
D017711 Nonlinear Dynamics The study of systems which respond disproportionately (nonlinearly) to initial conditions or perturbing stimuli. Nonlinear systems may exhibit "chaos" which is classically characterized as sensitive dependence on initial conditions. Chaotic systems, while distinguished from more ordered periodic systems, are not random. When their behavior over time is appropriately displayed (in "phase space"), constraints are evident which are described by "strange attractors". Phase space representations of chaotic systems, or strange attractors, usually reveal fractal (FRACTALS) self-similarity across time scales. Natural, including biological, systems often display nonlinear dynamics and chaos. Chaos Theory,Models, Nonlinear,Non-linear Dynamics,Non-linear Models,Chaos Theories,Dynamics, Non-linear,Dynamics, Nonlinear,Model, Non-linear,Model, Nonlinear,Models, Non-linear,Non linear Dynamics,Non linear Models,Non-linear Dynamic,Non-linear Model,Nonlinear Dynamic,Nonlinear Model,Nonlinear Models,Theories, Chaos,Theory, Chaos
D019380 Anti-HIV Agents Agents used to treat AIDS and/or stop the spread of the HIV infection. These do not include drugs used to treat symptoms or opportunistic infections associated with AIDS. AIDS Drug,AIDS Drugs,Anti-AIDS Agents,Anti-AIDS Drug,Anti-HIV Agent,Anti-HIV Drug,Anti-AIDS Drugs,Anti-HIV Drugs,Agent, Anti-HIV,Agents, Anti-AIDS,Agents, Anti-HIV,Anti AIDS Agents,Anti AIDS Drug,Anti AIDS Drugs,Anti HIV Agent,Anti HIV Agents,Anti HIV Drug,Anti HIV Drugs,Drug, AIDS,Drug, Anti-AIDS,Drug, Anti-HIV,Drugs, AIDS,Drugs, Anti-AIDS,Drugs, Anti-HIV

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