NDLI: Parameters identification of HIV dynamic models for HAART treated patients: A comparative study

Content Provider	IEEE Xplore Digital Library
Author	Laurino, M. Landi, A. Pannocchia, G.
Copyright Year	2014
Description	Author affiliation: Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy (Landi, A.) \|\| Dept. of Civil & Ind. Eng., Univ. of Pisa, Pisa, Italy (Pannocchia, G.) \|\| Dept. of Surg., Med., Mol., & Critical Area Pathology, Univ. of Pisa, Pisa, Italy (Laurino, M.)
Abstract	We present a comparative study of parameters identification of HIV dynamic models for naive patients that are treated with two different HAART (Highly Active Anti-Retroviral Therapy) protocols during a period of 48 weeks. Three HIV models of increasing complexity (in terms of number of state variables and parameters) have been chosen, and for each one the model parameters are computed by solving a nonlinear optimization problem via sequential quadratic programming (SQP). Model parameters are divided into “group dependent”, common to all patients treated with same HAART protocol, and “patient dependent”, specific for each patient, and are estimated in a way that an overall cost function comprising the fitting error of CD4+ concentration and viral load measurements. A preliminary parameter space grid search algorithm is performed in order to find a suitable initial guess for the SQP algorithm. Numerical results indicate that all considered models can give a good matching despite the scarcity of available measurements for each patient, and in this limited situation the minimal model appears to be (slightly) more effective than the other models.
Starting Page	2759
Ending Page	2764
File Size	202865
Page Count	6
File Format	PDF
ISBN	9781479932726
ISSN	07431619
e-ISBN	9781479932740
DOI	10.1109/ACC.2014.6859025
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-06-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Human immunodeficiency virus Load modeling Mathematical model Drugs Vectors Immune system Identification Systems biology Modeling and simulation
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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