Computational simulations of the immune system for personalized medicine: State of the art and challenges

Pappalardo, Francesco, Zhang, Ping, Halling-Brown, Mark, Basford, Kaye E., Scalia, Antonio, Shepherd, Adrian, Moss, David, Motta, Santo and Brusic, Vladimir (2008) Computational simulations of the immune system for personalized medicine: State of the art and challenges. Current Pharmacogenomics and Personalized Medicine, 6 4: 260-271. doi:10.2174/187569208786733839

Author Pappalardo, Francesco
Zhang, Ping
Halling-Brown, Mark
Basford, Kaye E.
Scalia, Antonio
Shepherd, Adrian
Moss, David
Motta, Santo
Brusic, Vladimir
Title Computational simulations of the immune system for personalized medicine: State of the art and challenges
Journal name Current Pharmacogenomics and Personalized Medicine   Check publisher's open access policy
ISSN 1875-6921
Publication date 2008-12-04
Sub-type Article (original research)
DOI 10.2174/187569208786733839
Volume 6
Issue 4
Start page 260
End page 271
Total pages 12
Editor Someya, Toshiyuki
Place of publication Netherlands
Publisher Bentham Science Publishers
Language eng
Subject C1
920108 Immune System and Allergy
060108 Protein Trafficking
Abstract The main goal of pharmacogenomics is to study the effects of genetic variation on patient responses to therapies. Its applications range from the evaluation of safety and efficacy of treatment to the optimization of therapies and therapeutic regimens. Pharmacogenomics is becoming increasingly important in immunology, for the development of new generation vaccines, immunotherapies and transplantation. The human immune system is a complex and adaptive learning system which operates at multiple levels: molecules, cells, organs, organisms, and groups of organisms. Immunologic research, both basic and applied, needs to deal with this complexity. We increasingly use mathematical modeling and computational simulation in the study of the immune system and immune responses. Thus, quantitative models that appropriately capture the complexity in architecture and function of the immune system are an integral component of the personalized medicine efforts. In silico models of the immune system can provide answers to a variety of questions, including understanding the general behavior of the immune system, the course of disease, effects of treatment, analysis of cellular and molecular interactions, and simulation of laboratory experiments. We herein present the ImmunoGrid project that integrates molecular and system level models of the immune system and processes for in silico studies of the immune function. The ImmunoGrid simulator uses Grid technologies, enabling computational simulation of the immune system at the natural scale, perform a large number of simulated experiments, capture the diversity of the immune system between individuals, and provide a basis for therapeutic approaches tailored to the individual genetic make-up.
Keyword Pharmacogenomics
Patient responses
Human immune system
Immunologic research
ImmunoGrid project
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

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