After a mathematical model was offered recently, now the body's immune response to flu may be captured using a computer model developed by scientists at the University of Rochester Medical Center.
Project leaders Dr. Hulin Wu and Dr. Martin S. Zand have revealed that their computer simulation tool is aimed at some day predicting the body's response to .
The researchers claim that they are the first to have successfully tested a computer simulation of major portions of the body's immune reaction to influenza type A, with implications for treatment design and preparation ahead of future pandemics.
They say that the new "global" flu model is built out of preexisting, smaller-scale models that capture in mathematical equations millions of simulated interactions between virtual immune cells and viruses.
"High-speed, accurate computer simulation tools are urgently needed to dissect the relative importance of each attribute of viral strains in their ability to cause disease, and the contribution of each part of the immune system in a successful counterattack. Real world experiments simply cannot be executed fast enough to investigate so many complex surprises, and we must keep pace with viral evolution to reduce loss of life," said Zand.
The researchers have revealed that their model predicts how rapidly the immune system's T and B cells respond to influenza type A virus infection.
They pointed out that depending on the pathogen at hand and a given patient's past exposure, either T cell or B cell responses might play a larger role in clearing the virus. One cell type may lead the immune counterattack in a person with a first-time infection, and another in a patient who has been infected before or vaccinated.
The researchers further revealed that the novel model also predicted that antiviral therapies might be more effective if taken in combination, but only if administered within two days of infection.
Unlike chronic HIV infection, the acute nature of influenza means there is a narrow time window during early infection when interfering with viral replication can reduce viral load.
The model also shows that a strong antibody response, along with local T cell expansion, will be important to ensure protection against future pandemics, suggesting that some unconventional therapies that rapidly boost immune responses might be effective in a worst case scenario of a pandemic influenza virus.
The researchers hope to contribute to the building of models that simulate swine flu infection across the entire U.S. population to better predict its course.
"The right computer model can provide a precise, hands-on way of measuring just how good our theories are about how the system responds to pandemic virus, and how to strengthen our defenses," said Wu.
An article on this research work has been published in the online edition of the Journal of Virology.