Bladewatch.com

http://expertvoices.nsdl.org/cornell-cs322/2008/03/23/use-of-computer-simulation-to-personalize-hiv-medications/

Some serious illnesses such as HIV tend to change, or mutate, rapidly within the body of a person suffering from the disease. Any number of factors can impact the ways the viruses mutate. For example, such factors may have to do with the properties of the patient’s genome, the treatments that were chosen earlier, and other biological factors. This leads doctors treating patients with these diseases to resort to a process that involves much guesswork, since it is not always apparent which treatment will work the best.

Recent research preformed at the University College London [1, 2] promises to change this way of working and to provide more robust solutions for professionals in the medical field. By using the techniques of grid computing, Prof. Peter Coveney and his team were able to generate results that test the medications on the Virtual Physiological Human.

Grid computing is the technique that allows researchers to separate their simulations over a large number of CPUs that need not be centrally located [3]. The Virtual Physiological Human is a project that aims to map the human body in a way that “will enable collaborative investigation of the human body as a single complex system” [4]. The application of the distributed computers allowed the time needed to conduct the simulation to be reduced dramatically, despite the huge amounts of data that need to be processed (on the order of 15 GB per simulations). For each patient, two simulations need to be run, one which considers the history of this patient and the other which attempts to predict the mutations of the virus. Currently, it is possible to complete this process in under two weeks.

Check out this interesting article highlighting how Grid/HPC technologies can be used not only in the commerical world, but for research, whether we’re talking about the SETI type solutions or in academic/medical research such as HIV or cancer. I wonder if we will see this kind of technology rolled out more in medical testing?

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