The method to harness the technology behind video games in explaining various biological systems, such as the human immune response to a tuberculosis bacterium has been demonstrated by a study led by an Indian-origin scientist.
By using graphic processing units (GPUs), which drive the spectacular imagery beloved of video gamers, Roshan D'Souza and his team has supercharged agent-based modeling, a powerful but computationally massive forecasting technique.
Computer science student Mikola Lysenko, who wrote the software, demonstrated how a swarm of bright green immune cells surrounds and contains a yellow TB germ on his computer screen.
The visual resembles 3D-animations from a PBS documentary, but are actually virtual T-cells and macrophages-the visual reflection of millions of real-time calculations.
"I've been asked if we ran this on a supercomputer or if it's a movie," said D'Souza.
He claimed that their model is much faster than high-tech agent modelling toolkits. However, the researchers claim that this current effort is small potatoes.
"We can do it much bigger. This is nowhere near as complex as real life," said D'Souza.
Now he wants to model how a TB infection could spread from the lung to the patient's lymphatic system, blood and vital organs.
Dr. Denise Kirschner, of the University of Michigan in Ann Arbor, developed the TB model and gave it to D'Souza's team, which programmed it into a graphic processing unit.
She claims that agent-based modeling hasn't replaced test tubes, but it is providing a powerful new tool for medical research, as computer models offer significant advantages.
"You can create a mouse that's missing a gene and see how important that gene is. But with agent-based modeling, we can knock out two or three genes at once," says Kirschner.
Particularly, agent-based modeling gives researchers an edge over other methodologies: they can virtually test the human response to serious insults, such as injury and infection.
Although agent-based modeling may never replace the laboratory entirely, it could reduce the number of dead-end experiments.
"It really helps scientists focus their thinking. The limiting factor has been that these models take a long time to run, and [D'Souza's] method works very quickly and efficiently," said Kirschner.
But D'Souza's team ruled out the problem by using GPUs, which can run models with tens of millions of agents with blazing speed.
"With a 1,400 dollars desktop, we can beat a computing cluster. We are effectively democratizing supercomputing and putting these powerful tools into the hands of any researcher. Every time I present this research, I make it a point to thank the millions of video gamers who have inadvertently made this possible," said D'Souza.