Microsoft Aims to Help Scientists Move Past Excel, Make Sense of Gene Data Overload

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Microsoft’s headquarters—the Seattle-based Fred Hutchinson Cancer Research Center. It’s one of the world’s leading biomedical research centers with 2,700 employees and an annual budget of more than $390 million. “We look forward to exploring the potential of Amalga Life Sciences to help us understand data in a rich and efficient way and ultimately help us meet our vision of enabling personalized medicine,” Hutch president Lee Hartwell, a Nobel Laureate, said in a Microsoft statement.

This program is being marketed to major research centers like the Hutch, and to all the Big Pharma companies and Big Biotech companies, Karkanias says. They have different motivations for giving this kind of program a try, he says. The basic researchers see the value in being able to sort through their vast piles of data more efficiently. One analogy comes from cartography. It’s possible to get from New York to Los Angeles by looking at a paper map and following highway turns and directions, but it’s more efficient to let a GPS device navigate along the way.

The pharmaceutical and biotech companies are interested mainly in getting various IT programs to reach efficient conclusions about drug candidates more quickly. The central problem of these industries is that only one out of 10 drugs entering clinical trials ever passes the gauntlet of tests required to win FDA approval, and companies struggle to identify which patients are likely to benefit or suffer unusual side effects, because of their particular genetic profile. They want software to help them increase this success rate, bringing down the cost of development, Karkanias says.

He made an analogy here to the aviation world, in which drug developers are essentially flying now without radar. Once radar came along, it enabled many, many more planes to fly simultaneously in the sky, and to do it much more safely. “Instead of one of 10 drugs succeeding in clinical trials, maybe only one out of 10 will fail,” Karkanias says, of the potential payoff of sophisticated health IT systems. This sounded way too utopian to me, then again, he used to work at Merck, so he’s no greenhorn to the challenges of the pharmaceutical business.

I checked with a hospital IT expert, Tom Wood of Swedish Medical Center in Seattle, to see if the similar version of Amalga is as good as it’s cracked up. He didn’t rave, but the answer was yes. The Amalga version that Microsoft sells to hospitals is easy to use, doesn’t require much support from the IT department, and is good at its stated purpose of fostering compatibility among many proprietary IT programs, says Wood, chief medical information officer at Swedish.

“We liked what we saw,” he says. But Swedish didn’t buy it, because it already has a single integrated software system to begin with (Epic), and no need to iron out the traditional kinks between systems, Wood says.

Microsoft hasn’t yet announced any partnerships with the big companies that make scientific instruments that pump out all this genomic data—companies like Roche, Life Technologies, and Illumina—although Karkanias definitely left me with an impression to stay tuned on that front.

Karkanias also says he’s not aware of any competitors with a product that has the breadth of scope to communicate across IT platforms as Amalga Life Sciences does. Other programs tend to be “highly vertical” or specialized to perform a narrow function, he says.

The big picture is to make drug development less of a risky, conjecture-based business, and provide much smarter predictive modeling of how drugs will behave in the body before spending years of effort and millions of dollars before finding out a drug is a dud. Karkanias used the airplane analogy again, saying that in the early days of aviation, engineers made planes and tested them to see if they’d fly, an expensive and risky proposition. Today, design is computerized, and flight simulation models test a plane long before a prototype is built, which gives those engineers the confidence that it will be assured as safe to fly.

“We want to do that for pharmaceuticals,” Karkanias says.

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  • joshuadf

    The UW is also piloting Amalga (formerly Azyxxi). I know nothing beyond public information, but the little I’ve seen does not seem to be anywhere near as easy to use as Excel. On the other hand, the researchers I talk to definitely see the need to move beyond Excel.

  • ss

    statistical environment R and scripting language perl do an infinitely better job than excel. anybody serious about informatics in biology uses these or similar tools, not excel. pre-packaged solutions are tricky in biology because of high variance in assay platforms between and even within vendors’ offerings.