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Case Study: Eli Lilly and Using IT to Accelerate Research
By Perry Glasser


  Table of Contents:
  1. Case Study: Eli Lilly and Using IT to Accelerate Research
  2. ' Introduction '
  3. ' Net Prophets '
  4. ' Power in Numbers '
  5. ' Lilly'
  6. ' Resources '

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Case Study: Eli Lilly and Using IT to Accelerate Research - ' Power in Numbers '
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Power in Numbers

Down the road? Think grid computing—using untapped computing power across Lilly's corporate landscape and elsewhere to solve complex research problems faster. Grid computing also might let organizations and companies inside the life sciences business share computing power, data and storage capacity via private networks or over the Web, and Lilly spokeswoman Joan Todd says the company is in discussions with several research institutions about future grid strategies. Grids could help Lilly add thousands of hours of computing power to any effort, thereby increasing the speed at which new compounds could be screened—or scrapped. Says Dunbar: "We are in the midst of two breathtaking revolutions—one in the biological sciences, and a second in the availability of computing power and associated network capabilities," Dunbar says. "Pharmaceutical IT success in the post-genomic era will be a product of integration of systems, data and the information."

Moving forward will also require more applications of the new science of bioinformatics, which Dunbar defines as "research, development or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze or visualize such data." Dunbar says he asks other drug companies this: "Does each chemist in your company have immediate access to every single compound in the company's chemical library with a latency of no more than a few seconds?" Then, he adds, "Ask yourself who owns the vision and the work product for an effort. If there is no clear answer, then worry."

Resource Library:

What's ahead for Dunbar? A lot more of the same. Dunbar summarizes the continuing challenge for his IT group and Lilly by saying that "the single biggest contributor [to costs and speed bumps] is poor information visibility in R&D, which in turn leads to poor decision-making, which contributes significantly to the upwardly spiraling costs and the disturbing slide in R&D productivity."

Will the revolution in biosciences, the rise of grid computing and the plummeting costs of data storage save the day for Lilly in the long run? It's hard to say, but Dunbar guesses that R&D productivity at Lilly "has probably doubled in recent years" thanks to some of the company's knowledge sharing initiatives already in place—and should continue to improve significantly.

But Dunbar concedes that aligning the three cultures of business, IT and science will continue to be difficult. Lilly, for all of its IT smarts, has only just begun to integrate itself into a speed demon. "We have made a lot of progress in IT," he says, "but the important part yet to be done is the full integration of all the tools. When we fully integrate, I suspect the results will be breathtaking." Dunbar is counting on it; Lilly, of course, can't afford to see it any other way.

Perry Glasser, the director of the writing program at Wichita State University, writes frequently about business and information technology.



 
 
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