Moving Research From The Lab To The Data CenterMoving Research From The Lab To The Data Center

Biotechnology companies are driving drug development from the laboratory to the data center. When it takes years of research and millions of dollars to bring a single drug to market, it makes sense for companies to put the burden of success or failure on IT environments that provide high-throughput computing and integrated access to research. Finding ways to effectively manage data that's critical to the development of lifesaving drugs was the focus Tuesday at the BioSilico 2002 conference in New York.

The four greatest challenges to the biotechnology and pharmaceuticals industries are data integration, data volume and computational throughput, security, and process control and knowledge management, says Vijay Pillai, director of Oracle Life Sciences' software development group. To meet these challenges, Oracle has teamed with hardware vendors such as IBM, Compaq, and Hewlett-Packard to deliver database and database integration software.

With "in silico" research, the computer becomes the laboratory, says Bill Blake, Compaq's VP of high-performance technical computing. The automotive and aerospace industries have been using mathematical models for years to study vehicle performance. "Life sciences industries like biotechnology and pharmaceuticals are now turning their attention to the hardware, software, and networking capacity necessary to reduce the latency of data availability," he says. The biotechnology industry in particular places strenuous demands on its IT systems as these companies turn their focus from the study of genes and proteins to more complex subject matter such as cells and tissue samples.

"This increasingly complex research is fueled by the pharmaceutical industry's demand to discover new drugs," Blake says. "The pharmaceutical industry turns technology into product and profit." Biotechnology is an industry of high risk and high reward, says Srini Chari, IBM Life Sciences' senior manager of solution architecture and strategy: "Many decisions regarding which drugs to develop and how to develop them are made with incomplete data."