Life Sciences

There is an explosion of data occurring across the Life Sciences landscape. But generating the data is only half the battle. The tougher challenge is transforming research data into information that guides the development of new drug therapies and other medical products.

Here are some of the ways our Life Sciences client companies are using IT to meet their challenges.

  • Data storage and processing – Genomics, bioinformatics and other life science initiatives are data-intensive requiring massive storage and processing power. But with long product development cycles, companies need to balance these needs with controlling costs.
  • Grid computing – Recognizing the sheer size of the projects they are conducting, many life sciences firms are collaborating through grid computing. That’s where they form clusters of networked, loosely coupled computers to create a virtual supercomputer that can perform very large tasks.
  • Integrating applications and processes – Many life sciences firms struggle with complex applications that were originally designed and deployed as independent, non-integrated processes. To become efficient, they are now integrating those applications and processes.