Knowledge Management for Life Sciences

The importance of XML-based information in life sciences has grown tremendously over the last two years, from R&D to clinical trials to manufacturing. Life science companies today, are required to transfer and share huge quantities of information among they myriad of researchers and partners involved in the product development life cycle.

The future of the life sciences market will be determined by how well companies acquire, share, and apply knowledge to exploit the wealth of new opportunities while minimizing the deluge of new risks and costs. But today, life sciences companies are struggling to provide researchers with a simple and effective means of searching and annotating large amounts of raw data, and an efficient way to share customized results with other researchers and partners.

Further aggravating this knowledge management problem, has been the explosion of new genomic data from the Human Genome Project (HGP), which has resulted in unprecedented opportunities to discover new drugs and methods based on newly discovered biological targets. Unfortunately, the 4-fold increase in the number of targets scientists that can now investigate has also resulted in a proportional increase in the risk of attrition for new drug candidates taking advantage of these novel targets. The reason for this increased risk of attrition is simply the lack of existing knowledge about these novel targets.

This session will outline how to:

* Streamline the research function, to provide more "intelligent" information, and significantly accelerate product development, clinical trials, and the manufacturing process.

* Leverage XML in conjunction with information "pipelines" to more effectively manage corporate knowledge by creating a dynamic, reusable and highly scalable XML content infrastructure.

* Acquire, share, and apply knowledge about novel targets to reduce the unprecedented new risks of attrition.

* Use sophisticated indexing and memory techniques to meet the vast content customization requirements that life science companies need to effectively manage their knowledge.