Developing Scalable IT to Support Life Science Data 2012

More information on Developing Scalable IT to Support Life Science Data

KEYNOTE SESSION: Getting More Value and Generating Knowledge from Large Volumes of Data and Studies

Generating More Knowledge from Our Data and More Value from Our Studies: The Value of Expert Skills

A major challenge in translational science is finding the relevant data, information and knowledge to allow meaningful correlation between pre-clinical observations and clinical outcomes. A big factor in this challenge is that the business drivers, processes, approaches, and cultures are very different between early stages of drug discovery and late stages of drug development, which lead to very different approaches to information management systems, data standards and vocabularies. A simple generalization is that Discovery systems and processes are designed for data exploration, while those in development are designed for regulatory submission, two very different objectives. This presentation will concentrate on the key success factors for leveraging information, generating new knowledge, and ensuring best informed decisions in our drug projects.