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Exploiting the Life Science Data Explosion to Speed New Drug Discovery

eriencing an industrialization of what were previously cottage industries. Where it was once acceptable to depend solely on data from your own lab, it is now essential to become part of a global data community. The need to manage data in a secure, organized and controlled manner has become a major issue. Quite simply, hard coded, hand managed systems are no longer good enough. Likewise, proprietary ‘integrated warehouses’ become cumbersome and costly to manage. Such solutions simply do not scale and do not meet the ever-increasing pace of drug discovery.

Making Biological Data Accessible
In an increasingly heterogeneous world, we find data sources crossing the bounds of technology. While this has been a reality in the IT world for some time, the requirements for data integration in the life sciences arena differs from traditional IT requirements in several important ways. The IT problem is characterized by the need to deal with data held in a variety of different systems within the organization, each a controlled system. In the life sciences space, data must be integrated from internal and external sources, where external sources are public and not under the control of the using organization. Public sources are, by their nature, dynamic: constantly, new data is added and existing data updated. To complicate the picture further, the methods available to access this data are often unstable, subject to revision by the controlling agency in response to their own changing requirements.

A variety of methods are needed to make this data accessible. First, you need an architecture that removes the physical storage and access mechanisms from the usability issues. Second, you need a consistent mediation point within the architecture that accepts a single ‘language’, which can be leveraged to efficiently query against disparate data sources. Standard IT based languages are not equipped
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