Biomedical Engineering Reference
In-Depth Information
Complexity
The pharmacogenomic laboratory exploring the genetic basis for aggression illustrates several key
characteristics of data management in the biotech industry. Foremost is the complexity of data
management, as summarized in
Table 2-4
. There are numerous data sources, including the volunteer
patients, clinical studies, genomic studies, and public and private online databases. Similarly, there
are a variety of applications that can be brought to bear on genomic and clinical data and the
biomedical literature, including search engines, statistical analysis applications, visualization tools,
simulations, communication applications, database management systems, electronic medical record
(EMR) systems, and genomic analysis recognition and manipulation, including sequence recognition.
Table 2-4. Complexity and Data Management. The typical R&D environment
in a biotech firm encompasses an array of data sources, applications,
formats, interfaces, and integration tools.
