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Optimising eClinical
Storage and Database Development
Figure 1: Secure ICT Framework to Permit the Integration of
To reach these demanding goals, Erasmus MC has set up a translational
Disparate Data Using Validated Capabilities from Inforsense and
medicine partnership with the WRI, which hosts one of the world’s
Oracle
largest biobanks. The WRI biobank contains DNA and serum samples
from US army soldiers and their family collected through six different
Importer
Encoded SNP
Userspace export
(cached)
data (cached)
report (cached)
medical centres across the US. Both Erasmus and WRI biobanks
SNP metadata
co-develop on a similar Oracle-based framework.
Userspace export
(cached)
report 2 (cached)
Patient metadata
Userspace export
Within this framework, programmers and analysts collaborate to
(cached)
report 3 (cached)
integrate clinical, histopathological, imaging, genomic, proteomic and
Virtual private
pharmacogenomic knowledge. This datamodel is based on Oracle 10g, database
which has bioinformatics functionalities and is used for storage and
integration to support high-throughput sample processing in both clinical LDAP user management
and research environments. Enhancements for Oracle 11 are jointly
developed for improved digital imaging and communications in medicine
(DICOM) support for medical images.
Erasmus MC is implementing a secure ICT framework to permit the
Single sign-on
integration of disparate data using validated capabilities from Inforsense
and Oracle (as illustrated in Figure 1). Inforsense technology has been
successfully applied by the pharma industry as well as by academia,
Figure 2: 3-D Virtual Reality Centre used to Examine
(Molecular) Imaging Modalities
including the US National Cancer Institute. The research data warehouse
infrastructure project will create a platform where clinicians and scientists
from different institutions (both public and private) active in translational
medicine can work collaboratively with access to the decision support
engine’s knowledge extraction tools.
In hospitals, traditional workflows involve biologists/technicians
performing laboratory tests and then passing the results to the clinician for
use in medical decision-making, with little interaction between the two
groups. In part, it has been difficult to take advantage of this junction
because it requires an understanding that spans both domains. One way
to gain an overview of both the biomedical and clinical disciplines is to
visualise the information. Capturing and integrating multidisciplinary
knowledge, data, scripts and encoding calculations leads to knowledge
retention and best practices (e.g. good laboratory practice).
There are many potential ways in which the process of bringing diverse
molecular and clinical data together can go wrong; therefore, standards
are required for data acquisition. The bioinformatics department at
Erasmus MC plays a bridging role in these multidisciplinary interactions
and oversees the management of molecular and clinical data.
As well as focusing on their own data, researchers have to simultaneously
Clinical Decision-making consider other sources of information such as from the scientific literature
Erasmus MC has invested extensively in developing advanced and patent databases. Text-mining tools and Google Scholar, for
computational and laboratory/clinical information management instance, can be helpful in understanding background information on
systems to collect, process, organise and visually present huge biomedical topics. Business intelligence tools provide the ideal framework
amounts of relevant biomedical data. Translating basic research into a for placing scientific data in context, and there are various software tools
form that has clinical utility requires a unifying IT platform that lets the and enterprise solutions that can be used to mine data from gene/protein
researchers themselves access, integrate and analyse information from databases for in silico biology applications, from the analysis of pathways
multiple data sources and make use of diverse tools to derive the of disease and disease risk to protein–protein interaction studies.
knowledge needed. Unfortunately, the IT infrastructures currently
used in academic hospitals are often inflexible and disparate – being Unravelling the genetic information encoded in the DNA of human cells
kept in ‘silos’ – thus hindering rather than helping such decision- has led to a rapid progression in the understanding of the roles of our
makers. Instead of providing support for dynamic and iterative thought genes in health and disease. Erasmus MC has made important
processes, most such ‘solutions’ end up either restricting innovation or contributions to this field, and has multiple platforms for high-quality
else rigidly dictating how users can develop their ideas and turn them gene and protein expression research, transgenic facilities and DNA
into practical solutions. analysis capacity to study SNPs in population studies of more than
18 DATA MANAGEMENT IN PHARMACEUTICAL RESEARCH & DEVELOPMENT
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