Linked data in pharma

Linked Data, an opportunity to mitigate complexity in pharmaceutical research and development
Bosse Andersson and Kerstin Forsberg AstraZeneca R&D Clinical Information Strategy
kerstin.l.forsberg@astrazeneca.comkerfors on Twitter, LinkedIn, Slideshare, Blogspot, citulike

Pharmaceutical research and development

Complexity
Pathophysiology?
Targets?
Phenotypes?
Biomarkers?
Costs?
QoL?
Outcomes?
Association and interpretationof all data needed
has become a too complex task for individuals, or even teams to handle.
Health care, pharma, academiaShared datasets
Different decisions and different types of applications.

Opportunities
Improve the research utility of shared datasets
organized for associations,
prepared for not yet defined use,
ready for automation where computers can function alongside us to mitigate the complexity

It’s like sex and teenagers …
Everybody is talking about Linked Data and Semantic Web, …
… many have tried parts of it, but …
few (if non) have done the real thing, and applied a sustainable and long term approach to use Linked Data principles and Semantic Web technologies to improve the research utility of their data.

Linked Data Management Apragmatic and iterative process
Three enablers
Linked Data principles, including establishing global namespaces of URI:s
Semantic web standards, also for provenance data and dataset descriptions
Open ontologies, with the required level of precision and consistency
Computers to work alongside scientists to automatically
Identify entities and assign URI:s
Structure data and capture provenance data
Mine for causal relationships and inconsistency

Linked data in pharma

by Kerstin Forsberg

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