Linked open drug data for pharmaceutical research and development

Abstract

There is an abundance of information about drugs available on the Web. Data sources range from medicinal chemistry results, over the impact of drugs on gene expression, to the outcomes of drugs in clinical trials. These data are typically not connected together, which reduces the ease with which insights can be gained. Linking Open Drug Data (LODD) is a task force within the World Wide Web Consortium's (W3C) Health Care and Life Sciences Interest Group (HCLS IG). LODD has surveyed publicly available data about drugs, created Linked Data representations of the data sets, and identified interesting scientific and business questions that can be answered once the data sets are connected. The task force provides recommendations for the best practices of exposing data in a Linked Data representation. In this paper, we present past and ongoing work of LODD and discuss the growing importance of Linked Data as a foundation for pharmaceutical R&D data sharing.

The ToxBank Data Warehouse: Supporting the Replacement of In Vivo Repeated Dose Systemic Toxicity Testing

“…RDF is the W3C proposed technology to link data on web pages, small resources or large databases, in a unified way. These Linked Resource or Semantic Web approaches are being adopted by the international life sciences community, such as the Health Care & Life Science interest group, [48] and EU projects such as OpenTox [27][28][29][30][31] and Open PHACTS. [49] The standards support many different applications; by adopting them we ensure that ToxBank will be fully interoperable with many other life science projects.…”

Linked Biomedical Dataspace: Lessons Learned Integrating Data for Drug Discovery

“…The Linking Open Drug Data (LODD) task force under the W3C Health Care and Life Sciences Interest Group (HCLS IG) has provided best practices and recommendations for transforming and exposing publicly available data about drugs in a LD representation [30]. Architectures like SQUIN [14] and FedX [32] could be configured for distributed querying across these data sources.…”

Supporting the Linked Data Life Cycle Using an Integrated Tool Stack

“…publishing statistical data and interpretation of statistics [5], improving tourism experience [6], pharmaceutical R&D data sharing [7], crowdsourcing in emergency management [4], etc. A few years ago, our analysis of the adoption of Semantic Web technologies by enterprises [2] has shown that companies benefit from features that improve data sharing and re-use (57 %), improve searching (57 %), allow incremental modelling (26 %), explicit content relation (24 %), identifying new relationships (17 %), dynamic content generation (14 %), personalization (10 %), open modeling (12 %), rapid response to change (10 %), reducing time to market (5 %), and automation (5 %).…”