Linked open drug data for pharmaceutical research and development

Samwald, Matthias; Jentzsch, Anja; Bouton, Christopher M. L. S.; Kallesøe, Claus Stie; Willighagen, Egon; Hajagos, Janos; Marshall, M. Scott; Prud’hommeaux, Eric; Hassanzadeh, Oktie; Pichler, Elgar; Stephens, Susie

doi:10.1186/1758-2946-3-19

Cited by 160 publications

(104 citation statements)

References 16 publications

(16 reference statements)

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“…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.…”

Section: Toxbank Data Warehouse Architecture and Technologiesmentioning

confidence: 99%

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

Kohonen

Benfenati

Bower

et al. 2013

Molecular Informatics

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The aim of the SEURAT‐1 (Safety Evaluation Ultimately Replacing Animal Testing‐1) research cluster, comprised of seven EU FP7 Health projects co‐financed by Cosmetics Europe, is to generate a proof‐of‐concept to show how the latest technologies, systems toxicology and toxicogenomics can be combined to deliver a test replacement for repeated dose systemic toxicity testing on animals. The SEURAT‐1 strategy is to adopt a mode‐of‐action framework to describe repeated dose toxicity, combining in vitro and in silico methods to derive predictions of in vivo toxicity responses. ToxBank is the cross‐cluster infrastructure project whose activities include the development of a data warehouse to provide a web‐accessible shared repository of research data and protocols, a physical compounds repository, reference or “gold compounds” for use across the cluster (available via wiki.toxbank.net), and a reference resource for biomaterials. Core technologies used in the data warehouse include the ISA‐Tab universal data exchange format, REpresentational State Transfer (REST) web services, the W3C Resource Description Framework (RDF) and the OpenTox standards. We describe the design of the data warehouse based on cluster requirements, the implementation based on open standards, and finally the underlying concepts and initial results of a data analysis utilizing public data related to the gold compounds.

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Section: Toxbank Data Warehouse Architecture and Technologiesmentioning

confidence: 99%

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

Kohonen

Benfenati

Bower

et al. 2013

Molecular Informatics

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“…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.…”

Section: Related Workmentioning

confidence: 99%

Linked Biomedical Dataspace: Lessons Learned Integrating Data for Drug Discovery

Hasnain

Kamdar

Hasapis

et al. 2014

Lecture Notes in Computer Science

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Abstract. The increase in the volume and heterogeneity of biomedical data sources has motivated researchers to embrace Linked Data (LD) technologies to solve the ensuing integration challenges and enhance information discovery. As an integral part of the EU GRANATUM project, a Linked Biomedical Dataspace (LBDS) was developed to semantically interlink data from multiple sources and augment the design of in silico experiments for cancer chemoprevention drug discovery. The different components of the LBDS facilitate both the bioinformaticians and the biomedical researchers to publish, link, query and visually explore the heterogeneous datasets. We have extensively evaluated the usability of the entire platform. In this paper, we showcase three different workflows depicting real-world scenarios on the use of LBDS by the domain users to intuitively retrieve meaningful information from the integrated sources. We report the important lessons that we learned through the challenges encountered and our accumulated experience during the collaborative processes which would make it easier for LD practitioners to create such dataspaces in other domains. We also provide a concise set of generic recommendations to develop LD platforms useful for drug discovery.

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“…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 %).…”

Section: Towards a Broader Adoptionmentioning

confidence: 99%

Supporting the Linked Data Life Cycle Using an Integrated Tool Stack

Nuffelen¹,

Janev

Martin

et al. 2014

Linked Open Data -- Creating Knowledge Out of Interlinked Data

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Abstract. The core of a Linked Data application is the processing of the knowledge expressed as Linked Data. Therefore the creation, management, curation and publication of Linked Data are critical aspects for an application's success. For all of these aspects the LOD2 project provides components. These components have been collected and placed under one distribution umbrella: the LOD2 stack. In this chapter we will introduce this component stack. We will show how to get access; which component covers which aspect of the Linked Data life cycle and how using the stack eases the access to Linked Data management tools. Furthermore we will elaborate how the stack can be used to support a knowledge domain. The illustrated domain is statistical data.

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Linked open drug data for pharmaceutical research and development

Cited by 160 publications

References 16 publications

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

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

Linked Biomedical Dataspace: Lessons Learned Integrating Data for Drug Discovery

Supporting the Linked Data Life Cycle Using an Integrated Tool Stack

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