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Vaccine and drug ontology in the study of mechanism and effect 2013 (VDOSME)


Edited by: Sivaram Arabandi, Yongqun He, and Cui Tao

Drugs and vaccines have contributed to dramatic improvements in public health worldwide. Over the last decade, there have been efforts in the biomedical ontology community that represent various areas associated with drugs including vaccines that extend existing health and clinical terminology systems (e.g., SNOMED, RxNorm, NDF- RT, and MedDRA) and their applications to research and clinical data. Although much progress has been made in the recent years in these ontologies, we still face many challenges in order to fully and logically represent drugs and vaccines, and efficiently use the ontologies. In the case of ontology representation, no consensuses have been achieved on how to ontologically represent many relevant areas, for example: (i) administration dose, route, and frequency, (ii) how to accurately represent adverse events, (iii) drug-drug interactions, drug-food interactions, etc (iv) experimental testing and analysis of vaccine/drug-induced immune responses, and (v) the complexity of time constraints for clinical events post vaccination or medication. Meanwhile, it is also a challenge to efficiently apply biomedical ontologies to solve research and clinical problems. For example, is there any advantage in applying ontologies for advanced literature mining in order to discover gene interaction networks underlying protective immunity or adverse events? How to apply ontologies for personalized medicine? How to use ontologies to improve the performance of complex vaccine/drug research and clinical data analysis? This workshop aims to bring together a diverse group of individuals from clinical, research and pharma-biotech areas to identify, propose, and discuss solutions for important research problems in the ontological representation of vaccine and drug information covering development and preparation, administration, mechanisms of action including induced host immune responses, adverse events, etc. This thematic series aims to provide a platform for discussing problems and solutions in the development and applications of biomedical ontologies to representing and analyzing vaccines/drugs, vaccine/drug administrations, vaccine/drug-induced immune responses, adverse events, and similar topics. Different computational methods, including literature mining of vaccine/drug-gene interaction networks, meta-analysis of host immune responses, time event analysis of adverse events, and Semantic Web applications, have been applied.

Collection published: 20 December 2013
Last updated: 6 August 2014

  1. Research

    Network-based analysis reveals distinct association patterns in a semantic MEDLINE-based drug-disease-gene network

    A huge amount of associations among different biological entities (e.g., disease, drug, and gene) are scattered in millions of biomedical articles. Systematic analysis of such heterogeneous data can infer nove...

    Yuji Zhang, Cui Tao, Guoqian Jiang, Asha A Nair, Jian Su, Christopher G Chute and Hongfang Liu

    Journal of Biomedical Semantics 2014 5:33

    Published on: 6 August 2014

  2. Research

    A framework for assessing the consistency of drug classes across sources

    The objective of this study is to develop a framework for assessing the consistency of drug classes across sources, such as MeSH and ATC. Our framework integrates and contrasts lexical and instance-based ontol...

    Rainer Winnenburg and Olivier Bodenreider

    Journal of Biomedical Semantics 2014 5:30

    Published on: 9 July 2014

  3. Editorial

    A 2013 workshop: vaccine and drug ontology studies (VDOS 2013)

    The 2013 “Vaccine and Drug Ontology Studies” (VDOS 2013) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. Drugs and vaccines have contributed to dramatic i...

    Cui Tao, Yongqun He and Sivaram Arabandi

    Journal of Biomedical Semantics 2014 5:16

    Published on: 20 March 2014

  4. Research

    Building a drug ontology based on RxNorm and other sources

    We built the Drug Ontology (DrOn) because we required correct and consistent drug information in a format for use in semantic web applications, and no existing resource met this requirement or could be altered...

    Josh Hanna, Eric Joseph, Mathias Brochhausen and William R Hogan

    Journal of Biomedical Semantics 2013 4:44

    Published on: 18 December 2013