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The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
The Translational Medicine Ontology: Driving personalized      medicine by bridging the gap from bedside to benchside
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The Translational Medicine Ontology: Driving personalized medicine by bridging the gap from bedside to benchside

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The Translational Medicine Ontology provides terminology that bridges diverse areas of translational medicine including hypothesis management, discovery research, drug development and formulation, …

The Translational Medicine Ontology provides terminology that bridges diverse areas of translational medicine including hypothesis management, discovery research, drug development and formulation, clinical research, and clinical practice. Designed primarily from use cases, the ontology consists of essential terms that are mapped to other ontologies. It serves as a global schema for data integration while simultaneously facilitating the formulation of complex queries across heterogeneous sources. We demonstrate the utility of the ontology through question answering over a prototype knowledge base composed of sample patient data integrated with linked open data. This work forms a basis for the development of a computational platform for managing information relevant to personalized medicine.

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    • 1. The Translational Medicine Ontology: driving personalized medicine by bridging the gap from bedside to bench
      1
      Bio-ontologies 2010:July 9, 2010
      Michel Dumontier
      on behalf of the HCLS TMO Subgroup
      Carleton University, Ottawa, Canada
    • 2. 2
      Bio-ontologies 2010:July 9, 2010
    • 3. HCLS TMO subgroup
      BosseAndersson, AstraZeneca, Lund, Sweden
      Colin Batchelor, Royal Society of Chemistry, Cambridge, UK
      Christine Denney, Eli Lilly, Indianapolis, IN, USA
      Christopher Domarew, Warrington Hospital, Warrington, UK
      AnjaJentzsch, FreieUniversitat, Berlin, Germany
      Joanne Luciano, Predictive Medicine Inc., Belmont, MA, USA
      Elgar Pichler, W3C HCLSIG
      Eric Prud'hommeaux, W3C, Cambridge, MA, USA
      Patricia L. Whetzel, Stanford University, Stanford, CA, USA
      Olivier Bodenreider, National Library of Medicine, Bethesda, MD, USA
      Tim Clark, Harvard Medical School, Cambridge, MA, USA ,
      Lee Harland, Pfizer, Sandwich, UK
      VipulKashyap, Cigna, Hartford, CT, USA
      Peter Kos, Harvard Medical School, Cambridge, MA, USA
      Julia Kozlovsky, AstraZeneca, Waltham, MA, USA
      James McGurk, Daiichi Sankyo, NJ, USA
      ChimezieOgbuji Cleveland Clinic, Cleveland,OH, USA
      Matthias Samwald, Digital Enterprise Research Institute, Galway, Ireland
      Lynn Schriml, University of Maryland, Institute for Genome Sciences
      Peter J. Tonellato, Harvard Medical School, Cambridge, MA, USA
      Jun Zhao, University of Oxford, Oxford, UK.
      Susie StephensJohnson & Johnson Pharmaceutical Research & Development L.L.C., Radnor, PA, USA.
      Bio-ontologies 2010:July 9, 2010
      3
    • 4. Goals of the W3C HCLSIG
      Advance the state of the art in knowledge discovery for health care and the life sciences
      Investigate approaches to facilitate the integration of patient care, clinical research and basic life science research
      Provide effective demonstrations of using Semantic Web technologies for knowledge representation, data integration, data visualization and question answering
      Bio-ontologies 2010:July 9, 2010
      4
    • 5. Personalized Medicine
      The ability to offer
      The Right Drug
      To The Right Patient
      For The Right Disease
      At The Right Time
      With The Right Dosage
      Genetic and metabolic data will allow drugs to be tailored to patient subgroups
      5
      Bio-ontologies 2010:July 9, 2010
    • 6. “If it were not for the great variability among individuals, medicine might as well be a science and not an art”
      Sir William Osler, 1892
      6
      Bio-ontologies 2010:July 9, 2010
    • 7. 7
      Bio-ontologies 2010:July 9, 2010
    • 8. 8
      Bio-ontologies 2010:July 9, 2010
    • 9. 9
      Bio-ontologies 2010:July 9, 2010
    • 10. The Semantic Web
      is the new global web of knowledge
      10
      Bio-ontologies 2010:July 9, 2010
      It is about standards for publishing, sharing and querying
      knowledge drawn from diverse sources
      It makes possible the answering
      sophisticated questions using
      background knowledge
    • 11. A growing web of linked data
      11
      Bio-ontologies 2010:July 9, 2010
    • 12. Bio-ontologies 2010:July 9, 2010
      How do we query across these linked data?
      12
    • 13. Formal Ontology as a Strategy
      13
      Bio-ontologies 2010:July 9, 2010
    • 14. Problem Statement
      Growing number of biomedical terminologies
      Over 200 listed at NCBO bioportal
      Ontologies are a formal specification of a conceptualization
      Not all are well formulated, nor properly formalized
      OBO Foundry to create a reference set of ontologies, but the task is enormous, until then, we need working solutions
      Increasing amounts of linked data
      Conceptualization is haphazard
      not formulated using formal ontologies
      Relations and types are not grounded to shared conceptualization.
      ontologies applied to linked data will be useful to integrate and provide support for queries
      Bio-ontologies 2010:July 9, 2010
      14
    • 15. TMO Approach
      Undertake extensive user-focused requirements
      Identify key entities and establish their relations
      Extend the conceptualization as specified by a foundational ontology
      Map linked data types to ontology types
      Develop knowledge base containing ontology + mappings + data
      Demonstrate query answering over TMO KB
      Bio-ontologies 2010:July 9, 2010
      15
    • 16. Survey reveals diverse needs and interests
      Bio-ontologies 2010:July 9, 2010
      16
    • 17. Preparation
      Generate plausible questions of interest
      Generate scenerios
      patient centric
      research centric
      chemoinformatics / drug discovery
      pharmacogenomics
      animal models
      integrative informatics
      drug therapy development
      Bio-ontologies 2010:July 9, 2010
      17
    • 18. Ontology
      • 75 classes out of an initial 90 types spanning material entities, processes, roles, informational entities
      Distinction among different kinds of material entities
      molecular entities vs chemical substances
      active ingredients vs pharmaceutical formulations
      Distinction among different kinds of informational entities
      medical
      medical history (a list of events & bodily features), diagnostic results
      drug
      dosage (specification), toxicity (reports), treatment safety (guidelines)
      Bio-ontologies 2010:July 9, 2010
      18
    • 19. Bio-ontologies 2010:July 9, 2010
      19
      223 class mappings
      from 60 TMO classes to 201 target classes over 40 ontologies
    • 20. Data
      Bio-ontologies 2010:July 9, 2010
      20
    • 21. Linking Open Drug Data (LODD)
      Bio-ontologies 2010:July 9, 2010
      21
    • 22. focus: Alzheimer’s Disease (AD)
      Incurable, degenerative, and terminal disease with few therapeutic options.
      Influenced by a range of genetic, environmental and other factors.
      Identification of prognostic biomarkers would significantly impact and guide the diagnosis, prescription, and development of therapeutic agents would significantly impact future practice.
      Efficient aggregation of relevant information to help understand the pathology would benefit researchers, clinicians, and patients and would also facilitate the development of target compounds to reduce or even prevent the burden of the disease.
      Bio-ontologies 2010:July 9, 2010
      22
    • 23. formalizing the Dubois AD diagnostic criteria
      Bio-ontologies 2010:July 9, 2010
      23
      # the panel is a textual entity
      dubois:panel2 a iao:IAO_0000300 .
      dubois:panel2 rdfs:label "Alzheimer Disease diagnostic criteria as reported in panel 2 of dubois et al - pubmed:17616482 [dubois:panel2]".
      # the panel is about alzheimer disease
      dubois:panel2 iao:is_about diseasome:74.
      # the panel is from the article
      dubois:panel2 ro:part_of <http://bio2rdf.org/pubmed:17616482>.
      # the panel is about diagnostic criterion
      dubois:panel2 iao:is_about tmo:TMO_0068.
      #inclusion criterion
      dubois:10 rdfs:label "Proven AD autosomal dominant mutation within the immediate family [dubois:10]" ;
      a tmo:TMO_0069;
      ro:part_of dubois:panel2;
      iao:is_about diseasome:74.
      # exclusion criterion
      dubois:16 rdfs:label "Major depression [dubois:16]" ;
      a tmo:TMO_0070;
      ro:part_of dubois:panel2;
      iao:is_about diseasome:74.
    • 24. Queries
      Clinic
      Have any AD patients been treated for other neurological conditions
      Patient 2 was found to suffer from AD and depression.
      Clinical Trial
      Since my patient is suffering from drug-induced side effects for AD treatment, identify an AD clinical trial with a different mechanism of action (MOA)
      Of the 438 drugs linked to AD trials, only 58 are in active trials and only 2 (Doxorubicin and IL-2) have a documented MOA. 78 AD-associated drugs have an established MOA.
      Research
      Which existing marketed drugs might potentially be re-purposed for AD because they are known to modulate genes that are implicated in the disease?
      57 compounds or classes of compounds that are used to treat 45 diseases, including AD, hyper/hypotension, diabetes and obesity
      Bio-ontologies 2010:July 9, 2010
      24
      http://esw.w3.org/topic/HCLSIG/PharmaOntology/Queries
    • 25. Future Directions
      Enhancement of ontology to increase coverage
      Increased formalization of patient records so as to facilitate patient recruitment
      Formalization of pathway diagrams and the aggregate set of processes they specify
      Refactoring of linked data
      more explicit representation of quantities/values
      Bio-ontologies 2010:July 9, 2010
      25
    • 26. The Translational Medicine Ontology
      Provides a global schema for the integration of linked data sets
      Establishes accurate mappings to relevant ontologies
      Demonstrative knowledge base focused around AD
      Bio-ontologies 2010:July 9, 2010
      26
    • 27. Bio-ontologies 2010:July 9, 2010
      27
      Acknowledgements

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