Ontology and Controlled Vocabulary in Clinical Trials

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Ontology and Controlled Vocabulary in Clinical
Trials
Javed Mostafa Jane Greenberg Rahul Deshmukh Lina
Huang
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Outline

• Clinical Trials
• SPIROMICS
• Application of Ontologies and Controlled
  Vocabularies
• Use Cases - Ontologies in Clinical Trials
• SPIRO-V Role of Ontology and Controlled
  Vocabularies in SPIROMICS
• SPIRO-V Where We Are Now
• Controlled Vocabulary Management - The Road Ahead
• Demo
• Questions?

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Clinical Trials

• Conducted by Government Organizations,
  Pharmaceutical Companies, Academic Research
  Centers etc.
• Mostly to assess safety and effectiveness of new
  medication or device
• Types
• Treatments - Combination of drugs
• Diagnostics
• Quality of Life - For patients with chronic
  illness

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Clinical Trials (Contd.)

• Phases
• Phase 0 - Protocol , Patient Identification
• Phase 1 Small Group (20-80) safety side
  effects of drug/treatment
• Phase II Larger Group (100-300)
• Phase III Large Group (1000-3000)
• Phase IV Drugs Risks, Benefits and Optimal
  Uses
• Duration 6 to 8 years
• Cost for pharmaceutical companies between 100 -
  800 Million
• In 2005, 8000 Clinical Trials, 24 Billion
  Invested

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SPIROMICS

• Subpopulations and intermediate outcome measures
  in COPD study (SPIROMICS)
• Primary Goals
• Identify and validate markers of disease severity
• Identify disease subpopulations
• Secondary Goals
• Clarify the natural history of COPD
• Develop bioinformatics infrastructure
• Generate clinical, radiographic and genetic data
  that can be used for future multisite clinical
  trials

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Application of Ontologies and Controlled
Vocabularies
Ontology , Controlled Vocabulary
Communication
Indexing
Functions
For people to talk the same language
To improve retrieval and analysis of data
Retrieval Browsing Visualization
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Use Cases - Ontologies in Clinical Trials

• Locating eligible patients for clinical trials
  IBM, Columbia University
• Matched patient data to SNOMED-CT ontology
• Semantic gulf between raw data and clinicians
  interpretation
• Structural representation of a disease ontology
  Influenza Infectious Disease Ontology
• Coverage of Infectious Disease Domain
• Clinical Trial Data Management System
  CancerGrid
• Model of study OR Dataset ? Forms, Services,
  Metadata Registry etc

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SPIRO-V Vision
SPIRO-V Clinical Trial Application
Ontology Visualization
Patient Identification
Specimen Tracking
SPIROMICS Knowledge Base Ontology
Clinical Trial DBMS
Mapping
Controlled Vocabularies Editing/ Management
SPIROMICS Controlled Vocabularies
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Where We Are Now

• Controlled Vocabularies Harvesting
• Goal - A COPD Vocabulary set to accurately
  describe all the SPIROMICS cohorts, phenotypes,
  and outcome measures.
• Two Approaches
• Manual
• Automatic

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Manual Approach

• Manual approach to collect vocabularies from
  authoritative sources on COPD
• Domain experts conduct quality control
• Downside
• Low efficiency
• communication, coordination takes time

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Consolidated Excel Spreadsheet
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Automatic Approach

• A relational database back end to store the
  terms, definitions and associations
• Incorporation of VCGS automatic metadata
  generation system for rapid harvesting
• Provide human review functionality to control the
  quality of terms and associations generated.
• Manage controlled vocabularies development
  process

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VCGS
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Manage Controlled Vocabulary

• Visualize vocabulary set and make it browsable,
  searchable, and editable.
• Vocabulary gathering workflow
• Suggest candidates -gt review -gt release/reject
• Collaborative initiatives co-authoring and
  discussion

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Demo

• Database
• Physical database in MySQL
• VCGS
• TemaTres
• SPIRO-V

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Questions?
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References

• http//clinicaltrials.gov/ct2/home
• http//www.cscc.unc.edu/spir/
• http//iswc2007.semanticweb.org/papers/809.pdf
• http//influenzaontologywiki.igs.umaryland.edu/wik
  i/index.php/Main_Page
• http//www.cancergrid.org/

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Collaborative thesaurus editing

• Level of user privileges
• Common users can suggest a candidate term, an
  association or a definition and provide feedback
• Authorized users can reject/accept the
  suggestions.
• Document changes and comments from different
  users.

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Ontology, Thesaurus, Controlled Vocabularies
Ontology
Thesaurus
Where We Are
Controlled Vocabularies