Difference between revisions of "DallasWorkshop"

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''Workshop organized by:''  
 
''Workshop organized by:''  
 
:[http://www.utsouthwestern.edu/findfac/research/0,2357,16416,00.html Richard Scheuermann], University of Texas Southwestern Medical Center, Dallas  
 
:[http://www.utsouthwestern.edu/findfac/research/0,2357,16416,00.html Richard Scheuermann], University of Texas Southwestern Medical Center, Dallas  
:together with [http://ontology.buffalo.edu/smith/ Barry Smith], for the National Center for Biomedical Ontology
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:together with [http://ontology.buffalo.edu/smith/ Barry Smith], for the National Center for Biomedical Ontology / University at Buffalo
  
 
''Sponsored by:''  
 
''Sponsored by:''  

Revision as of 06:17, 9 July 2008

Signs, Symptoms and Findings: First Steps Toward an Ontology of Clinical Phenotypes

Workshop organized by:

Richard Scheuermann, University of Texas Southwestern Medical Center, Dallas
together with Barry Smith, for the National Center for Biomedical Ontology / University at Buffalo

Sponsored by:

University of Texas Southwestern Medical Center Clinical and Translational Science Award (CTSA) Program
National Center for Biomedical Ontology (NCBO)

Date:

September 3-4, 2008

Venue:

Dallas/Fort Worth Airport Marriott [1].
Details with regard to discounted room rate will be sent to confirmed participants in due course.
There is no participation fee. Continental breakfast and refreshments will be provided to all registered participants at no cost.

This workshop is funded by the United States National Institutes of Health (NIH) through the NIH Roadmap for Medical Research, Grant 1 U54 HG004028, with support from the Clinical and Translational Science Award (1 U54 RR023468) and the Bioinformatics Integration Support Contract (1 N01 AI40076).

Information on the National Centers for Biomedical Computing can be found at: [2].

Overview

The aims of clinical and translational research are to achieve a better understanding of the pathogenesis of human disease in order to develop effective diagnostic, therapeutic and prevention strategies. Biomedical informatics can play an important role is supporting this research by facilitating the management, integration, analysis and exchange of data derived from and related to the research problems being studied. A key aspect of this support is to bring clarity, rigor and formalism to the representation of

1. disease initiation, progression, pathogenesis, signs, symptoms, assessments, clinical and laboratory findings, disease diagnosis, treatment, treatment response and outcome, and
2. the interrelations between these distinct entities both in patient management and in clinical research,

thus allowing the data to be more readily retrievable and shareable, and more able to serve in the support of algorithmic reasoning.

Goals

The tentative goals of the workshop will be to:

  • Utilize consistent ontological design and development principles to describe disease signs and symptoms, clinical and laboratory findings, and their interrelations.
  • Delineate the roles that signs, symptoms and findings play in both clinical patient management and in clinical research.
  • Develop a clear understanding and representation of the distinction between clinical and pre-clinical manifestations of signs, symptoms and findings.
  • Take first steps towards harmonizing the ontological representation of disease signs and symptoms and clinical and laboratory findings with existing and emerging standards in knowledge representation from the health informatics and bioinformatics communities
  • Explore incorporation of the results of this work into the CTSA Human Studies Metadata Repository framework

Provisional List of Participants

This is a working meeting and participation is restricted. Those wishing to communicate their interest in attending should contact Dr Richard Scheuermann [3] as soon as possible.

(** - Confirmed Participant)

  • Jonas Silva Almeida (University of Texas MD Anderson Cancer Center)
  • Sivaram Arabandi (Cleveland Clinic Semantic Database for Cardiovascular Surgery)
  • Robert Arp (National Center for Biomedical Ontology / University at Buffalo)**
  • Brian Athey (Ctr for Computational Medicine & Biology / Univ of Michigan Medical School)
  • Elmer V. Bernstam (University of Texas Health Science Center at Houston)**
  • Anita Burgun (Université de Rennes)
  • Helen Chen (Phillips)
  • Kei Cheung (Senselab / Yale University)
  • Christopher Chute (Mayo Clinic)
  • Timothy W. Clark (Mass General Institute for Neurodegenerative Disease / Harvard Medical School)**
  • Sherri de Coronado (National Cancer Institute / NIH)
  • Amar K. Das (Stanford Center for Biomedical Informatics Research)
  • Louis J. Goldberg (Ontology Research Group / University at Buffalo)
  • Jeffrey S. Grethe (BIRN / University of California at San Diego)
  • Herb Hagler (University of Texas Southwestern Medical Center at Dallas)
  • Udo Hahn (University of Jena)
  • Carol Hamilton (RTI International)
  • William Hogan (University of Pittsburgh Medical Center)
  • Zhangzhi Hu (PRO / Georgetown University Medical Center)
  • Charles Jaffe (HL7)
  • Andrew James (Division of Neonatology, The Hospital for Sick Children / University of Toronto)
  • David Karp (University of Texas Southwestern Medical Center at Dallas)
  • Bron Kisler (CDISC)
  • Harold Lehmann (John Hopkins Medical Institutions)
  • Suzanna Lewis (Lawrence Berkeley National Laboratory)
  • Daniele Merico (NEUROWEB)
  • Meredith Nahm (Duke Translational Medicine Institute)
  • Chimezie Ogbuji (Cleveland Clinic Semantic Database for Cardiovascular Surgery)
  • Chris Pierce (Heart and Vascular Institute / Cleveland Clinic)
  • John Quinn (HL7)
  • Dianne M. Reeves (NCI CBIIT / NIH)
  • Daniel Rubin (Stanford Center for Biomedical Informatics Research)
  • Alan Ruttenberg (Science Commons / Neurocommons)
  • Neil Sarkar (Marine Biological Laboratory, Woods Hole)
  • Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)
  • Lynn Schriml (University of Maryland)
  • Barry Smith (National Center for Biomedical Ontology / University at Buffalo)
  • Kent Spackman (International Health Terminology Standards Development Organization)
  • Robert Toto (University of Texas Southwestern Medical Center at Dallas)
  • Samson Tu (Stanford Center for Biomedical Informatics Research)
  • Ashley Xia (NIAID / NIH)
  • W. Jim Zheng (Biomedical Ontology Research Group, Medical University of South Carolina)

In addition to NCBO and the University of Texas Southwestern Medical Center, it is our goal to have the following communities represented: CTSA, HL7, CDISC, SNOMED, and OBO, as well as the NIH.

Tentative Agenda

Day 1: Wednesday, September 3

8:30am Registration and Continental Breakfast

• Session 1 - Health care and clinical research perspective

Presentations by local clinicians and clinical investigators
Presentations of selected CTSA use cases

• Session 2 - Brief overview of ontology formalisms

• Session 3 - Brief presentations of existing and emerging standards regarding the use of terminologies related to signs, symptoms and findings

• Session 4 - Proposals for ontology-based clarification and unification of ‘sign’, ‘symptom’, ‘finding’ and related terms with the goal of achieving improved understanding of what they are and how they relate to each other

Day 2: Thursday, September 4

8:30am Continental Breakfast

• Session 5 - Working session to utilize consistent ontological design and development principles to describe disease signs and symptoms, clinical and laboratory finding, and their interrelations

• Session 6 - Discussion of strategies to achieve convergence between the ontological representation of disease signs and symptoms and clinical and laboratory findings with the existing and emerging standards in knowledge representation from the health informatics and bioinformatics communities

4:00pm Close

Suggested Background Reading

NEUROWEB Project: From Clinically-Based Phenotypes to Genomics Integration

OBO Foundry: Coordinated Evolution of Ontologies to Support Biomedical Data Integration

Ontology-Guided Data Preparation for Discovering Genotype-Phenotype Relationships

PhenomicDB: A New Cross-Species Genotype/Phenotype Resource

Useful Links

Mammalian Phenotype Ontology

NCBO Bioportal

OBO Foundry ontologies

Phenotypic Quality Ontology