DallasWorkshop

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

Workshop organized by:

Richard Scheuermann, University of Texas Southwestern Medical Center, Dallas

Barry Smith, 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].

To take advantage of discounted rate at the conference hotel, guest room reservations must be secured no later than August 15. See Workshop registration form for further details.
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

Agenda

Day 1: Wednesday, September 3

8:30am - Registration and Continental Breakfast

9:00am - Opening remarks / Workshop goals (Richard Scheuermann)

9:15am - Session 1: Signs, symptoms and laboratory findings from a health care perspective: The need for ontology

Combining clinical exam and laboratory findings in the rheumatology clinic (David Karp)

Clinical signs and symptoms in neonatology (Andrew James)

10:30am - Refreshment Break

10:45am - Session 1 (continued)

Reasoning with clinical exam and laboratory findings: The case of myocardial infarction (Sivaram Arabandi)

12:00pm - Lunch, Sponsored by: Lead Horse Technologies

1:00pm - Session 2: Standardization of clinical and laboratory data in the context of clinical and translational research - use cases, strategies and vision

PATO and Phenote: From model organism phenotypes to clinical medicine (Suzanna Lewis)

Data standards from patient care to clinical and translational research: The CTSA perspective (Chris Chute)

Representation of clinical and laboratory findings in the CDISC SDTM (Bron Kisler)

3:00pm - Refreshment Break

3:30pm - Session 2 (continued)

The future of SNOMED-CT in the representation of clinical findings (Kent Spackman)

Problems with current approaches to clinical data (William Hogan)

Day 2: Thursday, September 4

8:30am - Continental Breakfast

9:00am - Session 3: Proposals for unification of standard terminologies for the representation ‘sign’, ‘symptom’, ‘finding’ and related terms

Laboratory data and metadata in laboratory information systems (Olivier Bodenreider and Anita Burgun)

An ontology-based approach for connecting disease pathogenesis with clinical/laboratory data (Richard Scheuermann)

10:30am - Refreshment Break

10:45am - Session 4: Working session to explore how consistent ontological design and development principles can lead to enhanced representation of signs and symptoms, clinical and laboratory finding, and their interrelations

12:00pm - Lunch Break

1:00pm - Session 5: Crossing the genotype/phenotype divide: 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 biology and bioinformatics communities.

2:30pm - Refreshment Break

2:45pm - Session 5 (continued)

4:00pm - Close

Confirmed Participants

This is a working meeting and participation is restricted.

Jonas Silva Almeida (MD Anderson Cancer Center / University of Texas)
Sivaram Arabandi (Heart & Vascular Institute / Cleveland Clinic)
John M. Armstrong (Lead Horse Technologies, Inc.)
Robert Arp (National Center for Biomedical Ontology / University at Buffalo)
Elmer V. Bernstam (University of Texas Health Science Center at Houston)
Olivier Bodenreider (Medical Ontology Research, National Library of Medicine / NIH)
Bruce Bray (Dept of Biomedical Informatics, University of Utah)
Anita Burgun (Université de Rennes)
Kei-Hoi Cheung (Senselab / Yale Center for Medical Informatics)
Christopher G. Chute (National Center for Biomedical Ontology / Mayo Clinic)
Paolo Ciccarese (Mass General Hospital / Harvard Medical School)
Timothy W. Clark (Mass General Institute for Neurodegenerative Disease / Harvard Medical School)
Gianluca Colombo (University of Milano-Bicocca, DISCo)
Tommie G. Curtis (SAIC, NCICB Contractor)
Amar K. Das (Center for Biomedical Informatics Research / Stanford University)
Louis J. Goldberg (Ontology Research Group / University at Buffalo)
Herb Hagler (University of Texas Southwestern Medical Center at Dallas)
William Hogan (University of Pittsburgh Medical Center)
Zhang-Zhi Hu (PRO / Georgetown University Medical Center)
Charles Jaffe (Health Level 7, Inc. (HL7))
Andrew G. 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)
Suzanna Lewis (Lawrence Berkeley National Laboratory)
Daniele Merico (NEUROWEB / University of Toronto & University of Milano-Bicocca, DISCo)
Pradeep Mutalik (Yale Center for Medical Informatics)
Meredith L. Nahm (Duke Translational Medicine Institute)
Chimezie Ogbuji (Cleveland Clinic Foundation)
Christopher Pierce (Heart and Vascular Institute / Cleveland Clinic)
John Quinn (Health Level 7, Inc. (HL7))
Alan Ruttenberg (Science Commons / Neurocommons)
Neil Sarkar (Marine Biological Laboratory)
Richard Scheuermann (University of Texas Southwestern Medical Center at Dallas)
Lynn M. Schriml (Institute for Genome Sciences, University of Maryland)
Barry Smith (National Center for Biomedical Ontology / University at Buffalo)
Kent A. Spackman (International Health Terminology Standards Development Organization)
Larry Streepy (Cleveland Clinic Foundation)
Nicole Washington (Lawrence Berkeley National Laboratory)
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.