1 CENTER FOR Biomedical Informatics Coming to Terms with the Biomedical Tower of Babel Implications for the design of a biomedical knowledge network Alexa T. McCray Center for Biomedical Informatics Harvard Medical School Board on Research Data and Information National Academy of Sciences February 26, 2013
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1 CENTER FOR
Biomedical Informatics
Coming to Terms with the Biomedical Tower of Babel
Implications for the design of a biomedical knowledge network
Alexa T. McCray
Center for Biomedical Informatics
Harvard Medical School
Board on Research Data and Information
National Academy of Sciences
February 26, 2013
2 CENTER FOR
Biomedical Informatics
“No aspect of human life has escaped the
impact of the Information Age, and
perhaps in no area of life is information
more critical than in health and medicine.”
U.S. National Academy of Engineering
Grand Challenges 2008
http://www.engineeringchallenges.org
3 CENTER FOR
Biomedical Informatics
1990-2003 Human Genome Project
2004-2010
2011-2020
Beyond 2020
Green ED. Nature 2011; 470(10):203-13
4 CENTER FOR
Biomedical Informatics
1990-2003 Human Genome Project
2004-2010
2011-2020
Beyond 2020
Green ED. Nature 2011; 470(10):203-13
Understanding the structure of genomes
5 CENTER FOR
Biomedical Informatics
1990-2003 Human Genome Project
2004-2010
2011-2020
Beyond 2020
Green ED. Nature 2011; 470(10):203-13
Understanding the biology of genomes
Understanding the biology of disease
6 CENTER FOR
Biomedical Informatics
1990-2003 Human Genome Project
2004-2010
2011-2020
Beyond 2020
Green ED. Nature 2011; 470(10):203-13
Advancing the science of medicine
7 CENTER FOR
Biomedical Informatics
1990-2003 Human Genome Project
2004-2010
2011-2020
Beyond 2020
Green ED. Nature 2011; 470(10):203-13
Improving the effectiveness of healthcare
8 CENTER FOR
Biomedical Informatics
An Inflection Point
National Research Council, 2011:9.
Toward Precision Medicine: Building a Knowledge Network
for Biomedical Research and a New Taxonomy of Disease
9 CENTER FOR
Biomedical Informatics
Precision Medicine
Toward Precision Medicine National Research Council, 2011
10 CENTER FOR
Biomedical Informatics
Precision Medicine
Toward Precision Medicine National Research Council, 2011
11 CENTER FOR
Biomedical Informatics
Precision Medicine
Toward Precision Medicine National Research Council, 2011
12 CENTER FOR
Biomedical Informatics
Precision Medicine
Toward Precision Medicine National Research Council, 2011
13 CENTER FOR
Biomedical Informatics
Precision Medicine
Toward Precision Medicine National Research Council, 2011
14 CENTER FOR
Biomedical Informatics
A New Taxonomy of Disease
“Could it be that something as fundamental as our current system for
classifying diseases is actually inhibiting progress?”
Toward Precision Medicine.
National Research Council, 2011:10
Symptomology New
Taxonomic
Classification
15 CENTER FOR
Biomedical Informatics
Wide Range of Data Sources Needed
Public Databases
Clinical Systems
Social Networking Sites
Laboratory Data
Biosensor Data
All have their own
Some use home-grown
terminologies
Syntax
Semantics
Some use standard
terminologies/ontologies
16 CENTER FOR
Biomedical Informatics
Terminology Use
Coding clinical data
Indexing and retrieving the literature
Annotating genomic data
Statistical reporting, epidemiologic studies
Outcomes measurement
Public health surveillance
Cost analysis
Information exchange and data integration
Data mining, aggregation
Natural language processing
…
17 CENTER FOR
Biomedical Informatics
Common Terminologies Varying scope, coverage,
rigor, and update schedules
18 CENTER FOR
Biomedical Informatics
How do we come to terms with this Biomedical Tower of Babel?
Unified Medical Language System (UMLS) is one large-
scale effort that has made progress toward facilitating
semantic interoperability of biomedical data
Recognize that a variety of communities of practice exist
Encourage consistency within those communities of practice
Discourage development of “redundant” terminologies/ontologies
Map terminologies to each other for maximum semantic interoperability
Recognize the value of curating data with standard terminologies
Develop robust NLP tools that take advantage of existing terminologies