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Yes We Can Yes We Can

Inauguration de Inauguration de l’Unité l’Unité Inserm Inserm U936 U936 Modélisation Modélisation des des connaissances connaissances biomédicales biomédicales February 6, 2009 February 6, 2009

Yes We Can Yes We Can

From biomedical informatics to translational research From biomedical informatics to translational research

De De l’informatique l’informatique biomédicale biomédicale à la à la médecine médecine translationelle translationelle

Olivier Bodenreider Olivier Bodenreider Lister Hill National Center Lister Hill National Center for Biomedical Communications for Biomedical Communications Bethesda, Maryland Bethesda, Maryland -

USA

USA

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Outline Outline

National Institutes of Health

Translational research

Enabling translational research

Anatomy of a translational research experiment

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 2

Anatomy of a translational research experiment

Promising results

Challenging issues

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National Institutes of Health National Institutes of Health

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National Institutes of Health National Institutes of Health

Research is the heart of the NIH mission

27 Institutes and Centers

Institutes (Cancer, Heart, Lung & Blood)

Centers (NCCAM, NCRR)

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Intramural

Intramural – – 6,000 researchers at NIH Institutes 6,000 researchers at NIH Institutes

Extramural

Extramural – – grants for research, research grants for research, research resources, training resources, training

http://www.nih.gov/

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Facts about NIH Facts about NIH

$29.5 billion appropriation from Congress

80% awarded via competitive grants to more than

80% awarded via competitive grants to more than 325,000 researchers at 3,000 organizations 325,000 researchers at 3,000 organizations

80,000 new applications received every year

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Average research grant = $355K, 4 years

10% to support the intramural research program

6,000 scientists, mainly on the NIH campus in

6,000 scientists, mainly on the NIH campus in Bethesda, Maryland Bethesda, Maryland

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Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 10

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National Library of Medicine National Library of Medicine

http://www.nlm.nih.gov/ http://www.nlm.nih.gov/ Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 12

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Collaboration NLM Collaboration NLM-

Inserm

Inserm

http://ist.inserm.fr/basismesh/mesh.html Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 13

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Research at NLM Research at NLM

Two research centers

National Center for Biotechnology Information (NCBI)

PubMed

Other knowledge base in the

Other knowledge base in the Entrez Entrez system ( system (GenBank GenBank Gene Gene

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Other knowledge base in the

Other knowledge base in the Entrez Entrez system ( system (GenBank GenBank, Gene, , Gene, PubMedCentral PubMedCentral, , PubChem PubChem, GEO, , GEO, dbGaP dbGaP,…) ,…)

Lister Hill National Center for Biomedical

Lister Hill National Center for Biomedical Communications Communications

Unified Medical Language System (UMLS)

ClinicalTrials.gov

Genetics Home Reference

…

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Medical Ontology Research Medical Ontology Research

Terminology, ontology and knowledge

Terminology, ontology and knowledge representation in the biomedical domain representation in the biomedical domain

Basic research

Applied research

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Applications

Natural language understanding

Automatic reasoning

Information visualization

Information integration

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Translational research Translational research

(Translational medicine) (Translational medicine)

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Translational medicine/research Translational medicine/research

Definition

Effective transformation of information gained from

Effective transformation of information gained from biomedical research into knowledge that can improve biomedical research into knowledge that can improve the state of human health and disease the state of human health and disease

[Butte, JAMIA 2008] Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 17

Goals

Turn basic discoveries into clinical applications more

Turn basic discoveries into clinical applications more rapidly (“bench to bedside”) rapidly (“bench to bedside”)

Provide clinical feedback to basic researchers

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Combining clinical informatics Combining clinical informatics and bioinformatics and bioinformatics

Associates

Clinical informatics

Electronic medical records

Clinical knowledge bases

C t ti l C t ti l

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Bioinformatics

Sequence databases

Gene expression

Model organism databases

Common computational resources

Biomedical natural language processing

Biomedical knowledge engineering

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Translational bioinformatics Translational bioinformatics

“…

“… the development of storage, analytic, and interpretive the development of storage, analytic, and interpretive methods to optimize the methods to optimize the transformation of increasingly transformation of increasingly voluminous biomedical data voluminous biomedical data into proactive, predictive, into proactive, predictive, preventative, and participatory health. preventative, and participatory health. Translational bioinformatics includes research on the Translational bioinformatics includes research on the

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development of novel techniques for the development of novel techniques for the integration of biological integration of biological and clinical data and clinical data and the evolution of clinical informatics and the evolution of clinical informatics methodology to encompass biological observations. methodology to encompass biological observations. The end product of translational bioinformatics is The end product of translational bioinformatics is newly found newly found knowledge knowledge from these integrative efforts that can be from these integrative efforts that can be disseminated to a variety of stakeholders, including biomedical disseminated to a variety of stakeholders, including biomedical scientists, clinicians, and patients. scientists, clinicians, and patients.”

AMIA strategic plan http://www.amia.org/inside/stratplan

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Aspects of translational research Aspects of translational research

Huge volumes of data

Publicly available repositories

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Publicly available tools

Data

Data-

driven research

driven research

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Huge volumes of data Huge volumes of data

Affordable, high

Affordable, high-

throughput technologies

throughput technologies

DNA sequencing

Whole genomes

Multiple genomes

Single nucleotide polymorphism (SNPs) genotyping

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Millions of allelic variants between individuals

Gene expression data from micro

Gene expression data from micro-

array experiments

array experiments

Text mining

Full

Full-

text articles

text articles

Whole MEDLINE

Electronic medical records

Genome

Genome-

wide association studies

wide association studies

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Publicly available repositories Publicly available repositories

DNA sequences

GenBank

GenBank / EMBL / DDBJ / EMBL / DDBJ

Gene Expression data

GEO,

GEO, ArrayExpress ArrayExpress

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Biomedical literature

MEDLINE,

MEDLINE, PubMedCentral PubMedCentral

Biomedical knowledge

OBO ontologies

Clinical data (genotype and phenotype)

dbGaP

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Publicly available tools Publicly available tools

DNA sequences

BLAST

Gene Expression data

GenePattern

GenePattern, … , … Culture of sharing encouraged by the funding agencies

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Biomedical literature

Entrez

Entrez, , MetaMap MetaMap

Biomedical knowledge

Protégé

Grants for tools and

resource development

Mandatory sharing plan in

large NIH grants

Mandatory sharing of

manuscripts in PMC for NIH-funded research

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Data Data-

driven research

driven research

Paradigm shift

Hypothesis

Hypothesis-

driven

driven

Start from hypothesis

Run a specific experiment

Collect and analyze data

Collect and analyze data Biomedical informatics as a supporting discipline for biology and clinical

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Collect and analyze data

Validate hypothesis (or not)

Data

Data-

driven

driven

Integrate large amounts of data

Identify patterns

Generate hypothesis

Validate hypothesis (or not)

Validate hypothesis (or not) through specific experiments through specific experiments biology and clinical medicine Biomedical informatics as a discipline in its own right, addressing important questions in medicine

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Translational bioinformatics as a Translational bioinformatics as a discipline discipline

“The availability of substantial public data enables

“The availability of substantial public data enables bioinformaticians bioinformaticians’ roles to change. Instead of just ’ roles to change. Instead of just facilitating the questions of biologists, the facilitating the questions of biologists, the bioinformatician bioinformatician, adequately prepared in both clinical , adequately prepared in both clinical science and bioinformatics, can ask new and interesting science and bioinformatics, can ask new and interesting

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questions that could never have been asked before. questions that could never have been asked before. […] […] There is a role for the translational There is a role for the translational bioinformatician bioinformatician as question as question-

asker, not just as infrastructure

asker, not just as infrastructure-

builder or

builder or assistant to a biologist assistant to a biologist.” .”

[Butte, JAMIA 2008]

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Enabling translational research Enabling translational research g

Clinical Translational Research Awards Clinical Translational Research Awards (CTSA) (CTSA)

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Translational research Translational research NIH Roadmap NIH Roadmap

http://nihroadmap.nih.gov/ Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 28

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Clinical and Translational Science Awards Clinical and Translational Science Awards

The purpose of the CTSA Program is to assist

The purpose of the CTSA Program is to assist institutions to forge a uniquely transformative, novel, institutions to forge a uniquely transformative, novel, and integrative academic home for Clinical and and integrative academic home for Clinical and Translational Science that has the consolidated Translational Science that has the consolidated resources to: resources to:

1) captivate, advance, and nurture a cadre of well

1) captivate, advance, and nurture a cadre of well-trained trained

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) p , , f ) p , , f multi multi-

and inter

and inter-

disciplinary investigators and research

disciplinary investigators and research teams; teams;

2) create an incubator for innovative research tools and

2) create an incubator for innovative research tools and information technologies; and information technologies; and

3) synergize multi

3) synergize multi-

disciplinary and inter

disciplinary and inter-

disciplinary

disciplinary clinical and translational research and researchers to clinical and translational research and researchers to catalyze the application of new knowledge and techniques to catalyze the application of new knowledge and techniques to clinical practice at the front lines of patient care. clinical practice at the front lines of patient care.

http://nihroadmap.nih.gov/

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CTSA program (NCRR) CTSA program (NCRR)

38 academic health centers in 23 states

14 centers added in 2008

60 centers upon completion

Funding provided for 5 years

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Total annual cost: $500 M

Annual funding per center: $4

Annual funding per center: $4-

23 M

23 M

Depending on previous funding

http://www.ncrr.nih.gov/clinical_research_resources/clinical_and_translational_science_awards/

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Clinical and Translational Science Awards Clinical and Translational Science Awards

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 31 http://www.ctsaweb.org/

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Other related programs Other related programs

National Centers for Biomedical Computing

“networked national effort to

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ff build the computational infrastructure for biomedical computing in the nation”

http://www.ncbcs.org/

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Other related programs Other related programs

Cancer Biomedical Informatics Grid (

Cancer Biomedical Informatics Grid (caBIG caBIG) )

Key elements

“an information network enabling all constituencies in the cancer community – researchers, physicians, and patients – to share data and knowledge.”

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Key elements

Bioinformatics and Biomedical Informatics

Community

Standards for Semantic Interoperability

Grid Computing

1000 participants from 200 organizations

Funding: $60 M in the first 3 years (pilot)

https://cabig.nci.nih.gov/

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Anatomy of a translational research Anatomy of a translational research y experiment experiment

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Integrating genomic and clinical data Integrating genomic and clinical data

Genomic data Clinical data

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No genomic data available for most patients

No precise clinical data available associated with

No precise clinical data available associated with most genomic data (GWAS excepted) most genomic data (GWAS excepted)

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Integrating genomic and clinical data Integrating genomic and clinical data

Genomic data

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 36

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Integrating genomic and clinical data Integrating genomic and clinical data

Genomic data

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 37 Upregulated Upregulated genes genes Diseases Diseases (extracted from text (extracted from text + MeSH terms) + MeSH terms)

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Integrating genomic and clinical data Integrating genomic and clinical data

Clinical data Genomic data

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 38 Coded Coded discharge discharge summaries summaries Laboratory Laboratory data data Upregulated Upregulated genes genes Diseases Diseases (extracted from text (extracted from text + MeSH terms) + MeSH terms)

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The Butte approach The Butte approach Methods Methods

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 39 Courtesy of David Chen, Butte Lab Courtesy of David Chen, Butte Lab

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The Butte approach The Butte approach Results Results

Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 40 Courtesy of David Chen, Butte Lab Courtesy of David Chen, Butte Lab

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The Butte approach The Butte approach

Extremely rough methods

No pairing between genomic and clinical data

Text mining

Mapping between SNOMED CT and ICD 9

Mapping between SNOMED CT and ICD 9-

CM

CM th h UMLS th h UMLS

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through UMLS through UMLS

Reuse of ICD 9

Reuse of ICD 9-

CM codes assigned for billing purposes

CM codes assigned for billing purposes

Extremely preliminary results

Rediscovery more than discovery

Extremely promising nonetheless

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The Butte approach The Butte approach References References

Dudley J, Butte AJ "Enabling integrative genomic analysis of high

Dudley J, Butte AJ "Enabling integrative genomic analysis of high-

impact human diseases through text mining."

impact human diseases through text mining." Pac Pac Symp Symp Biocomput Biocomput 2008; 580 2008; 580-

91

91

Chen DP, Weber SC,

Chen DP, Weber SC, Constantinou Constantinou PS, Ferris TA, Lowe HJ, Butte AJ PS, Ferris TA, Lowe HJ, Butte AJ "Novel integration of hospital electronic medical records and gene "Novel integration of hospital electronic medical records and gene expression measurements to identify genetic markers of maturation." expression measurements to identify genetic markers of maturation."

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p y g p y g Pac Pac Symp Symp Biocomput Biocomput 2008; 243 2008; 243-

54

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Butte AJ, "Medicine. The ultimate model organism."

Butte AJ, "Medicine. The ultimate model organism." Science Science 2008; 2008; 320: 5874: 325 320: 5874: 325-

7

7

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Promising results Promising results g

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Pharmacogenomics Pharmacogenomics of

f warfarin

warfarin

Narrow therapeutic range

Large

Large interindividual interindividual variations in dose requirements variations in dose requirements

Polymorphism involving two genes

CYP2C9

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VKORC1

Genetic test available

Development of models integrating variants of

Development of models integrating variants of CYP2C9 CYP2C9 and VKORC1 for and VKORC1 for predicting initial dose predicting initial dose requirements (ongoing RCTs) requirements (ongoing RCTs)

Step towards personalized medicine

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Integration of existing studies/datasets Integration of existing studies/datasets

49 experiments in the domain of obesity

Rediscovery of known genes

Identification of potential new genes

Analysis of genes potentially associated with

[English, Bioinformatics 2007] Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 45

nicotine dependence nicotine dependence

Rediscovery of known findings

Identification of networks of genes associated with

Identification of networks of genes associated with type II diabetes mellitus type II diabetes mellitus

[Sahoo, JBI 2008] [Liu, PLoS 2007; Rasche, MBC Gen. 2008]

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Drug Drug-

target networks

target networks

[Yildirim, 2007] Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications Lister Hill National Center for Biomedical Communications 46

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Challenging issues Challenging issues g g g g

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Challenging issues Challenging issues

Datasets

Ontologies

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Tools

Other issues

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Challenging issues Challenging issues Datasets Datasets

Lack of annotated datasets

Largely text

Largely text-

based (need for text mining)

based (need for text mining)

Limited availability of clinical data (EHRs, PHRs)

Need for

Need for deidentification deidentification

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Largely text

Largely text-

based (need for text mining)

based (need for text mining)

Heterogeneous formats

Need for conversion

Lack of metadata

Limited discoverability, limited reuse

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Challenging issues Challenging issues Ontologies Ontologies

Lack of universal identifiers for biomedical entities

Need for normalization through terminology integration

Need for normalization through terminology integration systems (e.g., UMLS) systems (e.g., UMLS)

Lack of standard for identifiers

Need for bridging across formats

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Need for bridging across formats

Lack of universal formalism

Need for conversion between formalisms

Limited availability of some ontologies

Delay in adopting standards

e.g., SNOMED CT

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Challenging issues Challenging issues Tools Tools

Lack of semantic interoperability

Difficult to combine tools/services

Limited scalability of automatic

Limited scalability of automatic reasoners reasoners

Difficult to process large datasets

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Other challenging issues Other challenging issues

Limited number of researchers “

Limited number of researchers “adequately adequately prepared in both clinical science and prepared in both clinical science and bioinformatics bioinformatics”

Need for validation of potential

Need for validation of potential in in silico silico

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discoveries through specific experiments discoveries through specific experiments

Collaboration with (wet lab) biologists

Must be factored in in grants

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Conclusions Conclusions

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Conclusions Conclusions

Translational medicine is an emerging discipline

We live in partially unchartered territory

Biomedical informatics is at the core of

Biomedical informatics is at the core of translational medicine translational medicine

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Strong informatics component to translational medicine

We live in exciting times

New possibilities for biomedical

New possibilities for biomedical informaticians informaticians

From service providers…

From service providers… …to biomedical researchers …to biomedical researchers

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Medical Medical Ontology Ontology Research Research Contact: Contact: olivier@nlm.nih.gov

livier@nlm.nih.gov

Olivier Olivier Bodenreider Bodenreider Lister Hill National Center Lister Hill National Center for Biomedical Communications for Biomedical Communications Bethesda, Maryland Bethesda, Maryland -