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Future Trends: Translational Informatics

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Future Trends: Translational Informatics James J. Cimino Chief, Laboratory for Informatics Development Mark O. Hatfield Clinical Research Center – PowerPoint PPT presentation

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Title: Future Trends: Translational Informatics


1
Future Trends Translational Informatics
  • James J. Cimino
  • Chief, Laboratory for Informatics Development
  • Mark O. Hatfield Clinical Research Center
  • National Institutes of Health
  • Institute for e-Health Policy, January 12, 2011

2
Genetics 101
DNA
3
The Genomic Timeline
4
Translational Research
The application of research findings in one
domain of study to another, (usually broader)
domain.
5
The Roles of Informatics
Clinical Knowledge
6
Promise of Translational Informatics
  • Diseases predicted by genes
  • Effectiveness of prevention
  • Diseases indicated by activation
  • Appropriate testing
  • Drug dose, toxicity and interactions
  • Drug effectiveness

7
Case Study
  • Patient with liver cancer and chest pain
  • Physician suspects pulmonary embolism
  • What is the best, least invasive test?
  • Will warfarin work to prevent further emboli?
  • What is the warfarin dose for this patient?
  • Will warfarin interact with other medications?

8
How does the nose form?
Ontogeny
  • Definitely genetic
  • Not a big protein!
  • 5 types of tissue
  • Billions of cells
  • Coordination in time and space
  • How many genes?
  • How many variants?

9
Genomics of a Single Disease
10
Why is this so hard?
Other Genes
Pathways
Replication
Translation
Amino Acids
DNA
Proteins
DNA
RNA
Transcription
Folding
Structures
Environment Factors
  • 3 billion base pairs in the human genome
  • 100 trillion cells in the human body

11
Types of Translational Informatics
  • Locating genetic sequences
  • Identifying genetic mutations
  • Tracking gene activation
  • Modeling protein folding
  • Simulating biologic pathways
  • Drug discovery
  • Personalized medicine

12
The NIH and Translational Informatics
  • GenBank

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The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)

16
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The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)
  • study disease-specific genetic differences
  • Database of Phenome and Genome (dbGAP)

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The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)
  • study disease-specific genetic differences
  • Database of Phenome and Genome (dbGAP)
  • archive of genotype-phenotype studies
  • Entrez

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The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)
  • study disease-specific genetic differences
  • Database of Phenome and Genome (dbGAP)
  • archive of genotype-phenotype studies
  • Entrez
  • Cross-resource search tool for translational
    queries
  • ClinSeq

25
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27
The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)
  • study disease-specific genetic differences
  • Database of Phenome and Genome (dbGAP)
  • archive of genotype-phenotype studies
  • Entrez
  • Cross-resource search tool for translational
    queries
  • ClinSeq
  • Complete sequencing of 1000 individuals
  • Biomedical Translational Research Information
    System (BTRIS)

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The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)
  • study disease-specific genetic differences
  • Database of Phenome and Genome (dbGAP)
  • archive of genotype-phenotype studies
  • Entrez
  • Cross-resource search tool for translational
    queries
  • ClinSeq
  • Complete sequencing of 1000 individuals
  • Biomedical Translational Research Information
    System (BTRIS)
  • reusing clinical research data (1.5 billion rows
    of data)
  • Infobuttons

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35
The NIH and Translational Informatics
  • GenBank
  • Over 100 million sequences (100 billion bases)
  • Genome-Wide Association Studies (GWAS)
  • study disease-specific genetic differences
  • Database of Phenome and Genome (dbGAP)
  • archive of genotype-phenotype studies
  • Entrez
  • Cross-resource search tool for translational
    queries
  • ClinSeq
  • Complete sequencing of 1000 individuals
  • Biomedical Translational Research Information
    System (BTRIS)
  • reusing clinical research data (1.5 billion rows
    of data)
  • Infobuttons
  • delivering translational knowledge to the point
    of care

36
Now What?
  • This biology stuff is complicated
  • Translational research is about applying findings
    from one domain to another domain
  • Translational informatics is the key to
    communicating data and knowledge between domains
  • Translational informatics research is a new field
  • We still need
  • Informatics research support (NCTR? NCTI? NIBI?)
  • Training (extramural and intramural)
  • Support for collaborative efforts (CTSAs)
  • Centralization of resources for efficiency and
    equity
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