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From human genomic research
to digital medicine
Jacques Fellay
School of Life Sciences
EPFL – Lausanne, Switzerland
Marching towards predictive,
preventive, personalized and
participatory (4P) medicine
A revolution in the making
Eric Green et al., Charting a course for genomic medicine from base pairs to bedside, Nature 2011
A revolution in the making
2001: A Species' Odyssey
3 billions base pairs (ATGC)
23’000 protein-coding genes
99.9% inter-individual identity (yet 4 millions differences)
99% identical to chimpanzee genome (yet 6% different genes)
The human genome
DNA
RNA
Proteins
ATGC
AUGC
20 amino acids
The flow of genetic information
Epigenome
Metagenome
Proteome
Metabolome
Transcriptome
Exploring the human genome
Sanger sequencing,
targeted genotyping
Genome-wide
genotyping (GWAS)
Exome
sequencing
Genome
sequencing
2001 2008
We are all different…
4 million DNA variants / individual
 Single nucleotide polymorphisms (SNPs)
 Small insertions/deletions (indels)
 Larger structural variants
• copy number variants (CNVs)
• inversions
• translocations
Exploiting human genetic variation
Identification of
relevant genetic variant
Prediction
models
Understanding of
underlying biology
Clinically useful
prediction
Clinically useful
therapies
Infection
Exposure
Viral control -
disease
progression
Resistance -
acquisition
HIV host genetic studies:
clinical phenotypes
Science 1996 Sep 27;273(5283):1856-62
Science 2010 Dec 10;330(6010):1551-7
Science 2007 Aug 17;317(5840):944-7
Genetic score and HIV disease progression
Fellay et al., PLoS Pathogens 2011
IL28B genotype and response
to anti-hepatitis C treatment
Ge, Fellay et al. Nature 2009
0
18.7
48.4
0.8
10
0
10
20
30
40
50
60
CC
n=18
AC
n=252
AA
n=1,010
Percentage
rs7270101
0
4.5
47.6
9.3
0
10
20
30
40
50
60
AA
n=10
CA
n=156
CC
n=1,114
Percentage
rs1127354
Hb decline >3g/dL
Hb level <10g/dL
ITPA-deficiency ITPA-deficiency
Fellay et al. Nature 2010
Hemoglobin drop, by ITPA genotypes and predicted function
ITPA genotype and anti-HCV
treatment-induced anemia
Who needs therapy?
Will therapy be effective?
When to start?
Which drug regimen?
For how long?
Will therapy be tolerated?
The clinical management of patients suffering from chronic
hepatitis C virus infection represents an ideal setting to
demonstrate the relevance of personalized medicine
A. Rauch & J. Fellay
Phase 1b trials:
• Comparable efficacy to IFN-a
• Synergistic effect with IFN-a
• Less side effects
- tissue specific receptor expression
Interferon-lambda: a promising HCV drug
- It starts here and now
- It raises extremely broad issues
 Across many fields: medicine, research, economy,
law, ethics, philosophy…
- It offers many avenues for job opportunities
 Development of new industry focused on
nanotechnology, medical IT, digitalization,
biobanking, impact assessment, wellness, etc.
Personalized health
By fostering programs of basic & applied research in:
-Genetics, genomics, proteomics, metabolomics
-Integrative (“systems”) biology and medicine
-Bioinformatics / Biomathematics (data analysis)
-Computational biology / modeling / imaging
-Computer sciences (data management /encryption)
-Ethics, law and economics
Personalized health: how to get there?
Research
By training trans-disciplinary scientists, engineers and
medical doctors, for instance through the teaching of:
-“Medicine 101” for scientists and engineers
-Quantitative sciences and technology for medical
students
Personalized health: how to get there?
Education
Through the creation of funding mechanisms that allow
the creation, maintenance and staffing of state-of-the-art
“technolomics” R&D platforms, needed both for research
in “systems medicine” and for clinical applications.
Through an in-depth reflection on (targeted) biobanking.
Through discussion / collaboration between national
bodies in charge of health care and biomedical research.
Personalized health: how to get there?
Infrastructure
By educating the population and keeping it properly
informed about the potential, progress and limitations of
personalized health, allowing for a public debate of all
relevant issues, and the exploitation of social networks
Personalized health: how to get there?
Social framework
PATIENT SOCIETY
Digital data
Health
information
Clinical
interface
Data generation
Data analysisClinical translation
Privacy & Ethics
Education & Training
A virtual “Digital Medicine Campus”
in Western Switzerland?
More than 60 medical, research and advocacy organizations
in 41 countries formed a global alliance to share patients'
genetic and clinical information in an effort to "dramatically
accelerate medical progress" in determining the biological
bases of inherited and infectious diseases, as well as shed
light on the effects of various treatments on different patients.
Thank you!
http://fellay-lab.epfl.ch

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Jacques Fellay, EPFL, pour la journée e-health 2013

  • 1. From human genomic research to digital medicine Jacques Fellay School of Life Sciences EPFL – Lausanne, Switzerland
  • 2. Marching towards predictive, preventive, personalized and participatory (4P) medicine A revolution in the making
  • 3. Eric Green et al., Charting a course for genomic medicine from base pairs to bedside, Nature 2011 A revolution in the making
  • 5. 3 billions base pairs (ATGC) 23’000 protein-coding genes 99.9% inter-individual identity (yet 4 millions differences) 99% identical to chimpanzee genome (yet 6% different genes) The human genome
  • 6. DNA RNA Proteins ATGC AUGC 20 amino acids The flow of genetic information
  • 8. Exploring the human genome Sanger sequencing, targeted genotyping Genome-wide genotyping (GWAS) Exome sequencing Genome sequencing 2001 2008
  • 9. We are all different… 4 million DNA variants / individual  Single nucleotide polymorphisms (SNPs)  Small insertions/deletions (indels)  Larger structural variants • copy number variants (CNVs) • inversions • translocations
  • 10.
  • 11.
  • 12. Exploiting human genetic variation Identification of relevant genetic variant Prediction models Understanding of underlying biology Clinically useful prediction Clinically useful therapies
  • 13.
  • 14. Infection Exposure Viral control - disease progression Resistance - acquisition HIV host genetic studies: clinical phenotypes
  • 15.
  • 16. Science 1996 Sep 27;273(5283):1856-62 Science 2010 Dec 10;330(6010):1551-7 Science 2007 Aug 17;317(5840):944-7
  • 17.
  • 18. Genetic score and HIV disease progression Fellay et al., PLoS Pathogens 2011
  • 19. IL28B genotype and response to anti-hepatitis C treatment Ge, Fellay et al. Nature 2009
  • 20. 0 18.7 48.4 0.8 10 0 10 20 30 40 50 60 CC n=18 AC n=252 AA n=1,010 Percentage rs7270101 0 4.5 47.6 9.3 0 10 20 30 40 50 60 AA n=10 CA n=156 CC n=1,114 Percentage rs1127354 Hb decline >3g/dL Hb level <10g/dL ITPA-deficiency ITPA-deficiency Fellay et al. Nature 2010 Hemoglobin drop, by ITPA genotypes and predicted function ITPA genotype and anti-HCV treatment-induced anemia
  • 21.
  • 22. Who needs therapy? Will therapy be effective? When to start? Which drug regimen? For how long? Will therapy be tolerated? The clinical management of patients suffering from chronic hepatitis C virus infection represents an ideal setting to demonstrate the relevance of personalized medicine A. Rauch & J. Fellay
  • 23. Phase 1b trials: • Comparable efficacy to IFN-a • Synergistic effect with IFN-a • Less side effects - tissue specific receptor expression Interferon-lambda: a promising HCV drug
  • 24. - It starts here and now - It raises extremely broad issues  Across many fields: medicine, research, economy, law, ethics, philosophy… - It offers many avenues for job opportunities  Development of new industry focused on nanotechnology, medical IT, digitalization, biobanking, impact assessment, wellness, etc. Personalized health
  • 25. By fostering programs of basic & applied research in: -Genetics, genomics, proteomics, metabolomics -Integrative (“systems”) biology and medicine -Bioinformatics / Biomathematics (data analysis) -Computational biology / modeling / imaging -Computer sciences (data management /encryption) -Ethics, law and economics Personalized health: how to get there? Research
  • 26. By training trans-disciplinary scientists, engineers and medical doctors, for instance through the teaching of: -“Medicine 101” for scientists and engineers -Quantitative sciences and technology for medical students Personalized health: how to get there? Education
  • 27. Through the creation of funding mechanisms that allow the creation, maintenance and staffing of state-of-the-art “technolomics” R&D platforms, needed both for research in “systems medicine” and for clinical applications. Through an in-depth reflection on (targeted) biobanking. Through discussion / collaboration between national bodies in charge of health care and biomedical research. Personalized health: how to get there? Infrastructure
  • 28. By educating the population and keeping it properly informed about the potential, progress and limitations of personalized health, allowing for a public debate of all relevant issues, and the exploitation of social networks Personalized health: how to get there? Social framework
  • 29. PATIENT SOCIETY Digital data Health information Clinical interface Data generation Data analysisClinical translation Privacy & Ethics Education & Training A virtual “Digital Medicine Campus” in Western Switzerland?
  • 30. More than 60 medical, research and advocacy organizations in 41 countries formed a global alliance to share patients' genetic and clinical information in an effort to "dramatically accelerate medical progress" in determining the biological bases of inherited and infectious diseases, as well as shed light on the effects of various treatments on different patients.