The document discusses the early development of genomic medicine and emphasizes the importance of collaboration, data analysis, and addressing privacy and security challenges. It highlights the Broad Institute's capabilities in genomic data production and the necessity for innovative technology and practices for effective data sharing and usage. The need for regulatory reforms and incentive structures to promote accessible and useful data is also underscored as organizations prepare for the future of genomic medicine.

1. Preparing For Genomic Medicine
September 2016: CXO Forum
Chris Dwan
Director, IT Architecture and Strategy
cdwan@broadinstitute.org @fdmts

2. Conclusions
• We are still in the early days of genomic medicine.
• Organizations who are effective at collaboration and
integrative data analysis will lead the next decade of
biomedical delivery*
• Privacy, security, and ensuring appropriate access to data
will be necessary challenges
• Technology and technologists will be a key differentiator
* Increasingly, you must be competent at these things to even participate.

3. Coming soon, to a patient near you

4. Coming soon, to a patient near you
This will be the new normal and
public expectation within 5 years

5. • Non-profit biomedical research
institute founded in 2004
• Fifty core faculty members,
from MIT and Harvard, plus
hundreds of associate
members.
• ~1000 employees
• >> 2,400+ researchers
Programs and Initiatives
focused on specific disease or biology areas
Cancer Genome Biology
Cell Circuits Psychiatric Disease
Metabolism Medical and Population
Genetics Infectious Disease
Epigenomics
Platforms
focused technological innovation and application
Genomics Data Sciences
Therapeutics Imaging
Metabolite Profiling Proteomics
Genetic Perturbation
The Broad Institute

6. • Non-profit biomedical research
institute founded in 2004
• Fifty core faculty members,
from MIT and Harvard, plus
hundreds of associate
members.
• ~1000 directly affiliated
personnel
• ~2,400+ associated researchers
Programs and Initiatives
focused on specific disease or biology areas
Cancer Genome Biology
Cell Circuits Psychiatric Disease
Metabolism Medical and Population
Genetics Infectious Disease
Epigenomics
Platforms
focused technological innovation and application
Genomics Data Sciences
Therapeutics Imaging
Metabolite Profiling Proteomics
Genetic Perturbation
The Broad Institute
“This generation has a historic opportunity and responsibility
to transform medicine by using systematic approaches in the
biological sciences to dramatically accelerate the
understanding and cure of disease”

7. Genomic Data Production @ Broad

8. Genomic Data Production @ Broad
~140 Whole Genome
Sequences / day

9. Genomic Data Production @ Broad
~140 Whole Genome
Sequences / day
~1PB data / month raw (> 40PB total holdings)
~15k cores (hybrid cloud) dedicated to primary analysis
100Gb/sec link to Internet2

10. Genomic Data Production in Context

11. Genomic Data Production in Context
We have learned a
vast amount in the
last decade

12. Genomic Data Production in Context
We have learned a
vast amount in the
last decade
The question is no longer “can we do
this?” but “what shall we do?”

13. People @ Broad

14. The future is already here – it’s just not very well
distributed
William
Gibson

15. The future is already here – it’s just not very well
distributed
William
Gibson

16. The right side of history
• Applications are containerized (Docker)
• Data is accessed RESTfully (S3 standard)
• Identity management is federated (Oauth2)
• Analytics are ubiquitous (HDFS / Spark)
• Public clouds (AWS, GCS, Azure) provide flexible commodity
infrastructure and surge capacity
• Data flow operations adopt serverless architectures (Lambda)
• Technologists are embedded in project teams (DevOps)
This is a multi year
journey. Start today.

17. Transition to Public Clouds

18. Genomes on the Cloud (April 2016)
Testing the
genome analysis
pipeline
“Go-live”

19. 3rd Party Companies Fill Cloud Feature Gaps
Cloudhealth dashboard atop the billing API
Storage $$
Network $$

20. Governance remains critical
$$ !!

21. The new normal

22. The new normal

23. The new normal

24. You move towards and become like that which you
think about.

25. The Big Data Healthcare Feeding Frenzy
• “If we sequence X new patients with condition Y every year,
the sequencing data alone will take up ALL THE
EXABYTES”*
• The data storage and analysis needs of precision /
personalized / genomic medicine are not unreasonable by
comparison with major, data driven industries.
• We can compensate by being thoughtful about what data we
store, how we store it, and how we share it.
* If you multiply a number by a sufficiently large number the product is a large number.

26. We’re starting to get a handle on
the basics
• Reduced footprint for genomic data
– 30X WGS: 200GB ==> 40GB
• Increasingly standardized and well integrated variant
calling and annotation tools
• Powerful public reference sets and tools

27. … people who had
nothing to do with
the design and
execution of the study …
... use another group’s data for their own ends …
… even use the data to try to disprove what the
original investigators had posited…
… some researchers have characterized as “research
parasites”
Fear, Uncertainty, and Doubt

28. The regulatory framework
• Under current law and practice, there is very limited
organizational upside to sharing PHI and EMR.
• Data use policies: Financial risk
• Research participation: Risk to privacy
• De-identification (AKA data mutilation) is not a viable, long
term strategy in the age of analytics
• Also, the compliance process, even in lightweight versions
is killing our ability to innovate.

29. “To be without method is deplorable, but to depend
entirely on method is worse.”
The Mustard Seed Garden Manual of Painting, 1679

30. Appropriate Usage: A framework
Any person
Should have appropriate access to any and all data
Necessary to correctly answer appropriate questions

31. Appropriate Usage: A new framework
Any person
Should have appropriate access to any and all data
Necessary to correctly answer appropriate questions
This looks almost nothing like our current regulatory framework.

32. What we need
• Incentive structures that reward making data accessible
and useful
– All indicators except the benefit of the patient lead to suboptimal behavior
– This will require courage.
• National / global data scale data repositories, standards,
and toolkits
– Death to walled gardens, monolithic systems, and GUIs.
– Life to APIs built for a global community (c.f. Amazon, 2002)
• Open, fearless conversation about data protection vs.
appropriate use
– Genomic data is inherently personally identifiable and should be treated as such
– “Appropriate usage” goes well beyond legal conformity

33. Standards are needed for genomic data
“The mission of the Global Alliance for Genomics
and Health is to accelerate progress in human
health by helping to establish a common framework
of harmonized approaches to enable effective and
responsible sharing of genomic and clinical data,
and by catalyzing data sharing projects that drive
and demonstrate the value of data sharing.”
Regulatory Issues
Ethical Issues
Technical Issues

34. This stuff is important
We have an opportunity to change lives and health
outcomes, and to realize the gains of genomic medicine, not
in an indefinite future, but this year.
We also have an opportunity to waste vast amounts of
money (very rapidly) and still not really help anybody.
I would like to work together with you to build a better future.
cdwan@broadinstitute.org

35. The right side of history
• Applications are containerized (Docker)
• Data is accessed RESTfully (S3 standard)
• Identity management is federated (Oauth2)
• Analytics are ubiquitous (HDFS / Spark)
• Public clouds (AWS, GCS, Azure) provide flexible commodity
infrastructure and surge capacity
• Data flows and transforms adopt serverless architectures (Lambda)
• Technologists are embedded in project teams (DevOps)
This is a multi year
journey. Start today.

36. Thank You