Health Datapalooza IV: June 3rd-4th, 2013 Illuminating Disease at the Speed of Light: How Big Data Is Accelerating Biomedical Research Convener: Marcia A. Kean, Chairman, Strategic Initiatives, Feinstein Kean Healthcare Moderator: Kevin Davies, Author, “The $1,000 Genome”; Founding Editor, Nature Genetics and Bio-IT World magazine; and Vice President Business Development, American Chemical Society Speakers: Amy P. Abernethy, Director, Center for Learning Healthcare (CLHC), Duke Clinical Research Institute Michael Cantor, Senior Director, Information Strategy and Analytics, World Research Development, Pfizer Dave King, Founder, Exaptive Robert McBurney, Chief Executive Officer, Accelerated Cure Project for Multiple Sclerosis Dietrich Stephan, Founder and Chief Executive Officer, Silicon Valley Biosystems (SV Bio) Until recently, biomedical research was conducted in small silos, separated by huge cultural and technical walls and inability to exchange data facilely. But the field is now exploding: massive amounts of complex, multi-dimensional clinical, imaging, and genomic data are being collected, aggregated, integrated, analyzed, and shared. The pioneers driving this digital transformation are working in novel collaborations among patients, providers, and scientists. In this session, speakers will showcase multimodal, computational, and analytic tools for biomarker discovery, patient stratification, and intelligent clinical decision solutions; high-speed genome profiling, with algorithms of individual and population profiles, for real-time molecular-based diagnoses of ‘mystery’ diseases; a point-of-care quality monitoring program used by clinicians, in which data are used for important research questions and then transitioned into clinical trials; and collection and aggregation of data and samples from patients with a neurological disease, enabling queries into markers of disease origins and discovery of new therapies.

3. The Innovation Bridge
Data liquidity
Real-time data use
Data reuse
Standards
Culture & Incentives
Learning

9. “Research quality clinical data”
Individual
patient
Research reports
Clinical operations
21% with pain >4/10 on
>2 visits

11. mHealth approach to quality patient
data collection
Software/Hardware Instrument
Process Reporting/Analytics

12. “Research quality clinical data”
Research Item(s) - Pain
Research Item(s) – Sleep
Clinical Review of
Systems…
Fatigue
Bleeding
Ringing in the ears
Pain
Sleep
Shortness of breath
Constipation
etc
Research Item(s) - Fatigue

13. Clinical Review of
Systems…
Fatigue
Bleeding
Ringing in the ears
Pain
Sleep
Shortness of breath
Constipation
etc
Integration of items from varied
sources
Research Items – Pain &
Sleep
Research Item(s) - Fatigue

14. Clinical Review of
Systems…
Fatigue
Bleeding
Ringing in the ears
Pain
Sleep
Shortness of breath
Constipation
etc
Drill down when needed
Research Items – Pain &
Sleep
Research Item(s) - Fatigue
Threshold trigger to
additional instrument
about pain (e.g. BPI)

15. Patient
reported
data
Linked to other datasets
Clinical and
administrative
data
Clinical trials
and research
related data
Molecular and
biological data

20. Logrank p<.0001
No Chemo
TKI/TKI
Other
TKI/mTOR/TKI
TKI/TKI/mTOR
TKI/mTOR
mTOR/TKI
mTOR
0.0
0 10 20 30 40 50
0.2
0.4
0.6
0.8
1.0
TKI
Overall Survival
SurvivalProbability

21. The Innovation Bridge
Data liquidity
Real-time data use
Data reuse
Standards
Culture & Incentives
Learning