Describes NCI's Center for Strategic Scientific Initiatives activities (2005 - 2017) as well as data and technology activities of the 2016 White House Cancer Moonshot Task Force (2016 - 2017).

1. Prostate Cancer Foundation Scientific Retreat: Young Investigator Day
Washington D.C.
October 4th, 2017
Jerry S.H. Lee, Ph.D.
Health Sciences Director
Deputy Director, Center for Strategic Scientific Initiatives (CSSI)
Joint Executive for Data Integration, Center for Biomedical Informatics and Information Technology (CBIIT)
Office of the Director, National Cancer Institute (NCI), National Institutes of Health (NIH)
Advancing Innovation and Convergence in Cancer Research:
National Cancer Institute’s Center for Strategic Scientific Initiatives

2. WHO i am & WHAT is cssi?
2016 at a glance
2017continuing the momentum

3. “…it is of critical national importance
that we …double the rate of progress
in the fight against cancer- and put
ourselves on a path to achieve in just
5 years research and treatment gains
that otherwise might take a decade or
more…”

4. 2003
Source NCI Factbooks (http://obf.cancer.gov/financial/factbook.htm)
201320102007
NCI Director
NCI Principal Deputy Director
10/18/06 07/12/10 04/01/15
Jerry joins 07/06
Von Eschenbach Neiderhuber Varmus Lowy
LowyBarkerBarker

5. 06
2005 2018
Joined NCI
Center for Strategic
Scientific Initiatives
(CSSI)
08
Official
“Other Duties
As Assigned”
09
Transitioned to
Deputy Director, CSSI
10 16
Served as Deputy Director for
Cancer Research and Technology
WH Cancer Moonshot Task Force
4/14/16
10/17/16
PhD in Chemical and Biomolecular Engineering
Nuclear and Cellular Mechanics: Implications for Laminopathies and Cancer

6. 2004
New Cancer Test Stirs Hope and Concern
Lancet 2002; 359: 572-577
2002
Nature 2004; 429: 496-497
2004

7. “The working group recommends
the initiation of a bold technology-
based project: Human Cancer
Genome Project.”
- National Cancer Advisory Board (NCAB) Working Group on
Biomedical Technology, February 16, 2005
https://deainfo.nci.nih.gov/advisory/ncab/workgroup/archive/sub-bt/NCABReport_Feb05.pdf

8. “…the unstated goal of the HCGP is to accelerate the discovery
of cures for cancers. The question we need to answer is not
whether the information generated will be useful, but whether, if
given $1.5 billion in “new” cancer money, would the HCGP
be the best application of that money toward the goal of
cancer cures…”
– Oct 21, 2005

9. “…investigator-initiated grants have
become impossible to get…young
researchers don’t have much of a
future…those that determine
funding…have lost sight of the most
important element…it is not large
research consortia, not new
technologies, not cancer centers, but
the young individual investigator…”
“…a human Cancer Genome
Atlas…would systematically sequence
tumor samples for mutations involved
in cancer to speed up the search for
new drugs and diagnostics…its project
price tag of $1.5 billion over a decade
was whittled down to a 3-year, $100
million pilot…”

11. 04/20/2016

12. NCI Center for Strategic Scientific Initiatives
(CSSI): Concept Shop
Dates indicate approval(s) by NCI Board of Scientific Advisors; *Program moved to NCI Division of Cancer Biology
“…to create and uniquely implement exploratory programs focused on the development and integration of advanced technologies, trans-
disciplinary approaches, infrastructures, and standards, to accelerate the creation and broad deployment of data,
knowledge, and tools to empower the entire cancer research continuum in better understanding and leveraging knowledge of the
cancer biology space for patient benefit…”
Mission
2003, 2007, 2011, 2013, 2014
2004, 2008, 2014
2005, 2010, 2015
2005, 2008 2010
2008, 2013* 2011, 2014
Deputy Director
Jerry S.H. Lee, PhD
Director
Douglas R. Lowy, MD

13. Translational from basic
science to human studies
Translational of new interventions into
the clinic and health decision making
Defining mechanisms,
targets, and lead molecules
New methods of diagnosis,
treatment, and prevention
Delivery of recommended and
timely care to the right patient
True Benefit to society
Controlled studies
leading to effective care

14.  Standards and protocols
 Real-time, public release of data
 Large, multi-disciplinary teams
 Pilot-friendly team environment to share
failures and successes
 Team members with
trans-disciplinary training
Translation Pace: How To Break Out of Current
Paradigm?
Key Needs (from community ‘02)
Turning the Crank… The potential to transform cancer drug
discovery and diagnostics
Paul et. al, Nature Rev. Drug Discovery, March 2010
$150M
Phase I: $273M
Phase II: $319M
Phase III: $314M
$48M
$414M$166M
$94M
~$1.8B/turn

15. “What is Water?”: Measurements  Insights
Color (clear, yellow, brown)
Taste (none, metallic, awful)
LOTS of
Quantitative
“Data”
Qualitative Descriptions
Phase (liquid, gas, solid)
Phase change (boil, melt, freeze)
Measurements
Taken
But also LOTS of
disagreements…
Boiling point = 92oC Boiling point = 100oC

16. “What is Water?”: Standards and Sharing of Data 
New Insights and Understanding
2400m
0m
New Parameter
“Pressure”
LOTS of
Quantitative
and
Reproducible
Data
(Steam Table)
New Understanding
• Phase boundaries
• V/L equilibrium
• Triple Point
(Phase Diagram)
• Define samples and protocols
• Share collected data
Boiling point = 92oC
Boiling point = 100oC

18. (12,000+ patient tumors and increasing)
2006-2015: A Decade of Illuminating the Underlying
Causes of Primary Untreated Tumors
Primary
tumor
(Localized)

19. 2005
12/13/2005
07/25/2005 E. Lander/L. Hartwell (NCAB Report)

20. “…to conduct this mini–cancer-genome project, a 29-person team, resequenced…11
breast cancer samples and 11 colon cancer samples…then winnowed out more than
99% of the mutations by removing errors…and changes that didn’t alter a protein.
…this yielded a total of 189 “candidate” cancer genes. Although some are familiar…most
had never been found mutated in cancer before. The results…are a ‘treasure trove’…
…the relatively small number of new genes common to the tumors reinforces concerns
about [NIH] The Cancer Genome Atlas…
…despite such doubts, the atlas project gets under way next week. NIH will announce
the three cancers to be studied in the pilot phase…the project is on an extremely
aggressive timeline…”

21. glioblastoma multiforme
(brain)
squamous carcinoma
(lung)
serous cystadenocarcinoma
(ovarian)
• Clinical diagnosis
• Treatment history
• Histologic diagnosis
• Pathologic status
• Tissue anatomic site
• Surgical history
• Gene expression
• Chromosomal copy number
• Loss of heterozygosity
• Methylation patterns
• miRNA expression
• DNA sequence
Biospecimen Core
Resource with more than
13 Tissue Source Sites
7 Cancer Genomic
Characterization Centers
3 Genome
Sequencing
Centers
Data Coordinating Center
Three Cancers- Pilot Multiple data types

22. 2008
GBM
Ovarian

23. #ofpatienttumorsamples
ARRA $
Rapid Acceleration from Stimulus Funding (2009-2011)
2006 2007 2008 2009 2010 2011
Patient Samples Collected
(Reality)
Patient Samples Collected
(Projected)
Patient Samples Collected
(No ARRA $)

24. Source: UCSC Cancer Genomic Heatmaps (CopyNumber GISTIC2) [https://genome-cancer.ucsc.edu/] Compiled by Jerry S.H. Lee, PhD, March 2013
Lung squamous:
Lung adeno:
Stomach adeno:
Breast carc:
Ovarian serous:
Kidney clear cell carc:
Prostate adeno:
Colon/rectum adeno:
Head & neck:
Glioblastoma:
343
356
237
866
559
493
171
575
306
563
Total: 5,979
Brain lower grade glioma: 180
Thyroid carc: 401
Uterine corpus end. carc: 492
Liver hep. carc: 97
Kidney pap. cell carc: 103
Bladder carc: 135
Cervical carc: 102
2013

25. Academic Industry
Courtesy of Peter Stojanov, Dana Farber, TCGA 2012 Courtesy of Nickolay Khazanov, Compendia Bioscience, TCGA 2012
Difference Perspectives Using TCGA Data (2012)

26. August 2015

27. Source: UCSC Cancer Genomic Heatmaps (CopyNumber GISTIC2) [https://genome-cancer.ucsc.edu/] Compiled by Jerry S.H. Lee, PhD, March 2013
Lung squamous:
Lung adeno:
Stomach adeno:
Breast carc:
Ovarian serous:
Kidney clear cell carc:
Prostate adeno:
Colon/rectum adeno:
Head & neck:
Glioblastoma:
343
356
237
866
559
493
171
575
306
563
Total: 5,979
Brain lower grade glioma: 180
Thyroid carc: 401
Uterine corpus end. carc: 492
Liver hep. carc: 97
Kidney pap. cell carc: 103
Bladder carc: 135
Cervical carc: 102

28. DNA RNA Protein
Central Dogma of Biology

29. Re-writing Central Dogma (2016)
On average across 375
tumor samples, ONLY 33%
of DNA/RNA predicted
cancer protein abundance
Zhang, B. et. al. Proteogenomic characterization of human colon and rectal cancer. Nature. 2014 Jul 20

30. http://cancerimagingarchive.net
• 33,000 total subjects
in the archive
• 67 data sets currently
available
• 21 from The Cancer
Genome Atlas project
• 10 from the Quantitative
Imaging Network
• Clinical trial data from
ECOG-ACRIN and RTOG

33. CPTAC Public Resources:
http://proteomics.cancer.gov
6.6 TB raw files
(142 TB equivalent downloaded)
898 “fit-for-purpose” targeted assays
(6,584 users/month)
349 mAbs available
(2,653 units distributed)

35. Overarching Structure of CPTAC 3.0
(2016 – 2021)
A. Proteome Characterization Centers
additional cancer types where questions
remain on their proteogenomic complexity
B. Proteogenomic Translational Research Centers
research models and NCI-sponsored clinical trial
C. Proteogenomic Data Analysis Centers
develop innovative tools that process and integrate
data across the entire proteome
Data, assays and resources - community resources
newtreatment-naïve
cancertypes
5-6
Henry Rodriguez
henry.rodriguez@nih.gov

36. Proteogenomic Translational Research Centers
Structure and Information
Applications must cover BOTH preclinical studies and studies
with clinical biospecimens from NCI-sponsored trials
Preclinical Research Arm
• Comprehensively characterize and quantitatively measure
proteins and their variants along with associated genomics
in preclinical cancer model samples
Clinical Research Arm
• Develop and apply quantitative proteomic assays to cancer-
relevant proteins identified in Preclinical Research Arm or
preliminary data, to NCI-sponsored clinical trial samples
(http://proteomics.cancer.gov/aboutoccpr/fundingopportunities/curr
ent/Reissuance-of-Clinical-Proteomic-Tumor-Analysis-Consortium)

39. http://www.cancer.gov/moonshot
October 17, 2016
“…established, within the Office of the Vice President, a
White House Cancer Moonshot Task Force, which will
focus on making the most of Federal investments,
targeted incentives, private sector efforts from industry
and philanthropy, patient engagement initiatives, and
other mechanisms to support cancer research and enable
progress in treatment and care…”
“…a Blue Ribbon Panel… will provide expert advice on the
vision, proposed scientific goals, and implementation of the
National Cancer Moonshot….the Panel will provide an intensive
examination of the opportunities and impediments in cancer
research…initial findings and recommendations of the Panel will
be reported to the National Cancer Advisory Board that will
provide final recommendations to the NCI Director…”

40. Cancer Moonshot
Federal Task Force
Vice President’s Office
“Blue Ribbon Panel”
Working Groups
NCAB
NCI
Courtesy of Dinah Singer (http://deainfo.nci.nih.gov/advisory/bsa/0316/0905Singer.pdf)

41. Catalyze New Scientific Breakthroughs
Unleash the Power of Data
Accelerate Bringing New Therapies to Patients
Strengthen Prevention and Diagnosis
Improve Patient Access and Care
STRATEGIC GOALS IMPLEMENTATION PATH
FEDERAL
PRIVATE/
NON-PROFIT
PUBLIC-PRIVATE
COLLABORATION
2/1/2016 10/17/2016

42. Cancer Moonshot Data & Technology Team
Co-Chairs: Dimitri Kusnezov (DOE), DJ Patil (OSTP), and Jerry Lee (OVP)
Members:
• John Scott (DoD)
• Craig Shriver (DoD)
• Cheryll Thomas (CDC)
• Frances Babcock (CDC)
• Teeb Al-Samarrai (DOE)
• Sean Khozin (FDA)
• Alexandra Pelletier (PIF)
• Maya Mechenbier (OMB)
• Henry Rodriguez (NCI)
• Karen Cone (NSF)
• Michael Kelley (VA)
• Louis Fiore (VA)
• Warren Kibbe (NCI)
• Betsy Hsu (NCI)
• Niall Brennan (CMS)
• Thomas Beach (USPTO)
• Claudia Williams (OSTP)
• Vikrum Aiyer (USPTO)
• Tom Kalil (OSTP)
• Kathy Hudson (NIH)
• Dina Paltoo (NIH)
• Al Bonnema (DoD)
• Michael Balint (PIF)
• Kara DeFrias (OVP)
• Greg Pappas (FDA)
• Erin Szulman (OSTP)
• Paula Jacobs (NCI)

44. Cancer
CenterPatient
Unable to
Share Primary
Care DataPrimary
Care
Cancer Diagnosis
and Treatment
Cancer
Survivor
Primary
Care
Unable to
Share Cancer
Care Data
Cancer
Relapses
(Months-
Years)
(Months-
Years)
Assumes returning to the same cancer care facility
Without a National Learning
Healthcare System for Cancer
Lost Opportunity to
Learn from Pre-Cancer
Clinical Data
Lost Opportunity to
Learn from Post-Cancer
Treatment Clinical Data

45. Vision:
Enable the creation of a Learning Healthcare System
for Cancer, where as a nation we learn from the
contributed knowledge and experience of every
cancer patient. As part of the Cancer Moonshot, we
want to unleash the power of data to enhance, improve,
and inform the journey of every cancer patient from the
point of diagnosis through survivorship.

46. Priorities Areas and Ongoing Activities
Priority Area A: Enabling a seamless data environment [If you build it…]
 MVP CHAMPION and NCI GDC
Priority Area B: Unlocking science through open [Make it easy AND
computational and storage platforms relevant to use…]
 APOLLO
Priority Area C: Workforce development using open [They will come…]
and connected data
 NCI-VA BD-STEP

48. Million Veteran Program Computational Health Analytics for
Medical Precision to Improve Outcomes Now
(MVP CHAMPION)
Department of Veterans Affairs (VA) and the Department of Energy (DOE) are announcing a new five-year
collaboration to apply the most powerful computational assets at the DOE’s National Labs to nearly half a million
veterans' records from one of the world's largest research cohorts -- the Million Veteran Program

49. REGION 1 REGION 2 REGION 4
REGION 3
VA Medical Centers Regional / Corporate Data
Warehousing and Analytical Environment
RDW
V20
V19
V18
V22
V21
MOSS
Farm
RDW
V12
V15
V16
V17
V23
MOSS
Farm RDW
V1
V2
V3
V4
V5
MOSS
Farm
MOSS Farm
•Performance Point Services
•Excel Services
•Reporting Services
•Analysis Services
•Collaboration Services
•Team Foundation Services
RDW
V6
V7
V8
V9V10
V11
MOSS
Farm
CDW
SAS
Grid
VINCI
Apps
PMAS
GIS
MOSS
Farm
Enterprise
Courtesy of Ross Fletcher (DC VAMC)

50. NCI Genomic Data Commons
launched at ASCO on June 6, 2016
https://gdc-portal.nci.nih.gov
2.6 PB of legacy data and 1.5 PB of harmonized data.

51. GDC Content
GDC
 TCGA 11,353 cases
 TARGET 3,178 cases
Current
 Foundation Medicine 18,000 cases
 Cancer studies in dbGAP ~4,000 cases
Coming soon
 NCI-MATCH ~3,000 cases
 Clinical Trial Sequencing Program ~3,000 cases
Planned (1-3 years)
 Cancer Driver Discovery Program ~5,000 cases
 Human Cancer Model Initiative ~1,000 cases
 APOLLO – VA-DoD ~8,000 cases
~56,000 cases

52. TCGA
2004
MATCH
2016
MPACT
LungMAP
ALCHEMIST
2004
How To Accelerate T2T3 Translation for Patients?
(2016)

53. 0
1000
2000
3000
4000
5000
6000
7000
8000
9000
10000
2013 2014 2015 2016 2017 2018 2019 2020
#oftumorsamples
Projected
Reality
Moonshot?
(Agency and International
Collaborations)
2009
2016

54. MCC Military Clinical Trials Network
Naval Medical Center
Portsmouth, VA
Clinical Trials
Increased Access
Referral Center
High cost/low volume
Genetics Counseling
Telehealth technologies
Training &Education
Distributed learning/fellowships
Standardized Clinical
Practice Guidelines
Evidenced-based clinical
practice & research
Patient Outreach
Education and information
MCC Membership
Murtha Cancer
Center
Naval Medical Center
San Diego, CA
Womack Army
Medical Center
Ft Bragg, NC
Keesler Air Force
Medical Center
Biloxi, MS
Lackland Air Force
Medical Center
San Antonio, TX
MCC Clinical Trials Network
Medical Treatment Facilities
MHS
Courtesy of Craig Shriver (DoD)

55. 20262016
How Could This Help the Patients? (2026)
VA
DoD
Proteogenomics
Characterization Centers
(PCC)
Proteogenomics Translational
Research Centers
(PTRC)

56. https://medium.com/cancer-moonshot/
Col. Craig Shriver, MD
Jennifer Lee, MD Henry Rodriguez,
PhD, MBA
5/26/16

57. 50 days (33)
43 days (28)

58. Patients with
new or recurrent
cancer diagnosis
Veterans
Active Duty &
DoD Beneficiaries
Civilians
Consents to
VA/DoD/NCI
APOLLO
research
program
The American
Genome Center
Co-enroll
MVP
Proteogenomics
Characterization
(~8,000 patients)
CPTAC PCC
+ MCC PRO / IHC
Residual tissue for CLIA-approved
targeted sequencing (CATS)
VA ORD
and
NCI-
sponsored
Clinical
Trials
NCI CTEP/CPTAC PTRC
VA Hospitals
Murtha Cancer
Center
Clinical Phenotype
& outcomes
Data aggregation, analysis, and sharing to
rapidly improve outcomes for active duty,
beneficiaries, veterans, and civilians
Murtha Cancer
Center
VA Hospitals
Adaptive Learning
Healthcare System
Clinical Data
Research Data
APOLLO – Applied Proteogenomics OrganizationaL Learning and Outcomes consortium
DaVINCI
Registry
DPALS CATS

60. APOLLO
DAVINCI

61. Applied Proteogenomics OrganizationaL Learning and Outcomes
APOLLO Leadership Meeting
August 29, 2016

62. Applied Proteogenomics OrganizationaL Learning and Outcomes
APOLLO Leadership Meeting
March 3, 2017
(~6 months)

64. https://proteomics.cancer.gov/programs/apollo-network

65. 7/17/2016
“…proteogenomics, which is -- as I used a metaphor
-- it’s like the genes are the full roster of a basketball
team….but the winning strategy comes from finding
out who their starting lineup is. The proteins are the
starters you're going to play against -- the five you
are going to have to defend against
I’m pleased to say, Mr. Prime Minister, that we've
signed three memorandums of understanding
between our two nations …we're going to be able to
share patient histories, proteogenomics and clinical
phenotypes data -- data on various proteins and
genetic characteristics of almost 60,000 patients in
Australia and the United States with full privacy
protections…
And I predict that you're going to see this repeated
around the world.”
- Vice President Biden, Australia
https://www.whitehouse.gov/the-press-office/2016/07/16/fact-
sheet-victoria-comprehensive-cancer-center-vice-president-biden

66. https://tinyurl.com/zr955sr
9/19/2016

68. http://proteomics.cancer.gov
9/16/2017

69. https://proteomics.cancer.gov/programs/
international-cancer-proteogenome-consortium
Henry Rodriguez, PhD, MBA

70. Secondary tumor
Primary tumor

71. Finding the Right “Needle” at the Right “Time” of Disease

72. Sources of Circulating “Needles” (Normal and Cancer Patients)
Bone Marrow GI Tract Skin
Tumor
Fetal DNA

73. https://medium.com/cancer-moonshot/blood-
profiling-atlas-in-cancer

74. BCRF has awarded a team science grant to Drs. Shriver
and Kuhn from the Department of Defense’s Murtha
Cancer Center and the University of Southern
California, while PCF is supporting Dr. Howard I. Scher
of Memorial Sloan Kettering Cancer Center (MSKCC)
and the Prostate Cancer Clinical Trials Consortium
(PCCTC).
The funds have been awarded to recognized leaders in
biomarker assay validation and are intended to
support pilot projects that will utilize multiple
technologies for analyzing rare events in the blood of
cancer patients and subsequently deposit the data
and associated protocols into the Blood PAC
commons.

75. Lauren Leiman
Executive Director
lauren@bloodpac.org
http://bloodpac.org

76. APOLLO

79. Modified from Abernethy et. al. JCO 2010

80. 1998 2004 2015

82. $?
Outcome?

83. https://nciformulary.cancer.gov/
Participating Companies (as of 03/21/2017)
• Bristol-Myers Squibb
• Eli Lilly and Company
• Genentech
• AstraZeneca
• Kyowa Hakko Kirin Co., Ltd.
• Loxo Oncology
• Xcovery Holding Company LLC
03/21/2017
Currently: 26 agents from 7 companies
Agents:
Alectinib; Atezolizumab; Bevacizumab; Cobimetinib; Durvalumab;
Ensartinib; Ipilimumab; Larotrectinib; LY3039478; Mogamulizumab;
Nivolumab; Obinutuzumab; Pertuzumab; Prexasertib; Savolitinib;
Selumetinib;Trastuzumab; Tremelimumab; Vemurafenib; Vismodegib;
Vistusertib; AZD1775; AZD5069; AZD5363; AZD8186; MEDI9447

84. NCI’s Patient-Derived
Models Repository
(PDMR)
https://pdmr.nci.gov

85. Oncology Care
Model
Centers for Medicare &
Medicaid Services Innovation
Center (CMMI)
The Innovation Center is pursuing the opportunity
to further its goals of better care, smarter
spending, healthier people through an oncology
payment model.
• Episode-based
• Emphasizes practice transformation
• Multi-payer model
Nearly ~3,200 physicians from 190 practices
spanning 16 commercial insurers are
participating in OCM
~150,000 unique beneficiaries/year
~200,000 episodes/year (~$6 billion/year)
~20% of CMS FFS chemo patients are in OCM
http://innovation.cms.gov/initiatives/Oncology-Care/
OCMSupport@cms.hhs.gov
Timeline: July 1, 2016-June 30, 2021

86. 1) Provide Enhanced Services
• Provide OCM Beneficiaries with 24/7 access
to an appropriate clinician who has real-
time access to the Practice’s medical
records
• Provide the core functions of patient
navigation to OCM Beneficiaries
• Document a care plan for each OCM
Beneficiary that contains the 13
components in the Institute of Medicine
Care Management Plan
• Treat OCM Beneficiaries with therapies that
are consistent with nationally recognized
clinical guidelines
2) Use certified electronic health record
technology (CEHRT)
3) Utilize data for continuous quality
improvement
Novel Therapies Adjustment
• Potential adjustment based on the proportion of
each practice’s average episode expenditures for
novel therapies
– Includes oncology drugs that received FDA
approval after December 31, 2014
– Use of the novel therapy must be consistent with
the FDA-approved indications for inclusion in the
adjustment
– Oncology drugs are considered “new” for 2 years
from FDA approval for that specific indication
Ron Kline, MD

87. 1997 20172002 2007 2012
10/23/2001
(~4 yrs old)
1/9/2007
(~10 yrs old)
iPod (10GB max)
iPhone
(EDGE, 16 GB max)
9/16/1999
(~3 yrs old)
802.11b WiFi
4/3/2010
(~13 yrs old)
iPad
(EDGE, 64 GB max)
4/23/2005
(~8 yrs old)
9/26/2006
(~9 yrs old)
7/15/2006
2/7/2007
UberX
7/1/2012
(~15 yrs old)7/11/2008
(~11 yrs old)
iPhone 3G
(16 GB max)
9/12/2012
(~15 yrs old)
iPhone5
(LTE, 128 GB max)
Google
Baseline
3/9/2015
(~18 yrs old)
Apple
ResearchKit
AI beats
human at Go
3/15/2016
(~19 yrs old)
HTC VR Headset
4/5/2016
(~19 yrs old)
7/14/2014
(~17 yrs old)
Next Gen
5/1/1997
AOL Instant
Messenger
4/21/1997
WinAMP(mp3)
4/28/2003
(~6 yrs old)
iTunes
Music Store

88. $640M
(FY74)
$5.39 B
(FY16)

90. Big Data Scientist Training Enhancement Program
(BD-STEP)
Graduates of BD-STEP would:
• have skillsets to perform next-generation patient-
centered outcomes research by manipulating and
analyzing large-scale, multi-element, patient data sets
to develop novel disease signatures or unique
performance-based clinical benchmarks
• have an understanding of real-time, performance-
driven health care delivery in the VA systems
Michelle Berny-Lang, NCIConnie Lee, VHA/EES
2017 Potential
Partners:

91. BD-STEP Sites and Fellows: 2016-2017

92. Courtesy of William Cerniuk, VHA Technology Director
William Cerniuk
VHA

93. Courtesy of William Cerniuk, VHA Technology Director

94. 94
National Cancer Data Ecosystem
Genomic
Data Commons
Data Standards
Validation and Harmonization
Imaging
Data Commons
Proteomics
Data Commons
Clinical Data
Commons
(Cohorts / Indiv.)
SEER
(Populations)
Data Contributors and Consumers
Researchers PatientsCliniciansInstitutions
Blood Profiling Atlas
Commons

98. NCI CSSI Science Day 2015
5/18/2015
“…Cancer research initiatives for trans-NCI benefit (started
in 2003; total awards ~100million/year; 25% first time NIH
grantees…”- Doug Lowy, 2015
Breakdown of Contact PI Status of New Awards Solicited by CSSI RFAs (FY05-FY14)

99. http://ascpt.onlinelibrary.wiley.com/hub/issue/10.1002/cpt.v101.5/
FDA
VA
CMS
NCI
NCI/DOE
NCI/VA/DoD

100. Acknowledgements/Thanks to the
“Secret Ingredients”
Clinical Sciences
Physical Sciences
Life Sciences

101. Learn More About Us…
http://cssi.cancer.gov
Jerry S.H. Lee, PhD
jerry.lee@nih.gov
@NCI_CSSI
@jleePSOC

102. Development of a Natural Language Processing
(NLP) Workbench Web Service
• Two Year Project (July 2016 – September 2018)
• Project Goals:
– Develop a Natural Language Processing (NLP) Workbench that utilizes
Web Services for analyzing unstructured clinical information
– Pilots for use in cancer registries and safety surveillance domains
– Code cancer data items to nationally adopted coding systems (ICD-O-3)
– Collect data from at least four national laboratories for the following
primary cancer sites (Breast, Lung, Prostate, Colorectal)
• 125 cases per cancer site from each laboratory for a total of at least 2,000 cases.
– Double annotation will be completed by certified tumor registrars with
a master reviewer
NLPWorkbench@cdc.gov

103. Sandy Jones (CDC)
NLP Workbench Web Service
Dos and Don’ts
• Will include processes with demonstrated
efficiency - is more than a collection of
general NLP components and workflows
• Will cover certain needs - cannot be the
panacea for all problems
• Will describe the process for the generation
of annotated datasets
• Intend to incorporate only open-source
solutions equipped to support the project
objectives and will not endorse ANY existing
solution