1. UCSF INFORMATICS DAY10 June 2014 1
UCSF INFORMATICS DAY:
INNOVATIVE INFORMATICS AT THE UCSF BREAST CARE CENTER
10 June 2014
Sue Dubman, Director IT & Informatics
Carol Franc Buck Breast Care Center
Alexandra Solomon, Athena & Applied
Genomics Program Manager

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Outline
 The UCSF Breast Care Center
o Leadership
o Mission and Vision
o Key Programs
o Organizational Framework
 UCSF Breast Care Center Integrated Platform
 Use Cases
o I-SPY2: Accelerating new treatments to market
o Athena: Integrating research and care
 Q&A

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UCSF Breast Care Center Leadership
Laura Esserman, M.D., M.B.A.
Director, UCSF Carol Franc Buck Breast
Care Center
Internationally-recognized Surgeon and
Breast Cancer Oncology Specialist
Visionary behind Informatics-enabled
research and care programs
Identified by San Francisco Chronicle as a
“Bay Area Person to Watch” in 2014
“A force of nature”
Laura Van’t Veer, Ph.D.
World renowned Molecular Biologist
Called by Cancer World, the “Person Behind
Personalized Medicine”
Inventor of MammaPrint, a diagnostic test
that foretells the risk of recurrence for breast
cancer patients
Winner, 2014 EU Prize for Women Innovators
Co-PI with Dr. Laura Esserman on one of key
BCC Programs enabled by Informatics

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Mission and Vision for the UCSF’s BCC
• Total Quality Management (TQM)
• Improve outcomes and quality of life for
Breast Cancer Patients
• While reducing overall costs
Mission
• Transform
• The way we do research
• The way care is provided
• How patients, providers, payers and other
stakeholders interact with each other and
the health care system
Vision

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EM
R
EHR
Patient
reported data
Clinical trial
management
& adaptation
Clinical trial
matching
Individualized
Connected
Care
Clinician
entered and
verified
UCSF Breast Care Integrated Platform

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Achieving the Promise of Total Quality Management:
Requires lotsof coordinationat each juncturethroughdevelopment, discovery and delivery,
from benchto bedsideand back

7. UCSF INFORMATICS DAY10 June 2014 7UCSF INFORMATICS DAY10 June 2014 7
I-SPY 2 CLINICAL TRIAL
A Replicable Model for
Accelerating Drug Development and Approval

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What problem are we solving?
 New oncology drugs take 10-
15 years to reach patients
 Price tag is $1+ billion
 Absence of innovation in trial
design/data collection tools
 Cancer is a subset of diseases
 Blockbuster approach won’t
work
Current path is UN-SUSTAINABLE

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I-SPY’s Primary Aim: Accelerate Pace of
Progress
Key Goals include:
Implement efficient trial designs with use of biomarkers
and/or surrogate endpoints to drive knowledge turns
 Increase therapeutic agents tested with a standing trial and
extensive network of clinical sites
 Integrate the processes of clinical care and research, both
technologically and culturally with team approach

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I-SPY’s Acceleration of
Knowledge Turns
Promising
qualifying
biomarker
I-SPY 2 TRIAL
amendment
approved
Continuous
enrollment
Drug
graduates or
is dropped
Full
Approval
Accelerated
Approval for
Agent/
Approval for
biomarker/PMA
SCREENING
PHASE
Adapts on drugs
(~60 patients)
Agent Enters
New agent/combination qualifies and
is approved for I-SPY 2
pCR not
confirmed
BIOMARKER
PHASE
CONFIRMATORY
PHASE
Adapts on biomarker
(~300 patients)

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22 Participating Trial Sites, Expanding to Canada
Screening40+ patientsper month

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Clinical Trial Data Capture – Advances with
TRANSCEND
 An integrated modular platform to support adaptive clinical
trials like I-SPY 2 TRIAL
 Structured, coded eCRFs with source documents attached
to CRF in Electronic Data Capture system
o Enable real-time, remote source data verification within EDC
 Randomization as an automated web service
o Using data that has been source data verified
 Combining evaluation of drugs and biomarkers together
o Scientists need access to data early and in an integrated fashion
(one stop shopping)
• Clinical, Pathology, Imaging data along with biomarker
data of various types (microarray, sequencing, etc.)

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TRANSCEND Platform
Data Flow
Key Features of TRANSCEND
 Scalability with Salesforce, cloud-based environment
 Modular, can securely integrate with other applications as well
RE App
Quartz
Scheduler
THE Force on SalesForce (Electronic Data Capture)
Data Coordinating
Center
Study Sites
Case Report
Forms
Agendia
caIntegrator
(Role based access
to data)
caArray
Research Labs
Automated
Manual
Integration Engine
(MirthConnect)
SMART
Randomization
Engine
-Single Sign On
-Pulls data from caArray
NBIA
(Imaging with AIM tool)
Reporting
(Pentaho)

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Advantages of Adaptive Design
 Learn if the drug works better or worse than you think, as
the trial progresses
 Act early
o Drop drugs quickly if they are ineffective or harmful
o Graduate sooner if they are clearly beneficial
 Learn, for each drug, which biomarkers are optimal
 Phase 2 conclusions will be more accurate, better
treatment of patients in the trial
 Follow on 3 trials can be smaller (usually)

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I-SPY 2 Major Accomplishments
 Demonstrated that endpoints work better by subtype
 Enlisted multiple pharma companies into same trial
 Developed I SPY 2 infrastructure
o IT systems to support adaptive learning
o New methods to distribute credit
 Accelerated Approval guidance issued by FDA
 Next Step: I-SPY 3 international confirmatory trial

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I-SPY 2/3 Partnership Opportunities
Collaboration with other therapeutic areas to
propagate I-SPY methodology
o Assist in setting up research networks
o Sharing of systems & technologies
Seeking partners for I-SPY 3 Trial
o Investors
o Research networks
o Delivery partners

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R&D, Product to Implementation: Linear Inefficiency

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...TO A MODEL THAT LEARNS BY RE-USE OF INFORMATION
Source: Buetow, BIO
• New biomarkers identified
• Validation conducted in silico
against clinical outcomes
Discovery
• Drug candidates targeted to defined sub-
groups
• Clinical trials enriched with appropriate
sub-group
• Clinical trial recruitment from “standing”
cohort of pre-enrolled volunteers
• NDA includes genomic data
Product Development
• All patients genotyped
• Clinical trial protocols used as treatment
plans, following regulatory approval
• Clinical decision support tools assist
physician by comparing the patient vs..
the Outcomes Database
• Each patient’s outcome de-identified and
fed back to the database
Clinical Care
• All clinical outcomes
captured and fed to
Outcomes Database
• “Sentinel” function
sounds alarm for safety
or opportunity for
expanded indications
Outcomes and
Surveillance
• Outcomes linked to molecular
profiles
• Algorithms identify linkages and
trends
• New hypothesis generated
Analysis and Learning
A Learning Health
Care System

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Athena
On mission to save lives by transforming how we deliver
care today, learn from our patients, create life-changing
science, and improve prevention and treatment options
today and tomorrow.

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Athena
Platform
Patient
Web services
(algorithms, risk
models, thresholds)
Athena Breast Health Network
Information Exchange
Breast Health
Specialist
Supportive cancer
services; primary
providers; care team
Patient

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Athena Breast Health Network
On a mission to achieve transformational change
Capture patient stories and preferences, tumor
biology, clinical performance
Deliver personalized prevention, screening, and
treatment
Deliver better care tomorrow by enabling care to be
an engine for discovery and improvement
Data in – knowledge outA UC-wide and affiliate program

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Automated delivery and patient submission of
targeted electronic intake forms based on
appointment
Athena
Platform
Patient
Web services
(algorithms, risk
models, thresholds)
Real-time assessment of risk, provider and
specialist communication, referral to
personalized resources and services
Breast Health
Specialist
Supportive cancer
services; primary
providers; care team
Patient

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Athena Technology Platform
!
!
!
Health!Ques+onnaire!System!
!
!
!
!
!
!
!
Shared!Ques+on!
Bank!
!
Contextual!
Answer!
Repository!
Questionnaire
Designer
Statistical
Analysis
Questionnaire Distribution
and Data Collection
Clinical
Decision
Support
Clinic
Workflow
Triggers
EMR
Integration
Process
Improvement
Dashboards
Customized
Consumer
Portal

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Increasing efficiency, reducing costs and
improving care
Athena
Platform
Referral
thresholds
met
Pended in APeX for clinician sign off
Psycho- oncology
Peer Support
Social W ork
Smoking Cessation
Genetic Counseling
W eight Management
Onco-fertility
Supportive Care
Services
Patient
Revenue for services
Better care
for patients

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Athena
Platform
Patient
Web services
(algorithms, risk
models, thresholds)
Personalized Screening
“one size does not fit all”
Breast Health
Specialist
Supportive cancer
services; primary
providers; care team
Patient
Genomic
Profiling
Breast
Density

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Strength In Numbers and Team Science
Dr. Barbara Parker, UCSD Dr. Robert Cardiff, UCD
Dr. Hoda Anton-Culver,
UCI
Dr. Laura van ‘t Veer ,
UCSF

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Athena wouldn’t be possible without many of you
 UCSF IT Teams (Radiology,
Interface, Clinical Inpatient,
HIMSS, Leadership)
 Athena IT Team and Program
Management Office (PMO)
 Athena UCSF Site team
 UCDavis Mirth Interface Team
 Molecular Biologists
 Epidemiologists
 Radiologists
 Genetic Counselors / Breast
Health Specialist
 Geneticists
 Surgeons
 Radiation Oncologists
 Oncologists
 Anthropologists
 Statisticians
 Social Workers
 Psycho-Oncologists
 Psychologists
 Nutrition and exercise
specialists
 Pathologists
 Reconstructive surgeons
 Mammography Technologists
 Administrators and Leadership
 Clinical Coordinators
 Laboratory Technicians
 Clinical staff
 Call center staff
 Patients

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“Never doubt that a small group of committed people can
change the world. Indeed it is the only thing that ever has.”
-Margaret Mead
“The greater danger for most of us lies not in setting our aim
too high and falling short; but in setting our aim too low, and
achieving our mark.”
- Michelangelo
The Challenges are Hard but...

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Athena UCSF Interfaces
*Athena platform collects discrete data; opportunities to integrate discrete data
mapped to health history etc. back into Epic.

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Data in,
Knowledge out
Capture patient stories and
preferences, tumor biology, clinical
performance
Deliver personalized prevention,
screening, and treatment
Deliver better care tomorrow by
enabling care to be an engine for
discovery and improvement