1. Translational Informatics
@ UCSF
1nf0rmatics Day
June 10th
, 2014
Sorena Nadaf M.S.,M.MI
Associate Director HDFCCC
Chief Informatics Officer, Director of Translational Informatics Program

2. “Science is evolving at an incredible pace.
It’s a revolutionary period. The fundamental
change is that biomedical science has
converged…
Elias Zerhouni, M.D.
2

3. 3
• The landscape of clinical, basic science, and
translational research has evolved and is still rapidly
changing
• Enabled by:
• Genomics, High Throughput Molecular Science
• Ubiquitous data communications & computing
• Driven by National Programs:
• Precision Medicine and Knowledge Networks
• NIH / NCI Roadmaps
• Translational & Biomarker Discovery Programs like
SPORE’s and SPECS
• BD2K

4. TIME
UNDERSTANDING
OF DISEASES
TRANSLATIONAL
RESEARCH
MANAGEMENT
OF
PATIENTS
INFORMATION Accelerating Personalization of Care
Challenge: Filling in the Gap

5. • Bridge the lab and clinic in both directions
• Accelerate development of individual targeted agents
Small molecules
Antibodies
siRNAs
• Accelerate development of individual biomarkers
Risk
Tumor Burden
Predictive markers for response

6. • Integration of Genomics, Molecular Diagnostics and Therapeutics
• Collaboration of Multiple Groups
•Academia, NIH/NCI, FDA, Pharma, Technology Partners
• Establish Translational Support Teams and Infrastructure
• Platform of common Informatics tools and Infrastructure
• Standards – Its all about this – really !
• Sustained Architecture
• Systems Interoperability and Data Integration

7. Landscape: “…multiple collaborating investigators working
as an investigative team in order to address complex
biomedical science problems…”
Leveraging Integrative Informatics Standards & Platforms
to Enable High-throughput
Translational Research
Infrastructure for Collection, Management, Preservation,
and Rapid Analysis of Clinical, Biomedical, and
Biospecimen data under compliant conditions

8. Mission
Deliver Suite of Services to support translational,
biomedical, and clinical research, as well as clinical care
improvement.
Focus
Development of Systems and Infrastructure for the
- Capture, Storage, Dissemination of Clinical, Biomedical, and
Research Data that can easily be merged, integrated, or aggregated
with other data sets.
- Integration of unified technology platforms leveraging
cutting-edge advances in Informatics and computing.

9. • Identify and prioritize informatics needs in consultation
with Faculty and Staff
• Evaluate alternative software and sometimes hardware
approaches and implement the selected solutions, with
the goal of building an advanced integrated informatics
environment
• Assure compliance with governance, quality control, data
privacy, and security standards for all informatics efforts.
• Oversee adoption of related national policies, guidelines
and standards for clinical and biomedical data / metadata

10. • Provide consultation to facilitate use of specialized
database software and bioinformatics tools
• Develop and implement customized software and
research databases
• Data : Security, Compliance, Sharing, Governance
• Relationship as appropriate with Vendor Community
• Provide Biomedical Informatics systems and expertise in
support of grants, projects, and the preparation of
manuscripts

11. •Provide Data Consultation and Research Design
•Clinical / Biomedical Research Infrastructure
•Clinical Research Informatics
•Decision Support Service Infrastructure
•Biospecimen / Tissue Informatics
•Biomedical Informatics
•High Performance Computing
•Data Management and Integration
•Data Marts & Data Mining
•Informatics Education & Domain Expertise

12. 1212
Centralized Research Data Management & Coordination
TITI
Program
Support
Services
Quality
Control
Integration
Adoption
Quality
Assurance
Training

13. • Infrastructure : Data Coordinating Center
• Clinical Research Informatics: Robust Clinical Data Capture &
Trials Management System: OnCore EDC and CTMS
(Lindsey Watt Alami Presentation Later Today)
• Clinical Registries (URM, REDCap)
• Biospecimen Informatics (BSM, STARS, LabVantage*)
• Patient Reported Outcomes (VissionTree)
• Federated Electronic Data Marts
• Business Intelligence Framework and Sophisticated Reporting
• Integration and Interoperability : CHR iRIS, APeX, Radiology
• NLP Methods and Tools
• HPC and BIG Data : High Performance Compute Resource:
TIPCC (Richard Johnston @ Genius Booth)

14. • OnCore Help-Desk
• Facilitate, Centralize, and Standardize Clinical Trial
Research Data Collection
• Example: Completion of Protocol Registration Form
and submission
• Example: Creating and Managing creation of all
Patient Study Calendars and CRF’s
• Reporting and Data Extraction and Integration
• Study information portal linkage locally and for Public
• Continued Training and Hands On Support
• Continued Data Quality Control and Auditing

15.  Total Protocols : 4171
 Total Active Protocols : 1682
 Total Protocol Documents : 31,695
 Total SAE’s : 2646
 Total Subjects : 28,028
 Active Users: 923
 Protocols added in last 12 months: 446
 222 oncology
 224 non-oncology
*As of April 2014 – UCSF Wide

17. • Phase I : HL7 Live Data Feeds
• APeX Patient Demographics
• APeX LABS
• Phase II:
• APeX RPE,
• APeX Billing Grid

18. Demographics (HL7 ADT: APeX > OnCore)
Push subject demographics information from EMR
Laboratory (HL7 ORU: APeX > OnCore)
Populate OnCore eCRFs with lab results from lab system
Protocol Setup (RPE) (OnCore > APeX)
Sets Up Study Subjects in APeX: Information from OnCore is
pushed to Epic to ‘flag’ subjects on a research study in OnCore:
Protocol Billing Grid (OnCore > APeX)
Provides an EMR with relative time points of a research study
calendar including codes, billing designations and modifiers for
assigned charge events & items.
Purpose is to support billing compliance.

19. Patient Demographics (Completed)
 Fundamental Building Block of Integration
 APeX Pushing Patient Demographic Data: i.e.
• MRN
• Name
• Race
• Ethnicity
• Gender
• Date of Birth
• Address
• Phone Number
 Ensures the MRN from the EMR is the SAME primary research
subject identifier: CRITICAL to the remaining, more advanced
layers of integration

20. Additional Interoperability Projects
• CHR’s iRIS iMedRIS
 Phase I :
o iRIS > OnCore (in Progress)
o iRIS Reporting via iMolytics Analytics
 Phase II : OnCore > iRIS (under planning)
• Radiology > OnCore (under planning)
• KBase / PMP Project (under discussion)
• VissionTree P.R.O (under discussion)
• coPath Pathology Reports
• coPath > OnCore BSM > Via i2e NLP Engine

21. Natural Language Processing: From Text to Meaning
21

22. Transform Text into Insights
Turn text
Into structured data
using sophisticated queries
To drive
analytics
APeX
Cancer
Registry
OnCore
Biobank

24. Discussion