Translational Informatics@ UCSF

1nf0rmatics Day

June 10th, 2014

Sorena Nadaf M.S.,M.MIAssociate Director HDFCCC

Chief Informatics Officer, Director of Translational Informatics Program

“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.

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• 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

TIME

UNDERSTANDING OF DISEASES

TRANSLATIONAL RESEARCH

MANAGEMENTOFPATIENTS

INF

OR

MA

TIO

NAccelerating Personalization of Care

Challenge: Filling in the Gap

• Bridge the lab and clinic in both directions

• Accelerate development of individual targeted agentsSmall moleculesAntibodiessiRNAs

• Accelerate development of individual biomarkersRiskTumor BurdenPredictive markers for response

• 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

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

MissionDeliver Suite of Services to support translational,

biomedical, and clinical research, as well as clinical care improvement.

FocusDevelopment 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.

• 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

• 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

•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

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Centralized Research Data Management & Coordination

TI TI

Program SupportServices

Quality Control

Integration

Adoption

QualityAssurance

Training

• 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)

• 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

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

• Phase I : HL7 Live Data Feeds• APeX Patient Demographics • APeX LABS

• Phase II: • APeX RPE, • APeX Billing Grid

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.

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

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

Natural Language Processing: From Text to Meaning

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Transform Text into Insights

Turn text

Into structured datausing sophisticated queries

To driveanalytics

APeX

Cancer

Registry

OnCore

Biobank

Discussion