The Cancer Biomedical Informatics Grid: An Information Infrastructure for Healthcare and Life Sciences Amy Walker CEO and Healthcare IT Strategist Center.

Slides:



Advertisements
Similar presentations
Manatt manatt | phelps | phillips New York State Health Information Technology Summit Initiative Overview and Update Rachel Block, Project Director United.
Advertisements

27 June 2005caBIG an initiative of the National Cancer Institute, NIH, DHHS caBIG the cancer Biomedical Informatics Grid Arumani Manisundaram caBIG - Project.
CVRG Presenter Disclosure Information Joel Saltz MD, PhD Director Comprehensive Informatics Center Emory University Translational Research Informatics.
EHR stakeholder workshop – 11th October EHR integration for clinical research: toward new interaction models ? Isabelle de Zegher.
Achieving Data Liquidity in the Cancer Community: A Coalition of All Stakeholders Marcia A. Kean, Feinstein Kean Healthcare Spring 2012 Internet2 Member.
Overview of Biomedical Informatics Rakesh Nagarajan.
University of Pittsburgh Department of Biomedical Informatics Healthcare institutions have established local clinical data research repositories to enable.
National Cancer Institute U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health NCI Perspective on Informatics and Clinical Decision.
Irish Health Research: Collaboration and Partnership HSE Regional Library & Information Health Research Seminar Dr. Steevens’ Hospital 11th February 2011.
July 3, 2015 New HIE Capabilities Enable Breakthroughs In Connected And Coordinated Care Delivery. January 8, 2015 Charissa Fotinos.
What is “Biomedical Informatics”?. Biomedical Informatics Biomedical informatics (BMI) is the interdisciplinary field that studies and pursues.
Measurable Interoperability for Archival Data Lewis J. Frey, PhD
Vivien Bonazzi Ph.D. Program Director: Computational Biology (NHGRI) Co Chair Software Methods & Systems (BD2K) Biomedical Big Data Initiative (BD2K)
Discovery of new medicines through new models of collaboration Simon Ward Professor of Medicinal Chemistry & Director of Translational Drug Discovery Group.
1 The UK Opportunity: what is experimental medicine? UNLOCK YOUR GLOBAL BUSINESS POTENTIAL Pre- clinical develop- ment Phase I Phase II Phase III Product.
The NIH Roadmap for Medical Research
National Health Information Infrastructure “Person(al)” Health This presentation does not necessarily reflect the view of the U.S. Government or the Institution.
CBIIT’s Roadmap: A Look Ahead Caterina E.M. Lasome, PhD, MBA, RN, CPHIMS Chief Operating Officer Center for Biomedical Informatics & Information Technology.
Discussion Topics Healthcare: Then, Now and in the Future
Bill Newhouse Program Lead National Initiative for Cybersecurity Education Cybersecurity R&D Coordination National Institute of Standards and Technology.
Building a Roadmap for Research IT John Brussolo Research IT Program Director September 6, 2012 © 2012 The Regents of the University of Michigan.
Johns Hopkins Technology Transfer 1 Translational Biomedical Research: Moving Discovery from Academic Centers to the Community Translational Biomedical.
NCI Review of the Clinical Trials Process 6 th Annual National Forum on Biomedical Imaging in Oncology James H. Doroshow M.D. April 7, 2005 Bethesda, Maryland.
1 Federal Health IT Ontology Project (HITOP) Group The Vision Toward Testing Ontology Tools in High Priority Health IT Applications October 5, 2005.
Cancer Clinical Trial Suite (CCTS): An Introduction for Users A Tool Demonstration from caBIG™ Bill Dyer (NCI/Pyramed Research) June 2008.
Using the Open Metadata Registry (openMDR) to create Data Sharing Interfaces October 14 th, 2010 David Ervin & Rakesh Dhaval, Center for IT Innovations.
A Systems Approach: BIG Health Consortium™ “The world we have created today has problems which cannot be solved by thinking the way we thought when we.
Anticipated FY2016 Appropriations Agency$ Million NIH200 Cancer70 Cohort130 FDA10 Office of the Natl Coord. for Health IT (ONC) 5 TOTAL215 Mission: To.
Precision Medicine A New Initiative. The Concept of Precision Medicine (PM) The prevention and treatment strategies that take individual variability into.
Integrated Biomedical Information for Better Health Workprogramme Call 4 IST Conference- Networking Session.
Chapter 6 – Data Handling and EPR. Electronic Health Record Systems: Government Initiatives and Public/Private Partnerships EHR is systematic collection.
The National Biomedical Imaging Archive (NBIA) In Action: An Introduction for Users A Tool Demonstration from caBIG® Presented by: Eliot Siegel, MD Maryland.
From Bench to Bedside: Applications to Drug Discovery and Development Eric Neumann W3C HCLSIG co-chair Teranode Corporation HCLSIG F2F Cambridge MA.
The Status of Health IT in British Columbia Elaine McKnight.
CRIX: toward a secure, standards-based, clinical research information exchange.
Treatment Summary University of California San Francisco Center of Excellence for Breast Cancer Care PI: Laura J Esserman MD MBA; Edward Mahoney; Elly.
Facilitate Scientific Data Sharing by Sharing Informatics Tools and Standards Belinda Seto and James Luo National Institute of Biomedical Imaging and Bioengineering.
This material was developed by Oregon Health & Science University, funded by the Department of Health and Human Services, Office of the National Coordinator.
Clinical Research Informatics at the University of Michigan Daniel Clauw M.D. Professor of Medicine, Division of Rheumatology Assistant Dean for Clinical.
The Importance of a Strategic Plan to Eliminate Health Disparities 2008 eHealth Conference June 9, 2008 Yvonne T. Maddox, PhD Deputy Director Eunice Kennedy.
THE MURDOCK Study: A Rich Data Resource for Biomarker Discovery and Validation Brian D. Bennett 1, Jessica D. Tenenbaum 1, Victoria Christian 1, Melissa.
Robert H. Wiltrout Director, CCR Director’s Address.
Health Management Information Systems Unit 3 Electronic Health Records Component 6/Unit31 Health IT Workforce Curriculum Version 1.0/Fall 2010.
NIH and the Clinical Research Enterprise Third Annual Medical Research Summit March 6, 2003 Mary S. McCabe National Institute of Health.
Clinical Research Informatics [CRI]. Informatics, defined generally as the intersection of information and computer science with a health-related discipline,
The National Cancer Imaging Archive (NCIA) In Action: An Introduction for Users A Tool Demonstration from caBIG™ Carl Jaffe, MD NCI-Cancer Imaging Program.
Subject Registrations Adverse Events Subject Registrations Biospecimens Lab Results IN: 1. Lab Results OUT: 1. Subject Registrations 2. Clinical Notes.
Component 1: Introduction to Health Care and Public Health in the U.S. 1.9: Unit 9: The evolution and reform of healthcare in the US 1.9c: Quality Indicators.
May 2007 CTMS / Imaging Interoperability Scenarios March 2009.
Welcome to the caBIG Community! The cancer Biomedical Informatics Grid (caBIG ® ) offers more than 120 open source tools, technologies and infrastructure.
All Hands Meeting 2005 BIRN-CC: Building, Maintaining and Maturing a National Information Infrastructure to Enable and Advance Biomedical Research.
Biomedical Informatics and Health. What is “Biomedical Informatics”?
Clinical and Translational Science Awards (CTSAs) Future Directions and Opportunities for ACNP investigators.
Enterprise Security Program Overview Presenter: Braulio J. Cabral NCI-CBIIT/caBIG Enterprise Security Program Coordinator.
The opportunities and challenges of sharing genomics data with the pharmaceutical industry Shahid Hanif, Head of Health Data & Outcomes, ABPI DNA digest.
1 Population Science SIG: Vision and Goals Paul K. Courtney Pop Sci SIG Lead Dartmouth College/Norris Cotton Cancer Center.
C3PR: An Introduction for Users A Tool Demonstration from caBIG™ Vijaya Chadaram Duke Cancer Center April 29, 2008.
Sachin H. Jain, MD, MBA Office of the National Coordinator for Health IT United States Department of Health and Human Services The Nation’s Health IT Agenda:
Semantic Web - caBIG Abstract: 21st century biomedical research is driven by massive amounts of data: automated technologies generate hundreds of.
NAACCR and caBIG® Interoperability
Jim Bland Executive Director, CRIX International
NATIONAL outreach Network
IHE Quality, Research and Public Health QRPH domain
pSCANNER’s Value: Beckstrom’s Law at Work
The Brookings Institution
Strategic Planning 3/31/2016.
Innovative Medicines Initiative:
What is “Biomedical Informatics”?
Clinical and Translational Science Awards Program
REACHnet: Research Action for Health Network
Presentation transcript:

The Cancer Biomedical Informatics Grid: An Information Infrastructure for Healthcare and Life Sciences Amy Walker CEO and Healthcare IT Strategist Center for Biomedical Informatics and Information Technology Working for the National Cancer Institute SAIC-F Health TechNet McLean, VA June 17, 2010

Key Concepts caBIG ® provides a rich collection of standards-based infrastructure and tools to facilitate and accelerate the critical functions in today’s discovery R&D processes caBIG ® approaches enable any organization to break down silos within their 4 walls, as well as between them and the outside world caBIG ® web-based services enable organizations to partake of capabilities a-la-carte or comprehensively across the discovery-development-care continuum Since caBIG ® has been developed by NCI, all capabilities are freely available and open to all Use of caBIG ® is widely supported through a diverse collection of government, academic, and commercial sources

The National Cancer Institute (NCI) Federal Government's principal agency for cancer research and training Part of the National Institutes of Health (NIH), one of 11 agencies that compose the Department of Health and Human Services (HHS) Established under National Cancer Institute Act of 1937, scope broadened by National Cancer Act of 1971 Coordinates National Cancer Program, including: –NCI-designated Cancer Centers –Cooperative Groups –National Community Cancer Centers Program

21 st Century Biomedicine Personalized, Predictive, Preemptive, Participatory Unifies clinical research, clinical care, and discovery (bench- bedside-bed) into a seamless continuum Results in improved clinical outcomes Accelerates the time from discovery to patient benefit Enables a health care system, not a disparate “sector” Empowers consumers in managing their health

How are we doing? Still Fighting a War We (think we) know “how cancer works” BUT: Estimated US cancer deaths 2009: 562,340 (American Cancer Society) Estimated new US cancer cases 2009: 1,479,350 (American Cancer Society) Cost of cancer deaths: $960.7 billion in 2000, estimated $1,472.5 billion in 2020 (Journal of the National Cancer Institute, Dec. 9, 2008)

caBIG ® Vision: A virtual web of interconnected data, individuals, and organizations that redefines how research is conducted, care is provided, and patients/participants interact with the biomedical enterprise. caBIG ® Mission: Connect the cancer research community through a shareable, interoperable infrastructure Deploy and extend standard rules and a common language to more easily share information Build or adapt tools for collecting, analyzing, integrating and disseminating information associated with cancer research and care The Cancer Biomedical Informatics Grid (caBIG ® )

caBIG ® Core Principles Open Access caBIG ® is open to all, enabling wide-spread access to tools, data, and infrastructure Open Development Planning, testing, validation, and deployment of caBIG ® tools and infrastructure are open to the entire research community Open Source The underlying software code of caBIG ® tools is available for use and modification Federation Resources can be controlled locally, or integrated across multiple sites

Unprecedented challenges, Unprecedented opportunities

The Cancer Biomedical Informatics Grid: An Information Infrastructure for Healthcare and Life Sciences John Speakman Associate Director, Clinical Sciences Center for Biomedical Informatics and Information Technology National Cancer Institute Health TechNet McLean, VA June 17, 2010

Biomedicine is Decades Behind the “Knowledge Economy” Curve Translational research and personalized medicine require integration of multiple modalities and dimensions of data (clinical care / clinical trials / pathology / imaging / gene expression / population data, etc.) This integration is currently achieved by custom-built point solutions, if at all As a result, the data is often locked away in incompatible formats and systems Research studies are artisanal, handcrafted from one-of-a-kind components; clinical trials take too long to initiate, too long to accrue patients and too long to report outcomes Access to, and maturity of, informatics tools within the research community is inconsistent

caBIG ® Overcomes the Obstacles to Data Integration Standard Language Islands of Information IT Systems Do Not Interoperate 40+ Software Tools Standardized Vocabularies National Grid for Data Sharing Interoperability Tsunami of Genomic and Clinical Data

How do you use it? Adapter between your Application and the Grid Adopting involves installing software applications already made to caBIG ® standards, integrating them into your workflow, and connecting to caGrid. Adapting involves modifying your existing software applications to be caBIG ® compatible, and then connecting to caGrid.

Reporting of serious/fatal ADRs Re-labeling (or recall) as needed Additional indications as warranted Candidate selection and Optimization Pre-clinical testing Phase I, II, III New Drug application and Approval Product launch Clinical adoption Biological pathways Target identification and validation DiscoveryProductDevelopment Outcomes & Surveillance Clinical Care 20th Century Biomedical Paradigm

ProductDevelopment Outcomes & Surveillance Clinical Care Analysis and Learning Discovery 21th Century Biomedical Paradigm: a Learning Health System

Software-Enabled Bridging of Research and Care RESEARCH Group A (10mg) Group B (30mg) Group C (control) Clinical Trial SOFTWARE CTMS Electronically Executed Protocol

Group A (10mg) Software-Enabled Bridging of Research and Care RESEARCH Group B (30mg) Group C (control) SOFTWARECARE Clinical Trial Group A (10mg) Treatment Plan Optimum Dose (30mg) CTMS Electronically Executed Protocol Electronic Health Infrastructure Clinical Practice Plan Physician

Government A Diverse NCI-Fostered Biomedical Ecosystem Researchers Clinical Communities Discovery Science Information Technology Underwriters/Payors Care Deliverers Consumers/ Patients Foundations Payers / Insurance Companies Industry Academia Research Infrastructure Electronic Health Records

Example Project: Lance Armstrong Foundation: Adolescent and Young Adult Biorepository Objectives Build an infrastructure to support biospecimen collection, storage, and sharing among academic sites Address patient privacy and intellectual property issues Integrate into a centralized portal

NCI has worked with ASCO to obtain requirements for an “Oncology- extended EHR”, now working with HL7 to define a structured specification, will subsequently develop a reference implementation Defining Electronic Health Records for Oncology Chemotherapy drugs Oncology-extended EHR

Utilizing “Smart” Electronic Health Records to Accelerate Research Data Repository Patient Outcomes Data Service Data on hundreds of thousands of patient encounters can be fed into the Patient Outcomes Data Service electronically This Service enables physicians to submit outcome data on patients, and query it for outcomes patterns.

Outcomes Portal

The Patient Outcomes Data Service is one of Many Services, Planned and Existing, for the Biomedical Community Patient Outcomes Data Service Cancer Knowledge Cloud Adverse Event Service Clinical Trials Service Patient Calendar Service Decision Support Service Treatment Plan Service

Epidemiologists Query data to seek correlations among genes, environment, outcome Develop standing online cohorts of volunteers Researchers Can Query the Data in the Cancer Knowledge Cloud Basic Researchers Generate new hypotheses Identify biomarker- outcome correlations Validate biomarkers in silico Clinical Researchers Seek clinical trial participants Enrich clinical studies with appropriate sub-groups Identify new indications Cancer Knowledge Cloud

Digression: Data Sharing Framework

Epidemiologists Query data to seek correlations among genes, environment, outcome Develop standing online cohorts of volunteers Researchers Can Query the Data in the Cancer Knowledge Cloud Basic Researchers Generate new hypotheses Identify biomarker- outcome correlations Validate biomarkers in silico Clinical Researchers Seek clinical trial participants Enrich clinical studies with appropriate sub-groups Identify new indications Cancer Knowledge Cloud

Epidemiologists New links to behaviors and exposures that increase / decrease risk of disease or disease reoccurrence New Knowledge From Research is Fed into the Cancer Knowledge Cloud Basic Researchers New drug targets Clinical Researchers Targeted drugs for molecularly-defined sub-groups Cancer Knowledge Cloud

All Stakeholders Benefit from the Cancer Knowledge Cloud Individualizing Clinical Care Physicians Cancer Knowledge Cloud Clinical Decision Support Tools Comparisons with other patients Alerts to potential drug interactions Alerts to genetic disease risks Opportunities for clinical trial enrollment

All Stakeholders Benefit from the Cancer Knowledge Cloud How do I compare to others? How do I get into a clinical trial? What should I expect from this treatment? Individualizing Clinical Care Physicians Understanding my options Patients / Consumers Cancer Knowledge Cloud

Contribute your Knowledge to Conquer Cancer

All Stakeholders Benefit from the Cancer Knowledge Cloud Improving the Healthcare System Comparative Effectiveness Quality Pharmaco- vigilance Individualizing Clinical Care Physicians Cancer Knowledge Cloud Understanding my options Patients / Consumers

Take-Home Messages caBIG ® provides standards-based infrastructure and tools to facilitate and accelerate critical functions in research and, increasingly, healthcare processes The Cancer Community writ large is moving towards large-scale data sharing, and those who are caBIG®-connected have an advantage caBIG® web-based services will soon enable organizations to partake of a-la-carte or comprehensive capabilities across the discovery-development-care continuum As the U.S. moves towards EHRs and full digitalization of health care, the caBIG® standards-based data interoperability will enable organizations to move data between regulators, health care providers, etc. Since caBIG® has been developed by NCI, all capabilities are freely available and open to all

Finding What You Need… If you want additional general information about caBIG ® If you want to receive our monthly e-newsletter If you want a complete overview of the caBIG ® program If you want a complete list of caBIG ® tools If you want a demo-for-the-perplexed Call (301)