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William S. Dalton, PhD, MDPresident, CEO & Center DirectorMoffitt Cancer Center & Research InstituteTampa, Florida
Transformation to Value-Based Personalized Healthcare: Cancer
as a Model
– Risk Factors– Genetics– Early Detection– Health Disparities
– Genomics/Proteomics– Imaging Modalities– Nanotechnology
– Molecular Oncology– Biomarker Analysis
– Primary Therapy • Multimodality • Target Based– Post Therapy • Surveillance– Clinical Trials Matching
– Recurrence Therapy– Drug Discovery– Adaptive Trial Design
– Behavioral Research– Psychosocial & Palliative Care– Family Needs– Health Outcomes
– Prevention– Lifestyle/Nutrition– Education
Intervention
Diagnosis
Prognosis
Treatment
Relapsed Disease
Survivorship Populations at Risk
Total Cancer Care: A Personalized Approach to a Patient’s Health Journey
(http://www.hhs.gov/myhealthcare/news/phc_2008_report.pdf; pg 243)
The Necessary Components
• Clinically annotated bio-repository for tumor and normal specimens
• Partnership among researchers, clinicians, regulators, policy makers, and patients to design an integrated information network system
The Approach for Cancer
The Total Cancer Care Protocol• Can we follow you throughout
your lifetime?• Can we study your tumor using
molecular technology?• Can we recontact you?
Wireless touch- screen tablet
Connects via secure interface and forwards HIPAA-compliant information to database
Consists of IRB Approved:
• Introductory Video
• Consent Video by PI
• Informed Consent
• Signature Capture
• Demographics Survey
Electronic Consenting System
Partners in the Fight Against Cancer
Expansion of consortium sites will encourage information exchange
Nexus Biostore
• Four unit capacity of 2.4 Million samples• Stores samples in a -80°C environment• Handles samples in a -20°C environment• Retrieves samples using NEXUS
proprietary ‘Cool Transition’ technology
• Flexibility to accommodate a wide variety of samples, vessels and labware
• Automated 24/7 monitoring system in place
• Automated Inventory functionality provides real-time inventory tracking of stored biospecimens
88Confidential and Proprietary
8
As of August 16, 2011As of August 16, 2011
Tumors Collected 28,146
Patients Consented78,615
Tumors Profiled14,604
Total Cancer Care To Date
M2Gen Offices, Bio-repository 100,000 sq ft in Tampa, FL
The Approach
Create a delivery system that will integrate new technologies into the standard of care and develop evidence-based guidelines for the
treatment of cancer.
Data Information Knowledge Wisdom
Improved
Medical
Practice
Four Portals to Total Cancer Care™
Next Generation Health and Research
Informatics Platform
Researcher View
Patient View
Administrators View
Clinician View
• Cohort Identification• Molecular Profiling• Comparative Effectiveness
• Personal Health Record• Longitudinal Follow-up• Personalized Search
• Operational Dashboards• Quality & Safety Reporting• Meaningful Use
• Decision Support• Clinical Pathways• Clinical Trial Matching• Access for Affiliate Network
The HRI Platform Defined
An integrated information platform that will create real-time relationships and
associations from disparate data sources needed to create new
knowledge for improved patient treatments, outcomes and prevention.
HRI Solution: Conceptual Architecture
Cancer Registry
LabVantage
Capstone
CEL Files
3M
Source Systems
Integrated Data Warehouse
Data Aggregation and Storage
Demographics Cancer Stage Diagnosis
Treatment Drugs Labs
Some representative examples of business level data domains
Data Factory Implementation
Data Profiling
Data Mapping
Data ModelingData Linkage
Data Sourcing
Patient Cohort Examples
Newly Diagnosed, Primary Pancreatic, having CEL File
Primary Breast Cancer, Survival Time >30 months, Disease Stage 1-4, Diagnosed with Type 2 Diabetes, currently on Metaformin
Female with myelodysplastic syndrome, currently taking vidaza as Ist course chemotherapy, initially diagnosed in 2007-2008
Galvanon
Core Front End
Information Delivery
HRI Demonstration
Number of patients in the HRI today & growing
Patient data available – drill down capabilities to 5 levels of detailed data elements.
Tissue specimen data available – drill down capabilities to 5 levels of detailed data elements.
The Need for Linked Queries
Patient 1
1-1-2009Lung Upper Lobe
6-30-2010Adenocarcinoma
NOS
Patient 2
1-1-2010Lung
Upper Lobe
1-1-2010Adenocarcinoma
NOS
6-30-2010Skin Trunk
LINK
Venn Diagrams
Four Portals to Total Cancer Care™
Next Generation Health and Research
Informatics Platform
Researcher View
Patient View
Administrators View
Clinician View
• Cohort Identification• Molecular Profiling• Comparative Effectiveness
• Personal Health Record• Longitudinal Follow-up• Personalized Search
• Operational Dashboards• Quality & Safety Reporting• Meaningful Use
• Decision Support• Clinical Pathways• Clinical Trial Matching• Access for Affiliate Network
Stakeholders as Partners
Total Cancer Care Multi-
Dimensional Data
Warehouse
Researcher View
How is Moffitt Benefiting from the RIE?
• Using the TCC Database to match patients to clinical trials– Right treatment for the right patient using molecular
markers for patient selection
• Development of Comparative Effectiveness Research Infrastructure– What works best for whom
• Integration of molecular, clinical, biospecimen and patient self-report data– Gene expression data, Exome sequencing data, SNP/CNV
data for new diagnostics, prognostic response and new drug discovery
Validation of a Predictive Model of Clinical Response to Concurrent Radiochemotherapy
Javier Torres-Roca, MD
(R21 CA135620)
Eschrich SA, et al., Int J Radiat Oncol Biol Phys, 2009
Figure 1Defining the pathway scale by mathematical modeling
A linear regression algorithm is used to model the pathway/network scale in the radiosensitivity continuum. Biological variables (ras status, p53 status and TO) known to influence radiosensitivity
along with gene expression are included in the model
Radiochemotherapy
TCC database: validation of clinical response
High-Throughput Sequencing
• Exome Sequencing– 361 breast and ovary biospecimens sequenced at
BGI• Whole exome sequencing (Agilent SureSelect 38MB kit )• Raw and analyzed data currently available
– 4,000 samples being sequenced at BGI• ~1,400 genes
– 500 lung, 400 kidney, 300 colon– 150 each: uterus, pancreas, ovary, endometrium– 100 each: heme malignancies, melanoma, breast– 50 each: stomach, esphagus, liver, cervix, soft tissue, rectum, anus– 650 undecided
– Whole genome sequencing: Melanoma• 13 match pairs at Wash U Genome Inst.
Project Timeline
12/29/10Samples enterLibrary Construction
1/04/111st case enteredsequencing pipeline
3/04/11All sequencingcomplete
• Melanoma whole genome sequencing
15 melanomas and matched normal pairs chosen from TCC bio-repository
Linked to TCC gene expression array and clinical follow-up databases
Completed in only 2 months
Further analysis by MCC Cancer Informatics Core
Funded by MCC and a gift from Donald A. Adam
Melanoma Comprehensive Research Center
Classification into high and low NF-kB
P50 CA121182
NF-kB and K-ras Signatures in lung cancerAmer Beg, PhD
Initial Study:• 400 Lung
Patients
• TCC database validating signatures
Correlation of NF-kB Signaturewith Ras Signature
Ras Signaturer=0.692 (p<0.001)
Immunology
Insulin-Like Growth Factor Axis & Colon Cancer Outcomes 300 Patient Cohort StudyErin Siegel, PhD
State of Florida, 09BN-13
Blood draws Anthropometrics Questionnaires (health
behaviors, symptoms & QOL)
Toxicity & QOL
Recruitment at Surgery Tumor Tissue Gene expression Profile Pre-surgery blood New Patient
Questionnaire Physical Activity Anthropometrics Quality of Life (QOL)
Treatment Information
Outcomes: Treatment Toxicity & response Quality of Life & symptoms Recurrence & survival
Follow-up
3M 6M 12M
*Green = utilizing TCC infrastructure
Cancer Epidemiology
• New information infrastructure to support PCOR or Comparative Effectiveness Research (CER) • Metadata-driven data model • Natural language processing algorithms • Developed novel data dictionary and metadata tools • Generated additional descriptive tool to understand
differences in patient response and validation for exponential failure.
• CER analyses to guide developing CER infrastructure• 3 CER studies on myelodysplastic syndrome
completed(Alan List, et al., submitted in Blood)
Patient Centered Outcomes Research (PCOR) David Fenstermacher, PhD
UC2 CA148332 (NCI Grand Opportunity grant)
Health Outcomes & Behavior
Using TCC Warehouse to Accrue Patients Jonathan R. Strosberg, MD
Phase 2 trial of single agent Roche gamma secretase inhibitor in metastatic CRC (PI, Jonathan Strosberg, MD) • Trial (NCI 8537) supported by CTEP N01 contract• Re-contacted Moffitt TCC patients using general eligibility
criteria• Enrolled 37 patients in 4 months• Time from LOI submission to last patient treated just over
10 months• OEWG/IOM expectation for N01 trial activation is 210 days
Clinical Trial Matching
Four Portals to Total Cancer Care™
Next Generation Health and Research
Informatics Platform
Patient View
• Personal Health Record• Longitudinal Follow-up• Personalized Search
Four Portals to Total Cancer Care™
Next Generation Health and Research
Informatics Platform
Clinician View
• Decision Support• Clinical Pathways• Clinical Trial Matching• Access for Affiliate Network
Clinical Pathways: Decision Support
• Decision support tools available at point-of-care that leverage:– Clinical outcomes studies– Comparative effectiveness data– Comprehensive disease models– Evidence-based clinical pathways
Clinical Pathways
Pathways Approach
• Clinical Priorities in Pathway development1. Efficacy
2. Toxicity
3. Cost
• Comprehensive Clinical Coverage
Work-up Disease Free Monitoring
Surgical Workflow Recurrence
Neoadjuvant Care Progression-Free Monitoring
Adjuvant Care Progression
Initial Rx/Induction 1st & Later Line Metastatic Therapy
Consolidation/Maintenance Molecular Diagnostics
Fixing Clinical Trials?
Current Clinical Trial Challenges
• Trial activation too slow• Trial accrual too slow• Patients do not want to leave home• 80% of cancer care delivered locally• Novel investigational trials performed in
Academic Medical Centers• Trials are searching for patients
Current Clinical Trial Challenges
• Cancer patients enrolled: 2-3 % in community and 10-12 % in cancer centers
• Early phase trials’ response rates too low• Early enrollers on Phase I trials are under-
treated• Small incremental benefits in large later phase
trials• Regulatory burden is increasing
Clinical Trials Vision
• Develop a consortium network for clinical trials (practices and hospitals)
• Obtain molecular data from patients’ tumors• Maintain real-time clinical data on patients • Match drugs to patients using molecular and
clinical data• Faster and smaller trials with increased response
rates
Trials designed for and directed to patients
Trials searching for patients
TODAY
TOMORROW
Paradigm Shift
344
275
220
209
167
134
107
42
30
Molecular Mapping to Produce Dynamic Pool of Trial-Ready Patients(Many Mapped to Pre-Selectively Enroll a Few)
Newly Diagnosed Metastatic/Locally-Advanced Patients
One Tumor Type
Y Could also limit to specific diseases (such as colon, lung, breast, pancreas) to ensure proper final mix
* Could allow primary biopsies for brain, prostate, pancreas, ovary, bladder, pancreas where distant metastases hard to access;* Could also assume physicians might consider a “diagnostic” Bx in a situation when otherwise they might pass
Assumptions Reducing Sample Size
Diminishing# of Patients
Trial-Ready
Potential “Positive” Factors:
Starting sample sizeY
Availability of biopsy* (-20%)
Adequacy of biopsy (-20%)
Assay failure (-5%)
Death/Morbid/Toxicity (-20%)
Temporal Readiness within 1 yr of the Bx (TTP < 1yr) (-20%)
Performance Status or inadequate Labs (-20%)
Prevalence of Mutation (-60%)
Pt/MD Choice of Rx (-30%)
To incorporate molecular characteristics
of the tumor, as well as the patient’s genetic
background, into an individualized treatment
plan to maximize clinical benefit to the
patient from specific anti-tumor agents.
Ultimate Goal of New Trials
Biomarker-driven trials at Moffitt
• Phase 3 RRM1/ERCC1 directed chemo in advanced NSCLC (completed)
• Phase 2 R115777 in elderly AML with specific 2-gene ratio (active)
• Phase 2 Notch inhibitor in mCRC (completed)
• Planned TCC consortium trials
• CY 2011 Pharma Trials
Dalton, Fenstermacher, et al, Clin Cancer Res; 16 (24) December 15, 2010
Designing a New Research & Healthcare Network Model
ResearchInformationExchanges
ResearchInformationExchanges
Hospitals & Healthcare Networks
Personal Health Records
Researchers Centers& Networks
Genomic Data &
AnnotationServices
Genomic Data &
AnnotationServices
Insurers
ResearchersPatients
Offices & Clinics
Rapid Learning Information System for Cancer Care & Research
Thank You