CTSA Program Webinarnode:type]/field... · 2021. 7. 28. · Early Detection Research Network (EDRN)...
Transcript of CTSA Program Webinarnode:type]/field... · 2021. 7. 28. · Early Detection Research Network (EDRN)...
The University of Rochester Center for Leading Innovation and Collaboration (CLIC) is the coordinating center for the Clinical and Translational Science Awards (CTSA) Program, funded by the National Center for Advancing
Translational Sciences (NCATS) at the National Institutes of Health (NIH), Grant U24TR002260.
CTSA Program WebinarJuly 28, 2021
clic-ctsa.orgclic-ctsa.org
Agenda
2
TIME TOPIC PRESENTER(S)
2:00 pm ET Welcome Sanae ElShourbagy Ferreira, PhD, MAHealth Specialist, Division of Clinical Innovation
2:00 pm - 2:15 pm NCATS & CTSA Program Updates Michael G Kurilla, MD, PhDDirector, Division of Clinical Innovation
2:15 pm – 2:25 pmTackling the Digital Divide to Improve Telehealth
Un-Meeting Report Out
Marisa McGinley, DO, MScUn-Meeting Principal Investigator,
Case Western Reserve University
2:25 pm – 2:55 pmEarly Detection Research Network: It Takes a Village Sudhir Srivastava, PhD, MPH
Senior Scientific Officer, Chief, Cancer Biomarkers
Research Group (CBRG), NCI, NIH
2:55 pm – 3:00 pm CLIC UpdatesAlfred Vitale, PhDDirector of Research Education, CLIC
3:00 pm ET Adjourn
NCATS/CTSA Program Updates
Michael Kurilla, MD-PhD
Director, Division of Clinical Innovation
NCATS
July 28, 2021
Budget: FY 2022
➢House Appropriations Committee
➢ Approved Labor/HHS/Educ appropriation bill (includes NIH) – 7/15/21
➢ Full House vote on bill expected this week
➢Senate Appropriations Committee
➢ Draft bill expected to be taken up in September
FY 2021
Enacted
FY 2022
Request
FY 2022
House
Difference
over FY 21
FY 2022
Senate
Difference
over FY 21
855.4 879.0 898.8 +42.4 ? ?
586.8 601.5 616.2 +29.3 ? ?
"up to 60.0" "up to 10%" "up to 60.0" 0 ? ?
CTSA
CAN
NCATS Total
Budget: FY 2022
➢ House Appropriation Report (accompanies bill):
➢Several items in report language directed at NCATS:
➢Clinical and Translational Science Awards (CTSA) Program
➢CTSA Diversity Supplements
➢Collaboration with Business Incubators
➢Rare Disease Research
➢Cures Acceleration Network
➢ https://www.congress.gov/117/crpt/hrpt96/CRPT-117hrpt96.pdf (pages 142-143)
JCTS Thematic IssueRe-engineering the Clinical Research Enterprise in Response to COVID-19:The CTSA Experience
• How the CTSA Program pivoted to address COVID-19’s particular challenge to our nation’s biomedical research enterprise
• Lessons learned and best practices for future public health emergencies
• Published June 2021
• Compendium of 14 articles by numerous CTSA institutions and scholars
https://www.cambridge.org/core/journals/journal-of-clinical-and-translational-
science/thematic-issues/re-engineering-the-clinical-research-enterprise-in-response-to-covid-19-the-ctsa-experience
https://clic-ctsa.org/news/newsletter-ansible-archive
Journal of Clinical and Translational Science Thematic IssueRe-engineering the Clinical Research Enterprise in Response to COVID-19:
The CTSA Experience• Foreword to the JCTS COVID-19 special issue• Re-engineering The Clinical Research Enterprise in Response to COVID-19: The Clinical Translational Science Award
(CTSA) experience and proposed playbook for future pandemics• Modifying laboratory testing via home brew during the COVID-19 pandemic• Building biorepositories in the midst of a pandemic• CTSA Pharmacies - Contribution to Research and Public Health During the COVID-19 Pandemic• Role of CTSA Institutes and Academic Medical Centers in Facilitating Preapproval Access to Investigational Agents and
Devices During the COVID-19 Pandemic• Managing the risks and benefits of clinical research in response to a pandemic• Clinical Research During the COVID-19 Pandemic: The Role of Virtual Visits and Digital Approaches• Health Disparities and Equity in the Era of COVID-19• Challenges and Lessons Learned for Institutional Review Board Procedures During the COVID-19 Pandemic• Research Informatics and the COVID-19 Pandemic: Challenges, Innovations, Lessons Learned, and Recommendations
• Informed Consent: Old and New Challenges in the Context of the COVID-19 Pandemic
• Response of the Trial Innovation Network to the COVID-19 Pandemic
• Prioritizing Studies of COVID-19 and Lessons Learned
• Community Engagement During COVID: A Field Report from Seven CTSAs
Journal of Clinical and Translational Science Thematic IssueRe-engineering the Clinical Research Enterprise in Response to
COVID-19: The CTSA Experience
Barry S. Coller, John B. Buse, Robert P. Kimberly, William G. Powderly, Martin S. Zand, Jeffrey H. Moran, Larry Kessler, Jennifer Moylan, CraigForrest, Karl Boehme, Josh Kennedy, Alex Greninger, Geoff Baird, Ericka Olgaard, Laura James, Jennifer A. Croker, Robin Patel, Kenneth S. Campbell, Marietta Barton-Baxter, Shannon Wallet, Gary S. Firestein, Olivier Elemento, Robert M. Macarthur, Ohad S. Bentur, Ian C. MacArthur, Anna S. Bartoo, Donna L. Capozzi, Jason A. Christensen, Amber L. Johnson, Kuldip Patel, Misty Gravelin, Jeanne Wright, M.E. Blair Holbein, Marlene Berro, Jennifer S. Brown, George A. Mashour, Kevin J. Weatherwax, Patrick A. Flume, Elie F. Berbari, Laura Viera, Rachel Hess, Janine Higgins, Jennifer Armstrong, Linda Rice, Laura True, Reza Shaker, Reynold A. Panettieri Jr., Tammy L. Loucks, Clare Tyson, David Dorr, Vesna D. Garovic, James Hill, David McSwain, Sally Radovick, Frank A. Sonnenberg, Jennifer A. Weis, Kathleen T. Brady, Patrick Nana-Sinkam, Jennifer Kraschnewski, Ralph Sacco, Jennifer Chavez, Mona Fouad, Tamas Gal, Mona AuYoung, Asmaa Namoos, Robert Winn, Vanessa Sheppard, Giselle Corbie-Smith, Victoria Behar-Zusman, Ann Johnson, Jason J Nichols, Erin Rothwell, Steve Dubinett, Arash Naiem, Richard J. Bookman, James J. Cimino, Christopher A Harle, Rhonda G. Kost, Sean Mooney, Emily Pfaff, Svetlana Rojevsky, Jonathan N. Tobin, Adam Wilcox, Nick F. Tsinoremas, Erin Rothwell, Donna Brassil, Marietta Barton-Baxter, Kimberly A. Brownley, Neal W. Dickert, Stephanie A. Kraft, Jennifer B. McCormick, Benjamin S. Wilfond, Rachel G. Greenberg, Lori Poole, Daniel Hanley, Harry P. Selker, Karen Lane, J. Michael Dean, Jeri Burr, Paul Harris, Consuelo H. Wilkins, Gordon Bernard, Terri Edwards, Daniel K. Benjamin, Jr. Dushyantha Jayaweera, Nora G. Singer, Myron S. Cohen, Anne M. Lachiewicz, Amanda Cameron, Naresh Kumar, Joel Thompson, Alyssa Cabrera, Denise Daudelin, Phillippe R Bauer, Erica E. Marsh, Michael D. Kappelman, Rhonda G. Kost, Gia Mudd-Martin, Jackilen Shannon, Louisa A. Stark, Olveen Carrasquillo, Christopher P. Austin, Samantha Jonson, Michael G. Kurilla
Thank you to the authors and to
Listening Session
7: Advocates for
Biomedical and
Translational
Research and General Medicine
August 4, 2021
2:00-3:15 p.m. ET
Register
https://www.nih.gov/arpa-h
NIH Policies & Updates• Request for Information (RFI) on Developing Consent Language for Future Use of
Data and Specimens (NOT-OD-21-131 Deadline September 29, 2021). More
information.
• Final NIH Policy for Data Management and Sharing - Update (NOT-OD-21-013).
Effective January 25, 2023.
• Updated Process for Requesting Drawdowns Outside of the Liquidation Period
(NOT-OD-21-149) Recipients unable to complete drawdowns from the HHS Payment
Management System within the 120-day liquidation period may submit a prior approval
request to the IC grants management specialist listed on the notice of award. The IC
will review and consider such requests on a case-by-case basis.
• Reminder Regarding Recipient and Applicant Grants Policy Related Inquiries
(NOT-OD-21-151) - Only authorized organizational representatives may submit policy-
related questions to the NIH grants policy inbox. Inquiries about general grant matters
should be directed to the recipient’s office of sponsored programs.
Funding Opportunities
Mobile Health Platform ROA (OTA-21-015C) soliciting proposals for the
adaptation and support of a scalable, configurable, and integrated
Mobile Health Platform (MHP) to provide RECOVER Initiative studies
with customized mobile applications and for enabling secure collection
of PASC digital health measures; Full Proposals must be received by
5:00 pm, ET, July 30, 2021.
Funding Opportunities
Early Detection Research Network (EDRN) Funding Opportunity Announcements (FOAs). Due Date September 9, 2021; letters of intent due 30 days prior to the application due date.
• EDRN Biomarker Characterization Centers (U2C): RFA-CA-21-035.
• EDRN Clinical Validation Centers (U01): RFA-CA-21-033.
• EDRN Data Management and Coordinating Center (U24): RFA-CA-21-034.
CTSA Program Info & Reminders
• Notice of Intent to Publish (NOITP) a Suite of Funding Opportunity Announcements (FOAs) for the National Center for Advancing Translational Sciences (NCATS) Clinical and Translational Science Awards (CTSA) ProgramNOT-TR-21-030. Inquiries: POC: Erica Rosemond, Ph.D. Email: [email protected].
• NCATS plans to solicit questions from the public after
publication of the new suite of CTSA Program FOAs.
Common questions will be addressed in a public Technical
Assistance webinar.
Upcoming:
• Pathways to Prevention (P2P)
Workshop: Improving Rural Health
Through Telehealth-Guided
Provider-to-Provider
Communication October 12-14,
2021 (Virtual) – Register here.
• CTSA Program Annual Meeting
December 1-3, 2021 (Virtual!)
clic-ctsa.org
Tackling the Digital Divide to Improve Telehealth Un-Meeting Report Out
Marisa McGinley, DO, MSc
Un-Meeting Principal Investigator,
Case Western Reserve University
• Telehealth was shown in several chronic conditions to improve access, reduce hospitalization rates, and have lower costs to the patient than traditional in person visits.
• Great potential to improve access and reduce disparities
• Concerns and limitations• exacerbate health disparities• perception of quality of telehealth visits• privacy concerns for patients with lower socioeconomic status and
crowded living conditions• low bandwidth precluding satisfactory videoconferencing• lower technological literacy among some older adults.• limited physical examination
• In response to an RFA from the CTSA coordinating center, CLIC, to organize an Un-Meeting, our CTSA Hub was selected among several applicants to host “Tackling the Digital Divide to Improve Telehealth” on March 26, 2021.
• The goal of the un-meeting was to identify the barriers and limitations of the current system to improve care delivery for patients.
Why did we do this?
Slides from Un-Meeting Dr. Ruth Schneider
Un-Meeting Team
Beth Spyke, MPAResearch Education & Training
Program Manager, CTSC, Cleveland Clinic
Shannon Swiatkowski, MS Research Operations Manager,
CTSC, CWRU
Audie Atienza, PhD Senior Program Officer, National Center
for Advancing Translational Sciences
Judy Giordano Collaborative Initiatives Coordinator,
CLIC
Robert White, MS Associate Director, IT and
Analytics, CLIC
Margaret Osborne Communications Specialist,
CLIC
Marisa McGinley, DO, MScNeurologist, Mellen Center for
Multiple Sclerosis, Cleveland Clinic; CTSC KL2 Scholar
Un-Meeting Principal Investigator
Un-Meeting Agenda
11:00-11:45 Welcome, Introduction, and Framing the Issues 4x4 presentations
11:45-12:00 Networking/Break I
12:00-12:45 Breakout Sessions I
12:45-1:00 Networking/Break II
1:00-1:45 Breakout Session II
1:45-2:00 Networking/Break III
2:00-3:00 Breakout Summaries and Closing Remarks
4 x 4 Presenters
Ruth Schneider, MDUniversity of Rochester “Telehealth in Clinical
Use”
Jay Alberts, PhDCleveland Clinic
“Remote Monitoring”
Emily YoderCMS
“Payor Role in Telehealth Care Delivery”
Lisa Bard Levine, MD, MBAThe MAVEN Project
“Telehealth and Underserved Areas”
Julie Rish, PhDCleveland Clinic
“Patient Perspective on Telehealth”
Kathy Wright, PhD, RNThe Ohio State University
“Connecting Urban Aging Residents through Telehealth”
Lori Uscher-Pines, PhDThe Rand Corporation
“Telehealth for Chronic Conditions: Substance use disorder treatment model”
Breakout Sessions
Telehealth in routine care and chronic
conditions
Remote monitoring and objective testing
Payor and policy considerations
Telehealth and underserved areas
Aging , urban and minority populations
Patient experience
Who attended
• Total participants: 104
• Clinicians
• Researchers
• governmental agencies, industry
• healthcare partners
• CTSA Hubs participating: 32
CTSA HUBS: Participating (32) Organizations/Industry (21)Case Western Reserve University (3) Center For Connected Health PolicyUniversity Of Colorado Denver Center To Advance Integrated Community Health (CAICH)CHILDREN'S RESEARCH INSTITUTE (George Washington) CharterColumbia University Health Sciences Cleveland FoundationDuke University Crain's Cleveland BusinessGeorgetown University Federal University Of Parana-brazilEmory University Genentech Johns Hopkins University Healthcare IT News / HIMSSMayo Clinic Rochester (2) Healthpartners (2)Medical University Of South Carolina (3) Kaiser Permanente Washington Health Research InstituteUniversity Of Pittsburgh At PittsburghStanford University National African American Male Wellness AgencyOhio State University National Patient Advocacy Foundation University Of Alabama At Birmingham NYC Health + Hospitals
Univ Of Arkansas For Med Scisj (2)Onestep Virtual Physical Therapy Alumni Of University Of Michigan
University Of California At Davis Specialist Telemed LLC.University Of California, San Francisco Spectrum HealthUniversity Of Chicago The Center To Advance Integrated Community HealthUniversity Of Cincinnati The MAVEN ProjectUniversity Of Iowa University Of New EnglandUniv Of Massachusetts Med Sch Worcester WVU Medicine
University Of Michigan At Ann ArborUniversity Of Minnesota (2)University Of New Mexico Health Scis CtrUniv Of North Carolina Chapel HillUniversity Of Rochester (5)University Of UtahUniversity Of VirginiaUniversity Of Washington (4)University Of Wisconsin-MadisonVirginia Commonwealth UniversityYale University
HUB Attendees &
Open Registration
58%
Healthcare Partners
6%
Leadership (NIH/Local
HUB)3%
CLIC / Conversation
Catalysts / Admin Team
33%
…by AffiliationMidwest,
25%
Northeast, 25%
North Central / West, 6%
Southern/Southwe …
Western,
16%
… HUBS by Region
Common Themes
• How do we make telehealth models sustainable?
• How do we make telehealth accessible and shift to what individual patients need?
• We need to engage patients and communities in this process
• We need to not focus on only traditional clinical outcome, we need to be transformative.
• We need to build trust, education, and literacy
• We need to take a step back and ask are we asking the right questions, are we making the right comparisons
• There is a need for national initiatives that transcend our individual academic, governmental, or industry silos.
Breakout Session Summaries
Survey Results
Survey Results
Participant Feedback
❑ Good discussion❑ I didn’t’ know what to expect. I came away with exciting
ideas, questions and topics to research❑ Easy conversations on some challenging topics. Diverse
respectful interactions❑ Varity of Telehealth programs at different levels serving
different patients❑ Time to discuss this important topic❑ Excellent and experience experts relevant topics❑ Topics were as expected.❑ There were national experts who provided excellent insights
into the next stage of telehealth addressing rural needs. I learned a lot.
❑ Will there be a summary or white paper of this meeting?❑ Great conference; well organized; good speakers❑ This planning team was fabulous. They were comprehensive
and made themselves available continually to help participants get comfortable with the situations regarding this conference whether it was the tech platform or the pre-recording. They seemed unflappable throughout!
Continuing the conversation
Next Steps
• Summaries from the breakout sessions and survey results were posted on the CLIC website
• Pursuing opportunities for collaborations• Funding mechanisms• Publications: Dr. McGinley has contacted several attendees and presenters with the plan to apply for Synergy paper funding when the next RFA is released
Thank you!
Early Detection Research NetworkIt Takes a Village
Sudhir Srivastava, PhD, MPHSenior Scientific Officer, Chief, Cancer Biomarkers Research Group (CBRG)
National Cancer Institute, National Institutes of Health
33
Why Early Detection: Screening and Early Detection Saves Life…
Etzioni et al., Nature Reviews Cancer 3, 243-252 (2003)
Extent of Overdiagnosis
Cancer Type Overdiagnosis (%)* Screening Modality
Breast 25 2 Mammography
Prostate 50-60 2 PSA
Lung 13-25 9 CT (NLST)
Melanoma About 50-60 2,9 Crude estimate based on
population Trend
Kidney No reliable estimate 2 No screening modality,
incidentally found
Thyroid >99% 2 Crude estimate; No
screening modality,
incidentally found
Sudhir Srivastava Eugene J Koay , Alexander D Borowsky , Angelo M De Marzo , Sharmistha Ghosh , Paul D Wagner , Barnett S Kramer (2019) Nature Reviews Cancer 19(6) 349-358
35
Screening Programs and Overdiagnosis
Bleyer A, Welch HG. N Engl J Med 2012;367:1998-2005.
Up to ~25% of
breast cancers diagnosed by mammography
are estimated as overdiagnosed,
with DCIS accounting for the largest proportion
of these.
250
200
150
100
50
0
Ne
w P
rost
ate
Can
cer
Cas
es a
nd
Dea
ths
(pe
r 1
00,0
00 m
en)
1975 1980 1985 1990 1995 2000
Deaths
New Cases
50-60% of prostate cancers
detected by PSA are
considered to be
overdiagnosed
U.S. Prostate Cancer Incidence vs. MortalityIncidence of Stage-Specific Breast Cancer in the U.S., 1976–2008
36
Audacity and Challenges with Screening Tests
• Lack screening tests for a majority of cancer types
• Screening tests are not very specific and sensitive, therefore yield false positives and false negatives
• Compliance is poor
• Overdiagnosis occurs
• Not accessible and affordable to underserved population
37
Biomarkers to Address Screening and Overdiagnosis:
State of the Science in Biomarker Research
• More than 60,000 papers on cancer biomarkers each year (2019 Medline Search)
• Around 4000–5000 on biomarkers for early detection
• 99% claim >90% sensitivity and specificity
• But very few, if any, get through regulatory approval
38
Cancer Biomarkers“Water, water everywhere, and not a drop to drink”
• Most studies fail to use biomarker scienceo Poor study design
o Lack of appropriate specimens and reagents
o Absence of analytical chemistry
o Inappropriate statistical methods
o Bias, chance and overfitting
o Incomplete protocol reporting
• Biology of early disease not well explored
• Unintentional selective reporting
• Lack of collaboration
Lack of Collaboration
39
A Team Science Approach to Biomarkers
• Scientists in the business of discovery
• Scientific laboratory experts to validate and standardize assays
• Clinician-scientists who:o Identify applications for biomarkers
o Determine what are the criteria for clinical success
o Identify or develop reference sets for biomarker validation
o Pursue formal prospective validation trials
• Biostatisticians who oversee process at every juncture
o Data management
o Milestones as biomarkers move from step-to-step
o Quality assurance
• Infrastructureo Data management
o Biorepositories – linked by informatics
This is the EDRN
40
Biomarker Team: Many Programs On Biomarkers “Hub and Spokes”
Programs
• Early Detection Research Network (EDRN)
• Molecular and Cellular Characterization of Screen-Detected
Lesions (MCL)
• Alliance of Glycobiologists for Cancer
• Exosome-Derived Analytes for Cancer
• Consortium for Imaging and Biomarkers (CIB)
• Liquid Biopsy for Early Cancer Assessment
• Translational Liver Cancer (TLC) Consortium
• Pancreatic Cancer Detection Consortium (PCDC)
• Chronic Pancreatitis, Diabetes and Pancreatic Cancer
(CPDPC)
• Pre-Cancer Atlas (PCA) Cancer Moonshot Program
Inter-Agency Agreements (IAA)
• Jet Propulsion Laboratory (JPL)/National Aeronautics and
Space Administration (NASA)
• National Institute of Standards and Technology (NIST)
• Pacific Northwest National Laboratory (PNNL)
• Center for Prostate Disease Research (CPDR)
EDRN
MCL
Alliance
NIST
CPDR
PNNL
JPL
PCACPDPC
PCDC
TLC
Liquid Biopsy
CIB
Exosome-Derived Analytes
US EDRN-Japan
US EDRN-Chile
US EDRN-China
https://prevention.cancer.gov/research-groups/cancer-biomarkers/about-cancer-biomarkers
41
Organizational Structure and Implementation
EDRN has been cited as a model organization (best practices for project management
driven by milestones and operational guidelines, manual of operations, and team
approach) by professional societies and scientific journals such as AACR, NCI
Translational Research Working Group, IOM, Nature, Science, J. Proteome Research.
Srivastava S. Wagner P, (2020) CEBP 29 (12) 2401-2410
42
EDRN: A Collaborative Community on Biomarker Research
Validation InformsDiscovery
Biomarker Developmen
tal Laboratories
Clinical Validation Centers
Biomarker Reference
Laboratories
Assay Development
Validation
Discovery
Network Consulting Team
Steering Committee & Executive Committee
Data Management & Coordinating Center
https://edrn.nci.nih.gov/docs
43
Strategic Partnerships It takes a village
• Precompetitive Data Sharing (e.g., proPSA with Beckman Coulter; PCA3 with GenProbe)
• Leveraging Resources
o Canary, Inc. uses EDRN Data management system for lung and prostate markers
o Lustgarten Inc. funded 20-hybridoma cell lines for pancreatic candidate markers
• International Partnerships
o Turkey, Chile (mesothelioma)
o China (HCC, lung)
o Cancer Research UK (in progress; pancreatic, lung)
o EU European Advanced Translational Research Infrastructure (in progress; www.eatris.eu)
o India-NCI
Operationalizing Rewards and Incentives for Collaboration
Incentives and Rewards for Collaboration
The Core Fund AKA “Headquarters Fund (HF)” is a tailored funding mechanism that provides collaborative funds for post-award planning and implementation of validation trials.
• Provides continuity for multi-year validation trials, commitment for out years are needed
• An integral part of individual grants’ milestones for bringing discovered biomarker to validation (an Incentive and Reward System); 30% funding is reserved for collaboration
• Used to seek services not available within the Network to develop collaborations
• Also supports the Associate Membership program
45
Informatic Infrastructure and
Validation Trial System
Bioinformatics: Biomarkers of Early Detection
In Translational Pathology of Early Cancer. W. Grizzle, S. Srivastava, eds. IOS Press 2012
Informatics in Proteomics: edited by Sudhir Srivastava, Taylor and Francis, 2005
46
Development of Biomarker Research Informatics
• Shared
Ontologies
• Cloud
Computing
• Data
Pipelines
• Machine
Learning
• Visualization
Sc ience Data
BiomarkersEDRN Knowledge
System
Publications
Protocols/Investigators
EDRN Data Commons
(LabCAS)
Consortium for Imaging and
B iomarkers (CIB)
REU
SE &
CO
LLA
BO
RATIO
NS
Center for Biomedical
In formatics and Information
Technology (CBITT caDSR)
In formatics Technology for
Cancer Research (ITCR)
Consortium for Molecular and
Cellular Characterization of
Screen-Detected Lesions (MCL)Development of systems and tools to
support biomarker research with secure and
public access portals:
• Biomarker Database development and data
capture and curation (>1000 BMs curated)
• Interactive, CLOUD-based workspace/data commons (LabCAS) development for secure,
pre-publication data capture, sharing and
analysis
• Development and implementation of
automated data analytic pipelines
• Data-files, Publications and Protocol Archiving
Systems (eSIS; eCAS)
http://edrn.nci.nih.gov/informatics/informatics
47
EDRN-Led Study Designs Ensure Rigor and and Reproducibility
Preclinical Exploratory
PHASE 1 Promising directions identified
Clinical Assay and Validation
PHASE 2 Clinical assay detects established disease
Retrospective Longitudinal
PHASE 3 Biomarker detects preclinical disease and a “screen positive” rule defined
Prospective Screening
PHASE 4
Extent and characteristics of disease detected by the test and the false referral rate are identified
Cancer Control
PHASE 5
Impact of screening on reducing burden of disease on population is quantified
Phases of Biomarker Discovery and Validation
PRoBE
Study
Design:Prospective-
Specimen-
Collection,
Retrospective-
Blinded-
Evaluation
Pivotal Evaluation of the Accuracy of a Biomarker Used for Classification or Prediction: Standards for Study Design
Margaret Sullivan Pepe et al.J Natl Cancer Inst 2008; 100:1432-1438
Phases of Biomarker Development for Early Detection of CancerMargaret Sullivan Pepe et al.
J Natl Cancer Inst, Vol. 93, No. 14, July 18, 2001
48
Ovarian Markers as an Example
Prioritization of >120 candidates through bioinformatic
analysis (expression and biological function); in silico
proteomics, and shot-gun proteomics
Discovery (1,000s)(BDLs and others)
Candidate Biomarkers Identified(BDLs, CVCs, BRLs)
Top 50 candidates tested using SRM or Bioplex using
clinical samples of cases and benign/healthy controls
Top 10 candidates tested in pre-clinical, longitudinal screening samples from the ROCA, CARET, and FCCC cohorts. Hierarchical longitudinal change-point statistical model developed to determine candidates rise significantly above background variation one or more years prior to detection of ovarian cancer in at least 10% of cases, at 98% specificity.
Validate findings on longitudinal screening samples from other cohorts: PLCO, WHI OS and UKCTOCS
Re-evaluate biomarker use in
clinical setting
Re-evaluate biomarker for
utility as an early detection or
risk marker
NO Development
(BDLs, CVCs, BRLs)
Pre-validation
(BDLs, CVCs, BRLs, DMCC)
NO
NO
NO
Validation(BDLs, CVCs, BRLs,
DMCC)
YES
Cost Effective?
YES
Milestones
Utilization of biomarker in clinical care
setting
49
FDA-approved Tests with Significant Clinical Application
• Two FDA-approved assays for determining risk of ovarian malignancy in women with an adnexal pelvic mass, who will be referred to a gynecologic oncology surgeon:
• OVA1/OVERA (5 analytes each) offered by
Vermillion, Inc.
2700 physicians in the US ordering OVA1 or its
reflex test (OVA1 followed by Overa/OVA2)
• ROMA (2-analytes plus menopausal status)
offered by Fujirebio, LabCorp.
50
Diagnostic Tests Having Clinical Impact: Percepta
• The Percepta classifier identifies patients with lung nodules who
are at low risk of cancer following an inconclusive bronchoscopy
result, making it possible to monitor these patients with CT scans
in lieu of invasive diagnostic procedure.
• The test is a 23-gene expression panel that measures mRNA in
cells taken from bronchial brushes during bronchoscopy.
• Validation of this test involved two clinical studies; The Airway
Epithelial Genes Expression (AEGIS -1 and AEGIS -2) in the
Diagnosis of Lung Cancer.
• Veracyte Inc. offers the test, which is reimbursed by Medicare.
Approximately 1,000 tests are now being performed quarterly in
the U.S., with close to 3,000 cumulative tests since July 2019.
Abnormal
cells
51
Diagnostic Tests Having Clinical Impact: MiPS
• Mi-prostate score (MiPS) helps evaluate a patient’s risk of having prostate cancer and the degree of its aggressiveness; it is usually performed after an abnormal PSA test and a digital rectal exam.
• MiPS combines three biomarkers, serum PSA, urinary PCA3, and urinary TMPRSS2:ERG, which has a high negative predictive value (98%) and sensitivity (97%).
• This test has been shown to avert 27% of unnecessary biopsies. EDRN investigators have made significant contributions to its discovery and validation.
• The development of the MiPS assay provides an example of continuous improvement. More than 1,600 tests have been performed at LynxDX, a reference laboratory, to date.
52
EDRN-Supported Transformative Research and its Impact on Clinical
Practice• ACS Guidelines on Early Age Screening of Colon Cancer Cited EDRN Findings (Cooper,
Markowitz, Brenner et al., 2018) on Early Onset of Colon Cancer through Stool Test (Sandy Markowitz)
• Blood-based biomarkers to screen for colorectal cancer with sensitivity and specificity like FIT, which could result in increase in the number of people being screened. The investigators and industry collaborators are in discussions with the FDA (Sandy Markowitz)
• Combining LDCT and biomarkers to better risk stratify patients for lung cancer screening, which could reduce the number of unnecessary LDCT, while also offering such screening to other populations that are currently not considered as high-risk but still harbor a large proportion of detectable lung cancers (Avi Spira, Pierre Massion)
• Liquid Biopsy (Pan-Cancer Detection) – originated within EDRN (Ken Kinzler)
• Circular RNAs in Body Fluids – discovered as biomarkers through EDRN support (Arul Chinnaiyan)
53
EDRN as an Accelerator and as a Brake…
• Clinical Reference Sets (CRS) used to select or discard biomarkers for given clinical use
• Rigorous science to refute unsubstantiated claims
• Provide a mechanism to fail cheaply and accurately
54
Resources: Biospecimen Reference Sets
Standard Biospecimen Reference Sets
(Frederick National Laboratory for Cancer
Research)
Bladder LiverBreast Pancreas
Colon Prostate
Lung Ovary
http://edrn.nci.nih.gov/resources/sample-reference-sets
First-ever concept originated and implemented within
EDRN for rapid evaluation of technologies and biomarkers
• EDRN has developed a mechanism
through which biomarkers are first tested
in Reference Sets for an intended use
• Reference Sets provide a triage system
that allows “Go or No-Go” decision-making
• If successful, a large validation study is
planned
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Verification of Biomarkers Using a Reference Set
56
Accountability and Reproducibility and Validation of Data
A Sharp Rise in Retractions
Prompts Calls for Reform
By CARL ZIMMER
Published: April 16, 2012
▪ An algorithm (Ovasure test) based on the levels of four proteins (leptin, prolactin, osteopontin and insulin-
like growth factor II) that could classify women as having ovarian cancer or not was developed by Dr. Gil
Mor of Yale University.
▪ The test's high sensitivity, specificity and 99.3% PPV caught the attention of EDRN. When EDRN
statisticians calculated the PPV, it was 6.5%, which was too low for the test to be of much use for
screening. Mor’s calculations were based on the wrong study population.
▪ Despite EDRN’s warnings about the errors, Mor went ahead with the test, and on 23 June 2008, LabCorp
announced the availability of the OvaSure test for between US$220 and $240.
▪ Concerns over the test, lack of validation, and exchange of letters between worried investigators reached
the FDA. On 7 August 2008 FDA sent a letter to LabCorp saying that the test "has not received adequate
clinical validation, and may harm the public health".
▪ Ovasure was pulled from the market on 24 October 2008.
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Food and Drug Administration (FDA) Approved Diagnostic Tests
Biomarker Purpose Year of ApprovalEDRN Principal Investigators
Industrial Partner
EsoCheck
Allows patients to undergo a non-invasive five-
minute office-based procedure to detect
Barrett’s Esophagus
2019
FDA-cleared tool
Sanford Markowitz, M.D.
Lucid Diagnostics
CancerSEEKDetection of genetic mutations associated
with pancreatic and ovarian cancer.
2019
FDA break through
device
Ken Kinzler, Ph.D., Robert Schoen, M.D.,
Randall Brand, M.D., Peter Allen, M.D.,
and Samir Hanash, M.D.
Thrive Detection Corp.
Overa (5 analytes: CA 125, apolipoprotein A-
1, transferrin, follicle-stimulating hormone,
human epididymis protein 4)
Prediction of ovarian cancer risk in women
with adnexal mass.2016
Zhen Zhang, Ph.D. and Daniel Chan, Ph.D.
Vermillion
%[-2]proPSAReduce the number of unnecessary initial
biopsies during prostate cancer screening.2012
Daniel Chan, Ph.D.
Beckman Coulter
PCA3 (Prostate Cancer
Antigen 3) RNA in urine
Determination of need for biopsy or repeat-
biopsy in patients at risk for prostate cancer.2012
John Wei, M.D.
Gen-Probe
Risk of Ovarian Malignancy (ROMA)
algorithm
Prediction of ovarian cancer risk in women
with pelvic mass.2011
Steve Skates, Ph.D.
Fujirebio Diagnostics
DCP and AFP-L3; a combined panel of
biomarkers
Risk assessment for development of
hepatocellular carcinoma.2011
Jorge Marrero, M.D.
Wako Diagnostics
OVA1TM (5 analytes: CA 125, prealbumin,
apolipoprotein A-1, beta2 microglobulin,
transferrin)
Prediction of ovarian cancer risk in women
with adnexal mass.2009
Daniel Chan, Ph.D. and Zhen Zhang, Ph.D.
Vermillion
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Biomarker Tests in Clinical Laboratory Improvement Amendments (CLIA) Laboratories
Biomarker Assay PurposeEDRN Principal Investigator
CLIA Laboratory
MiCheck (Glypican-1 protein and related signaling molecules)
Differentiate aggressive prostate cancer from non-aggressive cancer and no cancer
Daniel Chan, Ph.D.Minomic, Inc
Videssa (a multi-protein biomarker blood test)
Distinguish benign from malignant breast lesions
Joshua LaBaer, M.D., and Karen Anderson M.D.
Provista
DetermaVuLiquid biopsy test intended to facilitate clinical
decision making in lung cancerLouise Showe, Ph.D.
OncoCyte
Percepta (23-gene expression panel) Detection of lung cancerAvrum Spira, M.D.
Veracyte Inc.
Esoguard (methylated vimentin and cyclin A1)
Detection of Barrett’s esophagusSanford Markowitz, M.D.
Lucid Diagnositcs
Decipher Prostate Cancer Classifier Test (SChLAP1 and other lncRNAs)
Determination of prostate cancer aggressiveness
Arul Chinnaiyan, M.D., Ph.D.GenomeDx
Mucin panel (MUC4, MUC5AC, MUC16 and MUC 17)
Detection of pancreatic cancerSurinder Batra, Ph.D.
Sanguine Diagnostic and Therapeutics
MiPS (Mi Prostate Score Urine test), Multiplex analysis of TMPRSS2:ERG gene
fusion, PCA3 and serum PSADetection of prostate cancer
Arul Chinnaiyan, M.D., Ph.D.Gen-Probe
IHC and FISH for TMPRSS2:ERG fusion Detection of prostate cancerArul Chinnaiyan, M.D., Ph.D.
Roche
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Health EconomicsUse of Biomarkers Can Reduce Healthcare Costs
• 7.5 million screening colonoscopies at an average cost of $1,600 each year
• Just a 10% reduction in screening colonoscopies using could save $1.2
billion.
• 600,000 indeterminate lung nodules 8-30 mm undergo diagnostic work-up each
year (calculated by a random sample of private and academic pulmonologist
practices).
• Only one-third were cancer and two-thirds were benign
• The costs of CT Scan, bronchoscopes or FNAs, PET scans, and VATS were
about $9 billion
• One-third of these costs ($3 billion) could be saved by a blood test.
(Courtesy: Integrated Diagnostics.)
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Trending…
• 1st Generation Biomarkers: Relied on detection
of common biomarkers, such as antibodies,
antigens, and simple biochemical reactions
• 2nd Generation Biomarkers: Focused on more
Liquid Biopsy, such as circulating nucleic
acids and proteins for Multicancer Cancer Early
Detection Tests (MCED)
• 3rd Generation
• Biomarker and Data Science: AI
• PreCancer Atlas
• Synthetic Biomarkers
Jani V. Ilesh, June 13, 2013 N. Engl J Med
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Liquid BiopsyMulti-Cancer Early Detection Test
• Paucity of single markers that have the prerequisite sensitivity and specificity to detect a particular cancer type (single organ screening)
• Potential efficiency of universal cancer screening (UCS) in detecting cancers originating from multiple organ sites using markers that are either specific for a cancer type or common for multiple cancers
• Aggregate sample size provides better statistical power with screening for multiple cancers compared to single cancer screening
Hu, Wolfram and Srivastava, Trends in Cancer, Month 2020, Vol. xx, No. xx https://doi.org/10.1016/j.trecan.2020.09.003
62
DETECT-A Results• 96 cancers identified in ~10K enrolled women, ages 65-75; 24 cancers identified by SOC
• 26 cancers identified by blood test (14 by cfDNA mut., 11 by protein expr. & 1 combined cfDNA/protein) • 15 cancers identified by blood test and PET-CT• 11 cancers identified by blood test and other imaging
• 14 (31%) of 45 cancers in 7 organs for which no SOC screening test is available were first detected by blood testing
• (overall SN 27% at 99.6% SP & 28.3% PPV when MCED combined with PET-CT confirmation)
63
GRAIL’s Galleri Circulating Cell-free Genome Atlas (CCGA) Phase 2 study
64
Figure 4
Early-Stage Cancer Detection by CancerSeek and Galleri MCEDs
CancerSEEK
• 40% SN for stage I in initial retrospective (phase 2) study (with inclusion of circulating protein markers)
• Of 96 prospective cancers in DETECT-A, only 15 detected by ctDNA and 11 more by the protein markers
• Of 15 detected by cfDNA, only 1 at stage I and 1 at stage II• PPV: 19% (28% with PET-CT); SP 99.6%
• Tissue Of Origin (TOO): does not call TOO based on somatic mutations; relied on PET-CT
Galleri (only phase 2 data from CCGA study)• 18% SN for stage I
• 43% SN for stage II• Tissue Of Origin (TOO): >80% correct
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Synthetic Biomarkers: Confluence of Engineering and Medicine
▪ Synthetic biomarkers: When cancer cells (if present) are tricked/forced to produce a biomarker they otherwise would not, which can then be detected non-invasively because of increased/detectable concentration.
▪ Synthetic biomarkers offer better tumor-specificity because of built-in cancer-reactive modules. The cancer-reactive modules can involve the following steps:
▪ probes are given to patients through intravenous injection, inhalation or oral administration (systemic vs. local);
▪ probes are taken up and activated by precancer/cancer cells or the microenvironment;
▪ specific reporters are produced, released and shed into the circulation;
▪ body fluid such as blood and/or urine are collected and analyzed by ex vivo biochemical assays;
▪ diagnosis made or, in case of a tiered approach, recommended for additional diagnostic tests.
▪ Synthetic biomarkers can be multiplexed with optical probes to determine the location of incipient/early stage cancers.
▪ There are many challenges, which include optimal presentation at the tumor site, off-target activation, clearance from the system, potential toxicity, immunogenicity, etc., and these need to be resolved first.
Gabe, Ghosh and Srivastava (2021) Nature Reviews Cancer (in press)
66
Synthetic Biomarkers for Early Detection
A. Tumor-activatable nucleotide minicircles
(MCs) driven by a tumor-specific promoter
and encoding a secretable reporter protein.
B. MCs transfect many tissues, but reporter
protein production occurs nearly exclusively
within tumor cells, and the expressed
reporter is secreted into the bloodstream.
C. Collection of blood and detection of the
secreted reporter in plasma.
Example: Blood-based detection of tumor-driven biomarkers
Ronald et al., PNAS March 10, 2015 112 (10) 3068-3073
Size of MC ~4 kb
MCs have become one of the most promising non-viral vector platforms in terms of translation potential, potency, and safety.
67
Biomarker Research Going DigitalBiomarker and Data Science
In 2017, the FDA authorization for digital pathology in the US, the world's largest healthcare market,
constitutes a watershed moment for the healthcare industry.
Digital pathology enables one to view and diagnose
from digital images of surgical pathology slides prepared from biopsied and resected tissue.
• Data science/systems approaches and modeling for the
analysis, integration and interpretation of experimental data
(genomics, epigenomics, proteomics, metabolomics, imaging etc.) to define “disease dynamics” in screen-detected early
lesions
• Increasing trends toward digitizing histopathology and
histochemistry, along with imaging and molecular approaches to elucidate dynamic changes occurring during
progressive disease
• Need and capability to create a compendium of precancer
images to study semantic and phenotypic features and apply radiomic tools to decipher distinct features of screen-detected
and interval cancers
• Data available to others for developing AI, including Machine
Learning Language (MLL), to develop rendition of hard-to-read early-stage images for better interpretability and visualization
68
Preclinical Images: A Tell-Tale to Early Detection
• Large “pre-diagnostic” imaging datasets linked to diagnostic outcomes,e.g., 22 M CT scans/year and “cyst pandemic”
• Sharing of data acquired in routine patient care
• Development of reproducible AI systems o Model selection and trainingo Model validation and integrationo Periodic performance evaluation
68
Young, Ghosh, Abrams, Guillermo, Rinaudo and Srivastava Pancreas: August 2020 - Volume 49 - Issue 7 - p 882-886
22 M abdominal CT scans/year
69
What Is a Human Tumor Atlas?
A human tumor atlas can be defined as a multidimensional cellular,
morphological, and molecular mapping of human tumors,
complemented with critical spatial information (at cellular and/or
molecular level) that facilitate visualization of the structure,
composition, and multiscale interactions within the tumor ecosystem
as a function of time for a profound understanding of the tumor
trajectory from pre-invasive to invasive cancer, development of
metastasis, response to treatment, and resistance to treatment.
Srivastava, et.al Trends in Cancer, August 2018, Vol. 4, 532-536
70
Mapping the Spatial Organization Has Begun
Image Credit: Peter Sorger, Harvard Team
• All HTAN Centers characterize the
specimens (e.g. by imaging) and
generate a spatially resolved cell
type/state census using each Center’s
method of choice;
• Data recorded in a common repository to
enable joint analysis;
• These data would be helpful in
reconstructing the images in time and
space for a better resolution of subtle
changes in precancer lesions.
71
Seminal Discoveries Being MadeImmune Landscape is Being Explored
• Why are subsets of DCIS immunologically quiet… biologic possibilities include absence of neoantigens vs. immune suppression by the DCIS vs. maintenance of a privileged niche? This needs to be tested. (MCL-PCA).
• Immune cells infiltration is noted as early as pre-proliferative state of LUSC (Spira et. al.).
• Intestinal stem cells found to drive growth trajectory in FAP polyps (Snyder et. al).
• Immune response shapes the development of tumor.
• Identification of novel targets in infant leukemia via paired single cell epigenomics and transcriptomics (Tan et al., CHOP).
• Spatially restricted multicellular immune networks that differentiate MMRd and MMRp colon cancer and drive progression (Harcohen, HTAPP).
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Opportunity for Collaboration with CTSA, NCATS
• Trial Innovation Network (TIN) to collaborate on:
• Validation of Biomarkers for Clinical Utility Using Cohorts of High-Risk Subjects through Serial, Longitudinal Samples (Serum, Plasma and Other Body Fluids)
• Building Standard Reference Samples for Biomarker Verification
• Validation of Multi-Cancer Early Detection Tests
• Innovative biomarker discovery (in silico or wet lab) of less prevalent cancer through the EDRN Associate Membership Program
• Collaboration with and Leveraging CD2H and N3C resources and infrastructure for building pre-clinical image repositories with follow-up data on clinical, biomarkers, and outcome for building predictive models using AI tools: MLL, Deep Learning, etc.
• Joint Working Groups between EDRN and TIN and CD2H to explore opportunities in cancer early detection
73
Pre-Application Webinar for EDRN Funding Opportunities
• This is an online (virtual event) webinar for additional guidance on the preparation of applications in response to the FOAs for the EDRN BCCs, CVCs, and DMCC.https://edrn.nci.nih.gov/news-and-events/webinars/pre-application-webinar-for-edrn-funding-opportunities
• The National Cancer Institute has scheduled two pre-application webinars to discuss the three recently issued Funding Opportunity Announcements (FOAs) for the Early Detection Research Network (EDRN), including:
• RFA-CA-21-033 (CVC)
• RFA-CA-21-034 (DMCC)
• RFA-CA-21-035 (BCC)
74
National Cancer Institute
Centers for Disease Control and PreventionNational Institute of Standards and Technology
Jet Propulsion Laboratory
Food and Drug AdministrationDOD’s Center for Prostate Disease Research
Basic
Science
Bioinformatics/
Resources
ClinicalAcademia Industry
Government
EDRN
“It Takes A Village”
Thank You!
76
Biomarkers and BIG Data
• Multiplex data on biomarkers have accumulated faster than human can analyze.
• AI and Machine Learning tools are increasingly being used to deep dive into data (biochemical, molecular, and imaging) for analysis, interpretation and visualization.
Crichton …Srivastava et al., Cancer Biomarkers and Big Data: A Planetary Science Approach, Cancer Cell (2020), https://doi.org/ 10.1016/j.ccell.2020.09.006
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Histopathology and HistochemistryDigitization of Whole Mount Slides
clic-ctsa.org
CLIC UpdatesAlfred Vitale, PhD
Director of Research Education, CLIC
78
Request for ApplicationsUn-Meetings
Apply to host an in-person or virtual attendee-driven event without traditional rules and structure
One hub will receive funds, planning guidance and materials, and high-level coordination from CLIC
RFA Opening Date: August 16, 2021
RFA Deadline Date: September 27, 2021
Learn more: https://clic-ctsa.org/collaboration/clic-un-meetings
Contact: [email protected]
clic-ctsa.org
Reminder: Common Metrics Data Due August 31What’s Due and What’s New?
• Careers data
• KL2
and
• TL1
• Informatics data
• Program Summaries
• Informatics
• KL2 or TL1
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Check the
Operational
Guidelines
Before
Submitting
clic-ctsa.org
When and How?
• Data and Program Summaries – August 31, 2021
• The system will be locked on September 1, 2021
• CM-PRISM reporting software application
• Do you have an account?
• If not: https://clic-ctsa.org/form/add-member-v2-0
• Which metric – Careers, Informatics, Both
• What user type – Editor or Viewer
• Please allow 48 hours for account creation
• Questions: email us @ [email protected]
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clic-ctsa.org
The Informatics Common Metric
addresses the need to harmonize
data across the CTSA Program.
This enhances the ability to
collaborate on initiatives both
within and outside the consortium.
The metric also supports the
following
NCATS strategic objective:
“Develop interoperable and
integrative biomedical informatics
resources to facilitate translational
innovation in disease prevention,
diagnosis and treatment.”
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Interoperability
Ov erv iew
Data Quality
ProcessImprov ement
s
Personnel & Networks
Optimization
Informatics: The Journey to Interoperability
We consider the first five
webcasts an introduction to
informatics, created to build
foundational knowledge and to
define key terms. We encourage
you to watch them in order.
1. Introduction to Insights to Inspire 2021
2. Language of Informatics
3. Introduction to Informatics
4. Introduction to Maturity Models
5. Importance of Interoperability
The next seven webcasts include a
deeper dive into specific topics and
can be watched in any order.
6. Infrastructure and Data Quality
7. Data Standardization in Data Warehousing
8. Process Improvement
9. Partners and Networks
10. Personnel and Interdisciplinary Teams
11. Data Science Education for Informatics
12. How to Get to Interoperability
All webcasts in the 2021 Insights to Inspire series are now
available on our website!https://clic-ctsa.org/education/kits/informatics-journey-interoperability
(includes webcasts, slide decks, and transcripts)
Start
Here
Ov erv iew
Data Quality
ProcessImprov ement
s
Personnel & Networks
Optimization
Interoperability
clic-ctsa.org
Coming Soon:
CLIC “Cohorts for Change”: Anti-Racism workshop series for CTSAs
CLIC Education Team
Becoming a Culture-Centered Community of PracticeTiffany Danielle Pineda – University of Florida
Identifying and Assessing Institutional RacismDr. Simona Kwon – New York University
Undoing the Historical Legacy of Racism in ResearchDr. John Cullen – University of Rochester
Changing the Face of Biomedical ResearchDr. Felicity Enders – Mayo Clinic
Developing Leadership PathwaysDr. Giselle Corbie-Smith – University of North Carolina
Supporting an Accountable OrganizationDeborah DiazGranados – Virginia Commonwealth University
• October 2021 Launch
• 6-month cohort, with one focus area addressed per month
• Limited Space (up to 10 hubs can participate, 2 persons per hub)
• Combination of experiential, dialogic, and interactive learning
through synchronous and asynchronous opportunities
• Each focus area is led by a facilitator from the consortium and
includes:
• One facilitated synchronous 1.5 hour Zoom session per month
• Asynchronous learning materials and activities
• A participants-only interactive space to share ideas and resources,
ask questions or seek guidance from colleagues and facilitators
• A culminating project: developing action plans specific to their hubs
clic-ctsa.orgclic-ctsa.org
Reminders
• August Webinar is Canceled
• The next scheduled CTSA Program Webinar:
▪ Date: September 22, 2021
▪ Time: 2:00-3:00pm Eastern Time.
• Group coordinator:
• CTSA Program Webinar meeting archives/information:
▪ https://clic-ctsa.org/groups/ctsa-program-group
84
clic-ctsa.orgclic-ctsa.org
CLIC/NCATS Communication Channels
Sharing Content: CLIC Website
❖ News (Consortium News & Mike’s Blog):
clic-ctsa.org/news
❖ Events: clic-ctsa.org/events
❖ Education & Career Development Gateway:
https://clic-ctsa.org/education-careers
▪ Education Clearinghouse: clic-ctsa.org/education
▪ Opportunities Board: https://clic-ctsa.org/opportunities-board
▪ Diamond: https://clic-ctsa.org/diamond
❖Funding opportunities (RFAs):
▪ Synergy Papers: https://clic-ctsa.org/collaboration/clic-synergy-papers
▪ Un-Meeting
https://clic-ctsa.org/collaboration/clic-un-meetings
❖ NCATS: twitter.com/ncats_nih_gov
❖ CLIC: twitter.com/CLIC_CTSA
❖ Hashtag: #CTSAProgram
CLIC Contact Us
❖ Have a question and not sure where to direct it?
clic-ctsa.org/contact
Newsletters
❖ CTSA Ansible: Subscribe Here
❖ CLIC News Roundup: Subscribe Here
❖ NCATS e-Newsletter: ncats.nih.gov/enews
85
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CTSA Program Initiative Channels
ACT Network
❖ Website: http://www.actnetwork.us/National
❖ Subscribe to newsletter:
https://bit.ly/2HQGsM5
IREx
❖ Website: https://www.irbexchange.org
❖ Subscribe to newsletter: https://bit.ly/2TtQG7b
National Center for Data to Health
(CD2H)
❖ Website: https://ctsa.ncats.nih.gov/cd2h/
❖ To Join: N3C & CD2H Login/Registration
Recruitment Innovation Center (RIC)
❖ Website: https://trialinnovationnetwork.org/recruitment-innovation-center
❖ Subscribe to newsletter: https://bit.ly/2OpEDHc
SMART IRB❖ Website: https://smartirb.org
❖ Subscribe to newsletter: https://bit.ly/2JFbiK3
Trial Innovation Network (TIN)
❖ Website: https://trialinnovationnetwork.org
❖ Subscribe to newsletter: https://bit.ly/2TXHQDZ
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