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: rosemonde@mail.nih.gov.

• 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

55

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

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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)

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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)

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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.

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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

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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

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Young, Ghosh, Abrams, Guillermo, Rinaudo and Srivastava Pancreas: August 2020 - Volume 49 - Issue 7 - p 882-886

22 M abdominal CT scans/year

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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

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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.

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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

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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)

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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!

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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

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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: unmeetings@clic-ctsa.org

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 @ common_metrics@clic-ctsa.org

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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@clic-ctsa.org

• CTSA Program Webinar meeting archives/information:

▪ https://clic-ctsa.org/groups/ctsa-program-group

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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

Twitter

❖ 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

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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

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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

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Trial Innovation Network (TIN)

❖ Website: https://trialinnovationnetwork.org

❖ Subscribe to newsletter: https://bit.ly/2TXHQDZ

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