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Childhood Cancer Data Initiative Data Ecosystem genomics proteomics

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Learning from Every Child :
The NCI Childhood Cancer
Data Initiative
December 8, 2023
The Wake Forest Center for Artificial
Intelligence Research
@wakibbe
Warren A. Kibbe, Ph.D.
Vice Chair & Professor of
Biostatistics and Bioinformatics
Duke University School of Medicine
warren.kibbe@duke.edu
2
NCI Childhood Cancer Data Initiative (CCDI) –
Building A Community
Childhood and AYA cancers are rare diseases: only 4-5% of diagnosed cancers
In the US: About 16,000 cases for children from birth to 19 years of age
About 80,000 cases for young adults from 20 to 39 years of age
Acute need for datato support research
CCDI aims to build a
community focused on Pediatric and AYA Cancer
CCDI
improves
treatment
quality
of life
s u r v i v o r s h i
p
by
learnin
g from
every
child
Personal & Professional Background
•PhD in Chemistry at Caltech, Postdoc in molecular genetics of
RAS at the Max-Planck-Institute for Biophysical Chemistry
•Cancer research for 25+ years - cancer informatics, data
science, healthcare – open science, open data advocate
•Feinberg School of Medicine at Northwestern for 15+ years
•Director NCI CBIIT 2013-2017; NCI CIO 2013-2017; Acting NCI
Deputy Director for Data Science 2016-2017
•At Duke since 2017
•Currently on IPA with NCI to co-lead the CCDI
•Lost three grandparents to cancer, father to cancer in 2019
Disclaimer
The views I express are mine and not endorsed by Duke or NCI.
The importance of Open Science
Calls for greater transparency and ‘open data access’ in clinical research continue
actively.
“Open science is the movement to make scientific research, data and
dissemination accessible to all levels of an inquiring society”*
Open Science Project**: “If we want open science to flourish, we should raise our
expectations to: Work. Finish. Publish. Release.”
FAIR Principles: Findability, Accessibility, Interoperability, and Reusability***
TRUST Principles: Transparency, Responsibility, User focus, Sustainability and
Technology****
* https://www.fosteropenscience.eu/resources
** http://openscience.org/
*** https://www.nature.com/articles/sdata201618
****https://www.nature.com/articles/s41597-020-0486-7

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  • 1. Learning from Every Child : The NCI Childhood Cancer Data Initiative December 8, 2023 The Wake Forest Center for Artificial Intelligence Research @wakibbe Warren A. Kibbe, Ph.D. Vice Chair & Professor of Biostatistics and Bioinformatics Duke University School of Medicine warren.kibbe@duke.edu
  • 2. 2 NCI Childhood Cancer Data Initiative (CCDI) – Building A Community Childhood and AYA cancers are rare diseases: only 4-5% of diagnosed cancers In the US: About 16,000 cases for children from birth to 19 years of age About 80,000 cases for young adults from 20 to 39 years of age Acute need for datato support research CCDI aims to build a community focused on Pediatric and AYA Cancer
  • 3. CCDI improves treatment quality of life s u r v i v o r s h i p by learnin g from every child
  • 4. Personal & Professional Background •PhD in Chemistry at Caltech, Postdoc in molecular genetics of RAS at the Max-Planck-Institute for Biophysical Chemistry •Cancer research for 25+ years - cancer informatics, data science, healthcare – open science, open data advocate •Feinberg School of Medicine at Northwestern for 15+ years •Director NCI CBIIT 2013-2017; NCI CIO 2013-2017; Acting NCI Deputy Director for Data Science 2016-2017 •At Duke since 2017 •Currently on IPA with NCI to co-lead the CCDI •Lost three grandparents to cancer, father to cancer in 2019
  • 5. Disclaimer The views I express are mine and not endorsed by Duke or NCI.
  • 6. The importance of Open Science Calls for greater transparency and ‘open data access’ in clinical research continue actively. “Open science is the movement to make scientific research, data and dissemination accessible to all levels of an inquiring society”* Open Science Project**: “If we want open science to flourish, we should raise our expectations to: Work. Finish. Publish. Release.” FAIR Principles: Findability, Accessibility, Interoperability, and Reusability*** TRUST Principles: Transparency, Responsibility, User focus, Sustainability and Technology**** * https://www.fosteropenscience.eu/resources ** http://openscience.org/ *** https://www.nature.com/articles/sdata201618 ****https://www.nature.com/articles/s41597-020-0486-7
  • 7. 7 cancer.gov/CCDI #data4childhoodcancer Build a strong base: Progress requires data from many sources that is connected and easy to access. Assemble better data: Complete data sets are needed to understand each type of cancer. Make data easy to use: More thoughtful tools for analyzing data will help answer important questions. Improve treatments and outcomes: Data is the foundation that informs new treatments and improves lives faster.
  • 8. “Focus on the critical need to collect, analyze, and share data better in order to maximize NCI’s ongoing investment in pediatric and AYA cancers and survivorship. Tissue samples from patients with cancer in this age group are critically limited and a valuable resource. The overall goal of the CCDI is not simply to generate more data, but to build processes that transform data into knowledge that moves the field forward in meaningful ways. The CCDI supports the wider pediatric cancer community’s goal of maximizing the stated goal of “learning from every patient” so that ultimately those patients, survivors and their families can materially benefit in terms of higher cure rates and improved long-term health outcomes.” Aggregate and generate broad categories of data Develop infrastructure Engage with experts Empower patients & families Ensure appropriate policy and funding Develop strategy for survivorship Ensure diverse patient representation Enable improved patient outcomes and treatment Categories of Recommendations BSA CCDI Working Group Report 24 recommendations WG Report https://deainfo.nci.nih.gov/advisory/bsa/sub-cmte/CCDI/CCDI%20BSA%20WG%20Report_Final%20061620.pdf
  • 9. Ad Hoc Working Group in Support of the CCDI Kevin Shannon (Co-Chair) UCSF Otis Brawley (Co-Chair) Johns Hopkins Peter Adamson Sanofi Tom Curran Children’s Mercy James Downing St. Jude Julie Guillot Leukemia & Lymphoma Society Amanda Haddock Dragon Master Foundation Samuel Volchenboum U Chicago John Maris CHOP Andrew Kung MSKCC Warren Kibbe Duke Andrea Hayes- Jordan UNC Katherine Janeway DFCI Douglas Hawkins Seattle Children’s
  • 10. • Adapt treatments, diagnostics, and prevention strategies as knowledge is gained • Identify exceptional responders • Understand molecular landscape of rare cancers • Use germline for predisposition studies • Aggregate, federate • Data resource inventory • Identifiers for biospecimens • Develop NCCR • Tools for translation • Harmonize clinical and research terminologies • AL and ML approaches • Simplify data access • Bar coding for data • Aggregate 6 broad categories of data • Existing molecular • New “ideal” data types • Preclinical • Off-trial patient data • Develop national strategy for molecular characterization • Cancer model data Aggregate and generate data Develop infrastructure Enable improved patient outcomes and treatment • Allow patients to access their data • Creative ways to “opt in” • Engage with all stakeholders Empower patients & families BSA CCDI Working Group Recommendations
  • 11. • Make data representative of full spectrum of patients • Consent diverse populations • Develop long-term strategy for tracking patients across lifetime • Set expectations for data sharing • Commit to data sharing thru policy and funding • Convene experts for molecular characterization • Convene experts for NCCR • Engage with all stakeholders Engage with experts Ensure appropriate policy and funding Develop strategy for survivorship Ensure diverse patient representation BSA CCDI Working Group Recommendations
  • 12. Establish Goals of Initiative Identify Gaps, Needs, Research Priorities Develop Structure to Meet Goals, Addressing Gaps Set Milestones & Assessment Metrics Begin FY22-FY24 Concept Development Process State of the Union Kick-Off Symposium CCDI Structure (BSA/NCAB) CCDI Working Groups & CCDI Leadership BSA Working Group Report 2019 - 2021 NCI: Leverage existing programs, funding mechanisms, datasets for short-term solutions to implement vision 2022 - 2029 Issue Funding Opportunities Mix of funding based on NCI strategic planning CCDI Program Establishment
  • 14. 14 Pediatric/AYA data from multiple sources Improved understanding of why some cancers develop resistance or don’t respond to treatment Generation of new ideas for intervention Culture change towards improved collaboration and data sharing Development of new research and analytical tools CCDI NCI - COG Pediatric MATCH
  • 15. Patient Data Touchpoints Diagnosis Confirmation / Refinement Clinical presentation, biopsy, imaging Molecular Sequencing, proteomics, etc. Decision-making / Clinical Care Molecular Tumor Board, Review notes, treatment decisions Longitudinal Follow-up Outcomes Long-term outcomes Short-term outcomes Treatment Treatments, procedures, adverse events Secondary Cancer Recurrence Progression Data Touchpoint Epidemiology / Population Sciences Data – Familial data, environmental, registry, population studies, disease cohorts Screening, Diagnosis, Treatment
  • 16. Our ability to generate biomedical data continues to grow in terms of variety and volume Current sources of data molecular genome pathology imaging labs notes sensors icons by the Noun Project
  • 17. Diagnosis Molecular Characterization Molecular Tumor Board Treatment Follow-on Cancer Recurrence Long-term follow-up Outcomes Federated Data Ecosystem Cancer Data “Scorecard”
  • 18. Diagnosis Molecular Characterization Clinical Decision, Molecular Tumor Board Treatment Follow-on Cancer Recurrence Long-term follow-up Outcomes Federated Data Ecosystem Cancer Data “Scorecard” EHRs, LIMS, Radiology, Pathology Systems Tumor Board Systems, Hospital Systems, EHRs, Clinical Trial Matching EHRs, CDMS, Adverse Events, CTMS EHRs, LIMS, Radiology, Pathology Systems EHRs, CDMS, CTMS EHRs, Registries EHRs, LIMS, Radiology, Pathology Systems LIMS, Sequencing Systems
  • 20. 20 CCDI Molecular Characterization Initiative https://www.nih.gov/news-events/news-releases/nih-launches-program-offer-molecular-characterization-childhood-cancers Launched March 21, 2022 First patient enrolled April 2022
  • 21. 21 Childhood Molecular Characterization Initiative • Expand access to comprehensive molecular sequencing as a step towards the goal of reaching all children with pediatric cancer • Develop NCI-recommended guidelines for clinical and molecular data collection as part of standard of care • Create a comprehensive, harmonized, and integrated database of clinical, genomic, and phenotypic data for research • First patient was enrolled in April 2022! Clinical Service: Diagnostic clinical molecular characterization services for patients who might not otherwise have access to them Data to be collected (CLIA certified) • DNA: CLIA WES or NGS targeted panel • Fusion panel • Methylation: CLIA DNA Methylation array • Clinical annotation Research Discovery: Molecular characterization to learn more about disease subtypes and rare cancers Data to be collected (in additional to clinical/seq data on selected populations) • WGS/deep molecular (DNA) profiling • RNAseq • Longitudinal data
  • 22. 22 MCI  As of November 2023 – cumulative enrollment surpassed 2,000  1,965 patients from ~180 institutions have a sample shipped to the Biopathology Center o CNS: 1,397; soft tissue sarcoma: 429; rare tumors: 139  Phs002790: Monthly molecular characterization data releases (1,697 participants). o Deidentified clinical reports also available in JSON format (converted from PDF).  COG releases clinical data every 6 months  Clinical reports currently support 5 clinical trials:  Timely return of results has enabled trial enrollment in short windows.
  • 23. Clinical Sequencing at IGM (CLIA)  Targeted exome seq  Archer fusion  EPIC methylation array  Clinical/demographic PI: Elaine Mardis PO: Malcolm Smith Research-Grade Characterization (non-CLIA)  WGS  RNA-seq  Proteomics  Metabolomics  Other  Clinical COG Project: EveryChild (CNS tumors, sarcomas, or rare cancers) PI: Doug Hawkins/ Dx Chairs PO: Malcolm Smith MyPART Refractory or relapsed cancer types (adult & pediatric) with rare cancers (DNA/RNA) PIs: Brigitte Widemann, Karlyne Reilly CCDI Molecular Characterization Initiative: Clinical Pipeline CCDI Data Ecosystem (AWS) Deposit clinical and genomic data Return of CLIA genomic results to patients and providers CCDI Molecular Characterization Pipeline Protocol Enrollment (Goal: determine best strategy to treat & learn from each child) CCDI Funded PI: Jaime Guidry Auvil, Tony Kerlavage PO: Subhashini Jagu Specific to Enrollment Other NCI Studies Patient enrollment, CLIA tissue processing, clinical data collection, mechanism to return patient results Additional Sources of Tissue Samples & Clinical Data (NEW) The pipeline began accepting samples from PEC CNS tumors in April 2022
  • 24. Clinical Sequencing at IGM (CLIA)  Targeted exome seq  Archer fusion  EPIC methylation array  Clinical/demographic Research-Grade Characterization (non-CLIA)  WGS  RNA-seq  Proteomics  Metabolomics  Other  Clinical Kids First X01s CBTN (CNS tumors; PI: Adam Resnick), Sarcomas (PI: Adam Shlein) PO: Malcolm Smith PDX Models PI: PiVOT Consortium PO: Malcolm Smith Pediatric MATCH Dx/Normal tumors PI: Will Parsons/Katie Janeway PO: Nita Seibel Childhood Cancer Survivor Study (CCSS) (Secondary Cancers) PI: Greg Armstrong PO: Nita Seibel CCDI Molecular Characterization: Research Pipeline CCDI Data Ecosystem (AWS) Deposit clinical and genomic data Return of CLIA genomic results to patients and providers CCDI Molecular Characterization Pipeline Protocol Enrollment/ Sample Collection (Tissue & Clinical Data) **CCDI Funded PI: Broad Institute, Hudson Alpha/St. Jude PO: Malcolm Smith CCDI Funded PI: Jaime Guidry Auvil, Tony Kerlavage PO: Subhashini Jagu The pipeline released the first bolus of data for research use in November 2022
  • 25. Clinical Sequencing (CLIA)  Targeted exome seq  Archer fusion  EPIC methylation array  Clinical/demographic Research-Grade Characterization (non-CLIA)  WGS  RNA-seq  Proteomics  Metabolomics  Other  Clinical CCDI Protocol Pediatric Cancer Molecular & Clinical Characterization: CCDI Protocol CCDI Data Ecosystem Deposit clinical and omic data Return of CLIA genomic results to patients and providers Patient remains on CCDI Protocol; may be enrolled in sub- studies or clinical trials COG Project: EveryChild MyPART Other NCI Studies Additional Sources Kids First X01s PDX Models Pediatric MATCH CCSS Longitudinal follow-up for select patient cohorts CCDI Clinical Characterization Pipeline Comprehensive clinical characterization  Etiology, family history, medical history  Clinical, PRO, imaging  Pathology  NIH Rare Tumor clinics  National tumor Board  Genetic counseling Core set clinical characterization Future State/Vision: • A single study acts as an entry point clinical and research- grade sequencing • The study collects a comprehensive baseline and longitudinal dataset for all patients and an enriched dataset
  • 26. 26 • Gather data from every child diagnosed with cancer in the United States • It will:  Capture the cancer care trajectory of children and AYAs, including care provided outside of COG and other networks, to identify gaps and disparities in care and outcome  Track biospecimen availability  Provide access to data from underserved patients  Provide for consistent research consent  Allow for long-term follow up of childhood cancer patients • A critical component of this effort will be the National Childhood Cancer Registry (NCCR) CCDI National Childhood Cancer Cohort
  • 27. The National Childhood Cancer Registry (NCCR) 27 • Slides from Dr. Lynne Penberthy, NCI
  • 28. The National Childhood Cancer Registry (NCCR) 28 • NCCR is a centralized infrastructure that brings together existing data on all cancer patients ages 0 to 39 • Core data are derived from cancer registries • Data from registries are extended and expanded to include additional relevant information such as • Detailed treatment • Genomic characterization of the tumor • Risk of recurrence • Risk of subsequent primary cancers • With a goal to capture the complete trajectory of care from diagnosis throughout the patient’s life • Currently includes patients representing 77% of all childhood cancers with 21 state cancer registries participating
  • 29. What is a cancer registry? • Cancer registry data provide the base for the NCCR • Registries: • collect, store, and manage data on every person with cancer from diagnosis until death • are population based (capture all cancers within a defined geographic area) • have the legal authority to capture data on every cancer • require health care providers to report information on cancer patients to state registries 29
  • 30. The National Childhood Cancer Registry Components 30 Routine linkages will be performed centrally with external data sources including: • Complete registry abstracts for each cancer case (1995-2019+) • Survival data from National Death Index (NDI) & State vital records • Residential history data • essential to enable data to be linked over time for treatment, recurrence, subsequent cancers or adverse effects • Virtual Pooled Registry (VPR) • A national system of virtual connections for all state registries the supports • de-duplication (many pediatric patients receive care across state boundaries) and • allows capture of subsequent cancers as patients age
  • 31. New NCCR data sources Data sources currently used • Birth Records, Blood spots) Selected state vital records •Long-term follow-up center, AACCR Children’s Oncology Group SEER Cancer Registries Leveraging Existing SEER*DMS servers holding PII for Secure Data Platform Selected State Cancer Registries (including TX, TN, PA, IL, NJ, OH, FL) Instance of DMS*Lite For each registry to hold PII for linkages NCCR Database*** Combines de-identified data submitted from participating registries plus linked data from additional sources Conceptual Framework: National Childhood Cancer Registry ***NCCR Database– holds de-identified childhood cancer patient data submitted from participating registries. Infrastructure to support research on childhood cancers 31
  • 32. Why are the data from NCCR important: Providing a Report Card - Leukemia as an example* *https://seer.cancer.gov/statistics/nccr/ • Registries provide de-identified data on every patient with cancer in a defined geographic region • These data allow us to • Monitor progress (report card) of clinical care on outcomes • Help us identify groups of patients who may not be experiencing the benefit of the new treatments by age, racial and ethnic subgroups, or geographic area • Similar trends are being developed for survival and mortality 32
  • 35. 35 • Designed to federate data from multiple children’s cancer institutions and community-based and NCI-supported childhood/AYA data resources, featuring:  Patient-level data from all available sources  Easy access to data to enable deep analytics  Supports interoperability among existing data resources and with tools and other resources for use by researchers  Provide a central portal to find and analyze childhood/AYA cancer data CCDI Childhood Cancer Data Platform
  • 36. 36 Establish a Federated Pediatric Cancer Data Ecosystem:  Underlying data science infrastructure  Enhanced cloud-computing  Services linking clinical, image, & molecular data  Standards & tools for data interoperability  Data repositories (e.g. Pediatric Preclinical Data Commons)  Linked data (National Childhood Cancer Registry) Genomics Data Proteomics Data Cancer Models Molecular Imaging Data Clinical Trials Treatments Patient Outcomes Cohort Studies Electronic Health Records Preclinical Data Immuno-oncology Data Demographics Clinical Characterization Discovery Science  Clinical Studies/Care 
  • 37. Childhood Cancer Data Catalog CCDI Annual Symposium A guide to finding childhood cancer programs, registries, and repositories Slides thanks to Dr. Patrick Dunn, Frederick National Laboratory
  • 39. 39 ACatalog of Data Resources for Childhood Cancer Research A guide to relevant research programs, clinical trials, data sets and repositories to support the RACE for Children Act * https://datacatalog.ccdi.cancer.gov
  • 40. 40 cancer.gov/CCDI #data4childhoodcancer CCDI Data Ecosystem Components: Connecting the Data Primary databases  Cancer Research Data Commons (CRDC)  Childhood Cancer Clinical Data Commons (C3DC)  National Childhood Cancer Registry (NCCR) Knowledge Bases  Childhood Cancer Data Catalog  Molecular Targets Platform  Data Inventory  Participant Index Curation & Harmonization  Data Coordination Center – assist with data submission and harmonization
  • 41. 41 cancer.gov/CCDI #data4childhoodcancer Access to CCDI Data & Tools ccdi.cancer.gov  The CCDI Hub is an entry point for researchers, data scientists, and citizen scientists looking to use and connect with CCDI-related data.  It provides information and direct links to CCDI platforms, tools, and resources, along with additional technical information.  CCDI Hub 2.0 release  Integrate with CCDI Data Inventory; leverage existing Bento design, customized for CCDI.  e.g., https://dataservice.datacommons.cancer.gov/#/data  Sharing CCDI clinical metadata and linkages to sample data.
  • 43. 43 cancer.gov/CCDI #data4childhoodcancer  phs002790.v1.p1 (CNS, STS, rare tumors - MCI)  Case count: 1,552; Sample count: 4,377  phs002599.v1.p1 (Acute myeloid leukemia - OHSU)  Case count: 129; Sample count: 1347  phs002504.v1.p1 (Juvenile myelomonocytic leukemia - UCSF)  Case count: 188; Sample count: 388  phs002620.v1.p1 (Solid tumors - MSK)  Case count: 114; Sample count: 326  phs003111.v1.p1 (High-risk neuroblastoma - MSK)  Case count: 130, sample count: 488  phs002518.v1.p1 (All cancer types - USC)  phs002518.v1.p1 (All cancer types - USC)  Case count: 1036 Sample count: 2240  phs002529.v1.p1 (Solid tumors & leukemias - CMRI/KUCC)  Case count: 194; sample count: 373  phs002517.v1.p1 (Brain & other solid, hematologic malignancies - CHOP)  Case count: 1031; sample count: 3,225  phs000720.v4.p1 (Rhabdomyosarcomas whole- slide hematoxylin and eosin-stained images from COG trials ARST0331, ARST0431, D9602, D9803, and D9902)  Will be available through NCI’s Imaging Data Commons and listed in the Childhood Cancer Data Catalog CCDI Data Sets
  • 44. 44 CCDI Data Access  For the CCDI studies, genomic data is hosted in the Cancer Data Service (CDS), which is a data repository under the Cancer Research Data Commons infrastructure.  dbGaP maintains a list of the subject IDs, sample IDs, and consents.  Accessing controlled-access data and clinical/phenotypic files requires authorization through dbGaP.  Users can analyze CCDI data on the Cancer Genomics Cloud through the Cancer Data Service Explorer.  Here is a tutorial on how to import CDS data: docs.cancergenomicscloud.org/docs/import- cds-data CCDI_CGC_Data_Access_Inst ructions: datacatalog.ccdi.cancer.gov/CC DI_CGC_Data_Access_Instruct ions_1.0.pdf
  • 45. 45 Data Federation Demonstration Project Goal: Facilitate large-scale analytic research through heterogeneous data aggregation.  Make deidentified participant-level data (non- PHI/PII) findable across the sources, enabling the creation of a virtual cohort (without moving or warehousing data). Status Update:  Developed scientific use cases to drive requirements for data and an API.  Defining a minimal set of demographic and clinical phenotype data to allow queries across the CCDI Federation data resources.  Drafting API requirements for the CCDI Federation.
  • 46. 46 Childhood Cancer Clinical Data Commons (C3DC) Goal: Allows researchers to search for participant-level data collected from multiple studies to create synthetic cohorts. Status Update  Working on establishing the reference set of Common Data Elements (CDEs) that will constitute a pediatric cancer clinical data standard.  Created C3DC data model in GitHub.  Tentative MVP release Q4 of 2023. How do I find the CDEs? cadsr.cancer.gov/onedata/Home.jsp
  • 47. 47 cancer.gov/CCDI #data4childhoodcancer Childhood Cancer Data Initiative Participant Index (CPI) Goal: Link participants’ data from the Federation and the CCDI projects. Status Update  COG has provided an endorsement that authorizes institutes to share the COG IDs with NCI.  Received COG ID - USI pairs for MCI participants.  Will facilitate crosswalk of CBTN data to overlapping MCI participants  Received Kids First Study IDs mapped to USIs.  Working with other institutions to acquire mapped IDs  Identifying institutions to participate in PPRL process.  Working with NCCR  Defining the technical architecture for the database.
  • 49. 49 engage with CCDI • Visit the CCDI website to learn more (on the NCI website) • Review the BSA CCDI Working Group final report • Receive email updates from NCI on the CCDI • Contact the CCDI with questions about engagement, ongoing activities, or funding opportunities • Look for information about webinars starting in 2022

Editor's Notes

  1. The Childhood Cancer Data Initiative (CCDI) improves treatments, quality of life, and survivorship by learning from every child.
  2. As I believe many of you know, CCDI was first proposed in the 2019 State of the Union address to provide a total of $500M over 10 years to the NCI to support childhood and AYA cancers. It was decided to focus on data sharing to maximize the benefit and power of the critical data being generated to study childhood, adolescent, and young adult malignancies. CCDI is being leveraged to build a wider community centered around childhood cancer care and research data, one that can collectively improve treatments, quality of life, and survivorship by learning from every child and AYA. Specifically, this means collecting high-quality data, consistently, from every patient diagnosed, particularly those with ultra-rare forms of cancer. And that has to happen whether they are treated at major academic medical facilities or in their local communities. Further, those data have to be shared and made accessible in rapid, comprehensive fashion to ensure the every child and AYA can benefit. The long-term vision for NCI and for childhood/AYA cancer communities is to enhance data sharing, accessibility, and usability in a way that is most broadly beneficial. We want CCDI to serve as an example for how the larger adult research and participant communities can maximize their data value to benefit cancer research. 
  3. As NCI has done with other major initiatives, Dr. Sharpless convened this working group supporting CCDI to advise the Institute regarding opportunities to bring together or generate data describing cancers in children and young adults, and to identify and address gaps in data sharing to make it work better for patients, survivors and families. These members with diverse expertise in the pediatric research and care communities further sought to define the pressing scientific questions that would provide the opportunity to deliver significant changes in outcomes for kids with cancer when answered.
  4. NCI has long had a number of programs dedicated to research in childhood and AYA cancers and survivorship; several that have been ongoing for many years and several more programs that were launched more recently in the context of these Acts, the Cancer Moonshot and now CCDI efforts. CCDI is an important initiative of the NCI It allows us the opportunity to look across the investments NCI has already made to address childhood cancer, and think about how those can be linked and leveraged to increase progress We are confident that using CCDI to bring these datasets together in a thoughtful and meaningful way will begin to provide a firm foundation for the insights and innovation that this data-focused initiative can produce for many years to come. While these efforts are in some ways on independent paths, NCI is moving them forward together – parallel efforts that complement and strengthen each other, and that will naturally intersect in order to make each effort as scientifically strong as possible, to maximize their success, and their impact for children with cancer.
  5. While efforts are underway to develop the National Childhood Cancer Registry and the Pediatric Preclinical Data Commons here at the NCI, we recognize that CCDI activities started this year and moving forward will need to incorporate mechanisms to more actively federate with additional clinical and research data resources both within and outside of NCI. Our vision for establishing a wider ecosystem includes many types of data from discovery science, to patient care, to population and surveillance studies that can be queried in a meaningful way by a variety of stakeholders in the pediatric/AYA cancer communities. Components of this federated pediatric cancer data ecosystem include an essential underlying data science infrastructure, enhanced cloud-computing platforms, Services that link disparate information (including clinical, image & molecular characterization data) stored in data repositories and registries. Successful implementation of this CCDI infrastructure requires development and promotion of standards & tools for data interoperability, as well as a clear plan for sustainability & data governance to ensure long-term health and function of the ecosystem.
  6. Many resources are available now for clinical trials, data, and analysis More resources are being actively developed Finding relevant resources can be challenging
  7. Data Catalog is a NCI sponsored guide for exploring the
  8. CCDI is using each critical piece of data to help the research and clinical care communities complete the puzzle and provide the bigger picture that is needed to understand each individual cancer and improve lives for children and their families. Focusing CCDI activities on building sound infrastructure to manage and share clinical care and research data, developing and refining tools to analyze and use those data effectively, ensuring our research efforts create comprehensive and meaningful datasets that lead to impactful discoveries, and seeking to collect and use data that can be translated into novel therapies, will provide the pediatric/AYA cancer communities with the answers needed to make progress. The Childhood Cancer Data Initiative is committed to joining with the full community to improve treatments, quality of life, and survivorship by learning from every child.
  9. Planning efforts for these pending opportunities are currently underway and we expect to have more concrete information coming out over the next few months. So please do continue to check the CCDI website for updates.