This document discusses how academic medical centers must become truly digital enterprises to succeed in the future. It outlines how data sharing and use of data analytics will become increasingly important in biomedical research. Academic medical centers will need to improve efficiency, embrace open collaboration, and ensure current training prepares researchers for working with large, diverse data sources. However, balancing accessibility and security of data will also be critical as these digital transformations occur. The implications discussed could shape opportunities, scientific practices, and the value of data and analytics for academic medical institutions.
One Funder’s View for Advancing Open SciencePhilip Bourne
Robert Wood Johnson Foundation & SPARC Workshop on October 19, 2015 intended to catalyze a dialogue about opportunities for philanthropy and other funders in open access.
Big Data in Biomedicine – An NIH PerspectivePhilip Bourne
Keynote at the IEEE International Conference on Bioinformatics and Biomedicine, Washington DC, November 10, 2015.
https://cci.drexel.edu/ieeebibm/bibm2015/
One Funder’s View for Advancing Open SciencePhilip Bourne
Robert Wood Johnson Foundation & SPARC Workshop on October 19, 2015 intended to catalyze a dialogue about opportunities for philanthropy and other funders in open access.
Big Data in Biomedicine – An NIH PerspectivePhilip Bourne
Keynote at the IEEE International Conference on Bioinformatics and Biomedicine, Washington DC, November 10, 2015.
https://cci.drexel.edu/ieeebibm/bibm2015/
SCUP 2016 Mid-Atlantic Symposium: Big Data: Academy Research, Facilities, and Infrastructure Implications and Opportunities. John Hopkins, May 13, 2016
Abstract: http://j.mp/1MhWWei
Healthcare applications now have the ability to exploit big data in all its complexity. A crucial challenge is to achieve interoperability or integration so that a variety of content from diverse physical (IoT)- cyber (web-based)- and social sources, with diverse formats and modality (text, image, video), can be used in analysis, insight, and decision-making. At Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, we have a variety of large, collaborative healthcare/clinical/biomedical projects, all involving domain experts and end-users, and access to real world data that include: clinical/EMR data (of individual patients and that related to public health), data from a variety of sensors (IoT) on and around patients measuring real-time physiological and environmental observations), social data (Twitter, Web forums, PatientsLikeMe), Web search logs, etc. Key projects include: Prescription drug abuse online-surveillance and epidemiology (PREDOSE), Social media analysis to monitor cannabis and synthetic cannabinoid use (eDrugTrends), Modeling Social Behavior for Healthcare Utilization in Depression, Medical Information Decision Assistant and Support (MIDAS) with application to musculoskeletal issues, kHealth: A Semantic Approach to Proactive, Personalized Asthma Management Using Multimodal Sensing (also for Dementia), and Cardiology Semantic Analysis System (with applications to Computer Assisted Coding and Computerized Document Improvement).
This talk will review how ontologies or knowledge graphs play a central role in supporting semantic filtering, interoperability and integration (including the issues such as disambiguation), reasoning and decision-making in all our health-centric research and applications. Additional relevant information is at the speaker’s HCLS page. http://knoesis.org/amit/hcls
Gather evidence to demonstrate the impact of your researchIUPUI
This workshop is the 3rd in a series of 4 titled "Maximize your impact" offered by the IUPUI University Library Center for Digital Scholarship. Faculty must provide strong evidence of impact in order to achieve promotion and tenure. Having strong evidence in year 5 is made easier by strategic dissemination early in your tenure track. In this hands-on workshop, we will introduce key sources of evidence to support your case, demonstrate strategies for gathering this evidence, and provide a variety of examples. These sources include citation metrics, article level metrics, and altmetrics as indicators of impact to support your narrative of excellence.
SCUP 2016 Mid-Atlantic Symposium: Big Data: Academy Research, Facilities, and Infrastructure Implications and Opportunities. John Hopkins, May 13, 2016
Abstract: http://j.mp/1MhWWei
Healthcare applications now have the ability to exploit big data in all its complexity. A crucial challenge is to achieve interoperability or integration so that a variety of content from diverse physical (IoT)- cyber (web-based)- and social sources, with diverse formats and modality (text, image, video), can be used in analysis, insight, and decision-making. At Kno.e.sis, an Ohio Center of Excellence in BioHealth Innovation, we have a variety of large, collaborative healthcare/clinical/biomedical projects, all involving domain experts and end-users, and access to real world data that include: clinical/EMR data (of individual patients and that related to public health), data from a variety of sensors (IoT) on and around patients measuring real-time physiological and environmental observations), social data (Twitter, Web forums, PatientsLikeMe), Web search logs, etc. Key projects include: Prescription drug abuse online-surveillance and epidemiology (PREDOSE), Social media analysis to monitor cannabis and synthetic cannabinoid use (eDrugTrends), Modeling Social Behavior for Healthcare Utilization in Depression, Medical Information Decision Assistant and Support (MIDAS) with application to musculoskeletal issues, kHealth: A Semantic Approach to Proactive, Personalized Asthma Management Using Multimodal Sensing (also for Dementia), and Cardiology Semantic Analysis System (with applications to Computer Assisted Coding and Computerized Document Improvement).
This talk will review how ontologies or knowledge graphs play a central role in supporting semantic filtering, interoperability and integration (including the issues such as disambiguation), reasoning and decision-making in all our health-centric research and applications. Additional relevant information is at the speaker’s HCLS page. http://knoesis.org/amit/hcls
Gather evidence to demonstrate the impact of your researchIUPUI
This workshop is the 3rd in a series of 4 titled "Maximize your impact" offered by the IUPUI University Library Center for Digital Scholarship. Faculty must provide strong evidence of impact in order to achieve promotion and tenure. Having strong evidence in year 5 is made easier by strategic dissemination early in your tenure track. In this hands-on workshop, we will introduce key sources of evidence to support your case, demonstrate strategies for gathering this evidence, and provide a variety of examples. These sources include citation metrics, article level metrics, and altmetrics as indicators of impact to support your narrative of excellence.
Why is the NIH investing $100M at the intersection of data science and health research? The NIH seeks to invest in ways to help researchers easily find, access, analyze, and curate research data. Researchers want visual analytics, and to build the database into a “social network” – being able to “friend” or “like” the data.
This presentation outlines a mechanism for using the power of "Big Data", social networking and technology infrastructure to speed the process of curing a horrible disease.
Improving health care outcomes with responsible data scienceWessel Kraaij
Keynote presentation by Wessel Kraaij at the Dutch pattern recognition and impage processing society (NVPBV) 29/5/2018, Eindhoven.
This talk discusses
1. trends in health care and respondible data science and their intersection
2. Secure federated analytics on distributed data repositories
3. Generating clinically relevant hypotheses from patient forum discussions.
Enhancing collaboration in informatics solutions
Now more than ever, the need for establishing connections and closer collaboration is a priority for many organisations. This webinar will highlight how Medicines Discovery Catapult is looking to approach the issue of ensuring the right problems are being tackled by the right experts.
Presented by Mark Davies on 30th April 2020
mHealth and Wireless Technology Conference Partnering with academic organizat...P. Kenyon Crowley
How companies can partner with research organizations to accelerate research and development, evaluation of products, enhance usability, and create value. Includes funding relevant to mobile health companies.
The slide presentation that preceded of the annual Health Datapalooza in Washington DC, PCORI was pleased to participate in the latest installment in the Health Data Consortium and PricewaterhouseCoopers (PwC) Innovators in Health Data Series, a webinar featuring PCORI Executive Director Joe Selby, MD, MPH; NIH Director and PCORI Board of Governors member Francis Collins, MD, PhD; and Philip Bourne, PhD, NIH’s Associate Director for Data Science.
Similar to A Successful Academic Medical Center Must be a Truly Digital Enterprise (20)
Presented online as part of the NASM series in Advancing Drug Discovery see https://www.nationalacademies.org/event/40883_09-2023_advancing-drug-discovery-data-science-meets-drug-discovery
For a panel discussion at the Associate Research Libraries Spring meeting April 27, 2022, Montreal https://www.arl.org/schedule-for-spring-2022-association-meeting/
Frontiers of Computing at the Cellular and Molecular ScalesPhilip Bourne
3 basic points when establishing a new biomedical initiative. Presented at Frontiers of Computing in Health and Society, George Mason University, September 21, 2021.
NITRD Big Data Interagency Working Group Workshop: Pioneering the Future of Federally Supported Data Repositories Jan 13, 2021 - Opening comments on where we are and one suggestion of where we might go with an International Data Science Institute (IDSI) - A blue sky view.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
GIÁO ÁN DẠY THÊM (KẾ HOẠCH BÀI BUỔI 2) - TIẾNG ANH 8 GLOBAL SUCCESS (2 CỘT) N...
A Successful Academic Medical Center Must be a Truly Digital Enterprise
1. A Successful Academic Medical
Center Must be a Truly Digital
Enterprise
Philip E. Bourne, PhD, FACMI
Associate Director for Data Science
National Institutes of Health
Nina Matheson Lecture
AAMC November 7, 2015
Available on Slideshare
3. What is My Job?
Change the Culture of NIH
What Do I Do Next Week?
4. The NIH Data Timeline
6/12 2/14 3/14
• Recommendations:
• Sharing data & software through catalogs
• Support methods and applications development
• Need more training
• Need campus-wide IT strategy
• Hire CSIO
• Continued support throughout the lifecycle
11/15
5. A Question I ask Myself A Lot…
Are we at a point of deception soon to
see a major disruption to our
institutions?
6. Some Folks Think So…
Evidence:
– Google car
– 3D printers
– Waze
– Robotics
– Sensors
From: The Second Machine Age: Work, Progress,
and Prosperity in a Time of Brilliant Technologies
by Erik Brynjolfsson & Andrew McAfee
8. We Are At a Point of Deception
The 6D Exponential Framework
Digitization of Basic &
Clinical Research & EHR’s
Deception
We Are Here
Disruption
Demonetization
Dematerialization
Democratization
Open science
Patient centered health care
9. For Academic Medical Centers What
Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and
value of the enterprise
Open collaborative science becomes of increasing
importance
The value of data and associated analytics becomes
of increasing value to scholarship
Current training content and modalities will not match
supply to demand
Balancing accessibility vs security becomes more
important yet more complex
10. For Academic Medical Centers What
Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and
value of the enterprise
Open collaborative science becomes of increasing
importance
The value of data and associated analytics becomes
of increasing value to scholarship
Current training content and modalities will not match
supply to demand
Balancing accessibility vs security becomes more
important yet more complex
11. Hypothetical Example of That Value
Jane scores extremely well in parts of her graduate on-line neurology class.
Neurology professors, whose research profiles are on-line and well described, are
automatically notified of Jane’s potential based on a computer analysis of her scores
against the background interests of the neuroscience professors. Consequently,
professor Smith interviews Jane and offers her a research rotation. During the
rotation she enters details of her experiments related to understanding a widespread
neurodegenerative disease in an on-line laboratory notebook kept in a shared on-line
research space – an institutional resource where stakeholders provide metadata,
including access rights and provenance beyond that available in a commercial
offering. According to Jane’s preferences, the underlying computer system may
automatically bring to Jane’s attention Jack, a graduate student in the chemistry
department whose notebook reveals he is working on using bacteria for purposes of
toxic waste cleanup. Why the connection? They reference the same gene a number
of times in their notes, which is of interest to two very different disciplines – neurology
and environmental sciences. In the analog academic health center they would never
have discovered each other, but thanks to the Digital Enterprise, pooled knowledge
can lead to a distinct advantage. The collaboration results in the discovery of a
homologous human gene product as a putative target in treating the
neurodegenerative disorder. A new chemical entity is developed and patented.
Accordingly, by automatically matching details of the innovation with biotech
companies worldwide that might have potential interest, a licensee is found. The
licensee hires Jack to continue working on the project. Jane joins Joe’s laboratory,
and he hires another student using the revenue from the license. The research
continues and leads to a federal grant award. The students are employed, further
research is supported and in time societal benefit arises from the technology.
From What Big Data Means to Me JAMIA 2014 21:194
12. How to Get There?
Recognize an institutions
assets are increasingly digital
Recognize the value of those
assets
Recognize that those assets
are siloed
Put in place a governance,
financial and infrastructure
model that breaks down
those silos while maintaining
community trust
That is, protect the integrity
of the assets
http://cdn.makeagif.com/media/4-01-2014/Km_F3w.gif
16. NIH Genomic Data Sharing (GDS)
Policy
Purpose
– Sets forth expectations, responsibilities that ensure broad,
responsible sharing of genomic research data in a timely
manner
Scope
– All NIH-funded research generating large-scale human or
non-human genomic data – and their use for subsequent
research
• Data to be submitted to NIH-designated data repositories
(e.g., dbGaP, GEO, GenBank, WormBase, FlyBase, Rat
Genome Database)
– Applies to all funding mechanisms (grants, contracts,
intramural support) with no minimum threshold for cost
Released August 2014; effective January 25, 2015
gds.nih.gov
17. Other Areas I Hope the SDC Will
Address
Sharing of other data types
Machine readable data sharing plans
Data citation
18. For Academic Medical Centers What
Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and
value of the enterprise
Open collaborative science becomes of increasing
importance
The value of data and associated analytics becomes
of increasing value to scholarship
Current training content and modalities will not match
supply to demand
Balancing accessibility vs security becomes more
important yet more complex
20. “The HGP changed the norms around data sharing
in biomedical research.”
“The HGP changed the norms around data sharing
in biomedical research.”
21. Data Sharing Goes Global: GA4GH
Global Alliance for Genomics and
Health
Accelerating the potential of genomic medicine to
advance human health, by:
– Establishing common framework of approaches to enable
effective, responsible sharing of genomic and clinical data
– Catalyzing data sharing projects that drive and demonstrate
value of data sharing
Alliance*: >350 leading institutions (healthcare, research,
advocacy, life science, IT) representing 35 countries
Working groups (Clinical, Data, Security, Regulatory &
Ethics) assess, prioritize needs
– Form task teams to produce tools, solutions, demonstration
projects
*Statistics as of October 5, 2015
22. A Culture of Sharing
1999 20042003 2007 20142008
Research
Tools
Policy
NIH Data
Sharing Policy
Model
Organism
Policy
Genome-wide
Association
(GWAS) Policy
2012
NIH Public
Access Policy
(Publications)
Big Data to
Knowledge
(BD2K) Initiative
Genomic Data
Sharing (GDS)
Policy
Modernization of
NIH Clinical
Trials
White House
Initiative
(2013 “Holdren
Memo”)
23. Guiding Principle of NIH GWAS Policy
The greatest public benefit will be
realized if data from GWAS are made
available, under terms and conditions
consistent with the informed consent
provided by individual participants, in a
timely manner to the largest possible
number of investigators.
NIH expectation that data would be shared in the
NIH database of Genotype and Phenotype (dbGaP)
25. A Culture of Sharing
1999 20042003 2007 20142008
Research
Tools
Policy
NIH Data
Sharing Policy
Model
Organism
Policy
Genome-wide
Association
(GWAS) Policy
2012
NIH Public
Access Policy
(Publications)
Big Data to
Knowledge
(BD2K) Initiative
Genomic Data
Sharing (GDS)
Policy
Modernization of
NIH Clinical
Trials
White House
Initiative
(2013 “Holdren
Memo”)
26. NIH Public Access Policy for Publications
Ensures public access to published results of all
research funded by NIH since 2008
– Recipients of NIH funds required to submit final peer-
reviewed journal manuscripts to PubMed Central (PMC)
upon acceptance for publication
– Papers must be accessible to the public on PMC no later
than 12 months after publication
27. A Culture of Sharing
1999 20042003 2007 20142008
Research
Tools
Policy
NIH Data
Sharing Policy
Model
Organism
Policy
Genome-wide
Association
(GWAS) Policy
2012
NIH Public
Access Policy
(Publications)
Big Data to
Knowledge
(BD2K) Initiative
Genomic Data
Sharing (GDS)
Policy
Modernization of
NIH Clinical
Trials
White House
Initiative
(2013 “Holdren
Memo”)
28. Harnessing Data to Improve Health:
BD2K (Big Data to Knowledge)
NIH’s 6-year initiative to use data science to foster an
open digital ecosystem that will accelerate efficient,
cost-effective biomedical research to enhance health,
lengthen life, and reduce illness and disability
Programs and activities:
Advance discovery for biomedical research
Facilitate use and re-use of biomedical data
Develop analytical methods and software
Enhance biomedical data science training
31. The Commons
Digital Object Compliance: FAIR
Attributes of digital objects in the Commons
Initial Phase
• Unique digital object identifiers of some type
• A minimal set of searchable metadata
• Physically available in a cloud based Commons provider
• Clear access rules (especially important for human subjects data)
• An entry (with metadata) in one or more indices
– Future Phases
• Standard, community based unique digital object identifiers
• Conform to community approved standard metadata for enhanced
searching
• Digital objects accessible via open standard APIs
• Are physically and logical available to the commons
32. For Academic Medical Centers What
Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and
value of the enterprise
Open collaborative science becomes of increasing
importance
The value of data and associated analytics becomes
of increasing value to scholarship
Current training content and modalities will not match
supply to demand
Balancing accessibility vs security becomes more
important yet more complex
34. BD2K and Clinical Data Science Research
BD2K Centers of Excellence for Big Data
Computing
BD2K Targeted Software Topics
Challenges and Prizes
1. NIH-NSF IDEAS Lab
• Promotes New Collaborations
• Round 1 on Precision Medicine (August 2015), round 2 in
planning.
2. BD2K-Wellcome Trust-HHMI Open Science Prize
• Prize competition announced October 20, 2015.
• Supports development of technology platforms and tools that
make open biomedical data more discoverable, accessible,
analyzable, and citable
35. BD2K Targeted Software Topics
Supports innovative analytical methods and software tools
that address critical current and emerging needs of the
biomedical research
2015 Topics (18 awards, U01s)
– Data Compression
– Data Provenance
– Data Visualization
– Data Wrangling
2016 Topics (U01s, under review)
– Data Privacy
– Data Repurposing
– Applying Metadata
– 2016: Crowdsourcing and interactive Digital Media
(UH2)
36. For Academic Medical Centers What
Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and
value of the enterprise
Open collaborative science becomes of increasing
importance
The value of data and associated analytics becomes
of increasing value to scholarship
Current training content and modalities will not match
supply to demand
Balancing accessibility vs security becomes more
important yet more complex
38. For Academic Medical Centers What
Are the Implications of Such a Future?
Opportunities exist to improve the efficiency and
value of the enterprise
Open collaborative science becomes of increasing
importance
The value of data and associated analytics becomes
of increasing value to scholarship
Current training content and modalities will not match
supply to demand
Balancing accessibility vs security becomes more
important yet more complex
39. The Problem Statement
Access to digital research objects
when, how, and by whom are
authorized to access them in
accordance of the wishes of the
owner and/or laws and policies which
define accessibility
40. The Landscape
The Holdren Memo
Revisions to the Common Rule
Meaningful Use
Centralized IRBs
….
42. “And that’s why we’re here today. Because something
called precision medicine … gives us one of the greatest
opportunities for new medical breakthroughs that we
have ever seen.”
President Barack Obama
January 30, 2015
43. An Example of That Promise:
Comorbidity Network for 6.2M Danes
Over 14.9 Years
Jensen et al 2014 Nat Comm 5:4022
44. I not only use all the brains
I have, but all I can borrow.
– Woodrow Wilson
46. NIHNIH……
Turning Discovery Into HealthTurning Discovery Into Health
philip.bourne@nih.gov
https://datascience.nih.gov/
http://www.ncbi.nlm.nih.gov/research/staff/bourne/
47. A Culture of Sharing
1999 20042003 2007 20142008
Research
Tools
Policy
NIH Data
Sharing Policy
Model
Organism
Policy
Genome-wide
Association
(GWAS) Policy
2012
NIH Public
Access Policy
(Publications)
Big Data to
Knowledge
(BD2K) Initiative
Genomic Data
Sharing (GDS)
Policy
Modernization of
NIH Clinical
Trials
White House
Initiative
(2013 “Holdren
Memo”)
48. A Culture of Sharing
1999 20042003 2007 20142008
Research
Tools
Policy
NIH Data
Sharing Policy
Model
Organism
Policy
Genome-wide
Association
(GWAS) Policy
2012
NIH Public
Access Policy
(Publications)
Big Data to
Knowledge
(BD2K) Initiative
Genomic Data
Sharing (GDS)
Policy
Modernization of
NIH Clinical
Trials
White House
Initiative
(2013 “Holdren
Memo”)
49. Modernizing NIH Clinical Trials
Activities:
The Need
NIH-Funded trials published within 100 months of
completion
Less than 50% published within 30 months of completion
BMJ 2012;344:d7292
51. Increasing Clinical Trial Transparency
Proposed November 2014; Final Spring 2016 (est.)
Notice of Proposed Rulemaking: Clinical Trials
Registration and Results Submission (FDAAA, Section
801)
– Further implements statutory requirements on private and
public sponsors to register; report results on phase 2, 3,
and 4 trials
– Includes drugs, biologics, and devices (except small
feasibility)
Draft NIH Policy on Clinical Trial Information
Dissemination
– Extends Section 801 requirements to all NIH-funded clinical
trials
– Includes phase 1 trials and trials of non-FDA regulated
interventions such as behavioral trials
53. BD2K Targeted Software Topics
Supports innovative analytical methods and software tools
that address critical current and emerging needs of the
biomedical research
2015 Topics (18 awards, U01s)
– Data Compression
– Data Provenance
– Data Visualization
– Data Wrangling
2016 Topics (U01s, under review)
– Data Privacy
– Data Repurposing
– Applying Metadata
– 2016: Crowdsourcing and interactive Digital Media
(UH2)
54. Why Revisions to the Common Rule
is not sufficiently risk-based, resulting in both over- and
under-regulation of research activities;,,
is not tailored to new and emerging areas of research,
including social and behavioral research and research
involving the collection and use of genetic information
Infectious Disease Society of America. Grinding to a halt:
The effects of the increasing regulatory burden on
research and quality improvement efforts.
may not effectively inform subjects of psychological,
informational, or privacy risks;,, ,
does not adequately account for the needs of a “learning”
health-care system for continual quality improvement;,,
and
provides insufficient mechanisms to ensure the
consistency, quality, and accountability of IRB decision-
making.,,,
Editor's Notes
“As biology’s first large-scale project, the HGP paved the way for numerous consortium-based research ventures. The NHGRI alone has been involved in launching more than 25 such projects since 2000. These have presented new challenges to biomedical research — demanding, for instance, that diverse groups from different countries and disciplines come together to share and analyse vast data sets.”
“The HGP changed the norms around data sharing in biomedical research.”
2013 White House Initiative: “Increasing Access to the Results of Federally Funded Scientific Research”
Updated to include numbers through September 2015.
From Dina Paltoo [10/6/15]: “The data in the first slide is for all of dbGaP 2007-2014. The information came from a version of what is on the GDS website (https://gds.nih.gov/19dataaccesscommitteereview_dbGaP.html) and in a Nature Genetics paper (http://www.nature.com/ng/journal/v46/n9/full/ng.3062.html), but results from information that we receive from NCBI.”
The NIH Public Access Policy implements Division F Section 217 of PL 111-8 (Omnibus Appropriations Act, 2009).
http://publicaccess.nih.gov/policy.htm
OSP’s summary:
The NIH Public Access Policy for publications has been in a requirement for all recipients of NIH funds since 2008. It implements Division G, Title II, Section 218 of PL 110-161 (Consolidated Appropriations Act, 2008). The NIH Public Access Policy ensures that the public has access to the published results of NIH-funded research. It requires scientists to submit final peer-reviewed journal manuscripts that arise from NIH funds to the digital archive PubMed Central (PMC) upon acceptance for publication. Scientists can also deposit papers through partnerships NIH has established with publishers. To help advance science and improve human health, the Policy requires that NIH supported papers are accessible to the public on PMC no later than 12 months after publication.
Updated by ADDS group 8/25/15
Short term: produce a searchable catalog of physical and virtual courses; Funding diversity awards to work with BD2K Centers; Expand IRP training started Jan 2015 e.g. Software carpentry and Train the trainers
Long term: evaluation
Photos: FC tweet; RK screen grab
16 million hospital inpatient events (24.5% of total), 35 million outpatient clinic events (53.6% of total) and 14 million emergency
department events (21.9% of total
Figure 2. Cumulative percentage of studies published in a peer reviewed biomedical journal indexed by Medline during 100 months after trial completion among all NIH funded clinical trials registered within ClinicalTrials.gov
Public benefits to clinical trials data-sharing (OSP):
Inform future research and research funding decisions
Mitigate bias (e.g., non publication of results, especially negative results)
Prevent duplication of unsafe trials
Meet ethical obligation to human subjects (i.e., that results inform science)
Increase access to data about marketed products
All contribute to public trust in clinical research
Source: Ross JS, Tse T, Zarin DA, Xu H, Zhou L, Krumholz HM. Publication of NIH funded trials registered in ClinicalTrials.gov: cross-sectional analysis. BMJ 2012;344:d7292.
Text updated by Sarah Carr [10/7/2015] – also changed order to feature NPRM before Draft NIH Policy.
Nearly 900 Comments received on PPRM: Many simply stating broad support
Final Rule expected Spring 2016
Section 801 of the Food and Drug Administration Amendments Act (FDAAA)