Blockchain in Health Research 2019 was the 2nd annual summit hosted at Georgetown University on 27 Apr 2019 by Sean Manion, Science Distributed and Gilles Hilary, Georgetown University.

1. Blockchain in Health
Research
Sean T Manion, PhD
Science Distributed; Blockchain in Healthcare Global
Georgetown University, 27 Apr 2019

2. Agenda
• Introduction: Blockchain for Health Research – Sean Manion (Science Distributed; BiHG)
• HHS Accelerate Pilot – Video
• State of Blockchain in Health/Research – Sean Manion
• Presentation: HIPAA Readiness & Research – Heather Flannery (ConsenSys Health; BiHG)
• Panel: Regulatory & Readiness – Heather Flannery, Maureen Murat (Crowdie Advisors), Kate Gofman (AstraZeneca); moderated by
Sean Manion
• Blockchain Basics & Future Integration – Lauren Long, (Science Distributed); “The Blockchain Future and the Self” – Nicole Tay
(Science Distributed)
• Blockchain Platforms – Maria Esquela (Enable Alliance) Hyperledger Overview, Robert Miller (ConsenSys Health) Ethereum
Overview
• Presentation: Patient-centric Outcomes Research – Jason Goldwater (Atlas Research)
• Panel: Patient-centric to Public Health – Jason Goldwater, Tiffany Gray (DC Dept of Health; BiHG), Jason Cross (Rymedi); moderated
by Gilles Hilary
• Workshop: Blockchain for a TBI Research Network – Reem El Seed, Sean Manion
• Networking Social at The Tombs (Georgetown)
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
2

3. What is Science?
• Science is the systematic study of the
natural world
• Research is the application of the
scientific process: Observe,
Hypothesize, Test, Conclude
• Development is the application of
basic scientific findings in specific
areas like engineering (physical) and
medicine (health)
• Research & Development (R&D) is a
$2.5 Trillion annual industry
worldwide
• $150 Billion Health Science Research
annually in the US
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
3

4. Reasons for the problems with Science
• Scaled beyond optimal function in
traditional model
• Siloed across multiple systems
• Trust breakdown; limited sharing
• Misaligned incentives; publishing
• Quality decline with expansion of
peer-reviewed journals
• Decreasing return on investment
• HUGE upside in application of
blockchain and tokenization
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
4

5. Distributed Science Value Proposition
• Better Science (for Scientists)
• Problem: Reproducibility Issues; 20% of U.S. health science research can’t be replicated/reproduced*
• Solution: Improved reproducibility through transparency and immutable audit trail for research data; better
quality data from standardization; improved materials; increased meta-analysis capabilities
• Cheaper Research (for Funders)
• Problem: Expensive; decreasing ROI; $30 billion in U.S. health science on non-replicable research*
• Solution: Increased return on investment for research dollars spent; reduced data management costs through
blockchain/smart contracts, amplified with machine learning/AI; cheaper administration
• Faster Miracles (for Everyone)
• Problem: 17 years from bench to bedside; 2-5 years on administrative processes (my estimate)**
• Solution: Faster time from idea to treatment; improved outcomes with accelerated research and higher quality
data; improved tracking of individual contribution allowing for expanded permissioned access of data to more
researchers; faster administrative processes (e.g. IRB, grant review)
* “Economics of reproducibility in Preclinical Research” Freedman et al, PLoS 13(6) e1002165, 2015
** “Enhancing Federal Research: Traumatic Brain Injury & Blockchain Technology - Part 1.5, The Why.” Manion, Feb 2018 https://www.linkedin.com/pulse/enhancing-federal-research-
traumatic-brain-injury-part-sean-manion-1/
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
5

6. CAUTION - Blockchain is not Hot Sauce
• “Blockchain isn’t hot sauce, you
can’t just put that s*!t on
everything” – Samson Williams
• Blockchain can be overkill in some
applications
• Blockchain won’t solve problems
with humans
• OTOH: If you can do it with
existing technology, why aren’t
you?
• Blockchain changes the value
proposition
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
6

7. Blockchain/Distributed Ledger Technology (DLT)
• Blockchain is a
distributed ledger of
data transactions,
exchanges, or events.
• Allows a distributed
network to automatically
maintain a single,
virtually immutable
record based on an
agreed upon governance
protocol for consensus.
• Can be public,
permissioned, or private.
Incentives and
consensus proofs will
vary.
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
7
Example of a financial application of blockchain (By B140970324 - Wikimedia Commons)
More info: hyperledger.org/ (Hyperledger is the blockchain arm of the Linux foundation)

8. Blockchain Advantages
• Trust – enables secure identity & information
• Tamper-resistance – hard to manipulate
• Transparency – eminently auditable
• Accessibility – permissioned access
• Automation – via smart contract and AI
8
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019

9. Blockchain Challenges
• Integrating blockchain within existing system
• Higher value by integrating end to end and avoiding blockchain silos
• Majority/monopoly risk: A majority (not 100%) of ‘nodes’ can confirm that a transaction is valid i.e.
matches the blockchain history - the new transaction will be approved and added to the chain.
• Need to develop effective governance models among stakeholders
• Blockchain requires new rules of participation and operation, new procedures for decision making and new
de-centralized governance framework
• Regulatory development and enforcement
• File size limitations, mitigating solutions available (e.g. side chains)
• Conflicting commercial interests need to be balanced via technology transfer agreements
• Lack of maturity of blockchain technology
• While technology has constraints, adopting a specific approach helps to selectively implement
• Experimental and currently slow because of verifying contracts and cross--‐contract communication
• Nascent recognition as legal documentation
• Competing platforms
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Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019

10. Data
Collection
Data
Management
Data
Queries
Analysis Findings
Negative
Findings
Meta-
Analysis
Outside
Network
Findings
Other Meta-
Analyses
Clinical
Practice
Guidelines
Research Network Pathway – Current State
Network Site
Data Core
Publication
Systematic Review
Clinical Practice
Guideline
• Site data to central data core
• Data management at data core
• Sites send queries to data core
• Data core sends requested data
• Sites perform all data analyses
• Negative findings not reported

11. Data
Collection
Data
Management
Data
Queries
Analysis Findings
Negative
Findings
Meta-
Analysis
Outside
Network
Findings
Outside Meta-
Analyses
Clinical
Practice
Guidelines
Research Network Pathway – Future State
Network Site
Data Cloud
Publication
Systematic Review
Clinical Practice
Guideline
• Data stored locally and/or on cloud
• Distributed ledger of meta-data, usage
• Automated data management via smart contract
• Peer-to-peer permissioned sharing as queried
• Transparent, auditable analyses; increased replicability
• Success leads to more partners; fewer outside studies
• Background meta-analyses; replication of findings
Background meta-analyses

12. Blockchain Healthcare Ecosystem
Key Use Cases Areas (Examples):
• Admin, financial (Health & Human Services)
• Provider identity (Professional Credential
Exchange; Synaptic Health Alliance)
• Medical devices (Spiritus Partners, Napier
Edinburgh University, Scotland NHS)
• Pharma supply chain (Rymedi; Remedichain)
• Clinical trials (Boehringer Ingelheim, IBM)
• Prototype of running clinical trials in an untrustworthy
environment using blockchain. Wong et al. Nature
Communications volume 10, Article: 917 (2019)
• Publishing (Ledger journal, Blockchain in
Healthcare Today, Frontiers, Springer Nature)
• Clinical Support Tools (Elsevier, Diagnosis
Protocol)
• Electronic health record (Amsys; Rymedi)
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
12

13. HHS Moves Ahead on Blockchain for Acquisition
Modernization (Fed Tech Magazine, 17 Jan 2019)
• Blockchain as an infrastructure
layer across legacy systems with a
microservice strategy
• Robotic process automation and
machine learning for analysis
• Allows real time peer-to-peer data
sharing by 20,000 contract buyers
• Strategically sourced purchasing
info in seconds instead of months
• Live in Dec 2018; will impact
$25Billion in HHS purchasing;
expected 800-1000% ROI annually
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
13
“…we decentralized the execution of that data,
leveraging a microservices strategy, to actually empower
the acquisition workforce.”
- Jose Arrieta, HHS head of acquisition

14. Blockchain Healthcare Ecosystem
Key Use Cases Areas (Examples):
• Admin, financial (Health & Human Services)
• Provider identity (Professional Credential
Exchange; Synaptic Health Alliance)
• Medical devices (Spiritus Partners, Napier
Edinburgh University, Scotland NHS)
• Pharma supply chain (Rymedi; Remedichain)
• Clinical trials (Boehringer Ingelheim, IBM)
• Prototype of running clinical trials in an untrustworthy
environment using blockchain. Wong et al. Nature
Communications volume 10, Article: 917 (2019)
• Publishing (Ledger journal, Blockchain in
Healthcare Today, Frontiers, Springer Nature)
• Clinical Support Tools (Elsevier, Diagnosis
Protocol)
• Electronic health record (Amsys; Rymedi)
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
14

15. Blockchain for Research Ecosystem
• Small number of projects (<5% of
blockchain health or 0.1% overall)
• Only a handful focused primarily
on science
• Too broad; one-size doesn’t fit all
• No differentiation between
scientific disciplines & phases
• Insufficient approach to non-
monetary incentive systems
• Ex: 64 million hours of volunteer
peer-review each year can not be
monetized w/o integrity issues
15
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019

16. What are the
pre-publication
presentations?
What is the
quality or
confidence level?
How is feedback
captured?
Gray lit?
What are the
comments?
Are there
objective
criteria?
Crowd-sourced
peer review?
7. Publish &
Present
Are analyses tied
to original
hypotheses?
Are analyses
outlined in
protocol?
Justification of
new analyses?
Record of
attempted
analyses?
Statistical power?
Lit basis of
interpretation?
Quality of refs?
Replicable?
Retractions?
6. Analyze &
Interpret
What are the
data standards?
Will it be
mergeable with
other studies?
What are the
quality assurance
steps?
Is PHI secure?
Is there existing
data that can be
used?
How accessible is
the data?
What is the ROI
for the data?
5. Collect Data
Can parts of this
process be
automated?
Will that be
faster and more
reliable for
researchers and
regulator?
Can multiple IRBs
be aligned?
Can parts of IRB
review be
crowdsourced?
Can audits be
easier?
4. Regulatory
Approval
Where are
funds?
Does my plan
match
programmatic
need?
Have I applied
here before?
Why am I filling
in all this
information
again?
How is the
money being
tracked?
3. Get Funding
What methods
are available?
What variations
have been
developed?
Are skilled
collaborators
available?
Where?
Are other
resources (i.e.
space,
equipment)
available?
2. Plan research
What hypotheses
have already
been tested?
By whom?
When?
What happened?
What was the
approach?
What was the
result?
Current status?
1. Form Hypotheses
Distributed Science Opportunities?
• Where can things be improved in each area?
• Can blockchain/DLT facilitate and/or incentivize?
• What is the cost/benefit of implementation?
• If it can be achieved w/o blockchain/DLT, why isn’t it?
Questions to consider across the steps in science:
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
16

17. Farm to Table, Bench to Bedside: Health Research as Data Supply Chain
from “Advancing Health Research with Blockchain” (Manion) in HIMSS text book
Blockchain in Healthcare: Innovations that Empower Patients, Connect Professionals and Improve Care
Sean T Manion, PhD - Science Distributed seanmanion@sciencedistributed.com - Georgetown, Apr 2019
Seed
•Crop
•Strain
•Soil
Farm
•Plant
•Grow
•Harvest
Processing
•Cleaning
•Preparation
•Packaging
Distribution
•To consumer or
retail
•Next stage
processing
Table
•Restaurant
•Retail/Home
cooking
Idea
•Hypothesis
•Design
•Funding
Bench
•Research
execution
•Data Collection
•Basic to Clinical
Analysis
•Hypothesis
testing
•Statistics
•Interpretation
Dissemination
•Conference
presentation
•Peer-review
publication
Bedside
•Knowledge
translation
•Clinical practice
guidelines
Repeats several times
Food Supply Chain
• Linear progression
• Timeline: < 30 days*
• Key variables: type,
quantity, quality,
variables (e.g. temp)
Health Research Data
Supply Chain
• Parallel progression
• Timeline: 2-5yrs (x
multiple repeats)
• Key Variables: design,
methodology, patient
demographics research
contribution, statistical
approach, outcomes
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18. Blockchain, Cloud, & AI
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
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Photography by Lucy Hewett

19. More Information
• Blockchain in Healthcare Global
www.blockchaininhealthcare.global
• HIMSS Blockchain Task Force
www.himss.org/library/blockchain-healthcare
• HIMSS Text Book:
Blockchain in Healthcare: Innovations that Empower Patients, Connect Professionals and Improve Care
(1st Edition, 2019 by CRC Press, authors/editors: Metcalf, Bass, Hooper, Cahana, Dhillon + 48 additional)
Coming soon: Blockchain for Health Research: Curing Science and Transforming Medicine
By Sean Manion & Yael Bizouati-Kennedy (Taylor & Francis, late 2019/early 2020)
• IEEE Standards Association – Blockchain in Health and Life Sciences
www.standards.ieee.org/project/2418_6.html
• Frontiers special journal issue, “Blockchain for Distributed Research” –
Call for papers (22 Jul 2019); Publication (open access) in Fall 2019
www.frontiersin.org/research-topics/9698/blockchain-for-distributed-research
Sean T Manion, PhD - Science Distributed
seanmanion@sciencedistributed.com - Georgetown, Apr 2019
19

20. Science faces challenges from funding to reproducibility. Blockchain technology is maturing
beyond its financial origins at the right time to bring more signal and less noise to
science. The good it can do for science ranges from administrative streamlining or
accelerated grant and regulatory review to improved quality, transparency, and contribution
tracking in research and science publications.
From Astronomy to Genetics, Neuroscience to Public Health, experts in every area are
needed to help determine how blockchain may help their field, in order to realize the value it
can bring to each branch of science.
We are looking for manuscripts describing both empirical experience as well as theoretical
applications to any field from the experts and the technology partners that may assist.
Descriptions of how blockchain can be applied to science, the good it will do for advancing
knowledge, and the value it can bring is the main focus of this research topic. Information on
the challenges in each field is encouraged: limitations on data standards, complexity of data
and workflows, along with regulatory, administrative, cybersecurity, and other hurdles.
Submission Deadline: 22 July 2019
Webpage: https://www.frontiersin.org/research-topics/9698/
E-Mail: blockchain@frontiersin.org

21. The first peer-reviewed academic journal on blockchain from a
global academic publisher, Frontiers in Blockchain aims to unite both
academia and industry to drive blockchain research and innovation.
We offer:
• A fully Open Access platform for your research
• An average Peer Review time of 90 days from submission to final
decision
• Many opportunities to collaborate with fellow experts
• 7 Specialty Sections focusing on:
- Smart Contracts - Financial Blockchain
- Blockchain Technologies - Non-Financial Blockchain
- Blockchain for Good - Fourth Industrial Revolution
…and coming soon, Blockchain for Science
90
DAYS
REVIEW
366
EDITORS 36
COUNTRIES
18
ARTICLE
COLLECTIONS
blockchain@frontiersin.orghttps://www.frontiersin.org/journals/blockchain#