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Collaborative Computational Technologies for Biomedical
Research: An Enabler of More Open Drug Discovery
Sean Ekins, Ph.D., D.Sc.
Collaborations in Chemistry,
Fuquay-Varina, NC.
Antony J. Williams, Ph.D.,
Royal Society of Chemistry,
Wake Forest, NC.
In the long history of human kind (and animal kind, too) those who have learned
to collaborate and improvise most effectively have prevailed.
Charles Darwin
Open Drug Discovery • Pharma Companies spend >$50 billion annually on
R&D
• How much historical data/knowledge/information is in
the public domain? And where is it?
• How much generated data is truly competitive?
• Pre-competitive and public domain data could deliver
high value to drug discovery
– Data mining
– Model-building
– Integrating into in-house and online systems
There has to be a better way?
How to do
it better?
Openness
What can we
do with
software to
facilitate it ?
Make it Open
The future is more
collaborative and Open
We have tools
but need
integration
Open interfaces
• Groups involved traverse the spectrum from pharma, academia, not for
profit and government
• More free, open technologies to enable biomedical research
• Precompetitive organizations, consortia..
A Starting Point For a New Era?
Open InnovationOpen innovation is a paradigm that assumes that firms can and should use external ideas as well as
internal ideas, and internal and external paths to market, as the firms look to
advance their technology
Chesbrough, H.W. (2003).
Open Innovation: The new imperative for creating and profiting from technology.
Boston: Harvard Business School Press, p. xxiv
Collaborative InnovationA strategy in which groups partner to create a product - drive the efficient allocation of R&D
resources. Collaborating with outsiders-including customers, vendors and even competitors-a
company is able to import lower-cost, higher-quality ideas from the best sources in the world.
Open SourceWhile open source and open innovation might conflict on patent issues,
they are not mutually exclusive, as participating companies can donate their patents
to an independent organization, put them in a common pool or grant
unlimited license use to anybody. Hence some open source initiatives
can merge the two concepts
Some Definitions
• All pharmas have similar high level business processes
efforts
• Is there any competitive advantage?
• in informatics?
• www.pistoiaalliance.org - - companies and vendors
• Agree on the precompetitive space
• Shift from software to services
• e.g. sequence services
• Sequence Squeeze Competition for Next-gen sequencing
compression algorithm $15K prize
Major collaborative grants in EU: Framework, Innovative Medicines Initiative…NIH
moving in same direction
Cross continent collaboration CROs in China, India etc – Pharma’s in US / Europe
More industry – academia collaboration and ‘not invented here’ a thing of the past
More effort to go after rare and neglected diseases -Globalization and connectivity
of scientists will be key –
Current pace of change in pharma may not be enough.
Need to rethink how we use all technologies & resources…
Collaboration and Openness is Key
Improved Quality of data is essential
Open PHACTS : partnership between European Community and EFPIA
Freely accessible for knowledge discovery and verification.
Data on small molecules
Pharmacological profiles
ADMET data
Biological targets and pathways
Proprietary and public data sources.
Where Should We Draw The Precompetitive Boundary
Usually on tools
and
technologies for
early drug
discovery
Jackie Hunter has suggested
after Target ID and Validation
Chapter 4 of book..
Why not make everything upto
development precompetitive
e.g. share ADME/Tox data so
everyone understands failures for
a class of compounds?
Share ADME/Tox Models
Gupta RR, et al., Drug Metab Dispos,
38: 2083-2090, 2010
Could All Pharmas Share Their Data and Models?
Pfizer
Merck
GSK
Novartis
Lilly
BMS
Lundbeck
Allergan Bayer
AZ
Roche BI
Merk KGaA
Could combining
models give
greater coverage
of ADME/ Tox
chemistry space
and improve
predictions?
Data, Models and Software Becoming More Accessible- Free, Precompetitive and Open Efforts - Collaboration
Inside Company
Collaborators
Inside Academia
Collaborators
Molecules, Models, Data Molecules, Models, Data
Inside Foundation
Collaborators
Molecules, Models, Data
Inside Government
Collaborators
Molecules, Models, Data
IP
IP
IP
IP
Shared
IP
Collaborative platform/sBunin & Ekins DDT 16: 643-645, 2011
A Complex Ecosystem Of Collaborations: A New Business Model
Example ; Collaborative Drug Discovery Platform
• CDD Vault – Secure web-based place for private data – private by default
• CDD Collaborate – Selectively share subsets of data
• CDD Public –public data sets –
• Unique to CDD – simultaneously query your private data, collaborators’ data, & public data, Easy GUI
www.collaborativedrug.com
Tools for Open Science
• Blogs
• Wikis
• Databases
• Journals
• What about Twitter, Facebook, could these be
used for social collaboration, science?
Tools for Open Science
Name Website Function
myExperiment http://www.myexperiment.org/ Workflows, communities
DIYbio http://diybio.org/ Community for do it yourself biologists
Protocol online http://protocol-online.org/ Biology protocols
Open wetware http://openwetware.org/wiki/Main_Page Materials, protocols and resources
Open Notebook science
challenge
http://onschallenge.wikispaces.com/ Crowdsourced science challenge – initially
on solubility measurement
UsefulChem project http://usefulchem.wikispaces.com/ An example of one scientist’s open
notebook
Laboratree http://laboratree.org/pages/home Science networking site
Science Commons http://sciencecommons.org/ Strategies and tools faster, efficient web-
Tools for Open Science The Evolution of the e-lab Notebook
• Blogs - Will we see a shift as more scientists blog about
work?
• Wikis – creating more of these as a way to track work and
build databases
• Apps become e-lab notebooks
• Journals – more people create their own
• Combine all content = collaborative lab notebook
Scientists will use apps for science Apps connect to databases for content
Mobile Apps for Drug Discovery: Could They Facilitate Open Science?
Williams et al Chapter 28
Could pharma’s biggest
failing have been giving
everyone a PC?
Get the scientist out of their
office and back to the bench
Appify data – make
cheminformatics tools useful
Tablet better than phone?
Williams et al DDT 16:928-939, 2011
Open Drug Discovery Teams
A free app to collate social media
Saves hashtags on a topic
Chemistry aware
A new way to share links & info.
Access open knowledge
An alternative lab notebook
http://slidesha.re/GzVSPr
See Pfizer open innovation & rare disease vision
http://dl.dropbox.com/u/14511423/VRU.pptx
Crowdsourcing: power law for ChemSpider
• How can we engage more contributors?
• ChemSpider Rank-
frequency plot
• Curation a = 1.4
• Depositions a = 1.5
• Slope is a measure of
contribution by whom
• Driven by v. active
minority
• Power laws vary by
crowdsourcing type
Robin Spencer in Chapter 28
Drug Discovery Network
Could our Pharma R&D look like this
Massive collaboration networks – software
enabled. We are in “Generation App”.
Crowdsourcing will have a role in R&D. Drug
discovery possible by anyone with “app access”
Could apps improve crowdsourcing?
Ekins & Williams, Pharm Res, 27: 393-395, 2010.
Getting Chemists and Biologists to Collaborate?
• “Need them to be open minded for research direction”
• “A collaborator is not a means to their ends”
• “In a good collaboration “hypotheses” are viewed as temporary
starting points”
• “Take ownership and responsibility for research success and failure”
Victor Hruby – Chapter 7
• Ethics: effective communication, clear goals, shared and defined
responsibility for writing and publishing
McGowan et al Chapter 8
• Collaboration can be hampered by materials transfer agreements and
patents – need to standardize – use creative commons
• Wilbanks Chapter 9
The Need for Standards for Collaborative Technologies
• 1270 – standard size for bread loaves – Freiberg Germany
• We need standards for assay descriptions, structure representation, how data is
stored, data cleaning etc.
• 2012 – standard for collaborative software?
• Ekins et al Chapter 13
Standard name Website
The Open Biological and Biomedical Ontologies (OBO) http://www.obofoundry.org/
The Ontology for Biomedical Investigators (OBI) http://obi-ontology.org/page/Main_Page
The Functional Genomics Data Society (MGED) http://www.mged.org/index.html
Minimum Information About a Microarray Experiment (MIAME) http://www.mged.org/Workgroups/MIAME/miame.html
The Minimum Information About a Bioactive Entity (MIABE) http://www.psidev.info/index.php?q=node/394
Minimum Information for Biological and Biomedical Investigators (MIBBI) http://www.mibbi.org/index.php/MIBBI_portal
Minimum Information for Publication of real time QT-PCR data (MIQE) http://www.gene-quantification.de/miqe-press.html
Open Science: What is needed?
• Open tools – need good validation studies many
developed with no support
• Support those scientists making data open (e.g. J.C.
Bradley)
• Support companies/groups promoting software for data
sharing
• Lobby grant providers to require that grantees deposit
data in public domain. Make data quality a criterion for
funding
• Engage the community to help create what they want.
Rewards and recognition? - MORE collaboration can
benefit us all
• Give those that have been let go by industry another
route to discovery – materials, drugs, technologies
Open
Science
needs
You!
Open Science: The Landscape• Currently few scientists practice ONS – so we need to change this
• Missing an open database system for storing/sharing data globally
• Commercial versions exist
• Currently few Open journals – cost may be prohibitive to many
• How do we measure scientists contributions via Open Science
• Need to educate the next generation on collaboration and
collaborative software
• BIG DATA is on the way
Disruptive Strategy #1: NIH mandates
minimum data quality standards, strict timeline
for data submission, and open accessibility for
all data generated by publicly funded research.
Disruptive Strategy #2: Reboot the industry by
extending the notion of “pre-competitive”
collaboration to encompass later stages of
research to allow public private partnerships to
flourish. The role of large pharma is late stage
development and branding.
Disruptive Strategy #3: FDA takes a proactive
role in making available relevant clinical data
that will help to bridge the valley of death.
Ekins et al: Submitted 2012
Three Disruptive Strategies for Removing Drug Discovery Bottlenecks
Wikipedia vs Encyclopedia
Could open drug discovery
disrupt traditional drug
discovery?
Wikipedia
Fund and find the right
researchers with
CollaborationFinder
Ensure quality of molecule structures
and data in ChemSpider
Selectively share with collaborators to
retain IP with CDDOpenly share findings with
other researchers and public in
ODDT Ekins et al: Submitted 2012
Collaborative Informatics Technologies Could Disrupt Pharmaceutical Research
Maybe Darwin would have been a biohacker, citizen scientist, open scientist, collaborative
scientist…
Would he have been able to disrupt drug discovery?
Book chapter Authors
Santosh Adayikkoth, Renée JG Arnold, O.K. Baek, Anshu
Bhardwaj, Alpheus Bingham, Jean-Claude Bradley, Samir
K. Brahmachari, Vincent Breton, A. Bunin, Christine
Chichester, Ramesh V. Durvasula, Gabriela Cohen-Freue,
Rajarshi Guha, Brian D. Zhiyu He, David Hill., Moses M.
Hohman, Zsuzsanna Hollander, Victor J. Hruby, Jackie
Hunter, Maggie A.Z. Hupcey, Steve Koch, George A.
Komatsoulis, Falko Kuester, Andrew S.I.D Lang., Robert
Porter Lynch, Lydia Maigne, Shawnmarie Mayrand-Chung,
Garrett J. McGowan, Matthew K. McGowan, Richard J.
McGowan, Barend Mons, Mark A. Musen. Cameron
Neylon, Christina K. Pikas, Kevin Ponto, Brian Pratt, Nick
Lynch, David Sarramia, Vinod Scaria, Stephan Schürer,
Jeff Shrager, Robin W. Spencer, Ola Spjuth, Sándor
Szalma, Keith Taylor, Marty Tenenbaum, Zakir Thomas,
Tania Tudorache, Michael Travers, Chris L. Waller, John
Wilbanks, Egon Willighagen, Edward D. Zanders
&
Mary P. Bradley, Alex M. Clark
Thank You
ScientistsDB Logo by Kalliopi Monoyios
Email: [email protected]
Twitter: collabchem
Blog: http://www.collabchem.com/
Slideshare: http://www.slideshare.net/ekinssean
Email: [email protected]
Twitter: ChemConnector
Blog: www.chemconnector.com
Slideshare: www.slideshare.net/AntonyWilliams
Many thanks to our collaborators