ODDT, user guide, latest version

1. Open Drug Discovery Teams
(ODDT)
USER GUIDE and FAQs – Beta version
v0.9.12
May 2013
Dr. Sean Ekins
Collaborations in Chemistry, A division of Collaborations in Communications, Inc.
Dr. Alex M. Clark
Molecular Materials Informatics, Inc.
Project Description
The Open Drug Discovery Teams (ODDT) project provides a free iOS mobile app
(https://itunes.apple.com/app/oddt/id517000016) primarily intended as a research topic
aggregator of open science data integrated from various sources on the internet. To
date this has focussed on rare and neglected diseases as well as chemistry topics.
Sponsorship
Currently the mobile app is sponsored by the Royal Society of Chemistry (RSC). The
content of the app is independent of this, and is consists entirely of open access articles
and data.
Fig 1. About screen showing RSC sponsorship

2. User Guide
The entry screen to the app displays the topics ranked by use (Fig. 2).
Fig 2. Entry screen
Tapping a topic image opens the topic browser, starting with the incoming page. Newly
added content is listed on the right (Fig. 3).
Can use multiple
Twitter accounts user
icon
Stats summary
About App
News feed
Topic panels

3. Fig 3. Incoming screen
Each tweet that has been introduced into the data collection is considered to be a
document. A document can be endorsed or disapproved (Fig. 4),
Fig 4. Endorsing or disaproving factoids
The way things work presently is that new documents are added to the corresponding
topic headings, and if they get a positive endorsement, they stick around forever, unless
they get voted back down. Documents with zero-or-less endorsements get removed
after a week, which means that the data collection loses all record of the entry. The
latest version of ODDT records the number of new documents added to each topic per
day, and coarse levels of summary information. These statistical aggregates are
retained forever, which means that it is possible to track activity levels. Fig 3. shows an
extra button in the bottom left corner (i) that is shown on the first page when viewing a
topic. Pressing it brings up a statistics box (Fig 5) which could be useful for following
content.
Click here to endorse or
disapprove
Click here to preview article
Incoming data is sorted by
time of addition
Click on image to
open it

4. .
Fig 5. Statistics box for tuberculosis incoming
The hyperlinks to factoids can be followed. The recent page shows factoids with one or
more vote (Fig. 6).
Fig 6. Recent screen
The content section shows the most popular voted content in rank order (Fig. 7).
Recent
factoids with a vote
count of +1 or
better

5. Fig 7. Content screen
Molecule thumbnails can be viewed by tapping on the link to view inline (Fig 8A) or the
preview panel can be tapped on to view the molecular data, as interpreted by the app
(Fig 8B).
A
Click on image to open
it
Ranked
content
Content is currently
anything with a vote
count of +1 or
better, sorted by
most popular first

6. B
Fig 8. Viewing molecules
Back on the entry screen, tapping the statistics summary button opens a listing of
endorsements, disapprovals, injections and retirements for each hashtag (Fig. 9).
Fig 9. Endorsements
The appearance of the ODDT app on the iPhone (or iPod) is overall similar, with less
screen space for showing topics (Fig. 10)

7. Fig 10. iPhone appearance
Intended use of App
Topics
The selection of topics included in ODDT is driven by our interest in rare and neglected
diseases as well as in various aspects of chemistry. To date we have the following
topics covered: Tuberculosis, Malaria, Chagas disease, Leishmaniasis, HIV/AIDS,
Huntingtons disease, Sanfilippo syndrome, Global Genes, Green Chemistry, Drug
repurposing, Giant Axonal Neuropathy, Hunter syndrome, Real time chemistry,
Hereditary Neuropathy Foundation, H5N1, Rare Disease report, Fibromuscular
Dysplasia, iCancer and ACS Chemical Information.
All of these subjects have high potential for positively impacting the research
environment using computational approaches and dissemination information via mobile
apps.
We have defined a number of rare disease and chemistry related topics, corresponding
to Twitter hashtags:
#tuberculosis
#malaria
#hivaids
#huntingtons
#sanfilipposyndrome
#leishmaniasis
#chagas
#rarediseases
#h5n1
#greenchemistry
#hhf4gan
#MPSII #huntersyndrome #hunterparents
#realtimechem

8. #HNF
#raredr
#fmdaware
#icancer
#ACSCINF
What can you do to use ODDT?
It's simple:
1. If you see an article of interest or want to say something about any of these
topics then all you need to do is simply add the hashtag above. If you blog about
any of these topics we should be able to capture them from the keywords above.
2. If you want the document to be saved just add the hashtag #oddt – this causes a
tweet to "auto-endorse" itself when it is added to the topic.
That’s it.
ODDT is chemistry aware
As shown in Figs 7 & 8, ODDT handles molecule structures and enables them to be
opened in MolSync or SAR Table. This enables ODDT to be used to create databases
of small molecules and associated data. You can use your imagination of how you could
create datasets for the diseases that interest you and view that data in ODDT.
Where to next?
As the software collection evolves and improves in its capabilities, data from open
science will be integrated and made usable within a common framework. Team
members will be able to borrow and reuse a growing collection of existing data.
Networking and collaboration features will be introduced, allowing researchers to post
incomplete or speculative data, while other researchers fill in missing details, and the
community as a whole can debate, contest or endorse data based on its quality. ODDT
may also contribute to the nascent development of “nanopublications”. The app could
also be used as a type of open lab notebook whereby individual researchers share links
(URLs) to content and the app aggregates these.

9. While this system is nominally intended for annotation of content that is fully accessible
via the original URL, it is potentially quite useful to annotate documents to which many
users do not have access, e.g. articles that are behind a journal pay wall. The collective
annotations of the users who have access to the article may provide enough information
to allow some users to gain insights that would otherwise only be accessible by
purchasing and reading the full article. It also has potential as a path to assemble
articles from scratch, in a fully open medium, and institute a kind of informal peer
review. In addition this functionality goes further towards an open notebook use case
scenario in which the scientist publishes their results whenever a suitable point is
reached, whether or not the results are sufficiently complete to warrant dissemination in
a traditional peer reviewed article.
NIH Data Sharing Plan – Why ODDT could be the solution
Helping collaborators with their NIH grants (R01, U19, SBIR, STTR, etc.), one is struck
by something that has to be done early in most cases yet is usually left till last. That is of
course the DATA SHARING PLAN. To use the words from the NIH website
(http://grants.nih.gov/grants/policy/data_sharing/data_sharing_guidance.htm):
“In NIH's view, all data should be considered for data sharing. Data should be made as
widely and freely available as possible while safeguarding the privacy of
participants, and protecting confidential and proprietary data. To facilitate data
sharing, investigators submitting a research application requesting $500,000 or more of
direct costs in any single year to NIH on or after October 1, 2003 are expected to
include a plan for sharing final research data for research purposes, or state why data
sharing is not possible.”
For many of you with small molecules (chemicals) and associated data (for example
structure activity data) why not tweet your data and its related topic hashtag in ODDT?
Perhaps this simple template below could be of use. Also feel free to contact us if you
want your topics added to the app so you can use ODDT to solve your molecule data
sharing needs!
Here is some text you could use in your grant
[DATA SHARING PLAN
We will share data generated during the course of this program. This will be
achieved through tweeting a link to the data and use of the Open Drug Discovery
Teams software program:
(http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3503260/pdf/minf0031-0585.pdf).
This software is a freely available mobile app for Apple devices and covers many
neglected and rare disease topics. Molecules and data are visible to anyone using the
app and the data is also downloadable in several formats to enable reuse. ]
FAQ

10. -What platforms does ODDT run on?
The user interface is provided in the form of an iOS app, which runs on iPhone, iPod
and iPad devices. It can be downloaded freely from the Apple iTunes AppStore:
http://itunes.apple.com/app/oddt/id517000016
Versions for other platforms, such as Android and generic web, are planned, but for the
moment we are focusing on the most popular app platform.
-How do I interact with the ODDT app?
When you download and run ODDT, you are able to browse and view any and all of the
content, which is free and open. To interact with the system, you should ideally activate
your Twitter account. You have to configure Twitter from within the iOS system, and
then when the app requests permission to have access, you need to say yes. Once this
is done, you can endorse, disapprove or comment on factoids from within the app. This
is done by emitting a tweet from your account. The app will never use your Twitter
account without making it abundantly clear what is about to happen, i.e. you need to
press a button labeled Tweet. Once you have connected to Twitter, you will also be
able to view the statistics that are associated with your account. If you do not have a
Twitter account, or do not wish to use it, you can vote on content anonymously, but your
contributions will have less gravity, and you will not have any acknowledgment of your
participation.
-When I tell my rare disease friends and associates about the app, can I suggest that
they offer to add their rare disease?
Later versions of the app will add more disease topics, but by all means get them to
send us the disease names to add, along with a suggested Twitter hashtag, and an
image to display on the main screen.
-What does the Epsilon icon on the main screen stand for?
This can be used for tracking your activity, based on your Twitter account, both overall
and broken down by topic. Each time you endorse or disapprove a factoid, your count
goes up. If you tweet out a link to new content, using one of the topic hashtags, and it
gets endorsed by you or something else, it counts as an "injection". A "retirement" is a
factoid that got deleted due to lack of endorsement, following the one week grace
period.
-Where do the topics come from?
The initial choice of diseases/research topics was based on our diverse interests. In
future app versions we plan on crowd sourcing the topics, as well as the content and
ranking.

11. -When I tweet something on my account that relates to topicX should I always tag it
with: #ODDT #topicX
When you emit a tweet that has a link and one of the topic hashtags, it is assimilated as
a document (internally described as a "factoid"). By default it starts with an endorsement
rating of 0, which means that it will eventually be retired, unless someone endorses it. If
you also add the #oddt hash tag, it will auto-endorse, which means that it starts out as
a factoid with a +1 ranking, and the endorsement corresponds to the Twitter account
you used to post it.
For example:
1. @researcher: Progress on a cure for #malaria http://malaria.org/cure.html
2. @researcher: Progress on a cure for #malaria http://malaria.org/cure.html
#oddt
The first tweet starts with an endorsement of 0, and will eventually be deleted unless
somebody endorses it. The second tweet is equivalent to the first tweet followed by
@researcher endorsing it.
-Are hashtags case-sensitive?
No. #greenchemistry, #GreenChemistry and #GREENCHEMISTRY are all the same,
but #Green_Chemistry is different.
-How do I get my rare/neglected community involved ?
To get your team involved just get them all tweeting the hashtag for the topic of interest.
Get the scientists to share links to papers or ideas they want to put out there openly. If
we can create a community then we can store the information for mining later and reuse
across diseases, e.g. anyone can tweet molecules, structure activity data, summaries of
papers, links to news etc.
Encourage them to download the app, too, but they don't need an iPhone/iPad to
participate.
-Whats the difference between Incoming, Recent and Content?
Incoming: all tweets that have been converted into factoids, sorted by latest first.
Suitable for browsing for new content worthy of endorsing.
Recent: factoids that currently have a positive ranking, i.e. there is at least one
endorsement, and the endorsements are not outweighed by disapprovals. Sorted by
time most recently updated.
Content: currently similar to Recent, except that highest ranking is shown first.

12. -What sort of documents should I endorse?
The ODDT project is about collating open data for research. Documents that have links
to content that resides behind paywalls should probably not be endorsed unless there is
a reasonably detailed abstract or synoposis, or if the purpose is to associate links with
helpful metadata, e.g. chemical structures, or useful comments. For the disease-related
topics, endorsed documents should have direct or indirect relevance toward finding a
cure, such as the ongoing search for a drug, vaccine, antibody, gene-therapy, etc.
-How is the Open Drug Discovery Teams project funded?
Currently it isn't, other than limited sponsorship. The beta version was designed and
built by Sean Ekins and Alex M. Clark. The server is being temporarily hosted on
molsync.com. We are interested in exploring a variety of different funding opportunities.
References, posters and slides on ODDT
Ekins S, Clark AM and Williams AJ, Open Drug Discovery Teams: A Chemistry Mobile
App for Collaboration, Mol Informatics, 31: 585-597, 2012.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3503260/pdf/minf0031-0585.pdf
Clark AM, Williams AJ and Ekins S, Cheminformatics workflows using mobile apps,
Chem-Bio Informatics Journal, 13: 1-18 2013.
https://www.jstage.jst.go.jp/article/cbij/13/0/13_1/_pdf
Ekins S, Clark AM and Williams AJ, Incorporating Green Chemistry Concepts into
Mobile Applications and their potential uses, ACS Sustain Chem Eng, 1. 8-13, 2013.
http://pubs.acs.org/doi/pdf/10.1021/sc3000509
Ekins S, Waller CL, Bradley MP, Clark AM and Williams AJ, Four disruptive strategies
for removing drug discovery bottlenecks, Drug Discovery Today, 18: 265-271, 2013.
http://www.molmatinf.com/oddt.html
http://www.scimobileapps.com/index.php?title=Open_Drug_Discovery_Teams

13. http://www.slideshare.net/ekinssean/oddt-open-drug-discovery-teams-for-collaboration
http://figshare.com/articles/search?q=open+drug+discovery+teams&quick=1&x=0&y=0
Please contact us for further details at: aclark@molmatinf.com and
ekinssean@yahoo.com. You can learn more about the ODDT app at:
http://www.scimobileapps.com/index.php?title=Open_Drug_Discovery_Teams
And frequent blogs at http://www.collabchem.com and http://cheminf20.org.
Acknowledgments
We thank the Royal Society of Chemistry (RSC) for sponsoring the app. We
acknowledge all those who have provided ideas for topics or whose feedback has been
incorporated into the app. Photo for tattoo for Jonah’s Just Begun (Sanfilippo
Syndrome) courtesy of Jill Wood www.jonahsjustbegun.org