ODDT beta-user guide-v0.9.12amc

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

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

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 disapproveClick here to preview ar-ticle

Incoming data is sorted by time of addition

Click on image to open it

.

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

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 con-tent

Content is cur-rently anything with a votecount of +1 or better, sorted by most popular first

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)

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

#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.

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

-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 ac-count 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 ac-count, or do not wish to use it, you can vote on content anonymously, but your contribu-tions will have less gravity, and you will not have any acknowledgment of your participa-tion.

-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 im-age 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 pe-riod.

-Where do the topics come from?

The initial choice of diseases/research topics was based on our diverse interests. In fu-ture app versions we plan on crowd sourcing the topics, as well as the content and ranking.

-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 partic-ipate.

-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.

-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 Mo-bile 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

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: [email protected] and [email protected]. 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