Innovation

Innovation

Q&A with Barry Bunin, CEO of Collaborative Drug Discovery

The following is an interview conducted by Science Exchange with Barry Bunin, CEO of Collaborative Drug Discovery (CDD). You can find more info on CDD at: https://www.collaborativedrug.com/

Collaborative Drug Discovery Logo

Q: What prompted you to create CDD?

A: First we saw a need to broadly empower scientists with self-explanatory technologies for scientific data and decision management.   I especially noticed in academia there were brilliant scientists lacking the infrastructure and software tools that industry has to accelerate research and development.

Second we (we because CDD was a spinout of Eli Lilly where I (Barry) was an Entrepreneur in Residence working in Alpheus Bingham’s group) foresaw a time when due to the economics of specialization, more efficient drug discovery would demand a more collaborative model and mechanism to advance drugs.   Ergo the name Collaborative Drug Discovery (CDD), we needed an internet inspired platform to securely collaborate between the entire ecosystem of academic, startup, CRO, foundation, government, biotech and of course pharma researchers.  On a personal note, I wanted the platform to be equally applicable to Neglected and Commercial drug discovery after visiting some poorer countries.

While incubated within Lilly, we first called the “experiment” ChemBot, and considered it more a marketplace for data, models, and services (the later somewhat like Science Exchange).

It has evolved into a leading platform for handling scientific data privately, collaboratively and/or publicly.  The majority of researchers, of course, work in the private, secure modes, ergo the CDD Vault® emerged as the most descriptive name, to consistently emphasize the security even on the subconscious level, for our Collaborative Platform.  The other company we considering spinning out was focused on single drug opportunities, I felt CDD would have the maximum benefit for more scientists and projects – and it does!

Q: Who did you feel would use CDD when you started? Who is your intended customer base?

A:   It is ironic, because although it was a spin out of big pharma, our first customers were all academics (initially at UCSF).   One of the reasons Lilly invested and spun CDD out of Lilly as an independent company (now for over 8 years), was that we demonstrated there was a marketplace, even working solely with academic labs.   We did this very quickly, while developing the earliest prototypes.

I wanted to work on Neglected Diseases from day one.   This was very aligned with UCSF and especially the McKerrow Group, which was our first large customer.   The nice thing is a molecule is a molecule, an IC50 is an IC50, so I like to say we are target and therapeutic area “agnostic”.

Since we’ve iterated, improved and continuously optimized the product, the community, and the collaborations.   Today we work with all types of groups, from the most privacy sensitive big pharma to the smallest group aka an individual (one person startups bootstrapping).

Q: What are the specific service offerings and features of CDD?

A:  CDD offers simpler, easier to use software for chemical and biological data.   It is a robust solution for collaborating around data and people with capabilities for chemical registration, IC50s, plate/well data, mining, saved searches, shared collections and more.

One of the neat things about CDD as a web-based platform is it is always getting better at an accelerated rate as a function of our number of paying users (>32,000 logins last year), so the progress can be seen in a very non-marketing real way in the release notes post login at the bottom of the page.   It looks like an Art Gallery with all the images of scatterplots, heatmaps, curves, etc – I encourage folks to log in and check it out to judge for themselves (see: http://web.collaborativedrug.com/pages/signup).

There is also a beautiful Support Forum under help at the top that Anna created for those who want to go deep.   Yet even for the first time users, it is intuitive enough for both experts and novices to get value from the very first login.  That is the real art, to keep the complexity simple and useful.   Domain-wise, we started with small molecules, but we now have configurable terminology (“Set your own terminology”), so researchers can change molecules for antibodies or proteins or genes or sandwiches (if that is your research area).  Antibody Drug Conjugates (ADCs) is a new area where researchers are using CDD today, for example.

For all scientific domains, CDD has differentiating collaborative capabilities that allow researchers to get more insight and more progress out of the same headcount for existing or new collaborations.

Our sweet spot is researchers trying to do more with less (and who isn’t) as well as those open to the power of collaboration.  CDD has been a bit ahead of the curve on collaboration, but the mainstream market is starting to appreciate this is a powerful, practical, effective approach – and not all about holding hands and saying “kumbaya my lord”.   Collaboration is about understanding the collaborative workflow deeply around data and people to make it natural and more efficient, this allows one scientist who used to be able to deal with 1-2 projects in the same timeframe to gracefully consider 10-20 project, with the same amount or only double the work.  Management 101 is leveraging the best ideas in others’ brains.

We have a collaborative business model too, these are true collaborations where CDD really adds value to researchers projects and any researcher can pay for usage in any organization, geography or discipline.

Anyone with a budget can get a free evaluation online, 90% who get CDD keep it, so we know it has high value for folks.

Q: Are there typical projects or use-cases for CDD? How about interesting or novel ones?

A:  Typical use cases are archiving data from every experiment that otherwise would just be in separate excel files or files from instruments and mining the data for potency, selectivity, polypharmacology, therapeutic windows, or whatever the desired trends may be.

A more collaborative use case is a screening center uploading samples and plates one time, then pushing those parent-child plates to 20 different projects (all within a single secure CDD Vault), for 20 different researchers with different assays, so they each can see their 1/20 of the data, without 20x the work for the screening center.   This is not a hypothetical example, but a real one.

CDD allows researchers to stand on the shoulders of giants, whether for accumulated public data or simply to maintain momentum after someone loses a job, finishes a postdoc, etc.  Other examples are when a funding party (a big pharma, the Gates Foundation, NIH etc) just wants to see a field move forward more efficiently, independent of which horse(s) win the race.   For example, the NIH has announced using CDD for the Neuroscience Blueprint working with industry and academia on IP sensitive projects.  We’ve publicly announced our collaboration with the Gates Foundation where we work globally with TB researchers on pre-published work but have scraped the literature and patents for published data, so the whole field moves forward faster.   These are just the announced collaborations, for every one public announcement or data set, there are about 20x secure, private, or unannounced collaborations.  Here are half dozen announced case studies:

Q: I noticed you were in partnership with the Gates Foundation previously. What did that entail?

A:  We had been working on neglected diseases (African Sleeping Sickness, Malaria, Chagas, etc) from day one because we felt it was important.   When the Gates Foundation suggested we focus on TB, it resonated with our values.  1 in 3 people in the world have TB, even with first and second line treatments, therapies take up to 6 months, and multi- and extreme- drug resistance has emerged.   We have worked with the Gates Foundation on multiple collaborations, currently it is interesting from a collaborative space as we are helping support new types of collaborations between new types of partners in new ways.   More details will emerge over time.   We’re also proud of our work with GSK on the Malaria data they released from the Tres Cantos Open lab.  Novartis also pushed TB data publicly via CDD.

Q. Are you pursuing other new partnerships or initiatives?

A:  Yes, this one here with Science Exchange is a good example.  CDD is collaborative in our DNA, in our name, and that permeates everything we do.   Obviously we have a collaborative platform, where anyone can selectively and securely share data with anyone else (down to an individual object, measurement, image, etc)….but it is really also a new philosophy, a collaborative paradigm.   In addition to all the groups on our partners and users pages and case studies, our message for 2012 is how can we collaborate with you?

Now that our community and platform has gotten relatively large and useful, we are finding more and better ways to collaborate with researchers on multiple levels be that science, data, software, strategy, connections, collaborations – it is actually getting easier to provide more value for others with less work for us each cycle…a sign that the model is really working and scaling.

Q: How do you see CDD evolving over the next couple years?

A:   I think it’ll grow wings and fly.

Seriously, we need to evolve as a function of those we collaborate with – this is both on the software and ideas side.   I think the technology will get smarter, so it really is evolving in that sense, in some ways non-linearly.   We will be partnering more on the social side too.  For example, Science Exchange might be a good partner for our next community meeting at UCSF (currently planned for Spring 2013).   I’m also an optimist about the global economy, even in the shadow of the current downturn.  I think other countries will do to China what China has done to the west and it’ll be good for all of us, as everyone will become more efficient.   We take a long-term view in everything we do and do enough for today’s market to allow us to do it.   This is part of why I didn’t see a difference between working on global, neglected disease and commercial disease for drug discovery – even from a capitalist perspective.   I do think our collaborative capabilities will become recognized as particularly and uniquely useful in this new emergent paradigm.

One philosophy we’ve kept over the years is the idea that with a platform like CDD in the long-term there is no short-term.   By that I mean we have built in the quality, security, and performance into the platform, so as it’s grown the value always improves.   This comes from the concepts of TQM (Total Quality Management) and TDD (Test Driven Development), it was a real credit to Dr. Moses Hohman during our third design, but we have 5 lines of QA code for each 1 line of production code which is high not just for scientific software but any software anywhere. Similarly, we have 10K automated tests with each new build.   What this means for users is CDD is always backwards compatible even as it continuously improves and scales with users, data, collaborations gracefully.   Part of the philosophy behind Ruby on Rails (a platform also used for Twitter as well as CDD), is that as the platform grows, it becomes more solid and robust.  We have focused on scientists, perhaps some day if we get big enough we might shorten the name from Collaborative Drug Discovery to Collaborative Discovery, but at this stage we are pretty focused on the preclinical drug discovery space.   I think the core capabilities of handling lots of data gracefully and collaboratively could be broadly applied to many scientists and scientific problems – we tend to get new use cases and ideas from how people really use CDD.  There are scientists who login every day and use CDD as the Workhorse for their research.

Q. What impact do you see CDD having over the long term?

A:   We want to help every scientist in the world be more efficient, more creative, and more collaborative.

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