Bench Press

The Open Science movement is driven by the idea that collaboration and openness are good for innovation and discovery. After all, the logic goes, who is more likely to discover a cure for cancer: five research groups with different sets of skills and specializations who don’t share any information with one another, or five identical groups who actively pool their knowledge?

Ironically, that reasoning seems to have completely skipped over the biotech/pharmaceutical industry who seem intent on pursuing the “divided we fall” approach despite the escalating costs of drug development. The application of openness itself is especially relevant here, as a significant piece of the $800 million – $1.2 billion price tag that goes with bringing one drug to market is the cost of failed R&D projects.

This problem is one that is not only a burden on the shareholders and executives at these companies, but also a burden on the healthcare systems of people around the world, which end up paying more and waiting longer for drugs to make it through a company’s pipeline.

About a month ago, the New York Times cast a spotlight on this problem:

Although many companies have committed to publishing the results of clinical trials, whether or not they succeed, drug makers don’t typically publish information about projects that fail at an earlier stage. A result is that companies waste many millions going down experimental paths that their competitors have already found to be dead ends.

M.I.T. is proposing dead-end drug disclosure, a concept that goes by a euphemistic mouthful: “precompetitive information sharing.”

Drug makers may realize that the financial and medical value of sharing such information outweighs the competitive risk, said Dr. Gigi Hirsch, the executive director of the M.I.T. Center for Biomedical Innovation, the locus of the drug project. “There should be more information available about failed compounds in the interest of the greater good,” Dr. Hirsch said.

The traditional response from the pharmaceutical industry is one that is familiar to Open advocates – that intellectual property and proprietary platforms are necessary for the returns which drive investment in these spaces. But, this ignores two things.

First, the act of sharing information on failed assay hits helps to reduce the cost and time of development. The decision to invest in a particular R&D project is driven by returns, and returns are driven by development costs and the time it takes to get “money back”. While being more open about internal failures and successes will do little to change the cost of marketing, clinical trials, and many aspects of development, it will reduce a large portion of the time and cost of initial R&D (because of the wider availability of information) and the cost of failure (as there would be no need to pursue avenues of research on paths that have already been deemed a failure). So even if the prices and number of drugs sold diminish slightly due to the inability of a company to hold on to some early-stage proprietary advantage or the release of some of the details on their compound library, the time to market and cost of development diminish as well, helping to preserve the return on investment necessary to provide for the level of drug innovation and discovery that patients and doctors want.

Secondly, a move to openness does not necessitate unprofitability. It wouldn’t be realistic to ask companies to pursue a path which destroys the shareholder value they’ve been entrusted to protect. But, the fact that technology companies like Google and Nokia have been able to push open standards and open source yet retain profitability and innovation should hopefully signal to bio/pharmaceutical companies that it is possible to have both shareholder value and openness.

The path to profitable openness that technology industry practitioners like Google pursue is no different than the path that any company pursues: specialization. Google, for example, has specialized on high quality search results, effective advertisement targeting, and IT infrastructure management. As a result, there’s no reason for Google to prevent the broader technology industry from having access to the source code for its Chrome web browser, Android mobile operating system, or Google’s rich APIs to access the information you can find on its websites. In fact, Google seems to have understood that keeping its information closed would reduce innovation on the web, which would in the long-run hurt its own growth and profitability prospects.

I’d humbly wager that the value of protecting early stage failure and platform information is relatively minor in the grand scheme of pharmaceutical company value (and in fact some companies do publish failures, albeit only years after the experiment). I’d even humbly bet that major drug companies probably have much more significant expertise and differentiation in the steps after initial R&D, such as in compound refinement, clinical trials operation, process development, and computational analysis, etc. All of this should, at the minimum, shield existing drug companies from the “risks” of opening up on early-stage R&D failures and could even help existing drug companies compete by emphasizing these new capabilities as the determinants of success.

Nobody is saying that this path will magically materialize and produce awe-inspiring levels of profitability and growth overnight. But, when an industry is on the edge of a patent cliff (most blockbuster drugs are expected to become generic in the next couple of years), when its primary source of “value creation” seems to be in buying smaller companies, and when nations around the world are struggling with healthcare costs, I’d assert that the bio/pharmaceutical industry needs to change its practices.

As for how – I would propose the following compromise.

1. First, the NIH, PhRMA, or some other neutral authority should define a set of standards for what information should be contributed (balancing the desire to foster innovation through openness and the desire for companies to maintain the closedness they need to build proprietary advantages along other dimensions), create a standard for secure information sharing (which protects any individuals and patients and proprietary pipeline-related information) and govern compliance.
2. This body should then set up an information exchange/database for participating companies, academic institutions, government research centers, and medical institutions to share information and prevent non-compliant companies from gaining access (it’s not a perfect solution, but it could help assure companies who are worried that they will give up all of their information but not receive any in return).

This road would likely be a long and difficult one, but given the stakes and the potential benefits, I think it is one well worth taking.

(Image credit) (Image credit)

One challenge with getting scientists to collaborate over the internet is the difficulty of representing scientific data in a way that can be readily manipulated and analyzed. Take Chemistry for an example. How does one share information about pathways and chemical structures in a way which allows for an entire group to collaborate on particular problems (e.g. synthesis pathways)?

Imaginitik, a startup specializing in software to help companies and institutions use crowdsourcing, and partially funded by Pfizer, has one such idea (HT: VentureBeat). Most scientists who are working or have worked in chemistry or biology are familiar with software company CambridgeSoft’s scientific software products like ChemDraw or BioDraw. What Imaginitik did was combine CambridgeSoft’s software with the collaborative features of Imaginitik’s Idea Central software to create ChemBioConnect, a crowdsourcing platform for a company or institution to deploy.

The idea is pretty simple. Imagitinik’s Idea Central platform creates web portal where scientists and management can list topics that can benefit from a multi-person collaborative approach and organize responses/suggestions/workflow and to rate individual ideas and contributions. But what differentiates ChemBioConnect from other life sciences collaboration solutions or more generic crowdsourcing platforms is integration with ChemBioDraw’s interface which provides more features than a standard collaboration platform (which will only let you share pictures/text) and a more familiar and robust user-interface than other life sciences-targeted solutions. Interestingly, Imagitinik’s platform also allows the creation of personality profiles (e.g. “creative” or “inquisitive”) to better help scientists network and target the right set of people to solve these problems. Not surprisingly, Imagitinik’s funder Pfizer has been rolling out this solution since Spring 2009!

A poorly scripted demo video is below (I personally think the speaker focuses too much time on basic ChemDraw functionality and less time on how this ties together with the collaborative features for my taste):

I, unfortunately, haven’t had the chance to actually try out the software (although reasonable pricing for enterprise software, I don’t have $50,000 – $500,000 to shell out to evaluate the software), but I think this is a great look into what a prototype for scientific collaborative software:

• Web-based: The need for ease of access across many machines and locations and the need for a central repository with which to organize a group’s information generally means that collaborative platforms should be web-based or, if not, sufficiently web-like as to not be an issue.
• Social networking features: It doesn’t have to be a full-fledged version of Facebook or MySpace, but a collaborative tool should encourage its users to network with one another and allow people to show off what projects they’ve contributed to. Not doing this fails to create the sense of community and personal attachment that crowdsourcing/community collaboration need
• Integration with existing tools: It’s a sad fact of life that inertia is a big factor when people are deciding whether or not to use something. But it’s a fact nevertheless. The best way to encourage quality adoption is to make sure that tools that are commonly used by the target user base tie in nicely for two reasons. First, new users won’t have to learn a new set of techniques, interfaces, and processes to adopt. And secondly, the tools that currently exist oftentimes support features that are harder to develop and more useful than developers of new platforms would like to admit. Sure, lots of people (including this humble commentator) have bashed ChemDraw as clunky and awkward, but someone developing a chemistry crowdsourcing platform is likely to skimp on things like NMR-simulation or smooth rotation of a structure.
• Managed workflow: Collaboration, even face-to-face, can be very difficult because information and suggestions and ideas are not organized effectively. It’s not enough to let people share their information and insights. You have to organize them and create tools with which to evaluate and encourage action on them.

As I haven’t actually put my hands on the software, I’m not sure if ChemBioConnect already supports these, but there are two additional features that I’d strongly suggest a collaboration platform to have:

• Easy way to export work: Too often, developers of a platform or tool forget that there is a world beyond their innovations. This is especially true when people are testing out a piece of software for the first time – it’s important that they can quickly move a piece of work off the tool to integrate with the rest of their work schedule, whether it be in printed form, in the form of a presentation, on a PDF, in web page/HTML form, or even just as a industry file format to share with another. Going the extra mile to make this easy makes it easier for someone to try out your software as well as provides a valuable service that just may win an adopter over.
• Semantics: This is harder to describe, but many web-based tools are very rigid, requiring a user to identify exactly what they want to do and figure out what part of the website is best suited for that particular type of work. Better, instead, to apply semantics/language processing to figure this out for the user. One example of a product that has done this is Google Calendar. Instead of requiring a user to try to figure out which fields correspond to what data when trying to create a calendar entry, a user can simply enter “Lunch with Jenny at Chez Carla on Sept 9, 2009 from 9 PM to 11 PM”. Google will decode the string and fill in the appropriate data. This feature is especially powerful for a collaborative tool where a user doesn’t want to have to figure out if something is a “task” or an “event” or an “idea” and doesn’t want to have to memorize what each of the tool’s special quirks and vocabulary are.

Does anyone else have any thoughts on ChemBioConnect or on other principles of good collaborative tool design?

Previously, Ben wrote a post about innovative use of the virtual world Second Life for simulating N-body problems. One of the groups behind the impressive OpenSim mod, the Meta Institute of Computational Astrophysics (MICA), is incredibly unique in that the organization itself is an exploration into the utility of emerging virtual world (VW) technologies (e.g. SecondLife) for scientific and academic work.

A group of scientists from the California Institute of Technology, Princeton, Drexel University, and the Massachusetts Institute of Technology founded MICA in the spring of 2008 in order to explore and take advantage of what they saw as a new frontier in collaboration and information dissemination. MICA’s goals are¹:

• Exploration, development and promotion of VWs and VR technologies for professional research in astronomy and related fields.
• To provide and develop novel social networking venues and mechanisms for scientific collaboration and communications, including professional meetings, effective telepresence, etc.
• Use of VWs and VR technologies for education and public outreach.
• To act as a forum for exchange of ideas and joint efforts with other scientific disciplines in promoting these goals for science and scholarship in general.

In addition to the collaborative research we’ve written about before MICA also “conducts weekly professional seminars, bi-weekly popular lectures, and many other regularly scheduled and occasional professional discussions and public outreach events, all of them in [SecondLife].” A screenshot of one of their astrophysics seminars can been seen below. MICA has also begun experimenting with various teaching formats for undergraduate and graduate level courses.

MICA members attending a weekly astrophysics seminar by Dr. M. Trenti, given in the StellaNova sim in SecondLife.

What really impresses me about MICA however is their belief in the platform.

[W]e wish to lead by example, and demonstrate the utility of VWs and immersive VR environments generally for scientific research in fields other than humanities and social sciences (where we believe the case is already strong). In that process, we hope to define the “best practices” and optimal use of VR tools in research and education, including scholarly communications. This is the kind of activity that we expect will engage a much broader segment of the academic community in exploration and use of VR technologies. Second, we hope to develop new research tools and techniques, and help lay the foundations of the informational environments for the next generation of VR-enabled Web.

Hopefully MICA’s innovative use of SecondLife will prompt other scientists to follow. I definitely want to check out one of the lectures one of these days.

(Exploring Use of Virtual Worlds as a Scientific Research Platform: The Meta-Institute for Computational Astrophysics)