Principles of crowdsourcing—aka the concept of spontaneous group intelligence—are often identified with creative services, but they can also be used to advance scientific exploration. Crowdsourcing has, in fact, spurred the development of the open-notebook science movement, an approach that allows open access to raw scientific data to help solve scientific problems.

Open collaboration models have already been harnessed to help biopharmaceutical companies uncover novel insights and solutions such as identification of novel biomarkers, development of software and modeling tools, and optimization of clinical trial site selection.

InnoCentive was a startup incubated through the e.Lilly division of Eli Lilly and Co. Its Open Innovation Marketplace of more than 160,000 creative thinkers—listed on the website as engineers, scientists, inventors and businesspeople with expertise in life sciences, engineering, chemistry, math, computer science and entrepreneurship—is one example of a dynamic collaborative space for creative problem solving. It matches motivated “solvers” with “seekers” around a central challenge, with “significant financial awards,” says the company, from the seeker organizations.

It’s also worth considering how crowdsourcing principles coupled with open collaborative models could help identify patterns in clinical trial data that might contribute to innovative perspectives on product differentiation and new avenues for clinical development. Crowdsourcing and open collaboration might complement traditional market research or expert advisory boards by tapping into a global talent pool to help solve a vexing scientific or marketing issue.

Several companies are using open collaboration models to improve products and identify solutions. Here are a few:

• The BBC Digital Revolution is “an experiment in collaboration,” according to its website: “We want to hear the opinions, thoughts and experiences from the populace of the Web—you.” One project is an open source documentary the media company created that allows anyone to edit a documentary video for the BBC.
• A presentation on the Nature Precedings website, by Jean-Claude Bradley, illustrates how to use blogs and wikis to collaborate on scientific problems. In his pre-proposal to the National Science Foundation, he reflects on the current limitation of existing communication models and how these can be improved with open models: “The current system of dissemination of scientific data and knowledge is far less efficient than it needs to be to facilitate improved collaborative science, especially considering current publication vehicles and infrastructure.”
• The IBM Many Eyes project, now in beta, allows users to upload data and create visualizations that can be used by others. Its stated mission: “Our goal is to ‘democratize’ visualization and to enable a new social kind of data analysis.” In other words, by exposing the data to more minds for analysis, it’s possible to unmask perspective and insights that would otherwise have remained undiscovered.

A few practical applications of these concepts:

Assist with differentiation of a new drug. By subjecting the raw data to an audience wider than the internal team and a few key opinion leaders, one might identify specific subgroups or outcome measures that could be used by marketing teams to establish differentiation. A concrete example would be for pharmaceutical companies to give the raw data for the drug to an academic institution, whose analysis might yield patterns and trends previously undetected by the internal team or KOLs.

Facilitate the identification and implementation of new treatment paradigms and drug development targets. Open collaboration and data flow among multiple pharmaceutical companies, academic institutions and government organizations such as the FDA and NIH might help establish new targets for drug development as well as new standards for clinical trial design and data analysis. Examples of these types of projects are OMERACT, which networked collaboration to achieve consensus on trial design and outcome measurement in rheumatoid arthritis, and the MATRICS initiative, to drive acceptance of and identify drug development pathways for cognition in schizophrenia.

Create dynamic, adaptive and timely medical websites. Disease state and popular scientific websites can remain static and unitonal; there is little opportunity for dynamic interaction and exchange of ideas. By opening up the development of scientific content to a broader group of contributors around the Web, one can incorporate varying perspectives, as well as provide depth and coverage that would be more difficult with a smaller group. An example of such collaborative authoring is WikiDoc, “an open source website that allows an international community of health-care professionals to add and edit medical content in a process termed co-creation.” With thoughtful curation of content by an editorial staff, websites created using WikiDoc principles can span multiple therapeutic areas and provide an invaluable resource to various stakeholders in the health-care community.

The opportunities inherent in these approaches will continue to evolve as transparency standards permeate further into health-care communications. Within the appropriate privacy, regulatory and legal framework, crowdsourcing and open collaboration approaches that tap into collective wisdom might yield unexpected discoveries and offer tantalizing possibilities.