This will likely be the only time I ever write about anything in the life sciences field. I will be the very first to admit that I know almost nothing about the industry. Sometimes, however, a piece of news is too interesting to pass up. I’ll start with a (very) high-level background and then get to the good stuff.

Brief History of the Web

Web 1.0: Open standards emerged on top of existing network technologies to allow for broad dissemination of information electronically. Web 1.0 was the first massive incarnation of Tim Berners-Lee’s hypertext.

Web 2.0: Content creation tools (blogs, recommendation sites, social networks) allowed average users to contribute to content online rather than simply consume it. Thus, the web changed from a repository of documents to a repository of general knowledge and conventional wisdom. The total available information on the Web has exploded since 2004, when Web 2.0 is largely accepted to have taken off, and shows no signs of slowing down.

Web 3.0: It is yet to be determined how the Web will move forward, but broad consensus seems to indicate that data mining and application of intelligence algorithms will play an ever-more-dominant role. This makes sense: our ability to put data online has far outstripped our ability to understand that information. For a good overview of where the Web may go, take a look at this excellent presentation at the 2007 TED. A recent NY Times article talks about data mining initiatives taking place at Google and elsewhere.

Drug Development and the Public Domain

One of the primary tensions within modern science is that between public domain scientific knowledge and patented innovations used for private enrichment. Historically the scientific process has been extremely open; scholarship was done by academics funded by institutions through a tenure-based system and peer-review was their path to financial success and professional fulfillment. This can be traced far back into our scientific heritage, including the likes of Newton and Keppler.

Modern science still relies on public scholarship and peer review, but an additional layer of private research and productization has been added on top. Companies like Merck and Pfizer employ armies of researchers most of whose research is not formally written up and peer reviewed. Knowledge gained through this private process is used to create products (in this case, drugs) that are eventually sold to the public.

This process is protected through intellectual property rights granted by the government. The public benefit of drugs developed through this privatized process is thought to outweigh the cost of keeping knowledge out of the public domain. While there are some that argue over this calculus, it seems fairly sound to me. The results speak for themselves: compare the pharma industry today with the pharma industry of 100 years ago. Most of that innovation was driven by private resources and the corresponding financial incentives.

Where the Twain Shall Meet

The Web, as always, is a disruptive force. What has worked for 100 years can be improved upon using technologies and production models of the online world. This is exactly what Sage is trying to do. Sage is an online biotech research database. From a recent article:

Sage is built on the premise that vast networks of genes get perturbed, or thrown off-kilter, in complex diseases like cancer, diabetes, and obesity. Scientists can’t just pick one faulty gene or protein and make a magic bullet to shut it down. But what if researchers around the world capturing genomic profiles on patients could get all of their data to talk to each other through a free, open database? A researcher in Seattle looking at how all 35,000 genes in breast cancer patients are dialed on or off at a certain stage of illness might be able to make critical comparisons by stacking results up against a deeper and broader data pool that integrates clinical, genetic, and other molecular data from peers in, say, San Francisco, New Haven, CT, or anywhere else.

This could be the beginnings of a paradigm shift for pharma in much the same way that open source has been a paradigm shift for software. Open source software (OSS) has, over the space of the past 30 years, built itself into a serious competitor for even the largest and most sophisticated software firms. Is it possible that open source drug development could do the same? Things to consider:

• What technologies would be required to enable open source pharma?  OSS required code management tools, email, and message boards. Open source pharma will undoubtedly require far more, and an online knowledge base is an excellent start.


• Is there any way to align the interests of open source pharma to any of the players within the market?  IBM, HP, Oracle, and Google all have very strong alignment with OSS and are significant investors in the growth of the community.


• What type of community ethic would be required to create an open source pharma community?  Over the 30 years of its existence, OSS has stayed a coherent force due to its extremely strong community.  Could such a community exist within pharma?

Obviously there are a ton of problems.  What makes this concept so compelling is the confluence of technologies: huge increases in our medical knowledge and corresponding increases in our ability to publish and analyze information.  Just imagine all of the medical research in the world being available in one database that could be programmatically analyzed to create datasets  that simply didn’t exist in one place before.  Science has always been about standing on the shoulders of those who came before; every effort to make scientific knowledge more broadly accessible is a step forward for our civilization.