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.

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Lilly has demonstrated the viability of cloud computing in pharmaceutical R&D, according to Dave Powers, the firm’s associate information consultant for discovery IT. "We were recently able to launch a 64-machine cluster computer working on bioinformatics sequence information, complete the work, and shut it down in 20 minutes," he says, describing a project the firm executed using Amazon’s Elastic Compute Cloud (EC2) service. "It cost $6.40. To do that internally—to go from nothing to getting a 64-machine cluster installed and qualified—is a 12-week process."

What was most interesting about the article was the assessment of the cost/benefit analysis that the companies each went through before adopting the technology, something which is important to understand both for researchers/companies interested in adopting cloud computing techniques as well as for technologists/developers striving for broad adoption of their own special technologies. This particular case is especially enlightening as it flips the conventional wisdom – who said that all pharma IT systems and managers are slow to embrace change?

There are 4 key factors that seemed to play a role in “tipping” the large bio/pharma companies: (1) cost, (2) maturity, (3) third parties, and (4) the ability to achieve sizable benefits on a number of scales.

1. Cost: This is usually the “easy” part of new technologies. After all, if a technology is being considered as an alternative to conventional approaches, it usually has major cost or efficiency advantages. In this case, Cloud promoters/IT experts were able to make the case that the cost of buying, setting up, qualifying, and supporting IT infrastructure needed to support all internal demand for computing resources was much greater than the cost of outsourcing some computing needs to Cloud Computing providers. This cost, of course, is measured not only in terms of IT dollars spent,  but also in terms of the time needed to set up, qualify, and develop the necessary IT infrastructure as well as the potential dollars a company might lose by being less nimble.
2. Maturity: One of the major obstacles that new technologies face is that nobody trusts them. After all, why trust a new player with an unproven product for your ultra-important needs (especially when your job is on the line if your needs aren’t fulfilled), when your current setup is working “good enough”? In the case of Cloud Computing, however, the availability of well-known vendors (Microsoft, Google, Amazon, Rackspace, etc) who have had years of experience developing their own systems and product offering has been instrumental in wearing down the traditional resistance that new technologies tend to face. Amazon, especially, has built a well-known cloud platform (their Elastic Compute Cloud more commonly referred to as EC2), with:
   • Easy-to-use web interface
   • Range of offerings that are attractive to many customers (e.g. targeted offerings which distinguish the needs of web application providers versus high-performance scientific computing clusters)
   • Support for standard enterprise software to minimize the amount of re-work that CIOs/IT people will need to do
   • Professional SLA (service-level agreement) which legally obligates Amazon to provide a certain level of service
   • Simple billing system
3. Third party: The existence of third party players on a particular type of technology provide two things to companies interested in adopting a new type of technology. First, it is proof of a concept’s maturity. If a technology really is great, then there will be companies that aim to provide services or add-on products for users of that technology. Second, it simplifies the job of using the technology, as there will be companies who specialize in providing support and useful add-ons. In the case of Cloud Computing, there are a number of providers who specialize in helping companies deploy Cloud computing software or manage their use of computing resources. Companies like Eucalyptus and CycleComputing can provide support (for a fee) for companies interested in setting up their own cloud, and open source projects like Hadoop and research papers on how to use Amazon’s EC2 to do proteomics research not only validate Cloud Computing but provide free advice on how to set up research “clouds”!
4. Benefits achievable on multiple scales: Too often, new technologies promise grand benefits which can only be realized on very specific scales. Small pilots and full-scale transformations are not how companies make decisions and do not reflect the reality of how technology is used. Technology that only delivers significant benefits in small pilots or only work if all old technology is replaced by a new one will be very challenging to adopt. The beauty of the Cloud efforts detailed in the article is that they cover a wide range of scales. Benefits are easily realized regardless of if you outsource your entire IT infrastructure, or if you choose to only use the Cloud some of the time, or selectively avoid using the Cloud when regulatory concerns dictate it.

This is not to say that the adoption of cloud computing in these cases went perfectly smoothly. Amazon does experience service outages and there are still issues to be sorted out regarding SLAs and regulatory concerns, but their adoption by companies in an industry known for conservative IT practices is something that can and should be learned from.

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