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Harvesting Patient Data


By Michael A. Greeley

Sept 15, 2005 | There is heightened interest in business models that mine patient data for nuggets of actionable insights - insights for which Big Pharma will presumably pay a premium. A number of transactions of late are beginning to consolidate this industry (such as the Netherlands' VNU's approximately $7-billion merger with IMS Health, which is acquiring PharMetrics). This new evidence of liquidity is obviously good news for the venture investor.

Daniel Paterson, vice president, marketing and corporate development, with PharMetrics, says, "Selling outcome studies from health plans to pharma is exciting...the dollars are in marketing now, as they need more than just script data." He adds that the unmet need is in bridging the drug utilization information with medical improvements. Understanding usage patterns is ultimately of the most value when overall medical care is improved.

There is a parallel with bio-IT vendors looking at drug impact on a molecular or cellular level. These longitudinal data tools will allow pharma to optimize sales force deployments and distribution strategies based on medical impacts of their compounds across various population sets. This is the corollary to predictive pathway tools attempting to do the same by understanding molecular impacts on certain patient populations. These tools will have different impacts on the "four Ps" of the drug delivery ecosystem: physicians, patients, pharma, and payers. The objective is to drive down costs while improving efficiencies of healthcare delivery. Says Charles Popper, president of TechPar and former CIO of Merck: "Pharma is clearly looking for initiatives that will replace television ads...they want to monetize data in new and novel ways, as they are not getting the growth they wanted in lives covered." He observes that these are ways to get closer to the consumers - all very new thinking within pharma.

Marc Schiller, CEO of Adherence Tracking, a startup focused on capturing longitudinal patient data housed within pharmacy benefit management companies, feels that the opportunities are potentially enormous. Traditional solutions that simply report and analyze script data do not provide complete pictures. He also feels that the historic providers of these services have created a pricing umbrella that startup companies might exploit; it is not uncommon for pharma to pay more than $500,000 for a modest study.

There are some caution signs out there, however. For one, does pharma possess the requisite marketing talent to best leverage the data that these new tools promise to generate? A new generation of marketing executive needs to come of age within pharma. Additionally, historic compensation schemes were predicated on performance against IMS data, which raises issues around credibility and acceptance of new data. Ultimately, these are complex data sets, so there is the ongoing concern that this complexity cannot be neatly distilled to actionable data. This may begin to explain why IMS has a significant consulting practice that customers find necessary to effectively use their tools.


Capital Concerns
So where does that leave us? With the explosion in the number of data sources, many entrepreneurs are out building companies to interpret unique data sets. While the promise is seductive, gaining early revenue traction is still tricky. Pharma is notorious at "piloting" novel solutions, but converting these pilots into recurring sustainable revenue streams can be elusive. Venture investors will insist on seeing some signs of conversion before committing significant dollars.

The other concern often expressed is that large, established vendors can quickly compete with their own proprietary solutions, which, while not necessarily providing complete solutions, may be just good enough. The power of the incumbent is real; the ability to bundle and leverage solutions with consulting services is a powerful competitive advantage. Having a thoughtful response to that will be essential as you articulate your strategy.

Investors will also be interested in your partnering strategy - be it to access unique data or establish compelling channels of distribution. How you leverage or co-opt players in the greater ecosystem will be essential. But for many of us, the most important element of the strategy is to demonstrate extraordinary capital efficiencies. These data business models should be highly leveraged, which is to say you should not need to raise very much capital relative to the opportunity. Some of the companies recently sold have returned 2 to 4 times invested capital because of the care demonstrated in how capital was deployed. No wonder there is now renewed interest in this space.

Michael A. Greeley is managing general partner of IDG Ventures. E-mail:mgreeley@idgventures.com.

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