The business of pharmaceuticals revolves around the management of risk. Historically, that has meant assessing the risk of taking certain actions or of making particular decisions. But with the advent of expansive data, this has evolved to include assessment of the risk of not doing things.
I recently touched upon this in the context of marketers formulating arguments to persuade med-legal teams to give the “thumbs up” to some of their more innovative (“risky”) campaigns. Patricia Choumitsky, senior product manager, consumer relationship and digital marketing, UCB, is a notable flag-flyer of this approach. “We get in early and convey the risk of not doing these things,” she says.
AstraZeneca provides us with an even better example in this month's cover story, “Data: Deep is the New Big.” The pharma giant has been studying the effects of formulary decision-making on the total cost of treatment for patient populations within some of its late-stage commercial product categories.
Brian Sweet, executive director of health alliances at AstraZeneca, told MM&M's Marc Iskowitz, “We showed that the removal of a branded medicine in our portfolio from the preferred-tier status actually resulted in higher overall costs, which were related to cost of office and ER visits as well as disease-state related tests.” But can you use this information?
Absolutely. According to Sweet, by incorporating this type of research into dialogue with payers, AstraZeneca has been able to “solidify tier-placement decisions, with respect to our medication, that are more favorable than what you would expect [in] a generic market where we have to compete with late-stage commercial products.”
Of course, what has enabled AstraZeneca and others to adopt such research in pursuit of persuasive formulary arguments is the availability of data. Different data than before, and from the real world. In this example, AZ leveraged data from electronic health records and administrative claims to draw insights and construct insight-driven arguments regarding formulary decisions.
But, as a pharma company, it's highly unlikely you can navigate this world of data alone—you need good partners. (Once again in 2013 I'm talking about collaboration in the pharma industry.)
Partnerships between pharma and managed care are becoming increasingly commonplace. In fact, a recent PriceWaterhouse Coopers survey found that 43% of insurers said they would benefit from a data-sharing deal with pharma. AstraZeneca works with HealthCore, the health outcomes division of WellPoint, which helped the company extract the insights in the example above. And IMS Health also mines data for AZ in the EU, where “a lot of the discussion has been around discouraging the rapid uptake of a lot of very innovative products, and a higher reliance on existing products,” according to Jon Resnick, VP of real-world evidence solutions at IMS Health.
Meanwhile, PatientsLikeMe works with around 40 life-science companies to monitor how drugs are impacting patients in the real world—again, another trending requirement, particularly in Europe, but spreading to these shores. While this data provides a substantial (and relatively cheap) complement to the industry standard randomized controlled trial, it won't replace it anytime soon. “Anyone who works in this space,” says Sachin Jain, MD, chief medical information and innovation officer at Merck, “will tell you that … real-world data are hypothesis-generating rather than hypothesis-testing.”