News and Insights
Marrying Big Data with Personalized Medicine

Global healthcare systems are currently undergoing major transformations spurred by increasing regulation, record public debt and shrinking budgets. The U.S. has the dubious distinction of leading the way in this regard. The mandates of the Affordable Care Act, along with shrinking reimbursement to providers are fundamentally changing the operation of the U.S. healthcare system. At the same time, patients are being challenged to assume greater accountability for their own health, and the industry is moving to a model that better aligns stakeholder incentives to deliver on cost and quality. Healthcare providers and payers that have historically been siloed and fragmented are now exploring ways to collaborate and coordinate efforts to reduce costs while improving patient safety and healthcare quality.
Amidst lower reimbursement from payers and declining productivity in R&D, manufacturers are looking to develop high-value, cost effective and targeted drugs. It has long been maintained that personalized medicine offers the prospect of improved health, better outcomes, and less harm. Thus, it should not be surprising that the concept of personalized medicine has become a buzzword throughout the industry as manufacturers increasingly see it as the solution to many of their business needs. In fact, the number of personalized medicine products has more than quadrupled in recent years, from only 13 on the market in 2006 to more than 70 in 2012 and a recent report projects that the U.S. market for predictive personalized drugs will double, increasing from $9.2 billion in 2013 to $18.2 billion in 2019
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