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October 02, 2013
Big data in pharma: Defining and Driving Value
By: Jeff Elton Ph.D.

Recent estimates are that the US healthcare system could generate $300 billion in annual healthcare cost savings through efficiencies and quality improvements enabled by big data and analytics. The good news is that pharma, biotech and providers are starting to tap into this real-world data. This shift is manifesting itself in improved speed of decision making for clinical and commercial functions, more precise stratification of patients to new treatments, and new collaborative business models between biopharma, payers and providers. Improving the quality of care and outcomes realized by patients are the motivators, but the entire healthcare system is a beneficiary.

At a recent event, “Big Dip, Big Data in Pharma,” Accenture hosted a breakfast with leaders from the top life sciences companies around the world. The questions debated was how life sciences drive new insights and greater value from big data and real-world analytics, what are the early successes of this being done at scale, and where are the areas of greatest future opportunity?

Big data, big opportunities
Five key themes rang loud and clear in our session:

  • While the industry pipeline is improving, with more therapeutics targeting an array of diseases with high unmet medical needs, real-world data and analytics are required to support the value of these new innovations in support of fair reimbursement.

  • The practical use of real-world evidence begins before a therapeutic enters the clinic – even in late discovery – to establish the value requirements for the disease based on existing therapeutics and treatment paradigms.. This is where companies should examine the real-world benefits and follow-up of existing therapeutics, the unmet needs for the existing standard of care, and competitors’ products and pipeline.

  • Real world data and analytics can support clinical trial design, patient selection schema, and inform the collection of specific patient reported outcomes and economic data to establish ‘value’ throughout clinical development phases. Since specialty therapeutics often receive early approvals, this was highlighted as a real need to rare and niche diseases.

  • Real world data should be the foundation for Managed Markets, Commercial, and Medical Affairs strategies and programs – while there are clearly different goals for each function, commercial and managed markets are increasingly aligned and integrated. Medical Affairs has a broadening role of assuring and communicating the value of therapeutics with evidence for the benefit of large provider systems having to make tradeoffs in where they place scarce resources.

  • Real-world evidence needs a company strategy, a cross-functional approach, and to be integral to core management and resource allocation processes.

From 2013 and 2018 it is estimated that another $230 billion of sales are at risk of losing market exclusivity. While we are seeing an increase in R&D pipeline productivity, the top-line losses highlight the need to tap into real-world data and analytics in support of new business models that are both lean, laser focused on patient populations who are clearly beneficiaries of new therapeutics, and using real-world data enabled insights for strategic agility.

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