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Jan 9, 2013

Mayans Give Big Data a Big Break

The new collaborative environment is a data ecosystem that will transform the world in the current age.

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    2013 will bring big challenges—even Big Data challenges—but we’re also likely to see collaborative action across R&D and translational research and into the clinic. [© Sergej Khackimullin - Fotolia.com]

    Since the Mayans were wrong and we’re all still here in January, what are we all going to be doing apart from celebrating the start of another 2,500-year Mayan calendar? For the life sciences industry it’s time to start implementing all the sage advice and strategy of the last two years on cost reduction and innovation capture and to begin instituting real change. Business as usual is so last Mayan calendar….

    The life sciences have had a 50-year party. But like all parties, when the food and drink start to run out, the festivities either need to move on or the partygoers need to take a break. 2013 sees the effect of the after-party gathering: the core group that meets the following morning for a breakfast at the diner and time together in the park. There will be some new friends in the gang and a number of old ones missing, but the sense of camaraderie and shared purpose is clear. Work together and the recovery will be faster and more fun.

    The group of oldest friends, pharma and biotech, are now joined by a much more eclectic, broader, outward looking group of CROs, academia, clinicians, and patients.

    This new group of interdependent friends knows they can change the world, and the sparky conversation is tantalizing and thrilling: patient-centered healthcare, virtualized R&D, biomarker-driven prescribing, and telemedicine. It’s a heady mix of small- and large-molecule therapeutics, technology, disease prevention, and a healthcare revolution.

    The conversation is driven by fundamentals among which are financial and human elements. First, the costs. Payers are paying more every year for healthcare. According to the Economist, U.S. healthcare costs rose to $2.6 trillion in 2010, more than 100 times the cost in 1960. For the pharmaceutical industry there are also some stark figures: a 25% increase in the cost of the R&D pipelines but with no added corporate value, noted a Deloitte/Thomson Reuters report in 2011.

    However the most seismic changes are not about national or industrial P&L. The rise of patient power is inexorable and the availability of data has changed the balance of power forever. 2012 saw the publication of Eric Topol’s brilliant book, “The Creative Destruction of Medicine.” This provides a fly-on-the-wall insight to the post-party debate and an indication of where this new band of brothers can take the future of healthcare worldwide. To read the book, it is well worth a missed night’s sleep and the overexpression of CYP1A1 to deal with the caffeine to understand the possibilities and hear the home truths that are now hitting home in every switched-on boardroom and consulting room.

    Switched on to what? The power of data. IBM recently stated that between 50% and 90% of the world’s data has been generated in the last two years. This is not simply the proliferation of pointless videos of poor unfortunates tripping over or teaching you how to juggle hammers. The availability of genomic data, on-line, crowd-reviewed journals, secure deidentified real-world clinical information, and telemedicine data are astonishing and bewildering. To make this new world of medicine work, everyone in this new group will need to be able to make sense of and use this global treasure.

    The new collaborative environment is a data ecosystem that did not exist even in the last Mayan calendar, but it will transform the world in the current age. Even limiting our view to the R&D environment demonstrates that there are major efforts that must now be transformed from the whiteboard to the scoreboard:

    • Distributed R&D: To really bring together virtualized R&D a scientifically-savvy data infrastructure must underpin the logistics and relationship building efforts that has been set up over recent years. Data and IP are the currency and the product of this disruptive way of working. Simple but sophisticated collaborative data systems will make “right-time” decision-making a reality and bind the parties together in precompetitive and discreet relationships.
    • What-if scenario planning: Sophisticated tools and data technologies are needed to aggregate and provide data-driven guidance to portfolio managers, budget holders, and collaborative decision-makers.
    • Translational medicine: Secure systems that can combine electronic medical records, tissue samples, image, and ‘omics data enable a next-generation science for medical research. This combination of data is new, multi-stakeholder. and of unprecedented value. This unique mixture, allied to domain understanding, analytics, and tech, which can genuinely bridge bench to bedside to boardroom, is enabling. Production systems are now changing how this science is performed and redefining what speed and depth of science is possible in this new discipline.

    These new resources are transformational for Academic Medical Centers, Health Services, pharmaceutical companies, and medical science. This was recognized most recently by the $160 million (GBP100M) project announced by the U.K. Government last month to create longitudinal, sequence-centered data for 100,000 U.K. patients, and the launch of the Innovative Medicines Inititive project, eTRIKS, to provide precompetitive data systems for a consortium of pharma and academia.

    So is all this then just Big Data? No. It’s about changes in practice, gaining deep insights into what data need to be collected, and relying on smart (not just Big) systems that make the data usable. Next-generation sequencing is certainly an important technology, creating terabytes of data per sequence. However, it will only release its full potential if the data consumers at the front line can make sense of it. This takes more than just algorithms and extensible (Cloud) computing power. It takes an understanding of the data and how it is really going to be used.

    The definition of big data is diffuse and fluid. It has been coined by some as a combination of volume, velocity, and variety. This missed a vital component without which the others are rendered impotent: quality or, as the alliterative are now starting to add on, veracity.

    It is well established in life sciences and clinical environments that there remain significant gaps in data, which make data comparisons, Big or not, of limited value. Our work across industry and healthcare environments drives changes in clinical and R&D practice that address these data gaps and focus upon getting collaboration to work across these multiple disciplines to achieve what is needed. Improve the quality, improve the decision. This was put well by James McGurk, Ph.D., when he said at an IDBS Translational Medicine Symposium in London: “The more difficult it is for others to understand your data, the more likely it will be used badly.”

    As the new calendar turns over, be it for 12 or 30,000 months depending upon your world view, we see a new group of friends setting out to change the world for the better. No doubt there will be big challenges, even Big Data challenges, but 2013 will see collaborative action across R&D and translational research and into the clinic. After a long night out, that is just the news we need.


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