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Making Sense of Data Management in a Digital World

We already are aware of how the science business in general has changed, prompting leading companies to reevaluate the way they operate

by Mark Lanfear
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The incredible invention of social media and other Web-based technologies has transformed our personal lives in ways we really don’t have to think about anymore. Need to get in touch with a long-lost friend? A distant relative? An old colleague? Devote five minutes on the Internet and it’s usually done, thanks to all kinds of digital resources. As recently as ten years ago, however, this task would have been drastically more complicated—that’s how fast technology has radically changed the way we live.

Mark LanfearThe same thing is happening in the life sciences, though in much more complex ways and with far greater implications for scientific companies. We already are aware of how the science business in general has changed, prompting leading companies such as Pfizer, Roche, and Astra-Zeneca to reevaluate the way they operate, transforming some processes, especially in the collection and use of data, in innovative and highly productive ways. Whereas once these companies used to be considered traditional pharmaceutical organizations that produced the most important therapies of our time, they now have evolved even further into commercial health care providers. As a result, they are now able to cater to practically every health care trend—from personalized medicine to consumer products to other forms of life-enhancing products—all with a more watchful eye on safety, feedback, and compliance information. As challenging as this new way of operating continues to be, the welcomed byproduct is that these companies, by necessity, have had to lead the way in being equally personalized and innovative about gathering and analyzing the data required to accomplish their lofty goals. If these companies aren’t already well into the process of doing so, they are all certainly headed in the direction of making it easier for patients and research subjects to participate proactively in the health care discussion in much the same way that all of us would participate in a personal discussion with a friend through a variety of social networks.

These open lines of communication—where once they were closed due to regulatory norms, lack of technology, and fear of the unknown—are now positively affecting a great many across the scientific spectrum, from academic research and crowd-sourcing think tanks to the companies that sponsor clinical trials and the patients who will reap the benefits of life-enhancing treatments and even right down the line to the governmental bodies tasked with regulating product safety and effectiveness claims.

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But it also means that data no longer exists in a vacuum—and that the entire scientific industry will continually have to adapt to the infinite number of ways that we are now able to use that data. Not only are the possibilities of analyzing and applying data limitless, but so is the data itself. We are in fact being exposed today to profound amounts of knowledge, representing a true quantum leap forward as science becomes social and people become more and more willing, and comfortable, in sharing their experiences for the greater good and quicker development.

And yet this brilliance will only be able to build off itself if data managers, as well as the organizations that support them, as a whole, are willing to match—and even exceed—the savvy nature of the social media platforms that are allowing us all to move the research and development world forward. In many ways, data management used to be the skeletal system of the industry. By necessity, there was a rigidly defined set of goals, standard operating procedures, and compliance standards. It used to be that one case report form (CRF) page, with just one category of data, would be keyed into a database. Next, someone would have to clean and check that data. This process worked well in an age of limited resources, more limited information flow, and a different expectation in timelines. But now that the amount of potential knowledge is so great, previous finite systems fall dreadfully short of current capabilities as well as of the innovative possibilities of the near future. Social media and other technology platforms mean that data management and these leading professionals must now, in fact, operate much more like the nervous system, feeling and responding to all the sensations around them. The inputs are not just from one tactile place as they were in the past, but are from multiple media sources that need to be integrated and adapted to, and ultimately land in the “brain” where data is analyzed and objectively interpreted.

When not only the industry but the scientific community as a whole is able to completely embrace this new frontier in data analytics and the role of the data manager, the advantages will be staggering. We are already seeing the lines blur between electronic medical records and CRFs. Processes that used to be considered highly separate steps, such as clinical monitoring, source document verification, and data entry and edits, will only become more blended and matrixed so the information can be used at faster rates and in more efficient ways. Technology will continue to create a unique synergy between these subject matters that will continue to yield efficiencies in cost, quality, and time. Linkages of all this data will reduce the errors and redundant reporting of years past, while digital channels will continue to evolve and drive the sharing and collecting of data points and experiences that the commercial health providers, biopharmaceutical companies, and the like may not have even thought to collect or contemplate before. Scientific epiphanies will abound as a result, leading to life-saving medicine and life-enhancing products.

What are the best ways for companies to capture and integrate the knowledge that is discovered in social media, in patient communities, online, and face-to-face in this new digital era? At this speed of development, time will be the final judge. In the meantime, trial and error will likely inform which best practices work today and which ones will come to be accepted community wide.

Regardless of the constant changes in the way these free-flowing digital channels drive information, one thing is certain: an organization’s data analytics team can no longer be content to exist in the background, because their star is clearly rising. The infrastructure of the management of data has become the interactive face of our life science world. These processes will become the key to better science, and the role of the data management professional will no doubt take its new “natural” place at the forefront of this spectrum of collaboration.