The Voice of Experience: Alain Bernard

Vice President for Technical Operations, GPS (Governance & Prioritization and Science liaison), UCB SA


18 November 2014

1 min read

Scientific researchers are sitting on a mountain of data. Most of it is analyzed only once, with a particular question to be answered, and then never looked at again. But the investment in generating this data – and humanity’s need for the insights it could yield – are too great to let it remain buried.

With the advent of “Big Data” the pharmaceutical industry can at last begin to systematically mine new insights from this data. Industries such as retailing have blazed the path, transforming billions of individual data points on consumer goods into valuable knowledge.

The transition won’t be immediate. Today, most pharmaceutical companies cannot easily consolidate their data sets from different sites – or even from a researcher in the next lab – and find the patterns. But today’s technology can find the patterns, no matter how diverse the inputs. Let the intelligent software work and it will come back with answers you were dreaming to have or even, in some cases, never imagined. I call this “unexpected” knowledge. I’ve seen one vivid example and it was a gem buried in the rock – until the system pulled it out.

Technologies are evolving to get us where we need to go. Now that data is mostly electronic, we can automate analytics and free up the scientist’s mind. This also opens the door to opportunities such as: “Why not pool my local data with that of another colleague in my company?” Consider the possibilities if we could even share data among organizations. I may have A and you have B and someone else has C. Until we put them together, we have nothing. But when we do, we can deliver a cure to an unmet medical need.

Transforming data into knowledge should enable us to deliver sustainable value, with better quality, at higher speeds, with more confidence, while lowering the risk of our pharmaceutical products and services. The technologies exist. We simply have to apply them to mine the gems buried in that mountain of data. ◆

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