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Data-Driven Technologies are Shaking Up the Drug Development Process

Posted on March 15th, 2019 by in Pharma R&D

For many, many years, the findings of scientific research were published in an always-growing collection of scientific journals that spun off into more and more specialized disciplines. Researchers would eagerly await the publication of the latest edition of their favorite journals, and between the covers they would find the newest, most cutting-edge discoveries.

From even the earliest years of published research, scientists no doubt found it a challenge to keep track of valuable findings and to locate that data later on when they needed it to support their own work. But in recent decades, that has gone from a challenge to a gargantuan task that has become a complex discipline in its own right.

Today’s scientists have to think far beyond scholarly journals subscriptions and wrestle instead with search strategies and informatics. With thousands of publications and resources out there, some spanning hundreds of years, how will they uncover the information they need? What digital tools should they use in the search? What brand new technologies can help streamline their workflow?

From the publishers’ point-of-view, there is indexing, semantic data, machine learning, predictive analytics and so many other technologies (old and new) to employ in the effort to make information more easily accessible to researchers. AI is one of the most exciting avenues being used to boost drug discovery and development, but it is no cure-all.

In an enlightening piece titled “Data-driven drug development” in Scientific Computing World’s Lab Informatics Guide 2019, Jabe Wilson, consulting director of text and data analytics at Elsevier, talks in detail about the tools and technologies that are changing research practices at the desk and in the lab. Read the article here to learn more.

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