Giving Data the Gift of Meaning
Ever-growing datasets are a constant challenge when trying to develop efficient clinical trials. As more conventional approaches fail to give companies the competitive edge they need, can the insight provided by predictive analytical tools pick up the slack?
Gen Li, Jonathan Peachey | | Longer Read
An underpinning value of the pharmaceutical industry is its desire to provide solutions where there seem to be none – and yet each year the pharma machine continues to churn out drugs, which, rather than being first-of-kind treatments to combat areas of unmet need, are often alternative formulations of existing products. Despite the millions of dollars annually spent on R&D, true scientific breakthroughs seem few and far between.
Big data has become an industry buzzword – and could be particularly useful for improving clinical trials. The industry knows that big data has huge potential but pharma companies are inundated with data from various sources, which is often found in different formats and grows at an incredible velocity. Selecting data that will significantly impact the quality of clinical trials and result in breakthrough medicines is more than a trying task.
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