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Will Big Data Lead to Big Biotech Returns?

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Big Data could improve results in the biopharmaceutical industry—if companies can improve their use and avoid pitfalls, writes Jefferies’ Michael Yee in a report issued today.

The proper implementation of new data and analytics tools could “accelerate the probability of success” in the drug industry and boost process efficiencies, driving billions in cost savings, according to Yee. At the moment, the process is still in the very early stages, so benefits won’t be seen near-term. Nonetheless, he writes that biopharma companies see data as “ripe with opportunity,” and it’s not hard to see why: Bringing a single drug to market costs $2 billion on average, a figure that’s rising 10% annually, so any cost savings would be a big help.

In this way, using Big Data to “find better drugs at a lower cost” will put drug makers at an advantage by increasing return on investment. Companies that are using Big Data include Amgen (AMGN), Biogen (BIIB), Celgene (CELG), Gilead Sciences (GILD), Johnson & Johnson (JNJ), Eli Lilly (LLY), Merck (MRK), Novartis (NVS), and Regeneron Pharmaceuticals (REGN).

Yee writes that Big Data can help in a number of areas, including research and target discovery, drug discovery, clinical development, the manufacturing and supply chain, marketing and sales, and drug real-world evidence, although he argues that the huge amounts of data generated by scientific trials aren’t yet being mined well.

Moreover, Yee warns, there are drawbacks that drug makers have to be mindful of, including storage, ensuring privacy and security, and translating Big Data to actions that can be quantified and add to the bottom line.

The iShares Nasdaq Biotechnology ETF (IBB) is up 0.2%, to $108.71 in recent trading, and the SPDR S&P Biotech ETF (XBI) is up 1.3% to $95.37.

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Article Credit: Barron’s

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