By Ryan T.
The pharmaceutical industry has always relied heavily on data. That data consists of historical clinical trial results, cellular, genetic, microbial, molecular, proteomic, and metabolic data. With most, if not all, of this data being stored electronically and so much to sift through data mining has been highly advantageous in pharmaceutical research and development (Elvridge, 2016). Several proprietary and nonproprietary tools are available to researchers each with their own distinct differences. The pharmaceutical companies utilizing big data ranges from large companies to small firms since data mining effectively reduces the barrier of entry. This goes without saying, but big data mining does comes with risks and limitations when it comes to the pharmaceutical industry. Overall, the benefits far outweigh the risks though as developers and researchers continue improving their products.