Approaching the issue from the perspective of pharmaceutical research and development, Big Data is primarily being used to locate and isolate new disease vectors and pathways through the thorough analysis of massive amounts of Real World Data (RWD) in the form of medical files, hospital records, and other types of medical data not obtained through clinical trials. Modern data analytics platforms such as IBM Watson Foundations can deal with the astonishing load of information to which researchers now have easy access, and run analyses looking for meaningful correlations in infection, patient outcome, genomic and genetic data, lifestyle, and more. That’s the sort of work which once would have had to be performed by hand on sample sizes much smaller than, for example, the hundreds of thousands of ICU records Philips recently made available to medical researchers. A solid data analytics platform can effectively wrangle and interact with numerous streams of information and present results in a meaningful, easy-to-read manner that lets researchers make maximum use of it. That means better, more effective drugs in less time, giving an organization far greater opportunities for productive clinical trials at a much-reduced cost. And the rise of public-private consortia to make even more individual heath data available for the public good means that navigating, manipulating, and putting to work vast amounts of patient information are vital abilities any pharma company needs to possess.
This leaves the business of making and distributing pharmaceuticals.
You can only improve what you can measure, and Big Data gives pharma companies the ability to assess, analyze, and improve operations at every level, from manufacturing to warehousing to distribution to compliance. The benefits to overall operational efficiency are hard to describe, but simple to quantify, including as much as a 10% increase in efficiency in supply chain operations and shorter delivery schedules. Additionally, data analytics can help project global trends into the future, allowing the responsive organization to adjust operations accordingly. Big Data allows for easier and cheaper operational maintenance and optimized performance of every sector of your business.
In addition, Big Data can help protect you against regulatory penalties by allowing an operation to more effectively locate and eliminate problem areas in the manufacturing process; in one real-world example, a pharma company discovered that two batches using identical manufacturing processes displayed a variation in yield between fifty and a hundred percent, which could attract unwanted attention from the FDA. The use of data analytics allowed the company to track interdependencies and locate nine separate factors that affected yield, allowing them to correct the error and increase production by a solid fifty percent. Big Data allowed them to create a better product more efficiently while avoiding FDA penalties.
The truth about Big Data and Big Pharma is that, together, they are creating tighter operations producing higher quality, more effective pharmaceuticals. Leveraging data analytics means better patient outcomes and healthier businesses across the board.