Big data has become one of the biggest businesses around. The evolution of fields like network virtualization and machine learning has given businesses access to larger pools of data and far more sophisticated means of analyzing them than ever before. The result is supercharged businesses with reams of actionable intelligence. One industry that’s been slow to embrace big data is Big Pharma, but that could be changing, and it could change the business model in some rather fundamental ways.
An Industry in Turmoil
The pharmaceutical industry has long been one of the biggest businesses around, and its one well rooted in the United States. The U.S. enjoys a 45% share of the pharmaceuticals market, but the once thriving industry is by many accounts in decline. Legal issues have a large part to play in the business’ bad times. While false claims can steadily chip away at a pharmaceutical company’s profits, legitimate liability lawsuits can cost a company billions of dollars every year. But just as worrying is the stagnation of the research and development arms of these companies. It has been decades since R&D methodology has changed in any meaningful way, and these two problems tend to feed into one another. Drugs without the proper research behind them are too often rushed to market, and the resulting lawsuits force these companies to chase future profits, often without the proper oversight to protect the public interest.
A Renaissance on the Horizon
For many in the industry, Big data represents the sort of revolution that Big Pharma needs. The McKinsey Global Institute predicts that the fusion of big data with pharmaceutical research could result in an annual windfall of 100 billion dollars. It’s an exciting prospect because the advantages that big data offer could change the R&D methodology of Big Pharma in some truly seismic ways.
One of the most important advantages could come in the form of predictive modeling. Machine learning can analyze clinical and molecular data at a speed and level of accuracy that humans never could, and that could help researchers more easily identify molecules that could be successfully and safely developed into drugs. The result would be a production pipeline that’s both faster and safer, allowing more drugs to enter the market with the added advantage of less public harm and fewer filed lawsuits. The process of finding clinical trial subjects could likewise be accelerated. The outdated model of finding patients today relies largely on doctor’s visits, but new platforms like social media could help expand the pool and help clinical trials connect more readily with prospective patients. And with this larger pool in place, doctors can focus on more specific demographics to produce targeted studies, thus increasing accuracy and reducing time and costs. And when the information from each trial is digitized, it will become easier to share, spreading the knowledge more widely and creating a more healthy research ecosystem altogether.
An Opportunity For Major Change
There’s a lot of talk about “disruptive” technologies, and the pharmaceutical industry is particularly well suited for some major changes. Many in the industry have been slow to adopt big data. Integrating big data into existing infrastructure requires a significant investment, and the current lack of such investments in the industry make many of the biggest players hesitant to take the plunge without precedent. As a result, it may be emerging big data companies that shape the future of the industry. Illumina Inc. has made a name for themselves for their impressive DNA sequencers, while Thermo Fisher Scientific Inc. is drawing attention for their image analysis and analytic software. They just represent the tip of the iceberg as far as these technologies are concerned, but the precipitous rise in their stock values suggest a promising future. Investors are catching on to the value of these sort of developments, and pharmaceutical executives are sure to follow sooner rather than later.
